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description: The California State Wildlife Action Plan (SWAP) is required under the State and Tribal Wildlife Grants Program (SWG), which allows states and territories to receive Federal grant funds. It is a comprehensive vision for wildlife conservation initially completed in 2005 and updated in 2015. The GIS data for SWAP are divided into two types - terrestrial (vegetation macrogroup based) and aquatic(watershed based)data. This file contains the terrestrial targets. The SWAP defines "target" macrogroups throughout the state and describes their "Key Ecological Attributes", Environmental "Pressures"" (positive or negative) and "Strategies" for protection/enhancement of each target. Terrestrial targets are composed of specific macrogroups which are assigned target status based on what ecoregion and province they are within. A macrogroup may be a target within a certain ecoregion, but not a target within others. The macrogroups used in this data set come from CaLFIRE-FRAP data. Initially, CALFIRE-FRAP compiled the "best available" land cover data into a single data layer (FVEG15_1), to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data were updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. The landcover data were crosswalked to macrogroups based on the Manual of California Vegetation (MCV) for use in the California Department of Fish and Wildlife's (CDFW) State Wildlife Action Plan (SWAP) in 2015. The "best available" landcover dataset for California (FVEG15_1) was crosswalked to macrogroups, a level in the hierarchical vegetation classification from the California Manual of Vegetation (MCV), the California arm of the National Vegetation Classification System (NVCS). These data were developed for use in CDFW's 2015 SWAP update and presented in Chapter 5 of the SWAP document using common names which are used throughout the SWAP document. A crosswalk between SWAP common names and USNVC macrogroups names is found in Table D-21 in the Appendix Volume (Volume II) of the SWAP document. See the first table of each subsection in Volume I Chapter 5 for the crosswalks used to convert the California Wildlife Habitat Relationships (CWHR) system habitat types from FVEG15_1 to MCV macrogroup types. In some instances, a single CWHR category could me one of up to three macrogroups. In these instances, all three macrogroups were mentioned in the attribute table. A user should assess whether their habitat matches one of these macrogroups by looking at the table (from Chapter 5) on the page mentioned in the attribute table. The SWAP document locations of target conservation strategies and climate change adaptation strategies and target descriptions have been added to the attribute table for this dataset. The specific page locations (chapter and page)of the data sources are given in the attributes for the data. The page references are to Chapter 5 within the State Wildlife Action Plan 2015 Update, which is available at https://www.wildlife.ca.gov/SWAP/Final.; abstract: The California State Wildlife Action Plan (SWAP) is required under the State and Tribal Wildlife Grants Program (SWG), which allows states and territories to receive Federal grant funds. It is a comprehensive vision for wildlife conservation initially completed in 2005 and updated in 2015. The GIS data for SWAP are divided into two types - terrestrial (vegetation macrogroup based) and aquatic(watershed based)data. This file contains the terrestrial targets. The SWAP defines "target" macrogroups throughout the state and describes their "Key Ecological Attributes", Environmental "Pressures"" (positive or negative) and "Strategies" for protection/enhancement of each target. Terrestrial targets are composed of specific macrogroups which are assigned target status based on what ecoregion and province they are within. A macrogroup may be a target within a certain ecoregion, but not a target within others. The macrogroups used in this data set come from CaLFIRE-FRAP data. Initially, CALFIRE-FRAP compiled the "best available" land cover data into a single data layer (FVEG15_1), to support the various analyses required for the Forest and Rangeland Assessment, a legislatively mandated function. These data were updated to support on-going analyses and to prepare for the next FRAP assessment in 2015. The landcover data were crosswalked to macrogroups based on the Manual of California Vegetation (MCV) for use in the California Department of Fish and Wildlife's (CDFW) State Wildlife Action Plan (SWAP) in 2015. The "best available" landcover dataset for California (FVEG15_1) was crosswalked to macrogroups, a level in the hierarchical vegetation classification from the California Manual of Vegetation (MCV), the California arm of the National Vegetation Classification System (NVCS). These data were developed for use in CDFW's 2015 SWAP update and presented in Chapter 5 of the SWAP document using common names which are used throughout the SWAP document. A crosswalk between SWAP common names and USNVC macrogroups names is found in Table D-21 in the Appendix Volume (Volume II) of the SWAP document. See the first table of each subsection in Volume I Chapter 5 for the crosswalks used to convert the California Wildlife Habitat Relationships (CWHR) system habitat types from FVEG15_1 to MCV macrogroup types. In some instances, a single CWHR category could me one of up to three macrogroups. In these instances, all three macrogroups were mentioned in the attribute table. A user should assess whether their habitat matches one of these macrogroups by looking at the table (from Chapter 5) on the page mentioned in the attribute table. The SWAP document locations of target conservation strategies and climate change adaptation strategies and target descriptions have been added to the attribute table for this dataset. The specific page locations (chapter and page)of the data sources are given in the attributes for the data. The page references are to Chapter 5 within the State Wildlife Action Plan 2015 Update, which is available at https://www.wildlife.ca.gov/SWAP/Final.

A total of 109 Prop 1, 62 SWG, 63 Traditional ESA Section 6, and 51 Non-Traditional ESA Section 6 projects were analyzed from the years 2015-2018, 2015-2020, 2015-2020, and 2015-2019, respectively, in order to answer the following questions for each project (which resulted in qualitative data): Is the geographic scale of this project statewide? If so, proceed to question 12; otherwise, proceed to question 2. For a project not spanning the entire state, would it directly benefit anadromous fishes? If not, proceed to question 4; otherwise, proceed to question 3. For a project directly benefitting anadromous fishes, enter the salmonid ecoregion/s (see SWAP 2015 Figure 6.4-1) in which the project would be located, as well as the conservation target/s it would address, and the conservation strategy/strategies it would apply to those target/s (may enter more than one; these correspond to SWAP 2015 Table 6.7-1, on pages 6-19 to 6-20). If this is a multibenefit project, proceed to question 4. Otherwise, there are no further questions. For a project neither spanning the entire state nor directly benefitting anadromous fishes: a. Enter the geographic province/s that would bound the project site (may enter more than one; these correspond to SWAP 2015 Figure 1.5-1, on page 1-14), as well as the ecoregion/s and/or marine conservation units in which the project would be located (may enter more than one; these correspond to SWAP 2015 Figure 1.5-2, on page 1-16): b. Also, enter the hydrologic unit/s in which the project would be located (may enter more than one; these correspond to SWAP 2015 Figure 1.5-3, on page 1-17; note: hydrologic units overlap with ecoregions). For a project not directly benefitting anadromous fishes that would be sited in the Bay Delta & Central Coast geographic province (proceed to questions 6-11 for other locations), enter the conservation target/s it would address, under the appropriate conservation unit/s (may enter more than one; these correspond to SWAP 2015 Figure 5.3-2, page 5.3-10, and Table 5.3-1, pages 5.3-12 to 5.3-13). Also, enter the key ecological attribute/s of (may enter more than one; these correspond to SWAP 2015 Table 5.3-2, page 5.3-15) and pressure/s on the target/s (may enter more than one; these correspond to SWAP 2015 Table 5.3-11, pages 5.3-59 to 5.3-60) it would address. Finally, enter the conservation strategy/strategies that would be applied to the conservation target/s to change the pressure/s on their key ecological attributes (may enter more than one; these correspond to SWAP 2015 Table 5.3-11, pages 5.3-59 to 5.3-60). For a project not directly benefitting anadromous fishes that would be sited in the Cascades & Modoc Plateau geographic province (proceed to questions 7-11 for other locations), enter the conservation target/s it would address, under the appropriate conservation unit/s (may enter more than one; these correspond to SWAP 2015 Table 5.2-1, pages 5.2-9 to 5.2-11). Also, enter the key ecological attribute/s of (may enter more than one; these correspond to SWAP 2015 Table 5.2-2, page 5.2-13) and pressure/s on the target/s (may enter more than one; these correspond to SWAP 2015 Table 5.2-11, page 5.2-53) it would address. Finally, enter the conservation strategy/strategies that would be applied to the conservation target/s to change the pressure/s on their key ecological attributes (may enter more than one; these correspond to SWAP 2015 Table 5.2-11, page 5.2-53). For a project not directly benefitting anadromous fishes that would be sited in the Central Valley & Sierra Nevada geographic province (proceed to questions 8-11 for other locations), enter the conservation target/s it would address, under the appropriate conservation unit/s (may enter more than one; these correspond to SWAP 2015 Table 5.4-1, pages 5.4-12 to 5.4-17). Also, enter the key ecological attribute/s of (may enter more than one; these correspond to SWAP 2015 Table 5.4-2, page 5.4-18) and pressure/s on the target/s (may enter more than one; these correspond to SWAP 2015 Table 5.4-18, pages 5.4-91 to 5.4-93) it would address. Finally, enter the conservation strategy/strategies that would be applied to the conservation target/s to change the pressure/s on their key ecological attributes (may enter more than one; these correspond to SWAP 2015 Table 5.4-18, pages 5.4-91 to 5.4-93). For a project not directly benefitting anadromous fishes that would be sited in the Deserts geographic province (proceed to questions 9-11 for other locations), enter the conservation target/s it would address, under the appropriate conservation unit/s (may enter more than one; these correspond to SWAP 2015 Table 5.6-1, pages 5.6-11 to 5.6-13). Also, enter the key ecological attribute/s of (may enter more than one; these correspond to SWAP 2015 Table 5.6-2, page 5.6-14) and pressure/s on the target/s (may enter more than one; these correspond to SWAP 2015 Table 5.6-17, pages 5.6-75 to 5.6-77) it would address. Finally, enter the conservation strategy/strategies that would be applied to the conservation target/s to change the pressure/s on their key ecological attributes (may enter more than one; these correspond to SWAP 2015 Table 5.6-17, pages 5.6-75 to 5.6-77). For a project not directly benefitting anadromous fishes that would be sited in the Marine geographic province (proceed to questions 10-11 for other locations), enter the conservation target/s it would address, under the appropriate conservation unit/s (may enter more than one; these correspond to SWAP 2015 Section 5.7.2, page 5.7-6). Also, enter the key ecological attribute/s of (may enter more than one; these correspond to SWAP 2015 Table 5.7-4, page 5.7-27) and pressure/s on the target/s (may enter more than one; these correspond to SWAP 2015 Table 5.7-4, page 5.7-27) it would address. Finally, enter the conservation strategy/strategies that would be applied to the conservation target/s to change the pressure/s on their key ecological attributes (may enter more than one; these correspond to SWAP 2015 Table 5.7-4, page 5.7-27; note: SWAP 2015 conservation strategies were initially only developed for the Embayments, Estuaries, Lagoons target). For a project not directly benefitting anadromous fishes that would be sited in the North Coast & Klamath geographic province (proceed to question 11 for the South Coast), enter the conservation target/s it would address, under the appropriate conservation unit/s (may enter more than one; these correspond to SWAP 2015 Table 5.1-1, pages 5.1-9 to 5.1-12). Also, enter the key ecological attribute/s of (may enter more than one; these correspond to SWAP 2015 Table 5.1-2, page 5.1-13) and pressure/s on the target/s (may enter more than one; these correspond to SWAP 2015 Table 5.1-16, pages 5.1-79 to 5.1-81) it would address. Finally, enter the conservation strategy/strategies that would be applied to the conservation target/s to change the pressure/s on their key ecological attributes (may enter more than one; these correspond to SWAP 2015 Table 5.1-16, pages 5.1-79 to 5.1-81). For a project not directly benefitting anadromous fishes that would be sited in the South Coast geographic province, enter the conservation target/s it would address, under the appropriate conservation unit/s (may enter more than one; these correspond to SWAP 2015 Table 5.5-1, page 5.5-9). Also, enter the key ecological attribute/s of (may enter more than one; these correspond to SWAP 2015 Table 5.5-2, page 5.5-10) and pressure/s on the target/s (may enter more than one; these correspond to SWAP 2015 Table 5.5-170, pages 5.5-39 to 5.5-40) it would address. Finally, enter the conservation strategy/strategies that would be applied to the conservation target/s to change the pressure/s on their key ecological attributes (may enter more than one; these correspond to SWAP 2015 Table 5.5-170, pages 5.5-39 to 5.5-40). For a statewide project directly benefitting anadromous fishes (for a statewide project not benefitting anadromous fishes, skip to question 13), enter the conservation target/s it would address and the conservation strategy/strategies it would apply to those target/s (may enter more than one; these correspond to SWAP 2015 Table 6.7-1, on pages 6-19 to 6-20). For a statewide project not directly benefitting anadromous fishes, enter the sub-goal/s it would address, under the appropriate goal/s (may enter more than one; these correspond to SWAP 2015, page 4-3). This data and metadata were submitted by California Department of Fish and Wildlife (CDFW) Staff though the Data Management Plan (DMP) framework with the id: DMP000522. For more information, please visit https://wildlife.ca.gov/Data/Sci-Data.

General InformationThe SWAP defines "targets" throughout the state and describes "Strategies" for each target. The grouping for these targets is based on "Hydrologic Units" which are defined by "Hydrologic Unit Codes" (HUC's). Each code defines a watershed. 4-digit HUC's describe large watersheds which group the watersheds of many rivers. As the watersheds become more specific, numbers are added to the HUC to define them in more detail, so that an 8-digit hydrologic unit (HUC8) is much smaller than a 4 -digit hydrologic unit (HUC4). The HUC's in this data set are defined in the National Hydrography Dataset (NHD), which describes watersheds and waterbodies throughout the United States.Aquatic Targets in the SWAP are grouped by 4 to 12-digit HUC's into "Conservation Units". These units are described in the first table of each section of Chapter 5 of the SWAP report, which is available at https://www.wildlife.ca.gov/SWAP/Final. Each 4-digit HUC has one or more "Conservation Targets", which are composed of groups of specific targeted fish and/or other aquatic species or, in the Deserts, specific aquatic features. The foundation of the smaller groupings of this data set is the "Zoogeographic Provinces of California", a map in "Inland Fishes of California" by Peter Moyle. This document describes the native fish assemblage areas. The data defining these units was acquired from University of California at Davis Center for Watershed Science. This data set describes the Conservation Units, Targets, and conservation strategies (including Climate Change strategies) and provides the specific SWAP document pages on which to find details about strategies and other information about the targets.

The Nevada Wildlife Action Plan identifies these 22 Key Habitats (Caves and Mines ommitted for safety and sensitivity concerns) that form a framework for linking species conservation strategies to the landscape. These data were derived from the USGS Southwest Regional GAP landcover dataset, the BLM Geographic Names Information System, and the National Oceanographic and Atmospheric Administration major rivers dataset and crosswalked to fit the ecological framework of the Wildlife Action Plan.These data are not an exhaustive representation of the habitats described, and should only serve as a point of reference for habitat and wildlife conservation planning.

Values refer to Fig. 3.

The electric vehicle (EV) battery swapping service market is poised for significant growth, driven by increasing EV adoption, limitations of conventional charging infrastructure, and the inherent advantages of rapid battery swapping for enhancing vehicle uptime. The market, estimated at $2 billion in 2025, is projected to experience a robust Compound Annual Growth Rate (CAGR) of 25% from 2025 to 2033, reaching approximately $10 billion by 2033. This growth is fueled by several key factors. Firstly, the rising concerns about climate change and government incentives promoting EV adoption are creating a larger pool of potential battery swapping service users. Secondly, battery swapping addresses range anxiety and long charging times, crucial limitations hindering widespread EV acceptance. Thirdly, the increasing availability of standardized battery packs facilitates interoperability across different EV models, boosting the market's scalability. Finally, several innovative companies are developing advanced battery swapping technologies and business models, further propelling market expansion. The market is segmented by service type (subscription vs. pay-per-use) and EV type (Battery Electric Vehicles (BEVs) and Plug-in Hybrid Electric Vehicles (PHEVs)), with BEVs currently dominating the demand. However, the market faces certain challenges. High initial infrastructure investment costs for swapping stations pose a significant barrier to entry for new players. Standardization of battery packs remains a crucial aspect for widespread adoption and interoperability across different manufacturers. Furthermore, safety concerns related to battery handling and swapping procedures require stringent regulatory oversight and technological advancements. Despite these restraints, the long-term outlook remains positive, particularly in densely populated urban areas and regions with supportive government policies. The Asia-Pacific region, driven primarily by China and India, is expected to lead the market due to the rapid growth of the EV sector and government initiatives promoting battery swapping infrastructure. North America and Europe will also witness substantial growth, though possibly at a slightly slower pace due to a more established charging infrastructure. The competitive landscape is dynamic, with both established players like Panasonic and BYD, and innovative startups like Gogoro and NIO, vying for market share. Success will depend on technological innovation, strategic partnerships, and effective deployment of battery swapping infrastructure.

The traffic volumes in three different scenarios (Unit: pcu/h).

The two-wheeler battery swap cabinet market is experiencing robust growth, driven by the burgeoning electric two-wheeler (e-2W) sector and the increasing need for convenient and efficient battery charging solutions. The market, valued at $142 million in 2025, is projected to grow at a compound annual growth rate (CAGR) of 8.1% from 2025 to 2033. This growth is fueled by several key factors. Firstly, the rising adoption of e-2Ws in urban areas, particularly for last-mile delivery and personal commuting, necessitates efficient battery swapping infrastructure to overcome range anxiety and charging time limitations. Secondly, the increasing focus on sustainable transportation solutions and government incentives promoting electric mobility are further boosting market expansion. The diverse range of cabinet sizes (3-bay to 15-bay) caters to varying needs of businesses and operators, from small-scale deployments to large-scale battery swapping networks. Key players like Shenzhen Immotor Technology Limited, Hello, Inc., and China Tower are actively shaping the market landscape through innovation and strategic partnerships, focusing on optimizing cabinet design, deployment strategies, and integration with battery management systems. The market segmentation by application (instant delivery, C-side users) reveals distinct growth trajectories. The instant delivery segment is experiencing particularly rapid growth due to the high demand for quick and reliable deliveries in urban settings, while the C-side user segment (individual consumers) is exhibiting steady growth as e-2W ownership expands. Geographical expansion is another prominent trend. While Asia-Pacific currently holds a significant market share, driven by strong e-2W adoption in China and India, other regions like North America and Europe are witnessing increasing demand. However, challenges remain, including high initial investment costs for deploying battery swapping infrastructure, standardization issues related to battery compatibility, and the need for robust safety regulations to ensure reliable and safe operation of these cabinets. Overcoming these challenges will be crucial for continued market expansion and realizing the full potential of battery swap technology in the e-2W sector.

Snapshot img

Foreign Exchange Market Size 2025-2029

The foreign exchange market size is forecast to increase by USD 582 billion at a CAGR of 10.6% between 2024 and 2029.

The market continues to evolve, driven by several key trends and challenges. One significant trend is the increasing use of money transfer agencies, venture capital investments, and mutual funds in foreign exchange transactions. The Internet of Things (IoT) and artificial intelligence (AI) revolutionize banking and financial services, enabling real-time personal finance software and content delivery for travelers and businesses. The uncertainty of future exchange rates fuels the demand for 24x7 trading opportunities. As urbanization progresses and digitalization becomes more prevalent, the market is expected to grow, offering numerous opportunities for businesses and investors.

What will be the Size of the Foreign Exchange Market During the Forecast Period?

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The market, also known as the forex or FX market, is a decentralized global market for the trading of currencies. It facilitates the conversion of one currency into another for various reasons, including international trade, tourism, hedging, speculation, and investment. Participants in this market include financial institutions, non-financial customers, individuals, retailers, corporate institutes, and central banks. Currencies are traded 24 hours a day, five days a week, due to the presence of multiple time zones and the interbank network.
Currency swaps, interest rate differentials, monetary interventions, economic indicators, political developments, and investment flows are some of the key drivers influencing the market. International trade, balance of payments, and economic instability in various countries also significantly impact currency values. Speculation and hedging activities, particularly by corporations and financial institutions, contribute to the volatility of currency rates. The market is increasingly leveraging artificial intelligence and Internet of Things technologies to optimize trading strategies, with mutual funds utilizing these advancements to enhance portfolio performance and manage currency risk more efficiently. The forex market plays a crucial role in facilitating international business transactions and managing risks associated with currency fluctuations.

How is this Foreign Exchange Industry segmented and which is the largest segment?

The industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.TypeReporting dealersFinancial institutionsNon-financial customersTrade Finance InstrumentsCurrency swapsOutright forward and FX swapsFX optionsCounterpartyReporting DealersOther Financial InstitutionsNon-Financial CustomersGeographyNorth AmericaCanadaUSEuropeGermanyUKAPACChinaIndiaJapanSouth AmericaBrazilMiddle East and Africa

By Type Insights

The reporting dealers segment is estimated to witness significant growth during the forecast period. The market, also known as Forex or FX, is a global financial market where participants buy, sell, and exchange currencies. This market involves various market participants, including financial institutions, non-financial customers, and corporations. Currency swaps, individuals, retailers, corporates, hedge funds, wealth managers, and foreign exchange services are among the key players. The markets facilitate international trade and investment flows, with economic indicators, political developments, inflationary pressures, and interest rate differentials influencing currency values. Monetary interventions, speculation, and risk appetite are also significant factors.
Modern technology and electronic platforms have increased efficiency and accessibility, enabling 24-hour operation. Currency exchange services, monetary policies, and regulations, including those by central banks, impact the market. Economic events, financial crises, and strategic corporate activities can cause volatility. Hedging strategies, accessible platforms, and personal finance considerations are essential for individual investors, small businesses, and multinational corporations dealing with major currency pairs. Online trading platforms and trade balances are crucial for managing currency risks in an increasingly globalized business environment.

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The Reporting dealers segment was valued at USD 278.60 billion in 2019 and showed a gradual increase during the forecast period.

Currency pairs are the foundation of forex trading, with spot trading being one of the most common methods of buying and selling currencies. Forward contracts and swap deals offer traders the ability to lock in exchange rates for future transactions, managing ris

RNA isolated from the 0, 10, 25, 50 and 100 micromolar AFB1 cultures at 120 min treatment was used for cDNA microarray experiments. For each array hybridization experiment, RNAs from the treated sample and its corresponding time-matched control were co-hybridized to arrays and respectively quantified in different channels. A dye swap strategy was used to eliminate the dye bias. Keywords: dose response

Signal timing plans for Plan II under different scenarios (Unit: s).

The Electric vehicle battery swapping Market size was valued at USD 100.2 USD Million in 2023 and is projected to reach USD 127.48 USD Million by 2032, exhibiting a CAGR of 3.5 % during the forecast period. Battery Swapping is the technique of changing a discharged battery with a charged battery and putting it in a mom component (vehicle), whilst maintaining the discharged battery in a charging platform/station. This aids withinside the super-rapid charging of batteries. This gets rid of the variety barrier for electric powered vehicles, making an allowance for the standardisation and interchangeability of batteries from more than one companies. A swappable battery electric powered automobile is tons quicker than conventional charging strategies like plugging into an outlet or the use of a public charging station. This manner that drivers can get again on the street quicker, that is mainly useful for individuals who are journeying lengthy distances. The international Electric Vehicle Battery Swapping marketplace is developing often because of the call for for hassle-loose and low-priced answers for EV drivers. Recent developments include: In 2022, Ample secured USD 150 million in Series C funding to accelerate its battery-swapping network expansion. In 2021, Gogoro announced a partnership with Hero MotoCorp to launch a battery-swapping network in India. In 2020, BAIC introduced its first electric vehicle model with a battery-swapping feature.. Key drivers for this market are: Increasing Demand for Forged Products in Power, Agriculture, Aerospace, and Defense to Drive Industry Expansion. Potential restraints include: High Total Cost of Investment to Restrain Growth. Notable trends are: Rising Adoption of Automation in Manufacturing to Drive Market Growth.

Recommended design parameters and related MOE.

The Intelligent Battery Swapping for Two-Wheeled Electric Vehicles (2W EVs) market is rapidly evolving, driven by the global shift towards sustainable transportation solutions and the increasing demand for electric mobility. As cities become more congested and environmental concerns take center stage, battery swappi

IntroductionAn important impediment to the large-scale adoption of evidence-based school nutrition interventions is the lack of evidence on effective strategies to implement them. This paper describes the protocol for a “Collaborative Network Trial” to support the simultaneous testing of different strategies undertaken by New South Wales Local Health Districts to facilitate the adoption of an effective school-based healthy lunchbox program (‘SWAP IT’). The primary objective of this study is to assess the effectiveness of different implementation strategies to increase school adoption of the SWAP across New South Wales Local Health Districts.MethodsWithin a Master Protocol framework, a collaborative network trial will be undertaken. Independent randomized controlled trials to test implementation strategies to increase school adoption of SWAP IT within primary schools in 10 different New South Wales Local Health Districts will occur. Schools will be randomly allocated to either the intervention or control condition. Schools allocated to the intervention group will receive a combination of implementation strategies. Across the 10 participating Local Health Districts, six broad strategies were developed and combinations of these strategies will be executed over a 6 month period. In six districts an active comparison group (containing one or more implementation strategies) was selected. The primary outcome of the trial will be adoption of SWAP IT, assessed via electronic registration records captured automatically following online school registration to the program. The primary outcome will be assessed using logistic regression analyses for each trial. Individual participant data component network meta-analysis, under a Bayesian framework, will be used to explore strategy-covariate interactions; to model additive main effects (separate effects for each component of an implementation strategy); two way interactions (synergistic/antagonistic effects of components), and full interactions.DiscussionThe study will provide rigorous evidence of the effects of a variety of implementation strategies, employed in different contexts, on the adoption of a school-based healthy lunchbox program at scale. Importantly, it will also provide evidence as to whether health service-centered, collaborative research models can rapidly generate new knowledge and yield health service improvements.Clinical trial registrationThis trial is registered prospectively with the Australian New Zealand Clinical Trials Registry (ACTRN12623000558628).

(a) Background of clustering analysis for α = 1.6 from Fig 2, but with Euclidean distance used so that a projection matrix could be found to show the trajectories in the 2D principle coordinate plane (S1 Text Sec. 5.6). We aim to steer a local community (denoted as LC*, shown in magenta) in the blue cluster to the orange cluster. Three different scenarios are presented, per the three numbers above the arrows. Scenario 1: SISs swap. The SISs (23 and 81) of LC* were replaced by the SISs present in the orange cluster (60 and 51). The initial abundances of species 60 and 51 were drawn from , resulting in and altered community (green dot), and the GLV dynamics were simulated until the steady state was reached (white dot), which is located in the orange cluster as desired. Scenario 2: Dominating Species (DS) swap. The six most abundant species in LC* were removed and replaced by the six most abundant species from a local community in the orange cluster, with the initial condition after the switch of species shown as the red dot, and the dynamics were simulated until steady state was reached (white dot). Scenario 3: Fecal Microbiota Transplantation (FMT). The two SISs and 18 of the most abundant species (for a total of 20) were removed from LC* with the initial condition shown in blue (post-antibiotic state). Then the GLV dynamics were simulated (gray line) and the system converged to the black dot (CDI state). Then 1% of the steady abundances from an arbitrary LC in the orange cluster were added to the CDI state (gray dot, emulating oral capsule FMT) and the dynamics were then simulated until steady state was reached. (b) The SISs swap process was repeated ten times, each time the initial abundances of species 60 and 51 were randomly drawn from . Nine of the simulations are shown in black and the simulation that pertains to Fig 4a is shown in maroon. (c) The same analysis as for Fig 5a, in terms of SISs swap, but for α = 2. (d) The same analysis as for Fig 5a, in terms of SISs swap, but for α = 3.