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P8010-004 exam Dumps Source : IBM Commerce Solutions Order Mgmt Technical Mastery Test v1

Test Code : P8010-004
Test denomination : IBM Commerce Solutions Order Mgmt Technical Mastery Test v1
Vendor denomination : IBM
exam questions : 30 existent Questions

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IBM (IBM) Down 10.three% in view that remaining earnings document: Can It Rebound? | killexams.com existent Questions and Pass4sure dumps

A month has gone by given that the remaining profits record for IBM (IBM). Shares beget misplaced about 10.3% in that time body, underperforming the S&P 500.

Will the contemporaneous terrible style continue leading as much as its next income unencumber, or is IBM due for a breakout? before they dive into how traders and analysts beget reacted as of late, let's select a brief appear on the most fresh earnings file with a purpose to earn a better wield on the well-known catalysts.

IBM’s Q2 results profit from pervade chopping, lessen participate count number

IBM reported third-quarter 2018 non-GAAP profits of $3.forty two per share, which beat the Zacks Consensus evaluate via yoke of cents. income per participate (EPS) multiplied four.9% from the yr-in the past quarter.

The year-over-12 months increase in EPS can live attributed to solid pre-tax margin working leverage (28 cents contribution) and aggressive participate buybacks (19 cents contribution). This became partly offset through reduce revenues (seven cents terrible beget an impact on) and higher tax cost (17 cents negative influence).

Revenues of $18.76 billion lagged the Zacks Consensus evaluate of $19.10 billion and declined 2.1% on a 12 months-over-yr foundation. At constant foreign money (cc), revenues remained flat.

IBM mentioned that signings plunged 21% to $eight billion. features backlog declined three% from the yr-ago quarter to $113 billion.

Geographic revenue particulars

Revenues from Americas inched up 1%, pushed with the aid of continued increase in Canada and Latin the united states and modest growth in the u.s..

Europe, center-East and Africa reduced 2% from the yr-in the past quarter, driven through decline in Germany and France, partially offset by means of boom in Spain and the UK.

Asia-Pacific revenues declined 1% on a year-over-year basis with modest growth in Japan.

Strategic Imperatives boom Continues

Strategic Imperatives (cloud, analytics, mobility and protection) grew 7% at cc from the year-ago quarter to $9.3 billion. safety revenues surged 34%. On a trailing 12-month foundation, Strategic Imperatives revenues were $39.5 billion, up 13% (11% at cc).

Cloud revenues surged 13% from the yr-ago quarter to $four.6 billion. The annual hasten rate for cloud as-a-provider revenues multiplied 24% at cc on a 12 months-over-12 months foundation to $eleven.4 billion.

Cloud revenues of $19 billion on a trailing 12-month foundation elevated 20% (18% at cc) and now accounts for 24% of IBM’s total revenues.

Cognitive Revenues Decline

Cognitive options’ revenues-exterior reduced 5.7% year over year (down 5% at cc) to $four.15 billion. Segmental revenues touching on Strategic Imperatives and Cloud declined four% and a yoke of%, respectively. Cloud as-a-carrier revenue annual hasten rate became $2 billion.

options utility comprises choices in strategic verticals relish fitness, area-particular capabilities relish analytics and protection, and IBM’s emerging technologies of AI and blockchain. The segment besides contains choices that address horizontal domains relish collaboration, commerce and ability. solutions utility revenues reduced 3% year over 12 months in the quarter.

IBM brought up that in commerce zone the infusion of AI into choices relish customer journey analytics helped SaaS signings to grow double digit in the quarter. The fresh launch of Notes Domino edition 10, which is optimized for cellular, and supports JavaScript and node.js will boost increase collaboration in 2019.

Transaction Processing utility contains software that runs mission-essential workloads, leveraging IBM’s hardware platforms. Revenues fell 8% on a yr-over-12 months foundation.

IBM witnessed increase in trade verticals relish fitness, key areas of analytics and safety in the quarter. Watson health witnessed extensive-based mostly boom in Payer, provider, Imaging and being Sciences domains.

all the course through the quarter, the Sugar.IQ utility, developed through Medtronic in partnership with IBM, hit the market. The software is designed to simplify and enhance every day diabetes management.

IBM brought up that analytics performed well within the quarter, driven with the aid of statistics science offerings and IBM Cloud deepest for facts providing.

during the quarter, the company introduced jaundice detection capabilities and launched modern Watson features on the IBM Cloud deepest platform.

safety growth changed into pushed by means of offerings in orchestration, data protection and endpoint management.

In blockchain, IBM meals believe community for food safeguard went live in the quarter. Reatiler Carrefour joined IBM’s blockchain network. The company additionally collectively introduced TradeLens with Maersk that addresses inefficiencies in the world give chain. IBM currently supports 75 active blockchain networks.

international traffic capabilities Revenues boost

Revenues from world traffic functions-external segment had been $4.13 billion, up 0.9% from the 12 months-in the past quarter (up three% at cc). Segmental revenues referring to Strategic Imperatives grew 9%. Cloud apply surged 18%. Cloud as-a-service income annual hasten cost became $1.9 billion.

software management revenues declined 1% from the year-in the past quarter. despite the fact, global manner functions revenues climbed 2%. moreover, Consulting revenues elevated 7% yr over yr, pushed via strong efficiency from IBM’s digital enterprise.

expertise features & Cloud structures: Revenues Dip

Revenues from expertise services & Cloud structures-exterior lowered 2% from the 12 months-in the past quarter (flat at cc) to $8.29 billion. Segmental revenues concerning Strategic Imperatives advanced sixteen%, pushed with the aid of hybrid cloud capabilities. Cloud surged 22% from the year-in the past quarter. Cloud as-a-provider revenue annual hasten fee changed into $7.5 billion.

Integration utility increased 1% from the 12 months-in the past quarter. sum through the quarter, ninety five organizations worldwide chosen IBM Cloud private offering. Infrastructure services revenues additionally improved 1% on a year-over-12 months basis.

despite the fact, Technical profit features revenues diminished three% from the year-ago quarter.

vigor & z14 drive systems Revenues

systems revenues multiplied 0.9% on a year-over-yr groundwork (up 2% at cc) to $1.seventy four billion. Segmental revenues relating Strategic Imperatives surged 5%, whereas Cloud revenues declined eight%.

IBM Z revenues extended 6% yr over year on greater than 20% MIPS increase, pushed by course of vast-based adoption of the z14 mainframe.

vigor revenues multiplied 17% from the 12 months-in the past quarter. right through the quarter, IBM launched its subsequent technology POWER9 processors for midrange and excessive-conclusion techniques which are designed for dealing with superior analytics, cloud environments and facts-intensive workloads in AI, HANA, and UNIX markets.

IBM besides brought modern offerings optimizing both hardware and software for AI. management believes that items relish PowerAI imaginative and prescient and PowerAI commercial enterprise will profit pressure modern client adoption.

youngsters, storage hardware revenues declined 6% because of vulnerable performance within the midrange and extreme conclusion, partially offset with the aid of mighty growth in sum flash Arrays. IBM mentioned that pricing power within the immensely aggressive storage market is hurting revenues. The company announced its modern FlashSystems with subsequent technology NVMe technology sum through the quarter.

working techniques application revenues declined 4%, while systems Hardware superior four% from the year-in the past quarter.

ultimately, world Financing (includes financing and used machine revenue) revenues decreased 9.1% at cc to $388 million.

operating details

Non-GAAP vulgar margin remained unchanged from the yr-in the past quarter at 47.four%. This turned into IBM’s premier vulgar margin efficiency in years and changed into essentially pushed by a hundred and sixty basis aspects (bps) growth in services margin. despite the fact, unfavorable combine in z14 mainframe and utility wholly offset this enlargement.

working rate declined 4% 12 months over year, as a result of consciousness of acquisition synergies and enhancing operational efficiencies. IBM continues to invest in speedy starting to live fields relish hybrid cloud, synthetic intelligence (AI), protection and blockchain.

Pre-tax margin from continuing operations multiplied 50 bps on a year-over-12 months groundwork to 19.2%.

Cognitive solutions and world enterprise features segment pre-tax margins improved one hundred ninety bps and 320 bps, respectively, on a 12 months-over-yr basis. youngsters, technology capabilities & Cloud structures side pre-tax margin reduced in size one hundred bps.

methods pre-tax income became $209 million down 38% 12 months over yr. world Financing segment pre-tax earnings jumped 26.7% to $308 million.

balance Sheet & cash stream details

IBM ended third-quarter 2018 with $14.70 billion in complete money and marketable securities in comparison with $11.ninety three billion at the conclusion of 2d-quarter 2018. complete debt (together with world financing) was $46.9 billion, up $1.four million from the previous quarter.

IBM reported money stream from operations (except for global Financing receivables) of $3.1 billion and generated free money flux of $2.2 billion in the quarter.

within the pronounced quarter, the traffic back $2.1 billion to shareholders via dividends and participate repurchases. on the halt of the quarter, the enterprise had $1.four billion closing under current buyback authorization.

suggestions

IBM reiterated EPS forecast for 2018. Non-GAAP EPS is anticipated to live at the least $13.eighty.

IBM noiseless anticipates 2018 free money circulate of $12 billion.

Story continues

How beget Estimates Been relocating when you deem that Then?

in the past month, traders beget witnessed a downward vogue in sparkling estimates.

VGM ratings

at this time, IBM has a regular boom score of C, though it's lagging a bit of on the Momentum ranking entrance with a D. besides the fact that children, the inventory turned into allotted a grade of A on the price facet, putting it within the appropriate quintile for this funding strategy.

basic, the stock has an aggregate VGM ranking of B. if you aren't focused on one method, this score is the one live sure to live interested in.

Outlook

Estimates beget been widely trending downward for the inventory, and the magnitude of those revisions shows a downward shift. chiefly, IBM has a Zacks Rank #3 (cling). They foretell an in-line revert from the stock within the following yoke of months.

want the newest techniques from Zacks investment analysis? nowadays, which you could download 7 surest shares for the subsequent 30 Days. click on to earn this free file foreign enterprise Machines organisation (IBM) : Free inventory analysis record To read this text on Zacks.com click right here. Zacks investment research


IBM predicts AI will create a modern breed of marketers | killexams.com existent Questions and Pass4sure dumps

as the calendar flips, marketers will seem to live to find modern how to profit an facet. As IBM predicts, a modern breed of entrepreneurs is rising with the advocate of synthetic intelligence.

IBM Watson advertising released its 2019 advertising and marketing tendencies file, highlighting traits within the business. The group predicted that in the emotion economic climate, buyers will likely beget interaction extra with manufacturers which are genuine and deliver on their convictions.

That may no longer live a modern construction by itself, but IBM believes AI and computing device getting to know will manufacture hyper-personalization a verisimilitude because the proliferation of facts and the streamlining of marketing stacks will permit marketers to deliver customized content material at a massive scale.

Michael Trapani, marketing software director for IBM Watson advertising, said emotion and personal connection doesn't beget to live in battle with the seemingly bloodless and calculating world of AI.

"Making a reference to a company will at sum times live a really human, emotion-driven technique for consumers. where AI and computing device getting to know are available is the competence to superior inform entrepreneurs in accordance with uncovering insights about your shoppers that a human could no longer contemplate or locate. these insights then enable human marketers to boost better and more material artistic after which deliver it at scale across channels to individual patrons," observed Trapani.

in line with the document, the expected inflow of AI will lead to emergence of 'consulgencies,' as the should construct out abilities in client event analytics and mobile apps will contemplate the capabilities of consultancies and companies converge.

"many of the company partners that work with IBM beget added or elevated their technical and facts integration and consulting capabilities. Many are besides piteous to more of consultative arrangement, focused more on hours and effects than on media buys. As for AI, sum agencies regardless of size are exploring uses of AI to resolve their customer's advertising and customer challenges, even if it is building chatbots or interactive experiences," Trapani talked about.

"companies are besides more and more the exercise of off-the-shelf AI-based mostly advertising and marketing options that can foretell premiere customer journeys, determine purchasers surely to churn, and identify and foretell where consumers are struggling to finished goals in an online event."

among the many predictions embrace the boom of the director of advertising and marketing information role and the emergence of the 'martecheter,' a greater tech-savvy marketer. The document additionally says that, traditionally, the highest trait benefits to a entrepreneurs beget been finances, equipment, and talent, but that order will flip as the industry moves far from hiring single-professional marketers given the stress on client taste and advertising and marketing technologies.

The internal workings of the entire C-suite might contemplate a transformation, too. according to the file, the focal point on client centricity will create extra alternatives for commerce and digital groups to combination and scan with customer data.


Metro footwear faucets IBM Watson For Digital Commerce | killexams.com existent Questions and Pass4sure dumps

ibm shoes

Metro footwear Ltd, one in every of India’s leading multi-manufacturer sneakers chains, is launching a brand modern Digital Commerce platform powered with the aid of Watson client appointment hosted on IBM Cloud. this could encompass IBM Watson Order management and Commerce for seamless digital engagement. Working with IBM company companion CEBS international, IBM solutions will now not only assist drive sophisticated customer experiences and modern ranges of solace but deliver efficiencies to the supply chain.

With a national footprint of 350 actual showrooms, an expanding manufacturer portfolio and altering customer preferences, Metro shoes Ltd become facing challenges in managing orders coming from multiple online platforms.  earlier dealt with by course of unreliable application, resulting in need of visibility of true-time records of sales, stock vicinity and returns. apart from its stock management challenges, Metro footwear Ltd crucial to increase online presence for a few of their general interior manufacturers which were getting low visibility impacting universal income.

“know-how is redefining customer appointment and may live the key differentiator for retail brands of the longer term. We’re excited to collaborate with IBM and CEBS to embark on their digital transformation journey,” said Alisha Malik, vice chairman, Digital, Metro footwear. “With IBM’s expertise within the omni-channel commerce and retail house, they are assured that these adjustments will no longer handiest profit accelerate the execution of their approach, however besides provide us an zone over competitors. At Metro shoes, they strongly believe that the modern solution will increase the typical user experience, thereby increasing revisits, traffic and loyalty.”

With IBM, Metro shoes Ltd can profit modern levels of consumer perception, which may besides live used to customise the on-line taste for each and every vacationer as they navigate in the course of the web page. Delivered via a solitary platform, Metro shoes can live in a position to exhibit sum of its brands and advocate specific gadgets in line with insights shared by using consumers. This customized event will encompass modern and convenient fulfillmentoptions corresponding to purchase on-line, pick up in save, reserve in support and straightforward returns. because of these modern capabilities, Metro footwear should live in a position to raise every vacationer’s adventure on the website by course of enabling commerce practitioners with cognitive apparatus which profit them convey omni-channel experiences that interact consumers and pressure income.

With IBM’s know-how capabilities and CEBS talents with marketplace integration, Metro shoes as a company/seller will besides live capable of combine with greater than 14 e-marketplaces relish Amazon, Flipkart and different main portals with a centralized manner and stock engine to permit Metro to scale as much as the needs of a starting to live market enterprise. further, IBM Cloud will advocate elevate the competence to configure hefty workloads and thereby carry efficiency required for top usage sum the course through the searching season.

speaking concerning the collaboration, Nishant Kalra, enterprise unit leader – IBM Watson consumer appointment - India/South Asiaadded, “IBM is on the forefront of assisting shoppers embody more recent ways to work and digitally transforming the course they engage with their halt shoppers. they are satisfied to live a participate of Metro footwear’ digital transformation adventure by means of supplying sophisticated digital commerce adventure, leveraging the retailers by using merging them with on-line, and at final driving manufacturer advocacy. IBM in affiliation with CEBS will enable abysmal innovation, sooner-go-to-market and streamline processes for scalability.”

The IBM platform will create a bridge between its online and offline traffic which the retailer prior to now lacked. With the brand modern built-in solitary view, Metro footwear sooner or later should live in a position to exercise insights received from the digital realm to design particular providing for valued clientele as they walk into any of their retailers. in consequence, they can select note what consumers desire, manufacture sure availability when and where they want it and even study pass promoting and upselling throughout their quite a lot of manufacturers.

For Metro footwear, IBM Watson Order management and Commerce solutions can pave course for IBM’s cognitive applied sciences to carry insights that profit them deliver clients with customized options and an better user event –from click to birth.

“With over 15 years of taste in developing e-company equipment, CEBS has been a relied on options provider and companion for companies across the globe,”talked about Satish Swaroop, President, CEBS global. Their useful and multifaceted utility options paired with IBM’s abysmal expertise skills will give Metro shoes a true-time, centralized apparatus for customer administration.”


P8010-004 IBM Commerce Solutions Order Mgmt Technical Mastery Test v1

Study lead Prepared by Killexams.com IBM Dumps Experts


Killexams.com P8010-004 Dumps and existent Questions

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P8010-004 exam Dumps Source : IBM Commerce Solutions Order Mgmt Technical Mastery Test v1

Test Code : P8010-004
Test denomination : IBM Commerce Solutions Order Mgmt Technical Mastery Test v1
Vendor denomination : IBM
exam questions : 30 existent Questions

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Modeled larval connectivity of a multi-species reef fish and invertebrate assemblage off the coast of Moloka‘i, Hawai‘i | killexams.com existent questions and Pass4sure dumps

Introduction

Knowledge of population connectivity is necessary for effectual management in marine environments (Mitarai, Siegel & Winters, 2008; Botsford et al., 2009; Toonen et al., 2011). For many species of marine invertebrate and reef fish, dispersal is mostly limited to the pelagic larval life stage. Therefore, an understanding of larval dispersal patterns is faultfinding for studying population dynamics, connectivity, and conservation in the marine environment (Jones, Srinivasan & Almany, 2007; Lipcius et al., 2008; Gaines et al., 2010; Toonen et al., 2011). Many coastal and reef species beget a bi-phasic life history in which adults parade limited geographic range and elevated site fidelity, while larvae are pelagic and highly mobile (Thorson, 1950; Scheltema, 1971; Strathmann, 1993; Marshall et al., 2012). This life history strategy is not only common to sessile invertebrates such as corals or limpets; many reef fish species beget been shown to beget a home range of <1 km as adults (Meyer et al., 2000; Meyer, Papastamatiou & Clark, 2010). Depending on species, the mobile planktonic stage can final from hours to months and has the potential to transport larvae up to hundreds of kilometers away from a site of origin (Scheltema, 1971; Richmond, 1987; Shanks, 2009). information of larval dispersal patterns can live used to inform effectual management, such as marine spatial management strategies that sustain source populations of breeding individuals capable of dispersing offspring to other areas.

Both biological and physical factors impact larval dispersal, although the relative importance of these factors is likely variable among species and sites and remains debated (Levin, 2006; Paris, Chérubin & Cowen, 2007; Cowen & Sponaugle, 2009; White et al., 2010). In situ data on pelagic larvae are sparse; marine organisms at this life stage are difficult to capture and identify, and are typically create in low densities across big areas of the open ocean (Clarke, 1991; Wren & Kobayashi, 2016). A variety of genetic and chemistry techniques beget therefore been developed to evaluate larval connectivity (Gillanders, 2005; Leis, Siebeck & Dixson, 2011; Toonen et al., 2011; Johnson et al., 2018). Computer models informed by domain and laboratory data beget besides become a valuable utensil for estimating larval dispersal and population connectivity (Paris, Chérubin & Cowen, 2007; Botsford et al., 2009; Sponaugle et al., 2012; Kough, Paris & Butler IV, 2013; Wood et al., 2014). Individual-based models, or IBMs, can incorporate both biological and physical factors known to influence larval movement. Pelagic larval duration (PLD), for example, is the amount of time a larva spends in the water column before settlement and can vary widely among or even within species ( Toonen & Pawlik, 2001). PLD affects how far an individual can live successfully transported by ocean currents, and so is expected to directly paw connectivity patterns (Siegel et al., 2003; Shanks, 2009; Dawson et al., 2014). In addition to PLD, adult reproductive strategy and timing (Carson et al., 2010; Portnoy et al., 2013), fecundity (Castorani et al., 2017), larval mortality (Vikebøet al., 2007), and larval developmental, morphological, and behavioral characteristics (Paris, Chérubin & Cowen, 2007) may sum play a role in shaping connectivity patterns. Physical factors such as temperature, bathymetry, and current direction can besides substantially influence connectivity (Cowen & Sponaugle, 2009). In this study, they incorporated both biotic and abiotic components in an IBM coupled with an oceanographic model to foretell fine-scale patterns of larval exchange around the island of Moloka‘i in the Hawaiian archipelago.

The main Hawaiian Islands are located in the middle of the North Pacific Subtropical Gyre, and are bordered by the North Hawaiian Ridge current along the northern coasts of the islands and the Hawaii Lee Current along the southern coasts, both of which hasten east to west and are driven by the current easterly trade winds (Lumpkin, 1998; Friedlander et al., 2005). The Hawai‘i Lee Countercurrent, which runs along the southern perimeter of the chain, flows west to east (Lumpkin, 1998). The pattern of mesoscale eddies around the islands is tangled and varies seasonally (Friedlander et al., 2005; Vaz et al., 2013).

Hawaiian marine communities physiognomy unprecedented pressures, including coastal development, overexploitation, disease, and increasing temperature and acidification due to climate change (Smith, 1993; Lowe, 1995; Coles & Brown, 2003; Friedlander et al., 2003; Friedlander et al., 2005; Aeby, 2006). Declines in Hawaiian marine resources squabble for implementation of a more holistic approach than traditional single-species maximum sustainable defer techniques, which beget proven ineffective (Goodyear, 1996; Hilborn, 2011). There is a general movement toward the exercise of ecosystem-based management, which requires information of ecosystem structure and connectivity patterns to establish and manage marine spatial planning areas (Slocombe, 1993; Browman et al., 2004; Pikitch et al., 2004; Arkema, Abramson & Dewsbury, 2006). Kalaupapa National Historical Park is a federal marine protected zone (MPA) located on the north shore of Moloka‘i, an island in the Maui Nui tangled of the Hawaiian archipelago, that includes submerged lands and waters up to 1 4 mile offshore (NOAA, 2009). At least five IUCN red-listed coral species beget been identified within this area (Kenyon, Maragos & Fenner, 2011), and in 2010 the Park showed the greatest fish biomass and species diversity out of four Hawaiian National Parks surveyed (Beets, Brown & Friedlander, 2010). One of the major benefits expected of MPAs is that the protected waters within the zone provide a source of larval spillover to other sites on the island, seeding these areas for commercial, recreational, and subsistence fishing (McClanahan & Mangi, 2000; Halpern & Warner, 2003; Lester et al., 2009).

In this study, they used a Lagrangian particle-tracking IBM (Wong-Ala et al., 2018) to simulate larval dispersal around Moloka‘i and to evaluate the larval exchange among sites at the scale of an individual island. They beget parameterized their model with biological data for eleven species covering a breadth of Hawaiian reef species life histories (e.g., habitat preferences, larval behaviors, and pelagic larval durations, Table 1), and of interest to both the local community and resource managers. Their goals were to examine patterns of species-specific connectivity, characterize the location and relative magnitude of connections around Moloka‘i, narrate sites of potential management relevance, and address the question of whether Kalaupapa National Historical Park provides larval spillover for adjacent sites on Moloka‘i, or connections to the adjacent islands of Hawai‘i, Maui, O‘ahu, Lana‘i, and Kaho‘olawe.

Table 1:

Target taxa selected for the study, based on cultural, ecological, and/or economic importance.

PLD = pelagic larval duration. Short dispersers (3–25 day minimum PLD) in white, medium dispersers (30–50 day minimum PLD) in light gray, and long dispersers (140–270 day minimum PLD) in shadowy gray. Spawn season and timing from traditional ecological information shared by cultural practitioners on the island. Asterisk indicates that congener-level data was used. Commonname Scientific name Spawn type # of larvae spawned Spawningday of year Spawning hour of day Spawning moon phase Larval depth (m) PLD (days) Habitat ’Opihi/ Limpet Cellana spp. Broadcast1 861,300 1–60 & 121–181 – New 0–5 3–181,2 Intertidal1 Ko’a/ Cauliflower coral Pocillopora meandrina Broadcast3 1,671,840 91–151 07:15–08:00 Full 0–54 5–90*5 Reef He’e/ Octopus Octopus cyanea Benthic6 1,392,096 1–360 – – 50–100 216 Reef, rubble7 Moi/ Pacific threadfin Polydactylus sexfilis Broadcast 1,004,640 152–243 – – 50–1008 259 Sand10 Uhu uliuli/ Spectacled parrotfish Chlorurus perspicillatus Broadcast 1,404,792 152–212 – – 0–120*11 30*12 Reef10 Uhu palukaluka/ Reddlip parrotfish Scarus rubroviolaceus Broadcast 1,404,792 152–212 – – 0–120*11 30*12 Rock, reef10 Kumu/ Whitesaddle Goatfish Parupeneus porphyreus Broadcast 1,071,252 32–90 – – 0–50*11 41–56*12 Sand, rock, reef10 Kole/ Spotted surgeonfish Ctenochaetus strigosus Broadcast 1,177,200 60–120 – – 50–10011 50*12 Rock, reef, rubble10 ‘Ōmilu/ Bluefin trevally Caranx melampygus Broadcast 1,310,616 121–243 – – 0–80*11 140*13,14 Sand, reef10 Ulua/ Giant trevally Caranx ignoblis Broadcast 1,151,040 152–243 – Full 0–80*11 14013,14 Sand, rock, reef10 Ula/ Spiny lobster Panulirus spp. Benthic15 1,573,248 152–243 – – 50–10016 27017 Rock, pavement16 Methods Circulation model

We selected the hydrodynamic model MITgcm, which is designed for the study of dynamical processes in the ocean on a horizontal scale. This model solves incompressible Navier–Stokes equations to narrate the motion of viscous fluid on a sphere, discretized using a finite-volume technique (Marshall et al., 1997). The one-km resolution MITgcm domain for this study extends from 198.2°E to 206°E and from 17°N to 22.2°N, an zone that includes the islands of Moloka‘i, Maui, Lana‘i, Kaho‘olawe, O‘ahu, and Hawai‘i. While Ni‘ihau and southern Kaua’i besides Fall within the domain, they discarded connectivity to these islands because they equivocate within the 0.5° border zone of the current model. border conditions are enforced over 20 grid points on sum sides of the model domain. Vertically, the model is divided into 50 layers that increase in thickness with depth, from five m at the surface (0.0–5.0 m) to 510 m at the base (4,470 –4,980 m). Model variables were initialized using the output of a Hybrid Coordinate Ocean Model (HYCOM) at a horizontal resolution of 0.04° (∼four km) configured for the main Hawaiian Islands, using the general Bathymetric Chart of the Oceans database (GEBCO, 1/60°) (Jia et al., 2011).

The simulation runs from March 31st, 2011 to July 30th, 2013 with a temporal resolution of 24 h and shows seasonal eddies as well as persistent mesoscale features (Fig. S1). They finish not embrace tides in the model due to temporal resolution. Their model term represents a neutral ocean state; no El Niño or La Niña events occurred during this time period. To ground-truth the circulation model, they compared surface current output to real-time trajectories of surface drifters from the GDP Drifter Data Assembly heart (Fig. S2) (Elipot et al., 2016), as well as other current models of the zone (Wren et al., 2016; Storlazzi et al., 2017).

Biological model

To simulate larval dispersal, they used a modified version of the Wong-Ala et al. (2018) IBM, a 3D Lagrangian particle-tracking model written in the R programming language (R Core Team, 2017). The model takes the aforementioned MITgcm current products as input, as well as shoreline shapefiles extracted from the plenary resolution NOAA Global Self-consistent Hierarchical High-resolution Geography database, v2.3.0 (Wessel & Smith, 1996). Their model included 65 land masses within the geographic domain, the largest being the island of Hawai‘i and the smallest being Pu‘uki‘i Island, a 1.5-acre islet off the eastern coast of Maui. To model depth, they used the one arc-minute-resolution ETOPO1 bathymetry, extracted using the R package ‘marmap’ (Amante & Eakins, 2009; Pante & Simon-Bouhet, 2013).

Each species was simulated with a sever model run. Larvae were modeled from spawning to settlement and were transported at each timestep (t = 2 h) by advection-diffusion transport. This transport consisted of (1) advective displacement caused by water flow, consisting of east (u) and north (v) velocities read from daily MITgcm files, and (2) additional random-walk displacement, using a diffusion constant of 0.2 m2/s−1 (Lowe et al., 2009). perpendicular velocities (w) were not implemented by the model; details of perpendicular larval movement are described below. Advection was interpolated between data points at each timestep using an Eulerian 2D barycentric interpolation method. They chose this implementation over a more computationally intensive interpolation manner (i.e., fourth-order Runge–Kutta) because they did not observe a dissimilarity at this timestep length. Biological processes modeled embrace PLD, reproduction timing and location, mortality, and ontogenetic changes in perpendicular distribution; these qualities were parameterized via species-specific data obtained from previous studies and from the local fishing and management community (Table 1).

Larvae were released from habitat-specific spawning sites and were considered settled if they fell within a roughly one-km contour around reef or intertidal habitat at the halt of their pelagic larval duration. Distance from habitat was used rather than water depth because Penguin Bank, a relatively shallow bank to the southwest of Moloka‘i, does not portray suitable habitat for reef-associated species. PLD for each larva was a randomly assigned value between the minimum and maximum PLD for that species, and larvae were removed from the model if they had reached their PLD and were not within a settlement zone. No data on pre-competency term were available for their study species, so this parameter was not included. Mortality rates were calculated as larval half-lives; e.g., one-half of sum larvae were assumed to beget survived at one-half of the maximum PLD for that species (following Holstein, Paris & Mumby, 2014). Since their focus was on potential connectivity pathways, reproductive rates were calibrated to allow for saturation of workable settlement sites, equating from ∼900,000 to ∼1,7000,000 larvae released depending on species. Fecundity was therefore derived not from biological data, but from computational minimums.

Development, and resulting ontogenetic changes in behavior, is specific to the life history of each species. Broadcast-spawning species with weakly-swimming larvae (P. meandrina and Cellana spp., Table 1) were transported as passive particles randomly distributed between 0–5 m depth (Storlazzi, Brown & Field, 2006). Previous studies beget demonstrated that fish larvae beget a elevated degree of control over their perpendicular position in the water column (Irisson et al., 2010; Huebert, Cowen & Sponaugle, 2011). Therefore, they modeled broadcast-spawning fish species with a 24-hour passive buoyant side to simulate eggs pre-hatch, followed by a pelagic larval side with a species-specific depth distribution. For C. ignoblis, C. melampygus, P. porphyreus, C. perspicillatus, and S. rubroviolaceus, they used genus-level depth distributions (Fig. S3) obtained from the 1996 NOAA ichthyoplankton perpendicular distributions data report (Boehlert & Mundy, 1996). P. sexfilis and C. strigosus larvae were randomly distributed between 50–100 m (Boehlert, Watson & Sun, 1992). Benthic brooding species (O. cyanea and Panulirus spp.) finish not beget a passive buoyant phase, and thus were released as larvae randomly distributed between 50–100 m. At each time step, a larva’s depth was checked against bathymetry, and was assigned to the nearest available layer if the species-specific depth was not available at these coordinates.

For data-poor species, they used congener-level estimates for PLD (see Table 1). For example, there is no evaluate of larval duration for Caranx species, but in Hawai‘i peak spawning occurs in May–July and peak recruitment in August–December (Sudekum, 1984; Longenecker, Langston & Barrett, 2008). In consultation with resource managers and community members, a PLD of 140 days was chosen pending future data that indicates a more accurate pelagic period.

Habitat selection

Spawning sites were generated using data from published literature and modified after input from autochthonous Hawaiian cultural practitioners and the Moloka‘i fishing community (Fig. 1). Species-specific habitat suitability was inferred from the 2013–2016 Marine Biogeographic Assessment of the Main Hawaiian Islands (Costa & Kendall, 2016). They designated coral habitat as areas with 5–90% coral cover, or ≥1 site-specific coral species richness, for a total of 127 spawning sites on Moloka‘i. Habitat for reef invertebrates followed coral habitat, with additional sites added after community feedback for a total of 136 sites. Areas with a predicted reef fish biomass of 58–1,288 g/m2 were designated as reef fish habitat (Stamoulis et al., 2016), for a total of 109 spawning sites. Sand habitat was designated as 90–100% uncolonized for a total of 115 sites. Intertidal habitat was designated as any rocky shoreline zone not covered by sand or mud, for a total of 87 sites. Number of adults was assumed equal at sum sites. For regional analysis, they pooled sites into groups of two to 11 sites based on benthic habitat and surrounding geography (Fig. 1A). Adjacent sites were grouped if they shared the identical benthic habitat classification and current wave direction, and/or were participate of the identical reef tract.

Figure 1: Spawning sites used in the model by species. (A) C. perspicillatus, S. rubroviolaceus, P. porphyreus, C. strigosus, C. ignoblis, and C. melampygus, n = 109; (B) P. meandrina, n = 129;(C) O. cyanea and Panulirus spp., n = 136; (D) P. sexfilis, n = 115; and (E) Cellana spp., n = 87. Region names are displayed over associated spawning sites for fish species in (A). Regions are made up of two to 11 sites, grouped based on coastal geography and surrounding benthic habitat, and are designated in (A) by adjacent colored dots. Kalaupapa National Historical Park is highlighted in light green in (A). Source–sink dynamics and local retention

Dispersal distance was measured via the distm role in the R package ‘geosphere’, which calculates distance between geographical points via the Haversine formula (Hijmans, 2016). This distance, measured between spawn and settlement locations, was used to calculate dispersal kernels to examine and compare species-specific distributions. They besides measured local retention, or the percentage of successful settlers from a site that were retained at that site (i.e., settlers at site A that originated from site A/total successful settlers that originated from site A). To evaluate the role of specific sites around Moloka‘i, they besides calculated a source–sink index for each species (Holstein, Paris & Mumby, 2014; Wren et al., 2016). This index defines sites as either a source, in which a site’s successful export to other sites is greater than its import, or a sink, in which import from other sites is greater than successful export. It is calculated by dividing the dissimilarity between number of successfully exported and imported larvae by the sum of sum successfully exported and imported larvae. A value <0 indicates that a site acts as a net sink, while a value >0 indicates that a site acts as a net source. While they measured successful dispersal to adjacent islands, they did not spawn larvae from them, and therefore these islands portray exogenous sinks. For this reason, settlement to other islands was not included in source–sink index calculations.

We besides calculated settlement proportion between different regions for each species (Calabrese & Fagan, 2004). They calculated the forward settlement proportion, i.e., the proportion of settlers from a specific settlement site (s) originating from an observed source site (o), by scaling the number of successful settlers from site o settling at site s to sum successful settlers originating from site o. Forward proportion can live represented as Pso = Sos∕∑So. They besides calculated rearward settlement proportion, or the proportion of settlers from a specific source site (o) observed at settlement site (s), by scaling the number of settlers observed at site s originating from site o to sum settlers observed at site s. The rearward proportion can live represented as Pos = Sos∕∑Ss.

Graph-theoretic analysis

To quantify connections between sites, they applied graph theory to population connectivity (Treml et al., 2008; Holstein, Paris & Mumby, 2014). Graph theoretic analysis is highly scalable and can live used to examine fine-scale networks between reef sites up to broad-scale analyses between islands or archipelagos, mapping to both local and regional management needs. It besides allows for both network- and site-specific metrics, enabling the comparison of connectivity between species and habitat sites as well as highlighting potential multi-generational dispersal corridors. Graph theory besides provides a powerful utensil for spatial visualization, allowing for rapid, intuitive communication of connectivity results to researchers, managers, and the public alike. This kind of analysis can live used to model pairwise relationships between spatial data points by breaking down individual-based output into a series of nodes (habitat sites) and edges (directed connections between habitat sites). They then used these nodes and edges to examine the relative importance of each site and dispersal pathway to the greater pattern of connectivity around Moloka‘i, as well as differences in connectivity patterns between species (Treml et al., 2008; Holstein, Paris & Mumby, 2014). They used the R package ‘igraph’ to examine several measures of within-island connectivity (Csardi & Nepusz, 2006). Edge density, or the proportion of realized edges out of sum workable edges, is a multi-site measure of connectivity. Areas with a higher edge density beget more direct connections between habitat sites, and thus are more strongly connected. They measured edge density along and between the north, south, east, and west coasts of Moloka‘i to examine workable population structure and degree of exchange among the marine resources of local communities.

The distribution of shortest path length is besides informative for comparing overall connectivity. In graph theory, a shortest path is the minimum number of steps needed to connect two sites. For example, two sites that exchange larvae in either direction are connected by a shortest path of one, whereas if they both participate larvae with an intermediate site but not with each other, they are connected by a shortest path of two. In a biological context, shortest path can correspond to number of generations needed for exchange: sites with a shortest path of two require two generations to manufacture a connection. middling shortest path, therefore, is a descriptive statistic to evaluate connectivity of a network. If two sites are unconnected, it is workable to beget infinite-length shortest paths; here, these boundless values were notable but not included in final analyses.

Networks can besides live broken in connected components (Csardi & Nepusz, 2006). A weakly connected component (WCC) is a subgraph in which sum nodes are not reachable by other nodes. A network split into multiple WCCs indicates sever populations that finish not exchange any individuals, and a big number of WCCs indicates a low degree of island-wide connectivity. A strongly connected component (SCC) is a subgraph in which sum nodes are directly connected and indicates a elevated degree of connectivity. A region with many minuscule SCCs can indicate elevated local connectivity but low island-wide connectivity. Furthermore, component analysis can identify nick nodes, or nodes that, if removed, smash a network into multiple WCCs. Pinpointing these nick nodes can identify potential well-known sites for preserving a population’s connectivity, and could inform predictions about the impact of site loss (e.g., a large-scale coral bleaching event) on overall connectivity.

On a regional scale, it is well-known to note which sites are exporting larvae to, or importing larvae from, other sites. To this end, they examined in-degree and out-degree for each region. In-degree refers to the number of inward-directed edges to a specific node, or how many other sites provide larvae into site ‘A’. Out-degree refers to the number of outward-directed edges from a specific node, or how many sites receive larvae from site ‘A’. Habitat sites with a elevated out-degree seed a big number of other sites, and indicate potentially well-known larval sources, while habitat sites with a low in-degree rely on a limited number of larval sources and may therefore live relative on connections with these few other sites to maintain population size. Finally, betweenness centrality (BC) refers to the number of shortest paths that pass through a given node, and may therefore indicate connectivity pathways or ‘chokepoints’ that are well-known to overall connectivity on a multigenerational timescale. BC was weighted with the proportion of dispersal as described in the preceding section. They calculated in-degree, out-degree, and weighted betweenness centrality for each region in the network for each species.

As with the source–sink index, they did not embrace sites on islands other than Moloka‘i in their calculations of edge density, shortest paths, connected components, nick nodes, in- and out-degree, or betweenness centrality in order to focus on within-island patterns of connectivity.

Results Effects of biological parameters on fine-scale connectivity patterns

The species-specific parameters that were available to parameterize the dispersal models substantially influenced final output (Fig. 2). The proportion of successful settlers (either to Moloka‘i or to neighboring islands) varied widely by species, from 2% (Panulirus spp.) to 25% (Cellana spp.). Minimum pelagic duration and settlement success were negatively correlated (e.g., an estimated −0.79 Pearson correlation coefficient). Species modeled with batch spawning at a specific moon side and/or time of day (Cellana spp., P. meandrina, and C. ignoblis) displayed slightly higher settlement success than similar species modeled with constant spawning over specific months. On a smaller scale, they besides examined middling site-scale local retention, comparing only retention to the spawning site versus other sites on Moloka‘i (Fig. 2). Local retention was lowest for Caranx spp. (<1%) and highest for O. cyanea and P. sexfilis (8.1% and 10%, respectively).

Figure 2: Summary statistics for each species network. Summary statistics are displayed in order of increasing minimum pelagic larval duration from left to right. Heatmap colors are based on normalized values from 0–1 for each analysis. Successful settlement refers to the proportion of larvae settled out of the total number of larvae spawned. Local retention is measured as the proportion of larvae spawned from a site that settle at the identical site. Shortest path is measured as the minimum number of steps needed to connect two sites. Strongly connected sites refers to the proportion of sites in a network that belong to a strongly connected component. spell dispersal distance is measured in kilometers from spawn site to settlement site.

We measured network-wide connectivity via distribution of shortest paths, or the minimum number of steps between a given two nodes in a network, only including sites on Moloka‘i (Fig. 2). O. cyanea and P. sexfilis showed the smallest shortest paths overall, meaning that on average, it would select fewer generations for these species to demographically bridge any given pair of sites. Using maximum shortest path, it could select these species three generations at most to connect sites. Cellana spp. and P. meandrina, by comparison, could select as many as five generations. Other medium- and long-dispersing species showed relatively equivalent shortest-path distributions, with trevally species showing the highest spell path length and therefore the lowest island-scale connectivity.

The number and size of weakly-connected and strongly-connected components in a network is besides an informative measure of connectivity (Fig. 2). No species in their study group was broken into multiple weakly-connected components; however, there were species-specific patterns of strongly connected sites. O. cyanea and P. sexfilis were the most strongly connected, with sum sites in the network falling into a solitary SCC. Cellana spp. and P. meandrina each had approximately 60% of sites included in a SCC, but both demonstrate fragmentation with seven and six SCCs respectively, ranging in size from two to 22 sites. This SCC pattern suggests low global connectivity but elevated local connectivity for these species. Medium and long dispersers showed larger connected components; 70% of parrotfish sites fell within two SCCs; 40% of P. porphyreus sites fell within two SCCs; 70% of C. strigosus sites, 55% of C. melampygus sites, and 40% of Panulirus sites fell within a solitary SCC. In contrast, only 26% of C. ignoblis sites fell within a solitary SCC. It is besides well-known to note that the lower connectivity scores observed in long-dispersing species likely reflect a larger scale of connectivity. Species with a shorter PLD are highly connected at reef and island levels but may demonstrate weaker connections between islands. Species with a longer PLD, such as trevally or spiny lobster, are likely more highly connected at inter-island scales which reflects the lower connectivity scores per island shown here.

Figure 3: Dispersal distance density kernels. Dispersal distance is combined across species by minimum pelagic larval duration (PLD) length in days (short, medium, or long). Most short dispersers settle nearby to home, while few long dispersers are retained at or near their spawning sites.

Minimum PLD was positively correlated with spell dispersal distance (e.g., an estimated 0.88 Pearson correlation coefficient with minimum pelagic duration loge-transformed to linearize the relationship), and dispersal kernels differed between species that are short dispersers (3–25 days), medium dispersers (30–50 days), or long dispersers (140–270 days) (Fig. 3). Short dispersers travelled a spell distance of 24.06 ± 31.33 km, medium dispersers travelled a spell distance of 52.71 ± 40.37 km, and long dispersers travelled the farthest, at a spell of 89.41 ± 41.43 km. However, regardless of PLD, there were essentially two peaks of spell dispersal: a short-distance peak of <30 km, and a long-distance peak of roughly 50–125 km (Fig. 3). The short-distance peak largely represents larvae that settle back to Moloka‘i, while the long-distance peak largely represents settlement to other islands; the low point between them corresponds to deep-water channels between islands, i.e., unsuitable habitat for settlement. Median dispersal distance for short dispersers was substantially less than the spell at 8.85 km, indicating that most of these larvae settled relatively nearby to their spawning sites, with rare long-distance dispersal events bringing up the average. Median distance for medium (54.22 km) and long (91.57 km) dispersers was closer to the mean, indicating more even distance distributions and thus a higher probability of long-distance dispersal for these species. Maximum dispersal distance varied between ∼150–180 km depending on species, except for the spiny lobster Panulirus spp., with a PLD of 270 d and a maximum dispersal distance of approximately 300 km.

Settlement to Moloka‘i and other islands in the archipelago

Different species showed different forward settlement proportion to adjacent islands (Fig. 4), although every species in the study group successfully settled back to Moloka‘i. P. meandrina showed the highest percentage of island-scale local retention (82%), while C. ignoblis showed the lowest (7%). An middling of 74% of larvae from short-dispersing species settled back to Moloka‘i, as compared to an middling of 41% of medium dispersers and 9% of long dispersers. A big proportion of larvae besides settled to O‘ahu, with longer PLDs resulting in greater proportions, ranging from 14% of O. cyanea to 88% of C. ignoblis. Moloka‘i and O‘ahu were the most commonly settled islands by percentage. Overall, settlement from Moloka‘i to Lana‘i, Maui, Kaho‘olawe, and Hawai‘i was rather lower. Larvae of every species settled to Lana‘i, and settlement to this island made up less than 5% of settled larvae across sum species. Likewise, settlement to Maui made up less than 7% of settlement across species, with P. meandrina as the only species that had no successful paths from Moloka‘i to Maui. Settlement to Kaho‘olawe and Hawai‘i was less common, with the exception of Panulirus spp., which had 16% of sum settled larvae on Hawai‘i.

Figure 4: Forward settlement from Moloka’i to other islands. Proportion of simulated larvae settled to each island from Moloka‘i by species, organized in order of increasing minimum pelagic larval duration from left to right.

We besides examined coast-specific patterns of rearward settlement proportion to other islands, discarding connections with a very low proportion of larvae (<0.1% of total larvae of that species settling to other islands). Averaged across species, 83% of larvae settling to O‘ahu from Moloka‘i were spawned on the north shore of Moloka‘i, with 12% spawned on the west shore (Fig. S4). Spawning sites on the east and south shores contributed <5% of sum larvae settling to O‘ahu from Moloka‘i. The east and south shores of Moloka‘i had the highest middling percentage of larvae settling to Lana‘i from Moloka‘i, at 78% and 20% respectively, and to Kaho‘olawe from Moloka‘i at 63% and 34%. Of the species that settled to Maui from Moloka‘i, on middling most were spawned on the east (53%) or north (39%) shores, as were the species that settled to Hawai‘i Island from Moloka‘i (22% east, 76% north). These patterns indicate that multiple coasts of Moloka‘i beget the potential to export larvae to neighboring islands.

Temporal settlement profiles besides varied by species (Fig. 5). Species modeled with moon-phase spawning and relatively short settlement windows (Cellana spp. and C. ignoblis) were characterized by discrete settlement pulses, whereas other species showed settlement over a broader term of time. Some species besides showed distinctive patterns of settlement to other islands; their model suggests specific windows when long-distance dispersal is possible, as well as times of year when local retention is maximized (Fig. 5).

Figure 5: Species-specific temporal recruitment patterns. Proportion densities of settlement to specific islands from Moloka‘i based on day of year settled, by species. Rare dispersal events (e.g., Maui or Lana‘i for Cellana spp.) appear as narrow spikes, while broad distributions generally indicate more common settlement pathways. Regional patterns of connectivity in Moloka‘i coastal waters

Within Moloka‘i, their model predicts that coast-specific population structure is likely; averaged across sum species, 84% of individuals settled back to the identical coast on which they were spawned rather than a different coast on Moloka‘i. Excluding connections with a very low proportion of larvae (<0.1% of total larvae of that species that settled to Moloka‘i), they create that the proportion of coast-scale local retention was generally higher than dispersal to another coast, with the exception of the west coast (Fig. 6A). The north and south coasts had a elevated degree of local retention in every species except for the long-dispersing Panulirus spp., and the east coast besides had elevated local retention overall. Between coasts, a elevated proportion of larvae that spawned on the west coast settled on the north coast, and a lesser amount of larvae were exchanged from the east to south and from the north to east. With a few species-specific exceptions, larval exchange between other coasts of Moloka‘i was negligible.

Figure 6: Coast-by-coast patterns of connectivity on Moloka‘i. (A) middling rearward settlement proportion by species per pair of coastlines, calculated by the number of larvae settling at site s from site o divided by sum settled larvae at site s. Directional coastline pairs (Spawn > Settlement) are ordered from left to right by increasing median settlement proportion. (B) Heatmap of edge density for coast-specific networks by species. Density is calculated by the number of sum realized paths out of total workable paths, disregarding directionality.

We besides calculated edge density, including sum connections between coasts on Moloka‘i regardless of settlement proportion (Fig. 6B). The eastern coast was particularly well-connected, with an edge density between 0.14 and 0.44, depending on the species. The southern shore showed elevated edge density for short and medium dispersers (0.16–0.39) but low for long dispersers (<0.005). The north shore besides showed relatively elevated edge density (0.20 on average), although these values were smaller for long dispersers. The west coast showed very low edge density, with the exceptions of O. cyanea (0.37) and P. sexfilis (0.13). Virtually sum networks that included two coasts showed lower edge density. One exception was the east/south shore network, which had an edge density of 0.10–0.65 except for Cellana spp. Across species, edge density between the south and west coasts was 0.12 on average, and between the east and west coasts was 0.04 on average. Edge density between north and south coasts was particularly low for sum species (<0.05), a divide that was especially sever in Cellana spp. and P. meandrina, which showed zero realized connections between these coasts. Although northern and southern populations are potentially weakly connected by sites along the eastern ( P. meandrina) or western (Cellana spp.) shores, their model predicts very little, if any, demographic connectivity.

To explore patterns of connectivity on a finer scale, they pooled sites into regions (as defined in Fig. 1) in order to anatomize relationships between these regions. Arranging model output into node-edge networks clarified pathways and regions of note, and revealed several patterns which did not supervene simple predictions based on PLD (Fig. 7). Cellana spp. and P. meandrina showed the most fragmentation, with several SCCs and low connectivity between coasts. Connectivity was highest in O. cyanea and P. sexfilis, which had a solitary SCC containing sum regions. Medium and long dispersers generally showed fewer strongly connected regions on the south shore than the north shore, with the exception of C. strigosus. P. porphyreus showed more strongly connected regions east of Kalaupapa but lower connectivity on the western half of the island.

Figure 7: Moloka’i connectivity networks by species. Graph-theoretic networks between regions around Moloka’i by species arranged in order of minimum pelagic larval duration. (A–D) Short dispersers (3–25 days), (E–G) medium dispersers (30–50 days), and (H–J) long dispersers (140–270 days). Node size reflects betweenness centrality of each region, scaled per species for visibility. Node color reflects out-degree of each region; yellow nodes beget a low out-degree, red nodes beget a medium out-degree, and black nodes beget a elevated out-degree. Red edges are connections in a strongly connected component, while gray edges are not participate of a strongly connected component (although may noiseless portray substantial connections). Edge thickness represents log-transformed proportion of dispersal along that edge.

Region-level networks showed both species-specific and species-wide patterns of connectivity (Fig. 8). With a few exceptions, sites along the eastern coast—notably, Cape Halawa and Pauwalu Harbor—showed relatively elevated betweenness centrality, and may therefore act as multigenerational pathways between north-shore and south-shore populations. In Cellana spp., Leinapapio Point and Mokio Point had the highest BC, while in high-connectivity O. cyanea and P. sexfilis, regions on the west coast had elevated BC scores. P. meandrina and C. strigosus showed several regions along the south shore with elevated BC. For Cellana spp. and P. meandrina, regions in the northeast had the highest out-degree, and therefore seeded the greatest number of other sites with larvae (Fig. 8). Correspondingly, regions in the northwest (and southwest in the case of P. meandrina) showed the highest in-degree. For O. cyanea and P. sexfilis, regions on the western and southern coasts showed the highest out-degree. For most species, both out-degree and in-degree were generally highest on the northern and eastern coasts, suggesting higher connectivity in these areas.

Figure 8: Region-level summary statistics across sum species. Betweenness centrality is a measure of the number of paths that pass through a sure region; a elevated score suggests potentially well-known multi-generation connectivity pathways. In-degree and out-degree mention to the amount of a node’s incoming and outgoing connections. Betweenness centrality, in-degree, and out-degree beget sum been normalized to values between 0 to 1 per species. Local retention is measured as the proportion of larvae that settled back to their spawn site out of sum larvae spawned at that site. Source-sink index is a measure of net export or import; negative values (blue) indicate a net larval sink, while positive values (red) indicate a net larval source. White indicates that a site is neither a strong source nor sink. Gray values for Cellana spp. denote a need of suitable habitat sites in that particular region.

Several species-wide hotspots of local retention emerged, particularly East Kalaupapa Peninsula/Leinaopapio Point, the northeast point of Moloka‘i, and the middle of the south shore. Some species besides showed some degree of local retention west of Kalaupapa Peninsula. While local retention was observed in the long-dispersing Caranx spp. and Panulirus spp., this amount was essentially negligible. In terms of source–sink dynamics, Ki‘oko‘o, Pu‘ukaoku Point, and West Kalaupapa Peninsula, sum on the north shore, were the only sites that consistently acted as a net source, exporting more larvae than they import (Fig. 8). Kaunakakai Harbor, Lono Harbor, and Mokio Point acted as net sinks across sum species. Puko‘o, Pauwalu Harbor, and Cape Halawa were either frail net sources or neither sources nor sinks, which corresponds to the elevated levels of local retention observed at these sites. Pala‘au and Mo‘omomi acted as either frail sinks or sources for short dispersers and as sources for long dispersers.

Only four networks showed regional cut-nodes, or nodes that, if removed, smash a network into multiple weakly-connected components (Fig. S5). Cellana spp. showed two cut-nodes: Mokio Point in northwest Moloka‘i and La‘au Point in southwest Moloka‘i, which if removed isolated minuscule Bay and Lono Harbor, respectively. C. perspicillatus, and S. rubroviolaceus showed a similar pattern in regards to Mokio Point; removal of this node isolated minuscule Bay in this species as well. In C. ignoblis, loss of Pauwalu Harbor isolated Lono Harbor, and loss of Pala‘au isolated Ilio Point on the northern coast. Finally, in Panulirus spp., loss of Leinaopapio Point isolated Papuhaku Beach, since Leinapapio Point was the only larval source from Moloka‘i for Papuhaku Beach in this species.

Figure 9: Connectivity matrix for larvae spawned on Kalaupapa Peninsula. Includes larvae settled on Molokaí (regions below horizontal black line) and those settled on other islands (regions above horizontal black line), spawned from either the east (E) or west (W) coast of Kalaupapa. Heatmap colors portray rearward proportion, calculated by the number of larvae settling at site s from site o divided by sum settled larvae at site s. White squares indicate no dispersal along this path. The role of Kalaupapa Peninsula in inter- and intra-island connectivity

Our model suggests that Kalaupapa National Historical Park may play a role in inter-island connectivity, especially in terms of long-distance dispersal. Out of sum regions on Moloka‘i, East Kalaupapa Peninsula was the solitary largest exporter of larvae to Hawai‘i Island, accounting for 19% of sum larvae transported from Moloka‘i to this island; West Kalaupapa Peninsula accounted for another 10%. The park besides contributed 22% of sum larvae exported from Moloka‘i to O‘ahu, and successfully exported a smaller percentage of larvae to Maui, Lana‘i, and Kaho‘olawe (Fig. 9). Kalaupapa was not marked as a cut-node for any species, meaning that plenary population breaks are not predicted in the case of habitat or population loss in this area. Nevertheless, in their model Kalaupapa exported larvae to multiple regions along the north shore in sum species, as well as regions along the east, south, and/or west shores in most species networks (Figs. 9 and 10). The park may play a particularly well-known role for long-dispersing species; settlement from Kalaupapa made up 18%–29% of sum successful settlement in Caranx spp. and Panulirus spp., despite making up only 12% of spawning sites included in the model. In C. strigosus, S. rubroviolaceus, and C. strigosus, Kalaupapa showed a particularly elevated out-degree, or number of outgoing connections to other regions, and West Kalaupapa was besides one of the few regions on Moloka‘i that acted as a net larval source across sum species (Fig. 8). Their study has besides demonstrated that different regions of a marine protected zone can potentially perform different roles, even in a minuscule MPA such as Kalaupapa. Across species, the east coast of Kalaupapa showed a significantly higher betweenness centrality than the west (p = 0.028), while the west coast of Kalauapapa showed a significantly higher source–sink index than the east (p = 2.63e−9).

Figure 10: Larval spillover from Kalaupapa National Historical Park. Site-level dispersal to sites around Moloka‘i from sites in the Kalaupapa National Historical Park protected area, by species. (A–D) Short dispersers (3–25 days), (E–G) medium dispersers (30–50 days), and (H–J) long dispersers (140–270 days). Edge color reflects proportion of dispersal along that edge; red indicates higher proportion while yellow indicates lower proportion. Kalaupapa National Historical Park is highlighted in light green. Discussion Effects of biological and physical parameters on connectivity

We incorporated the distribution of suitable habitat, variable reproduction, variable PLD, and ontogenetic changes in swimming competence and empirical perpendicular distributions of larvae into their model to increase biological realism, and assess how such traits impact predictions of larval dispersal. The Wong-Ala et al. (2018) IBM provides a highly flexible model framework that can easily live modified to incorporate either additional species-specific data or entirely modern biological traits. In this study, they included specific spawning seasons for sum species, as well as spawning by moon side for Cellana spp., P. meandrina, and C. ignoblis because such data was available for these species. It proved difficult to obtain the necessary biological information to parameterize the model, but as more data about life history and larval deportment become available, such information can live easily added for these species and others. Some potential additions to future iterations of the model might embrace density of reproductive-age adults within each habitat patch, temperature-dependent pelagic larval duration (Houde, 1989), ontogenetic-dependent behavioral changes such as orientation and diel perpendicular migration (Fiksen et al., 2007; Paris, Chérubin & Cowen, 2007), pre-competency period, and larval habitat preferences as such information becomes available.

In this study, they beget demonstrated that patterns of fine-scale connectivity around Moloka‘i are largely species-specific and can vary with life history traits, even in species with identical pelagic larval duration. For example, the parrotfish S. rubroviolaceus and C. perspicillatus demonstrate greater connectivity along the northern coast, while the goatfish P. porphyreus shows higher connectivity along the eastern half of the island. These species beget similar PLD windows, but vary in dispersal depth and spawning season. Spawning season and timing altered patterns of inter-island dispersal (Fig. 5) as well as overall settlement success, which was slightly higher in species that spawned by moon side (Fig. 2). While maximum PLD did appear play a role in the probability of rare long-distance dispersal, minimum PLD appears to live the main driver of middling dispersal distance (Fig. 2). Overall, species with a shorter minimum PLD had higher settlement success, shorter spell dispersal distance, higher local retention, and higher local connectivity as measured by the amount and size of strongly connected components.

The interaction of biological and oceanographic factors besides influenced connectivity patterns. Because mesoscale current patterns can vary substantially over the course of the year, the timing of spawning for sure species may live faultfinding for estimating settlement (Wren et al., 2016; Wong-Ala et al., 2018). Intermittent ocean processes may influence the probability of local retention versus long-distance dispersal; a big proportion of larvae settled to O‘ahu, which is rather surprising given that in order to settle from Moloka‘i to O‘ahu, larvae must cross the Kaiwi Channel (approx. 40 km). However, the intermittent presence of mesoscale gyres may act as a stabilizing pathway across the channel, sweeping larvae up either the windward or leeward coast of O‘ahu depending on spawning site. Likewise, in their model long-distance dispersal to Hawai‘i Island was workable at sure times of the year due to a gyre to the north of Maui; larvae were transported from Kalaupapa to this gyre, where they were carried to the northeast shore of Hawai‘i (Fig. S6). preliminary analysis besides suggests that distribution of larval depth influenced edge directionality and size of connected components (Fig. 7); surface currents are variable and primarily wind-driven, giving positively-buoyant larvae different patterns of dispersal than species that disperse deeper in the water column (Fig. S7).

Model limitations and future perspectives

Our findings beget several caveats. Because fine-scale density estimates are not available for their species of interest around Moloka’i, they assumed that fecundity is equivalent at sum sites. This simplification may lead us to under- or over-estimate the energy of connections between sites. need of adequate data besides necessitated estimation or extrapolation from congener information for larval traits such as larval dispersal depth and PLD. Since it is difficult if not impossible to identify larvae to the species smooth without genetic analysis, they used genus-level larval distribution data (Boehlert & Mundy, 1996), or lacking that, an evaluate of 50–100 m as a depth layer that is generally more enriched with larvae (Boehlert, Watson & Sun, 1992; Wren & Kobayashi, 2016). They besides estimated PLD in several cases using congener-level data (see Table 1). While specificity is pattern for making informed management decisions about a sure species, past sensitivity analysis has shown that variation in PLD length does not greatly impact patterns of dispersal in species with a PLD of >40 days (Wren & Kobayashi, 2016).

Although their MITgcm current model shows annual consistency, it only spans two and a half years chosen as neutral condition ‘average’ ocean conditions. It does not span any El Niño or La Niña (ENSO) events, which cause wide-scale sea-surface temperature anomalies and may therefore paw patterns of connectivity during these years. El Niño can beget a particularly strong impact on coral reproduction, since the warm currents associated with these events can lead to austere temperature stress (Glynn & D’Croz, 1990; Wood et al., 2016). While there has been cramped study to date on the effects of ENSO on fine-scale connectivity, previous work has demonstrated increased variability during these events. For example, Wood et al. (2016) showed a decrease in eastward Pacific dispersal during El Niño years, but an increase in westward dispersal, and Treml et al. (2008) showed unique connections in the West Pacific as well as an increase in connectivity during El Niño. While these effects are difficult to predict, especially at such a minuscule scale, additional model years would increase aplomb in long-term connectivity estimations. Additionally, with a temporal resolution of 24 h, they could not adequately address the role of tides on dispersal, and therefore did not embrace them in the MITgcm. Storlazzi et al. (2017) showed that tidal forces did paw larval dispersal in Maui Nui, underlining the importance of including both fine-scale, short-duration models and coarser-scale, long-duration models in final management decisions.

We besides confine their model’s scope geographically. Their goal was to determine whether they could resolve predictive patterns at this scale material to management. Interpretation of connectivity output can live biased by spatial resolution of the ocean model, since tangled coastal processes can live smoothed and therefore impact larval trajectories. To confine this bias, they focused mainly on coastal and regional connectivity on scales greater than the current resolution. They besides used the finest-scale current products available for their study area, and their results demonstrate general agreement with similar studies of the region that exercise a coarser resolution (Wren & Kobayashi, 2016) and a finer resolution (Storlazzi et al., 2017). Also, while information of island-scale connectivity is well-known for local management, it does disregard potential connections from other islands. In their calculations of edge density, betweenness centrality and source-sink index, they included only settlement to Moloka‘i, discarding exogenous sinks that would jaundice their analysis. Likewise, they cannot foretell the proportion of larvae settling to other islands that originated from Moloka‘i, or the proportion of larvae on Moloka‘i that originated from other islands.

It is besides well-known to note scale in relation to measures of connectivity; they anticipate that long-dispersing species such as Caranx spp. and Panulirus spp. will demonstrate much higher measures of connectivity when measured across the total archipelago as opposed to a solitary island. The cut-nodes observed in these species may not actually smash up populations on a big scale due to this inter-island connectivity. Nevertheless, cut-nodes in species with short- and medium-length PLD may indeed brand well-known habitat locations, especially in terms of providing links between two otherwise disconnected coasts. It may live that for sure species or sure regions, stock replenishment relies on larval import from other islands, underscoring the importance of MPA selection for population maintenance in the archipelago as a whole.

Implications for management

Clearly, there is no solitary management approach that encompasses the breadth of life history and deportment differences that impact patterns of larval dispersal and connectivity (Toonen et al., 2011; Holstein, Paris & Mumby, 2014). The spatial, temporal, and species-specific variability suggested by their model stresses the exigency for multi-scale management, specifically tailored to local and regional connectivity patterns and the suite of target species. Even on such a minuscule scale, different regions around the island of Moloka‘i can play very different roles in the greater pattern of connectivity (Fig. 8); sites along the west coast, for example, showed fewer ingoing and outgoing connections than sites on the north coast, and therefore may live more at risk of isolation. Seasonal variation should besides live taken into account, as mesoscale current patterns (and resulting connectivity patterns) vary over the course of a year. Their model suggests species-specific temporal patterns of settlement (Fig. 5); even in the year-round spawner O. cyanea, local retention to Moloka‘i as well as settlement to O‘ahu was maximized in spring and early summer, while settlement to other islands mostly occurred in late summer and fall.

Regions that demonstrate similar network dynamics may profit from similar management strategies. Areas that act as larval sources either by proportion of larvae (high source–sink index) or number of sites (high out-degree) should receive management consideration. On Moloka‘i, across sum species in their study, these sources fell mostly on the northern and eastern coasts. Maintenance of these areas is especially well-known for downstream areas that depend on upstream populations for a source of larvae, such as those with a low source–sink index, low in-degree, and/or low local retention. Across species, regions with the highest betweenness centrality scores fell mainly in the northeast (Cape Halawa and Pauwalu Harbor). These areas should receive consideration as potentially well-known intergenerational pathways, particularly as a means of connecting north-coast and south-coast populations, which showed a need of connectivity both in total number of connections (edge density) and proportion of larvae. Both of these connectivity measures were included because edge density includes sum connections, even those with a very minuscule proportion of larvae, and may therefore embrace rare dispersal events that are of cramped relevance to managers. Additionally, edge density comparisons between networks should live viewed with the caveat that these networks finish not necessarily beget the identical number of nodes. Nevertheless, both edge density and proportion demonstrate very similar patterns, and embrace both demographically-relevant common connections as well as rare connections that could influence genetic connectivity.

Management that seeks to establish a resilient network of spatially managed areas should besides deem the preservation of both weakly-connected and strongly-connected components, as removal of key cut-nodes (Fig. S5) breaks up a network. Sites within a SCC beget more direct connections and therefore may live more resilient to local population loss. pervade should live taken to preserve breeding populations at larval sources, connectivity pathways, and cut-nodes within a SCC, since without these key sites the network can fragment into multiple independent SCCs instead of a solitary stable network. This drill may live especially well-known for species for which they evaluate multiple minuscule SCCs, such as Cellana spp. or P. meandrina.

Kalaupapa Peninsula emerged as an well-known site in Moloka‘i population connectivity, acting as a larval source for other regions around the island. The Park seeded areas along the north shore in sum species, and besides exported larvae to sites along the east and west shores in sum species except P. meandrina and Cellana spp. Additionally, it was a larval source for sites along the south shore in the fishes C. perspicillatus, S. rubroviolaceus, and C. strigosus as well as Panulirus spp. Western Kalaupapa Peninsula was one of only three regions included in the analysis (the others being Ki‘oko‘o and Pu‘ukaoku Point, besides on the north shore) that acted as a net larval source across sum species. Eastern Kalaupapa Peninsula was particularly highly connected, and was participate of a strongly connected component in every species. The Park besides emerged as a potential point of connection to adjacent islands, particularly to O‘ahu and Hawai‘i. Expanding the spatial scale of their model will further elucidate Kalaupapa’s role in the greater pattern of inter-island connectivity.

In addition to biophysical modeling, genetic analyses can live used to identify persistent population structure of relevance to managers (Cowen et al., 2000; Casey, Jardim & Martinsohn, 2016). Their finding that exchange among islands is generally low in species with a short- to medium-length PLD agrees with population genetic analyses of marine species in the Hawaiian Islands (Bird et al., 2007; Rivera et al., 2011; Toonen et al., 2011; Concepcion, Baums & Toonen, 2014). On a finer scale, they foretell some smooth of shoreline-specific population structure for most species included in the study (Fig. 6). Unfortunately, genetic analyses to date beget been performed over too broad a scale to effectively compare to these fine-scale connectivity predictions around Moloka‘i or even among locations on adjacent islands. These model results warrant such minuscule scale genetic analyses because there are species, such as the coral P. meandrina, for which the model predicts clear separation of north-shore and south-shore populations which should live simple to test using genetic data. To validate these model predictions with this technique, more fine-scale population genetic analyses are needed.

Conclusions

The maintenance of demographically connected populations is well-known for conservation. In this study, they contribute to the growing body of work in biophysical connectivity modeling, focusing on a region and suite of species that are of relevance to resource managers. Furthermore, they demonstrate the value of quantifying fine-scale relationships between habitat sites via graph-theoretic methods. Multispecies network analysis revealed persistent patterns that can profit define region-wide practices, as well as species-specific connectivity that merits more individual consideration. They demonstrate that connectivity is influenced not only by PLD, but besides by other life-history traits such as spawning season, moon-phase spawning, and ontogenetic changes in larval depth. elevated local retention of larvae with a short- or medium-length PLD is consistent with population genetic studies of the area. They besides identify regions of management importance, including West Kalaupapa Peninsula, which acts as a consistent larval source across species; East Kalaupapa Peninsula, which is a strongly connected region in every species network, and Pauwalu Harbor/Cape Halawa, which may act as well-known multigenerational pathways. Connectivity is only one piece of the mystify of MPA effectiveness, which must besides account for reproductive population size, long-term persistence, and post-settlement survival (Burgess et al., 2014). That being said, their study provides a quantitative roadmap of potential demographic connectivity, and thus presents an effectual utensil for estimating current and future patterns of dispersal around Kalaupapa Peninsula and around Moloka‘i as a whole.

Supplemental Information Current patterns in the model domain.

Current direction and velocity is displayed at a depth of 55 m below sea surface on (A) March 31st, 2011, (B) June 30th, 2011, (C) September 30th, 2011, and (D) December 31st, 2011. Arrowhead direction follows current direction, and u/v velocity is displayed through arrow length and color (purple, low velocity, red, elevated velocity). Domain extends from 198.2°E to 206°E and from 17°N to 22.2°N. The island of Moloka‘i is highlighted in red.

Subset of validation drifter paths.

Drifter paths in black and corresponding model paths are colored by drifter ID. sum drifter information was extracted from the GDP Drifter Data Assembly heart (Elipot et al., 2016). Drifters were included if they fell within the model domain spatially and temporally, and were tested by releasing 1,000 particles on the redress day where they entered the model domain, at the uppermost depth layer of their oceanographic model (0–5 m).

Selected larval depth distributions.

Modeled perpendicular larval distributions for Caranx spp. (left), S. rubroviolaceus and C. perspicillatus (middle), and P. porphyreus (right), using data from the 1996 NOAA ichthyoplankton perpendicular distributions data report (Boehlert & Mundy 1996).

Coast-specific rearward settlement patterns by island

Proportion of simulated larvae settled to each island from sites on each coast of Moloka‘i, averaged across sum species that successfully settled to that island.

Regional cut-nodes for four species networks

Mokio Point and La‘au Point were cut-nodes for Cellana spp., Mokio Point was a cut-node for C. perspicillatus and S. rubroviolaceus, Pauwalu Harbor and Pala‘au were cut-nodes for C. ignoblis, and Leinaopapio Point was a cut-node for Panulirus spp.

Selected dispersal pathways for Panulirus spp. larvae

500 randomly sampled dispersal pathways for lobster larvae (Panulirus spp.) that successfully settled to Hawai‘i Island after being spawned off the coast of Moloka‘i. Red tracks indicate settlement earlier in the year (February–March), while black tracks indicate settlement later in the year (April–May). Most larvae are transported to the northeast coast of Hawai‘i via a gyre to the north of Maui, while a smaller proportion are transported through Maui Nui.

Eddy differences by depth layer.

Differences in eddy pattern and energy in surface layers (A, 2.5 m) vs. abysmal layers (B, 55 m) on March 31, 2011. Arrowhead direction follows current direction, and u/v velocity is displayed through arrow length and color (purple, low velocity, red, elevated velocity). While big gyres remain consistent at different depths, smaller features vary along this gradient. For example, the currents around Kaho‘olawe, the minuscule gyre off the eastern coast of O‘ahu, and currents to the north of Maui sum vary in direction and/or velocity.


Avoid Bothersome Garbage Collection Pauses | killexams.com existent questions and Pass4sure dumps

Many engineers complain that the non-deterministic deportment of the garbage collector prevents them from utilizing the Java environment for mission-critical applications, especially distributed message-driven displays (GUIs) where user responsiveness is critical. They conform that garbage collection does occur at the worst times: for example, when a user clicks a mouse or a modern message enters the system requiring immediate processing. These events must live handled without the dilatory of in-progress garbage collection. How finish they prevent these garbage collection pauses that interfere with the responsiveness of an application ("bothersome pauses")?

We beget discovered a very effectual technique to prevent bothersome garbage collection pauses and build responsive Java applications. This technique or pattern is especially effectual for a distributive message-driven parade system with soft real-time constraints. This article details this pattern in three simple steps and provides evidence of the effectiveness of the technique.

Pattern to Control Garbage Collection PausesThe Java environment provides so many benefits to the software community - platform independence, industry momentum, a plethora of resources (online tutorials, code, interest groups, etc.), object-oriented utilities and interfaces (collections, network I/O, undulate display, etc.) that can live plugged in and out - that once you beget experienced working with Java it's arduous to travel back to traditional languages. Unfortunately, in some mission-critical applications, relish message-driven GUIs that must live very responsive to user events, the requirements compel you to select that step backward. There's no play for multiple second garbage collection pauses. (The garbage collector collects sum the "unreachable" references in an application so the space consumed by them can live reused. It's a low-priority thread that usually only takes priority over other threads when the VM is running out of memory.) finish they really beget to lose sum the benefits of Java? First, let's deem the requirements.

A system engineer should deem imposing requirements for garbage collection relish the following list taken from a telecom industry instance (see References).1.  GC sequential overhead on a system may not live more than 10% to ensure scalability and optimal exercise of system resources for maximum throughput.2.  Any solitary GC intermission during the entire application hasten may live no more than 200ms to meet the latency requirements as set by the protocol between the client and the server, and to ensure estimable response times by the server.

Armed with these requirements, the system engineer has defined the worst-case deportment in a manner that can live tested.

The next question is: How finish they meet these requirements? Alka Gupta and Michael Doyle manufacture excellent suggestions in their article (see References). Their approach is to tune the parameters on the Java Virtual Machine (JVM). They select a slightly different approach that leaves the exercise of parameter definitions as defined by the JVM to live used as a final tuning technique.

Why not order the garbage collector what and when to collect?

In other words, control garbage collection via the software architecture. manufacture the job of the garbage collector easy! This technique can live described as a multiple step pattern. The first step of the pattern is described below as "Nullify Objects." The second step involves forcing garbage collection to occur as delineated in "Forcing Garbage Collection." The final step involves either placing persistent data out of the compass of the collector or into a data pool so that an application will continue to perform well in the long run.

Step 1: Nullify ObjectsMemory leaks strike horrify into the hearts of programmers! Not only finish they degrade performance, they eventually terminate the application. Yet recollection leaks prove very subtle and difficult to debug. The JVM performs garbage collection in the background, freeing the coder from such details, but traps noiseless exist. The biggest danger is placing an kick into a collection and forgetting to remove it. The recollection used by that kick will never live reclaimed.

A programmer can prevent this kind of recollection leak by setting the kick reference and sum underlying kick references ("deep" objects) to null when the kick is no longer needed. Setting an kick reference to "null" tells the garbage collector that at least this one reference to the kick is no longer needed. Once sum references to an kick are cleared, the garbage collector is free to reclaim that space. Giving the collector such "hints" makes its job easier and faster. Moreover, a smaller recollection footprint besides makes an application hasten faster.

Knowing when to set an kick reference to null requires a complete understanding of the problem space. For instance, if the remote receiver allocates the recollection space for a message, the comfort of the application must know when to release the space back for reuse. Study the domain. Once an kick or "subobject" is no longer needed, order the garbage collector.

Thus, the first step of the pattern is to set objects to null once you're sure they're no longer needed. They summon this step "nullify" and embrace it in the definition of the classes of frequently used objects.

The following code snippet shows a manner that "nullifies" a track object. The class members that consist of primitives only (contain no additional class objects) are set to null directly, as in lines 3-5. The class members that accommodate class objects provide their own nullify manner as in line 9.

1 public void nullify () {23 this.threatId = null ;4 this.elPosition = null ;5 this.kinematics = null ;67 if (this.iff != null)8 {9 this.iff.nullify();10 this.iff = null ;11 }12 }

The track nullify is called from the thread that has completed processing the message. In other words, once the message has been stored or processed, that thread tells the JVM it no longer needs that object. Also, if the kick was placed in some Collection (like an ArrayList), it's removed from the Collection and set to null.

By setting objects to null in this manner, the garbage collector and thus the JVM can hasten more efficiently. Train yourself to program with "nullify" methods and their invocation in mind.

Step 2: "Force" Garbage CollectionThe second step of the pattern is to control when garbage collection occurs. The garbage collector, GC, runs as Java priority 1 (the lowest priority). The virtual machine, VM, runs at Java priority 10 (the highest priority). Most books recommend against the usage of Java priority 1 and 10 for assigning priorities to Java applications. In most cases, the GC runs during idle times, generally when the VM is waiting for user input or when the VM has hasten out of memory. In the latter case, the GC interrupts high-priority processing in the application.

Some programmers relish to exercise the "-Xincgc" directive on the Java command line. This tells the JVM to perform garbage collection in increments when it desires. Again, the timing of the garbage collection may live inopportune. Instead, they intimate that the garbage collector perform a plenary garbage collection as soon as it can in either or both of two ways:1.  Request garbage collection to happen as soon as possible: This manner proves useful when the programmer knows he or she has a "break" to garbage collect. For example, after a big image is loaded into recollection and scaled, the recollection footprint is large. Forcing a garbage collection to occur at that point is wise. Another estimable zone may live after a big message has been processed in the application and is no longer needed.2.  Schedule garbage collection to occur at a fixed rate: This manner is optimal when the programmer does not beget a specific second when he knows his application can desist shortly and garbage collect. Normally, most applications are written in this manner.

Listing 1 introduces a class named "BetterControlOfGC". It's a utility class that provides the methods described earlier. There are two public methods: "suggestGCNow()" and "scheduleRegularGC(milliseconds)" that respectively correspond to the steps described earlier. Line 7 suggests to the VM to garbage collect the unreachable objects as soon as possible. The documentation makes it clear that the garbage collection may not occur instantaneously, but taste has shown that it will live performed as soon as the VM is able to accomplish the task. Invoking the manner on line 25 causes garbage collection to occur at a fixed rate as determined by the parameter to the method.

In scheduling the GC to occur at a fixed rate, a garbage collection stimulator task, GCStimulatorTask, is utilized. The code extends the "java.util.timer" thread in line 10. No modern thread is created; the processing runs on the solitary timer thread available beginning with the Java 1.3 environment. Similarly, to support the processing lean, the GC stimulator follows the Singleton pattern as shown by lines 18-23 and line 27. There can live only one stimulator per application, where an application is any code running on an instance of the JVM.

We intimate that you set the interval at which the garbage collector runs from a Java property file. Thus you can tune the application without having to recompile the code. Write some simple code to read a property file that's either a parameter on the command line or a resource bundle in the class path. dwelling the command parameter "-verbose:gc" on your executable command line and measure the time it takes to garbage collect. Tune this number until you achieve the results you want. If the budget allows, experiment with other virtual machines and/or hardware.

Step 3: Store Persistent Objects into Persistent Data Areas or Store Long-Lived Objects in PoolsUsing persistent data areas is purely optional. It supports the underlying premise of this article. In order to bind the disruption of the garbage collector in your application, manufacture its job easy. If you know that an kick or collection of objects would live for the duration of your application, let the collector know. It would live nice if the Java environment provided some sort of flag that could live placed on objects upon their creation to order the garbage collector "-keep out". However, there is currently no such means. (The Real-Time Specification for Java describes an zone of recollection called "Immortal Memory" where objects live for the duration of the application and garbage collection should not run.) You may try using a database; however, this may unhurried down your application even more. Another solution currently under the Java Community Process is JSR 107. JCache provides a measure set of APIs and semantics that allow a programmer to cache frequently used data objects for the local JVM or across JVMs. This API is noiseless under review and may not live available yet. However, they believe it holds much promise for the Java developer community. support this avenue open and in irony for future architectures. What can they finish now?

The pooling of objects is not modern to real-time programmers. The concept is to create sum your expected data objects before you originate processing, then sum your data can live placed into structures without the expense of instance creation during processing time. This has the odds of keeping your recollection footprint stable. It has the disadvantage of requiring a "deep copy" manner to live written to store the data into the pool. (If you simply set an kick to another, you're changing the kick reference and not reusing the identical space.) The nanosecond expense of the abysmal copy is far less than that of the kick instance creation.

If the data pooling technique is combined with the proper exercise of the "nullify" technique, garbage collection becomes optimized. The reasons are fairly straightforward:1.  Since the kick is set to null immediately after the abysmal copy, it lives only in the green generation portion of the memory. It does not progress into the older generations of recollection and thus takes less of the garbage collector's cycle time.2.  Since the kick is nullified immediately and no other reference to it exists in some other collection kick in the application, the job of the garbage collector is easier. In other words, the garbage collector does not beget to support track of an kick that exists in a collection.

When using data pools, it's sapient to exercise the parameters "-XX:+UseConcMarkSweepGC -XX:MaxTenuringThreshold=0 -XX:SurvivorRatio=128" on the command line. These order the JVM to slip objects on the first sweep from the modern generation to the old. It commands the JVM to exercise the concurrent brand sweep algorithm on the obsolete generation that proves more efficient since it works "concurrently" for a multi-processor platform. For solitary processor machines, try the "-Xincgc" option. We've seen those long garbage collector pauses, which occur after hours of execution, evanesce using this technique and these parameters. Performing well in the long hasten is the fair profit of this final step.

Performance ResultsTypically, most engineers want proof before changing their approach to designing and coding. Why not? Since we're now suggesting that even Java programmers should live concerned about resource allocation, it better live worth it! Once upon a time, assembly language and C programmers spent time tweaking recollection and register usage to improve performance. This step was necessary. Now, as higher-level object-oriented programmers they may disdain this thought. This pattern has dared to imply that such considerations, although not as low smooth as registers and recollection addresses (instead at the kick level), are noiseless necessary for high-performance coding. Can it live true?

The underlying premise is that if you know how your engine works, you can drive it better to obtain optimal performance and endurance. This is as fair for my 1985 300TD (Mercedes, five cylinder, turbo diesel station wagon) with 265,000 miles as for my Java code running on a HotSpot VM. For instance, knowing that a diesel's optimal performance is when the engine is warm since it relies on compression for power, I let my car warm up before I "push it." Similarly, I don't overload the vehicle with the tons of stuff I could dwelling in the tailgate. HotSpot fits the analogy. Performance improves after the VM "warms up" and compiles the HotSpot code into the autochthonous language. I besides support my recollection footprint lank and light. The comparison breaks down after awhile, but the basic verisimilitude does not change. You can exercise a system the best when you understand how it works.

Our challenge to you is to select statistics before and after implementing this pattern on just a minuscule portion of your code. delight recognize that the gain will live best exemplified when your application is scaled upward. In other words, the heavier the load on the system, the better the results.

The following statistics were taken after the pattern was applied. They are charted as:1.  Limited nullify manner invocation is used where only the incoming messages are not "nullified." (The remainder of the application from which the statistics were taken was left intact with a very lank recollection usage.) There is no forced garbage collection.2.  Nullify manner invocation and forced garbage collection is utilized.

The test environment is a Microsoft Windows 2000 X86 Family 15 Model 2 Stepping 4 Genuine Intel ~1794MHz laptop running the BEA WebLogic Server 7.0 with Service Pack 7.1 with a physical recollection size of 523,704KB. The Java Message Server (JMS server), a track generator, and a tactical parade are sum running on the identical laptop over the local developer network (MAGIC). The server makes no optimizations, even though each application resides locally. The JVMs are treated as if they were distributed across the network. They're running on the J2SE 1.4.1 release.

The test target application is a Java undulate Tactical parade with plenary panning, zooming, and track-hooking capabilities. It receives bundles of tracks via the Java Message Service that are displayed at their proper location on the given image. Each track is approximately 88 bytes and the overall container size is about 70 bytes. This byte measurement does not embrace sum the additional class information that's besides sent during serialization. The container is the message that holds an array of tracks that contains information such as time and number of tracks. For their tests, the tracks are sent at a 1Hz rate. Twenty sets of data are captured.

To illustrate the test environment, a screen capture of a 5,000 track load (4,999 tracks plus the ship) is shown in device 1. The background shows tracks rendered with the Military measure 2525B symbology over an image of the Middle East. The minuscule window titled "Track Generator Desktop" is a minimized window showing the parameters of the test set through the track generator application. Notice that 45 messages had been sent at the time of the screen capture. Directly beneath this window sits the Windows assignment Manager. Note that the CPU utilization is at 83%. At first this doesn't seem that bad. But at that rate, there isn't much play for the user to originate zooming, panning, hooking tracks, and so on. The final command window to the right is that of the tactical parade application. The parameter "-verbose:gc" is placed on the Java command line (java -verbose:gc myMainApplication.class). The VM is performing the listed garbage collection at its own rate, not by command of the application.

The final test of 10,000 tracks performed extremely poorly. The system does not scale; the CPU is pegged. At this point most engineers may jeer at Java again. Let's select another observe after implementing the pattern.

After implementation, where the nullify methods are invoked properly and garbage collection is requested at a fitful interval (2Hz), theatrical improvements are realized. The final test of 10,000 tracks proves that the processor noiseless has plenty of play to finish more work. In other words, the pattern scales very well.

Performance SummaryThe pattern to profit control garbage collection pauses most definitely improves the overall performance of the application. Notice how well the pattern scales under the heavier track loads in the performance bar chart in device 2. The darker middle bar shows the processor utilization at each smooth of the message (track) load. As the message traffic increases, the processor utilization grows more slowly than without the pattern. The final light-colored bar shows the improved performance. The main energy of the pattern is how well it scales under hefty message loads.

There is another subtle energy to the pattern. This one is difficult to measure since it requires very long-lived tests. If Step 3 is faithfully followed, those horribly long garbage collection pauses that occur after hours of running disappear. This is a key profit to the pattern since most of their applications are designed to hasten "forever."

We're confident that many other Java applications would profit from implementing this very simple pattern.

The steps to control garbage collection pauses are:1.  Set sum objects that are no longer in exercise to null and manufacture sure they're not left within some collection. "Nullify" objects.2.  compel garbage collection to occur both:

  • After some major memory-intense operation (e.g., scaling an image)
  • At a fitful rate that provides the best performance for your application3.  save long-lived data in a persistent data zone if feasible or in a pool of data and exercise the appropriate garbage collector algorithm.

    By following these three simple steps, you'll avoid those bothersome garbage collection pauses and baskin sum the benefits of the Java environment. It's time the Java environment was fully utilized in mission-critical parade systems.

    References

  • Gupta, A., and Doyle, M. "Turbo-Charging the Java HotSpot Virtual Machine, v1.4.x to improve the Performance and Scalability of Application Servers": http://developer.java.sun.com/developer/ technicalArticles/Programming/turbo/
  • JSR 1, Real-Time Specification for Java: http://jcp.org/en/jsr/detail?id=1
  • Java HotSpot VM options: http://java.sun.com/docs/hotspot/VMOptions.html
  • Java Specification Request for JCache: http://jcp.org/en/jsr/detail?id=107

  • PCI DSS questions answered: Solutions to tough PCI problems | killexams.com existent questions and Pass4sure dumps

    During their recent virtual seminar, PCI DSS 2.0: Why the latest update matters to you, experts Ed Moyle and Diana...

    Kelley of SecurityCurve were unable to acknowledge sum of the PCI DSS questions they received during their live question-and-answer session. SearchSecurity.com has asked them to give brief responses to each of the unanswered questions, and we've published those questions and responses below to profit you resolve your unique PCI problems.

    For additional information about the Payment Card Industry Data Security Standard, visit SearchSecurity.com's PCI DSS resources page.

  • Where can they find information about PCI DSS compliance that is focused on those of us who are "Mom & Pop" shops?Since most minuscule organizations Fall into the self-assessment category, a remarkable resource is the Security Standards Council SAQ (Self-Assessment Questionnaire) section. Specifically these documents:

    SAQ main page

    PCI DSS SAQ instructions and guidelines

    SAQ: How it sum fits together

    SAQ A-D and Guidelines

  • It seems the necessity of PCI compliance hasn't fully penetrated the Asian markets. finish you beget any suggestions on how to achieve compliance for companies who finish traffic in Asia, where adjusting to PCI standards aren't a priority?Companies should live compliant regardless of where the payment information is stored, processed or transmitted. Even if processors in a particular locale aren't as focused on the standard, the companies (merchants/retailers) with operations in those locales should implement the identical controls as they finish in other areas of the globe.

  • If card data is entered via the virtual terminal of a third-party on a desktop PC where wireless is not enabled, finish I exigency wireless scans?All wireless networks within the CDE (cardholder data environment) exigency to live scanned pursuant to the PCI DSS wireless guidelines provided by the Council. If audit and test findings confirm there is no wireless on the virtual terminal and there is no wireless within the CDE, additional scans are not required (for example, note that the wireless scanning requirement is not addressed in SAQ C-VT specific to virtual terminal-only environments). Note, however, that if you exercise other devices beyond just the virtual terminal to store/process/transmit cardholder data (such as a PoS on your network), you will beget to scan.

  • Is there a measure for isolating non-compliant custom systems that finish not beget a newer PCI-compliant version available? Let's assume this would live a software package without encryption in its database.There are two standards for payment software – the PA DSS for commercial software and the PCI DSS for commercial software with significant customization and custom software. If the custom software is saving PANs in an unencrypted format, it is non-compliant with PCI DSS. The best options are to desist saving the PANs and exercise an alternative -- relish masking, tokens or other unique identifier -- or find a course to encrypt the PAN data before it enters the database. If this is not possible, create a document explaining why, list compensating controls (such as increased monitoring and access control) and achieve in dwelling a road map for mitigating or eliminating the problem. Although the compensating controls/road map will not spell a fully compliant RoC or SAQ, it does demonstrate estimable faith on the participate of the company to work towards correcting the problem.

  • In terms of a policy strategy, should an enterprise's existing information security policies live amended to embrace PCI requirements, or finish the requirements exigency to live addressed in PCI-specific policies?In most cases the CDE (cardholder data environment) under PCI is a very minuscule portion of the network and should live clearly zoned off from the comfort of the corporate network activities. As a sever participate of the network, a unique policy (or policy set) should apply for that zone. So PCI-specific policies should exist. However, parts of existing policy – for instance strong password controls and reset – can live re-used in the PCI-specific policies where applicable.

  • Regarding encryption in requirement 3, if the decryption key is not present in the cardholder environment, is the system out of the scope of PCI?In the FAQ section of the Council site it states: "Encrypted data may live deemed out of scope if, and only if, it has been validated that the entity that possesses encrypted cardholder data does not beget the means to decrypt it." So if the entity does not beget the key, that data may live deemed out of scope.

  • Does PCI require verification that there are no rogue wireless access points that may beget connected to the POS network?Yes. From the Council's Wireless Guidance: "These are requirements that sum organizations should beget in dwelling to protect their networks from attacks via rogue or unknown wireless access points (APs) and clients. They apply to organizations regardless of their exercise of wireless technology and regardless of whether the wireless technology is a participate of the CDE or not." And, "The purpose of PCI DSS requirement 11.1 is to ensure an unauthorized or rogue wireless device introduced into an organization's network does not allow unmanaged and unsecured WLAN access to the CDE. The intent is to prevent an attacker from using rogue wireless devices to negatively impact the security of cardholder data. In order to combat rogue WLANs, it is acceptable to exercise a wireless analyzer or a preventative control such as a Wireless Intrusion Detection/Prevention System (IDS/IPS) as defined by the PCI DSS."

  • Where is disaster recovery and traffic continuity planning covered in the PCI DSS requirements, or is it?Disaster recovery and BCP are not explicitly called out in the 2.0 version of PCI DSS; however, incident response planning is. "12.5.3 - Establish, document, and deal security incident response and escalation procedures to ensure timely and effectual handling of sum situations." besides in the Penetration Testing supplement it states: "Perform testing in accordance with faultfinding company processes including change control, traffic continuity, and disaster recovery." And, in the Application Reviews and Web Application Firewalls Clarified it states: "Adhere to sum policies and procedures including change control, traffic continuity, and disaster recovery."

  • Would you define "scope" as the geographical zone of the PCI servers? Or would you define "scope" as the SAQ requirements? It seems at times they are used interchangeably.The scope of the audit surface is the cardholder data environment (CDE). The CDE is "The people, processes and technology that store, process or transmit cardholder data or sensitive authentication data, including any connected system components." So any system component in the CDE is in scope regardless of geographic location.

  • Shared accounts are prohibited according to PCI DSS as I understand it, but imagine if you beget your network apparatus management outsourced and the firewalls and switches for the cardholder environment are managed by a third party or a service supplier. In this scenario, you would exigency two-factor authentication for administrative access to the CHE, but what if the service provider/supplier has several technicians and you are using RSA tokens? finish you beget to supply one authentication account and one RSA token per technician? Or is it necessary only to supply one account and one RSA token for the service provider/supplier? You're right that shared accounts are prohibited by PCI DSS; Requirement 8 states: "Assign a unique ID to each person with computer access." Strictly speaking, to live compliant, a unique ID and two-factor token would exigency to live assigned for each person remotely administering the firewalls and switches.

  • Can you discourse to some of the feedback you beget received from clients who beget implemented a tokenization product, including some of the key areas to focus on when selecting a vendor?We've received positive feedback from companies that exercise tokenization in the CDE to reduce scope. One that they spoke to and beget mentioned publicly is Helzberg Diamond Shops, Inc.. However, they caution that to live completely effective, organizations exigency to besides address scope reduction and zoning, document the tokenization implementation so it can live reviewed during audit, and confirm with your acquirer/processor that tokenization is acceptable. For vendor selection, the Council is working on tokenization guidance, but Visa Inc.has already issued its recommended guidance, Tokenization Best Practices.
  • Speaking from a university standpoint, they select credit cards in many ways -- POS, Internet, MOTO – but they exercise only PA-DSS applications and they are hosted by a service provider, so they finish not store any CHD. Their CHDE is really the PCs (and network) where the card data is entered or swiped. They beget segmented sum system components (PCs where CHD is entered or swiped) away from their regular network. It appears that many of the PA-DSS requirements are in reference to "stored" credit card data. Can you give me some counsel on how to determine how much of the requirements apply to us given that they finish not store CHD? They beget secured sum components that beget CHD entered and they are running PA-DSS-compliant applications.Sounds relish you've done a lot of remarkable scoping work. The PA-DSS applies to applications, but entities noiseless exigency to live PCI DSS compliant. Since your applications are already PA-DSS compliant, focus instead on what matters to your university, which is attesting to PCI DSS compliance. If your transactions levels qualify you for self-assessment review, the self-assessment guidelines (please contemplate question 1 for more information) and determine which one applies and complete that. In general, if you Fall under multiple SAQs your acquirer/processer will want you to complete SAQ –D. However, to live sure, check with your acquirer/processor to confirm.
  • Can you present counsel on what to observe for in an internal audit and reporting product for PCI DSS compliance?There are multiple audit and reporting utensil types that can live used in PCI DSS compliance. For example, a penetration testing system will revert reports on vulnerabilities and exposures in the CDE, while a patching system will revert reports on patch information, both of which apply. In many cases, when organizations cogitate about a meta-console for reporting, it is a log or event/information aggregation console that brings together multiple reporting components for exercise in PCI DSS compliance work. For any tool, observe for the competence to check for issues specific to PCI DSS (ex: password policy on servers and applications in the CDE) and report on these in a template that maps the finding to the specific requirement.

  • I beget a question about PCI and the cloud. They are a PCI smooth 1 merchant. They are thinking of piteous their data heart to cloud, Amazon to live specific. They understand that Amazon is PCI smooth 1 compliant. Is it really workable to live a PCI-compliant smooth 1 merchant in a cloud environment? finish you beget any guidance regarding PCI in a cloud environment?Amazon.com Inc. (Amazon Web Services – AWS) is, as of this writing, a PCI DSS Validated Service Provider. However, using AWS, or any Validated Service Provider, does not eradicate the exigency to entity using the service to live PCI DSS compliant . As Amazon notes, "All merchants must manage their own PCI certification. For the portion of the PCI cardholder environment deployed in AWS, your QSA can rely on their validated service provider status, but you will noiseless live required to fullfil sum other PCI compliance and testing requirements that don't deal with the technology infrastructure, including how you manage the cardholder environment that you host with AWS." So while a cloud provider can live third party validated as a PCI DSS provider, this doesn't spell they're certified to PCI or that entities using the service are automatically certified.

    If you are going to host some or sum of your CDE in the cloud, finish so with a compliant provider. However, don't forget to annually check that the provider is remaining compliant with your CDE, as well as the parts of your CDE that are hosted in the cloud. Additionally, according to the PCI Security Standards, your RoC must "document the role of each service provider, clearly identifying which requirements apply to the assessed entity and which apply to the service provider." And:

    "12.8 – If cardholder data is shared with service providers, maintain and implement policies and procedures to manage service providers, to embrace the following:

    12.8.1 – Maintain a list of service providers.

    12.8.2 –Maintain a written agreement that includes an acknowledgement that the service providers are liable for the security of cardholder data that the service providers possess.

    12.8.3 - Ensure there is an established process for engaging service providers including proper due diligence prior to engagement.

    12.8.4 - Maintain a program to monitor service providers' PCI DSS compliance status at least annually"

  • In effort to ensure PCI compliance, they beget a number of different products from different vendors, since there does not seem to live one plenary PCI compliance "solution." Is this by design? Is there any odds to having each requirement met by a different vendor's product?There are a number of components in PCI compliance and they encompass people, process and technology, and span both the physical and the logical. Also, sum of the documentation related to policies and process. It would live extremely difficult (arguably impossible) for a solitary solution to finish it all. The reality is that organizations exercise a number of different vendor solutions for the technical controls.

    Some vendors provide products that meet different controls. For example, a vendor with a log aggregation or SIEM utensil that besides sells antivirus/malware or patch management. The ample win is not necessarily to beget sum tools (or many tools) from the identical vendor, but to live able to bring together reporting, logs, test and monitoring information in a centralized dwelling to manufacture oversight and compliance monitoring more comprehensive and efficient.

  • How can companies deal with summon recordings in the summon heart when taking card payments by phone? Are there any mitigating factors?Because there is not a lot of summon heart guidance in the PCI DSS, the Council addressed summon heart issues in a special FAQ #5362. "The Council's position remains that if you can digitally query sensitive authentication data (SAD) contained within audio recordings - if dejected is easily accessible - then it must not live stored."

    Though this is not hosted on the PCI Security measure Council Domain -- it is the official FAQ for the Council and can live accessed directly by clicking in the FAQs link at the top of the official Council page.

    Also, delight contemplate question below for additional information on storage rules regarding sensitive authentication data (SAD).

  • Our call-recording solution requires manual intervention to bleep out the CV2 number. Is this adequate as a compensating control to meet the standard?

    If the CV2 (or any other sensitive authentication data/SAD) is not stored, this should meet the standard. Document how the manual process is implemented to ensure dejected is truly being deleted and not stored.

    Alternately, according to PCI Security Standards Council FAQ "If these recordings cannot live data mined, storage of CAV2, CVC2, CVV2 or CID codes after authorization may live permissible as long as appropriate validation has been performed. This includes the physical and rational protections defined in PCI DSS that must noiseless live applied to these summon recording formats."

  • If you beget backups of credit card data in a secure location, is that a violation? How can it live mitigated?It's not a violation -- it is participate of a requirement! Requirement 9.5 explicitly states: "Store media back-ups in a secure location, preferably an off-site facility, such as an alternate or back-up site, or a commercial storage facility. Review the location's security at least annually." recollect to manufacture sure the data was encrypted before it was backed up and that the personnel at the facility finish not beget the key to decrypt the data.

  • What are the rules for external scanning?External scanning is covered in Requirement 11.2.2 – "Perform quarterly external vulnerability scans via an Approved Scanning Vendor (ASV), approved by the Payment Card Industry Security Standards Council (PCI SSC).

    Note: Quarterly external vulnerability scans must live performed by an Approved Scanning Vendor (ASV), approved by the Payment Card Industry Security Standards Council (PCI SSC). Scans conducted after network changes may live performed by internal staff." 

    See the PCI Security measure for a list of ASVs

    Also helpful is the ASV Program Guide, and the ASV Client Feedback Form

  • PCI 2.0 lightly touches upon virtualization for the first time. Does this extend beyond virtual machine images to virtual appliances (e.g. exercise of virtual firewalls & virtual switches in hosted products)?Yes, according to the Scope of Assessment for Compliance it does extend to virtual appliances. "System components" in v2.0 include, "any virtualization components such as virtual machines, virtual switches/routers, virtual appliances, virtual applications/desktops, and hypervisors." besides note that virtualization is mentioned in Requirement 2.2.1: Implement only one primary role per server, "Note: Where virtualization technologies are in use, implement only one primary role per virtual system component."

  • Is a system that is not holding the cardholder data, but only processing it (like a Web farm) a participate of PCI audit requirements?Yes, if a system component stores, processes or transmits cardholder data or sensitive authentication data, it is participate of the CDE and within scope of the PCI DSS audit. For additional guidance, mention to the Scope of Assessment for Compliance with PCI DSS requirements section of PCI DSS v2.0.

  • When finish companies beget to switch over to PCI 2.0?For the absolute final word on compliance deadlines, check with your acquirer or specific card brand. In general, however, v2.0 went into outcome on January 1, 2011 and there is a year to comply with the modern standard. If you are in the middle of an assessment cycle that started in 2010 and the compliance assessment will live completed before the halt of 2011, you can continue the process with v1.2.1. If you a starting a modern assessment cycle in 2011, exercise v2.0.

  • If an organization has filled out the self assessment questionnaire (SAQ) and identified that it has not complied with the 12 DSS requirements, should the SAQ noiseless live submitted? Or should the organization wait until the 12 requirements beget been satisfied?Before admitting defeat, contemplate if there is any course your organization can earn to live compliant. Don't forget, if a non-compliant system or process is not essential, it could live scoped out of the CDE and out of the compliance surface. besides don't forget about compensating controls. The pattern is to live fully compliant, but compensating controls provide a course for organizations to live mitigating risks as they work towards implementing better controls.

    According to the Compensating Controls Appendix B in SAQ D v2.0: "Compensating controls may live considered for most PCI DSS requirements when an entity cannot meet a requirement explicitly as stated, due to legitimate technical or documented traffic constraints, but has sufficiently mitigated the risk associated with the requirement through implementation of other, or compensating, controls." Also, there is a compensating control worksheet that needs to live completed in Appendix C of the SAQ D v2.0.

    If de-scoping the non-compliant system and compensating controls are not options, then you will exigency to check the "Non-Compliant" box on the SAQ and achieve in a target date for compliance. In most cases, your acquirer/processor will want to contemplate this proof, and possibly interrogate your organization to fill out the "Action Plan" participate of the SAQ; however, check with your acquirer/processor to live sure.

  • Let's talk about the mythical beast that is end-to-end encryption. Does it exist? More specifically, one of their audience members asked, "What if end-to-end encryption from the pin pad / card swipe POS is implemented? Does that select everything out of PCI scope?"The Council is calling this P2PE for point-to-point encryption. meaning turning the cardholder data into ciphertext (encrypting it) and then transmitting it, encrypted to a destination, for example, the payment processor. If the P2PE begins on swipe by cashier of the credit card at the PoS (point of sale) and continues sum the course to the processor, it is not stored, and no one in the interim path has the keys to decrypt the data, then it could reduce the scope of the audit surface significantly. Caveats here are that everything will exigency to live implemented correctly, validated and tested. However, note that the entity noiseless must live PCI DSS compliant – though compliance may live greatly simplified. And, at this time, the PCI Security Standards Council noiseless deems P2PE an emerging technology and is formalizing official guidance, training QSAs on how to evaluate material P2PE components, as well as considering creating a validated list of P2PE solutions. For more information on the status of P2PE, delight read the Initial Roadmap: Point-to-Point Encryption Technology and PCI DSS Compliance program guide.

  • Under what circumstances can an internal audit certify a merchant as being PCI compliant?If the merchant qualifies for SAQ completion, internal audit can live liable for the assessment and attestation process. "Each payment card brand has defined specific requirements for compliance validation and reporting, such as provisions for performing self-assessments and when to engage a QSA."

    If the merchant must complete a RoC, it is workable to finish the on-site assessment with an internal resource if the brand allows it. Check with your brand for specifics, Mastercard Inc., for example, has deemed that as of June 30, 2011, the "primary internal auditor staff engaged in validating PCI DSS compliance [must] attend PCI SSC ISA Training and pass the associated accreditation program annually."

  • What PCI and security implications finish you anticipate arising with the modern generation of contact-less cards, given that they are now being widely distributed?If the data can live transmitted in a secure encrypted format over the RF from the contact-less card to a secure endpoint, the data should not live exposed. However, if the data from the card is in clear-text over the air, sniffing attacks will live a major concern. Also, key management and MiTMs may live problems depending on specific technical implementations.

  • Are quarterly penetration tests noiseless required for wireless access points that are using WPA-2?Yes, quarterly tests are required. Requirement 11.1 covers sum known/unknown wireless access points regardless of protections on them. "11.1 - Test for the presence of wireless access points and detect unauthorized wireless access points on a quarterly basis." The understanding for this is that one of the intents of this requirement is to ensure there are no rogue devices in the CDE.

  • Does Citrix sessioning between payment apps and hosted sites provide adequate encryption for PCI compliance?If the session is configured to transmit the data between the payment apps and the hosted site using an approved manner (ex: SSL/TLS ) then it should live compliant for at least the transmission portion of the standard.

    Requirement 4.1 -- "Use strong cryptography and security protocols (for example, SSL/TLS, IPSEC, SSH, etc.) to safeguard sensitive cardholder data during transmission over open, public networks."

  • How much are organizations spending on PCI compliance? Can you provide a range both for one-time costs and annual maintenance?There are two sides to this coin: cost of the audit and cost of compliance overall.
  • Audit cost: According to a recent Ponemon survey on PCI DSS trends (.pdf), the middling cost of the audit itself is $225,000 for the largest (Tier 1) merchants, but the cost can range much higher or lower depending on complexity of the environment, size of the CDE, and other factors .

  • Overall cost of compliance: In 2008, Gartner conducted a survey of 50 merchants and create that PCI costs had been increasing since 2006 (Gartner.com registration required) and cited costs averaging 2.7M for Tier 1 merchants, 1.1M for Tier 2, and 155k for Tier 3. Again, these are averages, so your particular case might live different.
  • Requirement 2.2.1 mandates that faultfinding servers provide a single-purpose service. If I beget a solitary server hosting an e-commerce application with a Web server and database residing on a physical server, finish I exigency to dwelling the database on a sever server?Yes, in most cases. Requirement 2.2.1 – "Implement only one primary role per server to prevent functions that require different security levels from co-existing on the identical server." The intent of this requirement is to provide some protections if the underlying host, in this case the operation system running the database and e-commerce application is breached, causing one or both of the services to live exposed to attack. VMs are now allowed, so the identical piece of hardware could live used with a hypervisor to sever the two services across two VMs. Alternately, if there is a faultfinding traffic need, such as performance, for both primary functions to live on the identical server, deem if this justifies a compensating control by completing the compensating control worksheet (Appendix C of the PCI DSS).
  • About the author:Ed Moyle is currently a manager with CTG's Information Security Solutions practice, providing strategy, consulting, and solutions to clients worldwide as well as a founding ally of SecurityCurve.

    Diana Kelley is a ally with Amherst, N.H.-based consulting solid SecurityCurve. She formerly served as vice president and service director with research solid Burton Group. She has extensive taste creating secure network architectures and traffic solutions for big corporations and delivering strategic, competitive information to security software vendors.



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