Conservation Blueprint 2.2: Priorities for shared action

Sep 28, 2017 (Last modified Nov 12, 2018)
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Blueprint 2.2
The Blueprint is a living spatial plan for sustaining natural and cultural resources in the face of future change. It identifies opportunities for shared conservation action, prioritizing the lands and waters of the South Atlantic based on natural and cultural resource indicator models and a connectivity analysis. So far, more than 500 people from over 150 organizations have actively participated in developing the Blueprint. To learn more about the Blueprint, visit the Blueprint page. To learn more about the indicators, visit the indicator page. Click here to explore Blueprint 2.2 in the Simple Viewer.

Priority Categories
Highest priority for shared action: the most important areas for natural and cultural resources based on indicator condition. This class covers 10% of the South Atlantic geography.

High priority for shared action: important areas for natural and cultural resources based on indicator condition. This class covers an additional 15% of the South Atlantic geography; together, the highest and high priority categories cover 25%.

Medium priority for shared action: above-average areas for natural and cultural resources based on indicator condition, capturing potential restoration opportunities. This class covers 20% of the South Atlantic geography; together, the highest, high, and medium priority categories cover 45%.

Corridors: connections between large patches of highest priority areas and secured lands, optimized for efficiency and indicator condition in a least cost path analysis. This category covers an additional 5% of the South Atlantic geography; in total, the Blueprint covers 50%.

Input Data
Ecosystem Integrity Scores 2.2
Corridors 2.2

Indicator Analysis
We used Zonation, an open-source spatial conservation planning framework software, to prioritize areas within Blueprint 2.2 using the individual indicator data layers. ​The Indicators 2.2 folder in the Blueprint 2.2 data gallery on the CPA contains the data layers for all natural and cultural resource indicators used to create Blueprint 2.2. Some indicators not used in the Blueprint due to data limitations are classified as “indicators not used in Blueprint”.

For more detail on the model parameters and specific indicators used in the Zonation analysis for each ecosystem, please visit the Ecosystem Integrity Scores 2.2 folder in the Blueprint 2.2 data gallery.

Selection Algorithm
For each ecosystem, except for the open water portion of estuaries, we used the core area Zonation algorithm. This algorithm focuses on minimizing indicator loss and maintaining a balanced representation across all indicators. It begins by including all potential cells in the Blueprint and iteratively removes cells that will result in the least relative indicator loss. The first cell removed is the lowest priority and the final cell retained is the highest.

According to the Zonation manual, core area Zonation “tries to retain core areas of all [indicators] until the end of cell removal, even if the feature is initially widespread and common. Thus, at first only cells with occurrences of common features are removed. Gradually, the initially common features become more rare, and cells with increasingly rare feature occurrences start disappearing. The last site to remain in the landscape is the cell with the highest (weighted) richness. This is the site that would be kept last if all else was to be lost” (Moilanen et al. 2014, page 32).

Choosing Run Options
Indicator weights - We began ecosystem runs with all indicators weighted equally. Due to the small extent of some indicators (potential hardbottom condition and low-urban historic landscapes), equal weighting of indicators in the Zonation run resulted in undesirable outputs in some locations. These areas were identifed by particpants in the workshops. To resolve this, we reduced the indicator weight for these indicators as follows.

For the potential hardbottom condition indicator, the Zonation results did not include any areas in the extent of the indicator in high priority (outside the top 10%) or below. This meant that even areas with the lowest indicator values and no overlap with other high indicator values would end up in the highest priority class. To resolve this, we reduced the indicator weight until some areas with lower indicator values were in the high priority class (outside the top 10%). We tested weights of 0.75, 0.6, 0.5, 0.25, and 0.1.

For the low-urban historic landscapes indicator, the Zonation results were similar to the potential hardbottom indicator results above, but also did not include any areas in the extent of the indicator in medium priority (outside the top 25%) or below. This meant that even areas with the lowest indicator values and no overlap with other high indicator values would end up in the high or highest priority class. To resolve this, we reduced the indicator weight until some areas with lower indicator values were in the medium priority class (outside the top 25%). We tested weights of 0.75, 0.6, 0.5, 0.25, 0.1, 0.075, and 0.05.

There was also a single indicator, urban open space, where high values had little overlap with high values of other indicators. That indicated strong trade-offs between that indicator and all others. We reduced the weight of that indicator until at least some of the pixels with the highest indicator value dropped below the top 10% of the prioritization. We used intervals 0.75, 0.5, 0.25, 0.1. All other indicators not discussed above were weighted equally in the final Zonation run.

Warp factors - Warp factor specifies how many cells will be removed at once during each iteration. We used warp 10 for all ecosystems.

Approach for Open Water Estuaries
The integrity scores for this system are based on the only indicator that covers the open water estuaries (coastal condition), so it was not necessary to use Zonation to prioritize this area. Because of this, the open water part of estuaries were treated differently than the other ecosystems. Instead of using Zonation, we used the ArcGIS Slice function to bin the coastal condition indicator into 100 equal area classes. Each of these classes covers roughly the same area (1% of the open water estuaries). This allowed us to use this layer in the same way as the Zonation outputs. For more details on this approach, please visit the estuarine open water ecosystem score layer.

Corridors 2.2
We generated the corridors through a connectivity analysis. For more details on the connectivity methods, including the model parameters used and an explanation of how hubs and resistance were defined, visit the Corridors 2.2 layer in the Blueprint 2.2 data gallery.

We used Linkage Mapper, an ArcGIS-based tool designed to support regional wildlife habitat connectivity analysis, to create corridors for Blueprint 2.2. In the terrestrial environment, we defined hubs as large areas of high ecosystem integrity scores from the Zonation analysis and large patches of secured land from TNC’s Secured Lands Database. In the marine environment, we defined hubs as large areas of marine and estuarine ecosystem integrity. Linkage Mapper connected these hubs in a least-cost path analysis optimized for ecosystem integrity scores. To minimize edge effects with adjacent LCCs, we also used secured lands hubs and local connectedness data from The Nature Conservancy’s Resilient Land Project to incorporate corridors that connect to hubs outside the South Atlantic LCC boundary.

Combining Ecosystem Integrity Scores and Connectivity
The final Blueprint covers 50% of the South Atlantic landscape, divided into priority categories as described in the Priority Categories section above. To combine the results of the Zonation indicator analysis and the Linkage Mapper corridor analysis into the final Blueprint, we followed these steps:

Creating the Inland Blueprint
1) We mosaiced the ecosystem score layers to stitch together the results of the Zonation prioritization for each terrestrial ecosystem (beach and dune, estuarine marsh, forested wetland, freshwater marsh, maritime forest, pine and prairie, upland hardwood). In this mosaiced inland Zonation output layer, each pixel in the South Atlantic inland geography has a continuous value ranging from 0 to 1 according to its rank in its ecosystem’s Zonation prioritization.
2) We used the ArcGIS-Slice Reclassify function to divide this mosaiced layer into 100 classes, grouping together pixels with the same score range across different ecosystems. Each class (ranging from 1 - 100) covers ~1% of the inland area. The 1 class contains the lowest indicator scores across all inland ecosystems collectively, while 100 contains the highest.
3) Pixels in classes above 90 are in the highest tier of indicator condition. We selected all slice classes > 90 and classified them as “highest priority for shared action”.
4) Pixels in classes above 75 that aren’t already classified as highest priority are in the second-highest tier of indicator condition. We selected all slice classes > 75 and ≤ 90 and classified them as “high priority for shared action”.
5) Pixels in classes above 56 that aren’t already classified as highest or high priority are in the third-highest tier of indicator condition. We selected all slice classes > 56 and ≤ 75 and classified them as “medium priority for shared action”. This makes up the first portion of the medium priority class.
6) Any inland hubs used in the connectivity analysis that that were not already classified as highest, high, or medium priority in the steps above were added to the medium priority class. This ensured that the large patches of secured lands used as hubs in the connectivity analysis can score no lower than medium priority in the Blueprint. This added an additional 1% of total area to the medium priority class.
7) The inland corridor layer was then used to fill in corridors. Any pixel identified as a corridor in the terrestrial corridor analysis that was not already assigned to the highest, high or medium priority categories in the steps above was classified as “corridors” in Blueprint 2.2. This contributes an additional 5% to the total Blueprint area, ensuring the final Blueprint ultimately covers 50% of the South Atlantic landscape.

Creating the Marine Blueprint
1) We mosaiced the marine ecosystem score layerwith the open water estuarine ecosystem score layer. In this mosaiced marine layer, each pixel in the South Atlantic marine geography has a continuous value ranging from 0 to 1 according to its rank in its ecosystem’s Zonation prioritization.
2) We used the ArcGIS-Slice Reclassify function to divide this mosaiced layer into 100 classes, grouping together pixels with the same score range across different ecosystems. Each class (ranging from 1 - 100) covers ~1% of the marine area. The 1 class contains the lowest indicator scores across all marine ecosystems collectively, while 100 contains the highest.
3) Pixels in classes above 90 are in the highest tier of indicator condition. We selected all slice classes > 90 and classified them as “highest priority for shared action”.
4) Pixels in classes above 75 that aren’t already classified as highest priority are in the second-highest tier of indicator condition. We selected all slice classes > 75 and ≤ 90 and classified them as “high priority for shared action”.
5) Pixels in classes above 55 that aren’t already classified as highest or high priority are in the third-highest tier of indicator condition. We selected all slice classes > 55 and ≤ 75 and classified them as “medium priority for shared action”.
6) The marine corridors layer was then used to fill in corridors. Any pixel identified as a corridor in the marine corridor analysis that was not already assigned to the highest, high or medium priority categories in the steps above was classified as “corridors” in Blueprint 2.2. This step ensures that the final Blueprint ultimately covers 50% of the South Atlantic landscape.

Combining the Inland and Marine Components into Blueprint 2.2
1) The final step was to combine the inland and marine results into a single raster representing the final Blueprint 2.2. We did this using the ArcGIS-Cell Statistics Maximum function.

Known Issues

-- Some aquatic areas, particularly smaller rivers and streams, are over-prioritized. The imperiled aquatic species indicator is at a subwatershed (HUC12) scale while the species hotspots it seeks to depict are often only a part of that subwatershed.
-- Some aquatic areas important for migratory fish are being under-prioritized in areas far upstream due to issues in the migratory fish connectivity indicator.
-- Piedmont prairie areas are under-prioritized. A new indicator that includes some piedmont prairie plants is in development and will hopefully be ready for the next Blueprint update.
-- Urban open space is poorly captured in Georgia and South Carolina. The TNC Secured Lands database used in this indicator is missing many urban protected areas in these states. An update in the near future will fill in many of these missing urban protected areas.
-- Congaree National Park is under-prioritized. This is likely due to the forested wetland bird indicator under-predicting Swainson’s warbler in the area. Methods for resolving this issue are under development.
-- Some forested wetlands are under-prioritized (e.g., some areas along the Black River in Clarendon, Sumter, and Lee Counties of South Carolina). This appears to caused by issues with depicting both current and historic forested wetlands. A finer resolution approach for the next Blueprint, which is under investigation, should help improve this issue.
-- Sections of some rivers seem to be under-prioritized including the Nottoway, Lumber, Lynches, North Fork of the Edisto, Salkahachee, Ocmulgee, Aucilla, Lower Wakulla, Econfina, and St. Marks. Investigation of this issue is ongoing.
-- Important Carolina Bays are often included in large patches of medium priority but the bays and nearby areas should be higher priority. Different methods for resolving this issue are under investigation.
-- Some small patches of longleaf pine with good local conditions are under-prioritized (e.g., South Quay Sandhills Natural Area Preserve). Ongoing efforts to improve fire tracking and develop a finer resolution Blueprint could improve this issue in future updates.
-- Some large patches of working lands are under-prioritized, particularly in the Big Bend of Florida. Improved working lands and patch size metrics are in development. For the Big Bend of Florida, using the Southeast Conservation Adaptation Strategy Blueprint, which combines the South Atlantic and Peninsular Florida Blueprint, greatly improves this issue.
-- Mouths of many priority rivers are under-prioritized where they transition into the estuarine ecosystem. These open water parts of the estuary ecosystem tend to have poorer water quality and thus low scores on the coastal condition index. Additional indicators for the open water parts of the estuarine ecosystem are under development and should resolve this issue.
-- The priorities for the open water part of the estuary ecosystem are based only on the coastal condition index and do not include a number of other important natural and cultural components of that ecosystem. Additional indicators for the open water parts of the estuarine ecosystem are under development.
-- Some deepwater coral areas that haven’t been surveyed/mapped are likely under-prioritized. Investigation into an approach that combines known areas with suitability models is ongoing.
-- Some marine areas in the far eastern part of the LCC, particularly beyond the Blake Plateau, may be under-prioritized due a lack of survey data for marine birds and mammals in that region.

Background
The lands and waters of the South Atlantic are changing rapidly. Climate change, urban growth, and increasing human demands on resources are reshaping the landscape. While these forces cut across political and jurisdictional boundaries, the conservation community does not have a consistent cross-boundary, cross-organization plan for how to respond. The South Atlantic Conservation Blueprint is that plan.

In 2012, developing a Conservation Blueprint became the 3-5 year mission of the South Atlantic Landscape Conservation Cooperative (LCC). In 2013, the cooperative adopted natural and cultural resource indicators as shared measures of success. In 2014, the steering committee approved Blueprint Version 1.0. This first version of the Blueprint was created by combining expert input from workshops with existing regional and state plans. Click here to access Blueprint 1.0 in the Conservation Planning Atlas (CPA). Blueprint 2.0, released in June 2015, was a completely data-driven plan that identified priority areas for shared conservation action based on ecosystem indicator condition and connectivity. Click here to access Blueprint 2.0 in the CPA. Blueprint 2.1, released in August 2016, was a small data-driven update to the Blueprint that used the same overall methods as Version 2.0, but incorporates improved data for some of the indicators. Click here to access Blueprint 2.1 in the CPA. Blueprint 2.2, the current version, also maintains the methods of 2.0 and 2.1 and incorporates updated indicator data.

Intended Uses
Due to its coarse resolution and broad scope, the Blueprint is not intended for use in isolation of other more locally and/or resource-specific layers. Instead, it is designed to complement other more detailed information by identifying the best places for shared action at the ecosystem level. Intended uses include: finding places to pool resources, raising new conservation dollars, guiding infrastructure development, developing conservation incentives, showing how local actions fit into a larger strategy, and locating places to build resilience to major disasters. Conservation practitioners are already using the Blueprint to inform conservation action and investment across the geography.

Literature Cited
Anderson, M.G., A. Barnett, M. Clark, C. Ferree, A. Olivero Sheldon, J. Prince. 2016. Resilient Sites for Terrestrial Conservation in Eastern North America. The Nature Conservancy, Eastern Conservation Science.

Hoctor, T. S., M. H. Carr, P. D. Zwick. 2000. Identifying a linked reserve system using a regional landscape approach: the Florida ecological network. Conservation Biology 14:984-1000.

McRae, B. and Kavanagh, D. Linkage Mapper User Guide: Version 1.0. 2014. <http://www.circuitscape.org/linkagemapper>

Moilanen, A., and B. A. Wintle. 2006. Uncertainty analysis favours selection of spatially aggregated reserve networks. Biological Conservation 129:427-434.

Moilanen, A., L. Meller, J. Leppänen, F.M. Pouzols, H. Kujala, A. Arponen. 2014. Zonation Spatial Conservation Planning Framework and Software V4.0, User Manual.

White, T.H., JR., J.L. Bowman, B.D. Leopold, H.A. Jacobson, W.P. Smith, and F.J. Vilella. 2000. Influence of Mississippi alluvial valley rivers on black bear movements and dispersal: Implications for Louisiana black bear recovery. Biological Conservation 95:323–331.

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Content date:
2017-09-28 20:08:38 (creation Date), 2017-10-05 20:44:44 (lastUpdate Date), 2017-11-01 21:03:09 (Release Date), 2016-08-12 21:42:41 (Start Date), 2017-11-01 21:42:41 (End Date)
Citation:
South Atlantic Landscape Conservation Cooperative(administrator), South Atlantic Landscape Conservation Cooperative(Principal Investigator), 2017-09-28(creation), 2017-10-05(lastUpdate), 2017-11-01(Release), Conservation Blueprint 2.2: Priorities for shared action, http://www.southatlanticlcc.org/blueprint/
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South Atlantic Landscape Conservation Cooperative
South Atlantic Landscape Conservation Cooperative
South Atlantic Landscape Conservation Cooperative
South Atlantic Landscape Conservation Cooperative
South Atlantic Landscape Conservation Cooperative
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This work is licensed under a Creative Commons Attribution 4.0 International License. The indicator data and maps provided are only intended for use as a reference tool for landscape-level conservation planning efforts.
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SouthAtlantic LCC
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The South Atlantic LCC encompasses and ecologically diverse 89 million acres across portions of six states, from southern Virginia to northern Florida. The geography also includes the marine environment within the federal Exclusive Economic Zone The South Atlantic region is a place where major urban...