Combined Zonation Results 2025

We used version 5 of Zonation for the entire Southeast Blueprint. We ran Zonation within seven zones. Zonation ranks the pixels in each zone according to their indicator scores, using a modeling approach that tries to conserve high-value representations of all indicators collectively. Pixels that rank higher in Zonation become higher priority in the Blueprint. INLAND CONTINENTAL Zonation Inputs To create the inputs for each inland continental Zonation run, clip the inland continental indicators to the 4 inland continental zones. Note: For more details on the mapping steps, code used to create this layer is available [in the Southeast Blueprint 2025 Data Download] under > 6_Code. The zones serve as the boundaries of each Zonation run. Each Zonation run in the inland continental geography includes: * All indicators that occur in a given zone, clipped to that zone * All subregions that occur in a given zone Zonation Run Settings Determining Indicator Weights We use Zonation to identify a network of priorities that includes the areas most important for all indicators collectively. Since the goal is to create a balanced portfolio where all indicators are represented, in a perfect world, we would weight each indicator equally. However, in some cases, we have to downweight indicators that would otherwise have an outsized impact on the Blueprint priorities. The way Zonation ranks pixels on the landscape can be influenced by factors like an indicator’s spatial rarity within a given zone and the distribution of high and low values (i.e., is the indicator’s distribution top-heavy or bottom-heavy). In addition, some indicators are based on coarse-scale data. Other indicators have a wide spread of high to low values, but the data provider only intends the highest values to be considered good candidates for conservation action. In these situations, we use weighting to limit the disproportionate influence of certain indicators. We developed four standard indicator weighting rules to ensure that: * Indicators with coarse scale or information have less of an influence * Spatially limited (i.e., rare) indicators were not overprioritized * Subregional indicators that don’t cover most of their target ecosystem were not overprioritized * Indicators with limited overlap of below-average values in a given zone were not overprioritized In a handful of edge cases, we developed additional exceptions to those four rules. The section below describes the application of the standard rules and additional exceptions. Indicators with coarse scale or information One indicator (estuarine coastal condition) has a much coarser spatial scale than the other indicators in the Blueprint. Estuarine coastal condition interpolates data from a relatively small number of sampling points into broad condition scores. Four other indicators (imperiled mammals, imperiled amphibians and reptiles, grassland and savanna extent, and grassland and savanna restoration) are based on relatively coarse information. For the imperiled species indicators, they use very broad definitions of what is potential species habitat and what areas are within a species range. For the grassland indicators, estimating grassland condition is particularly challenging, which results in large areas with coarse estimates of their current or potential condition. All of these indicators oversimplify more site-specific variation in ecosystem health and habitat value, so we reduce their weight by 0.7 across all zones to limit their influence on the Blueprint priorities. This allows other indicators with more detailed information to play a stronger role in teasing out key places within broad areas of importance for these coarser indicators. Spatially limited indicators With equal weights, the entire area of many indicators that cover a limited part of a zone (e.g., South Atlantic beach birds, greenways and trails) is identified as a high priority. To address this issue, we weighted indicators based on the proportion of their total area with values ≥1 in a given zone. For indicators where the proportion of ≥1 values was between 0.09 and 0.5, we set their weights equal to that proportion. For example, we set the imperiled aquatic species indicator weight to approximately 0.26 in the Coastal Zone because that was the proportion of indicator pixels analyzed by Zonation in that zone with a value ≥1. For indicators where the proportion of ≥1 values was ≤0.09, we set their weights equal to that proportion multiplied by 3. We found that indicators in this range began to be underprioritized when only using the unadjusted proportion. For indicators where the proportion of ≥1 values was 0.5 and higher, we set their weight to 1.0 unless they were covered by the exceptions discussed below. Subregional indicators that don’t cover most of their target ecosystem Nine indicators use source datasets that only cover specific subregions and do not apply to the majority of their target ecosystem (Mississippi Alluvial Valley forest birds - protection, Mississippi Alluvial Valley forest birds - reforestation, West Coastal Plain and Ouachitas forested wetland birds, West Coastal Plain and Ouachitas open pine birds, West Gulf Coast mottled duck nesting, South Atlantic forest birds, South Atlantic beach birds, South Atlantic low-urban historic landscapes, South Atlantic maritime forest). For example, South Atlantic forest birds does not capture important forest bird habitat that occurs elsewhere in the Southeast. While these indicators help the Blueprint identify important areas within these subregions, they can also unfairly penalize areas that aren’t covered by the models that would otherwise score highly due to their habitat or ecosystem value. This can cause Zonation to overprioritize the subregions that happen to be covered by these indicators. To reduce these unintended negative impacts, we reduce the weight of these indicators by 0.5. Indicators with limited overlap of below-average values in a given zone In a few cases, an indicator that targets a specific ecosystem will occur primarily in one zone, but spill over the boundary slightly into a neighboring zone. When this handful of overlapping pixels scores relatively low for that indicator, Zonation will often overprioritize these low-scoring areas. This occurs because Zonation can only see the range of indicator values that occur in a given zone—so while they score low overall, they are the highest values in that zone, which makes these areas seem more important than they actually are. To address this, we multiply the weight of the four indicators that have a small amount of overlapping below-average values in a given zone by 0.1. This rule applies to East Coastal Plain open pine birds and resilient coastal sites in the Greater Appalachians, Gulf coral and hardbottom in the Central West, and imperiled aquatic species in the Marine. Other exceptions Intact habitat cores in the Arid West The Arid West Zone is composed of much drier ecosystems that are climatically distinct from the rest of the SECAS geography. Intact habitat cores does not perform as well in this zone for distinguishing natural, unfragmented areas from more altered areas. As a result, the standard “spatially limited indicators” weighting rule caused Zonation to overprioritize the Arid West. To mitigate this, we reduced the weight of this indicator to 0.7 in the Arid West only. Lakes and reservoirs The open water areas of lakes and reservoirs are particularly tricky. None of the indicators provide highly detailed information about relative importance of pixels in these areas. This can result in computational challenges for Zonation, particularly when the weight for this indicator is too high. To address this, we used a modified version of the weight rule described under “spatially limited indicators”. Just like the spatially limited indicator rule, we set the weight equal to the proportion of ≥1 values. Unlike the spatially limited indicator rule, we did not multiply that proportion by 3 when the proportion was ≤0.9. This kept the weight low enough to avoid computational issues in Zonation. Spatially limited Indicators on the edge of weighting thresholds In some cases, indicators that are right on the edge of weighting thresholds can cause issues. Intact habitat cores in the Coastal Zone is just below the 0.5 “spatially limited indicators” threshold, and applying that weighing rule caused this indicator to be underrepresented. Falling on the other side of the threshold would have resulted in a weight of 1.0 instead of <0.5. To address this, we set the weight to 1.0. Marginal Loss Rule CAZMAX: This setting is consistent with basic core-area Zonation (commonly CAZ) in Zonation 4, which was used in previous versions of the Blueprint. It tries to always cover high-value locations for all indicators, even if this comes with the cost of achieving lower average coverage across all indicators. Additional Connectivity Methods To increase the overall aggregation of the priorities, we included each indicator twice in each zone. The first version of the indicator in the input file is just the indicator layer as-is. For the second version, we have Zonation do a connectivity transformation. This approach of using both regular and connectivity transformed versions of indicators is described in the Zonation manual. It helps balance locally important places and nearby connectivity. For the connectivity transformation, we used the negative exponential dispersal kernel. This is commonly used in modeling animal movements (Moilanen et al. 2024). We used a parameter of 1, which aligns with a mean dispersal distance of 1 pixel. For the cut parameter, which sets a distance to stop the connectivity transformation, we used a value of 5 pixels. Beyond that distance, the distribution already has only a minimal impact on values anyway. Zonation Weights for Each Zone To see the weights used for each indicator in each zone, see the Zonation feature list files available [in the Southeast Blueprint 2025 Data Download] under > 6_Code. MARINE CONTINENTAL Zonation Inputs To create the inputs for the marine continental Zonation run, clip the marine continental indicators to the Continental Marine Zone. Note: For more details on the mapping steps, code used to create this layer is available [in the Southeast Blueprint 2025 Data Download] under > 6_Code. The Continental Marine Zone serves as the boundaries of the Zonation run. This Zonation run includes: * All indicators that occur in the Continental Marine Zone, clipped to that zone * All marine continental subregions Zonation Run Settings Determining Indicator Weights We developed indicator weighting rules to ensure that: * Spatially limited indicators were not overprioritized * Priorities were relatively balanced between Gulf and Atlantic areas Spatially limited indicators With equal weights, the entire area of many indicators that cover a limited part of the Continental Marine Zone (e.g., estuarine coastal condition, Atlantic estuarine fish habitat) is identified as a high priority. To address this issue, we weighted indicators based on the proportion of their total area with values ≥1. For indicators where the proportion of ≥1 values was between 0.1 and 0.5, we set their weights equal to that proportion. For example, we set the Gulf coral and hardbottom indicator weight to approximately 0.217 because that was the proportion of pixels analyzed by Zonation in the Continental Marine Zone with a value ≥1. For indicators where the proportion of ≥1 values was ≤0.1, we set their weights equal to that proportion multiplied by 3. We found that indicators in this range began to be underprioritized when only using the unadjusted proportion. For indicators where the proportion of ≥1 values was 0.5 and higher, we set their weight to 1.0 unless they were covered by the “balancing Atlantic and Gulf” rule below. Balancing Atlantic & Gulf priorities The Continental Marine Zone includes many indicators that only cover either the Atlantic or the Gulf. In order to better balance priorities across those areas, we made two modifications to the “spatially limited indicators” weighting rule. The first modification was only weighting bird, mammal, and turtle indicators when the proportion of ≥1 values was less than 0.3. The second change was increasing the weight of two indicators that were getting significantly under-represented in the Blueprint priorities (Atlantic coral and hardbottom, Gulf deep-sea coral richness) from 0.3 to 0.6. Marginal Loss Rule CAZMAX: This setting is consistent with basic core-area Zonation (commonly CAZ) in Zonation 4, which was used in previous versions of the Blueprint. It tries to always cover high-value locations for all indicators, even if this comes with the cost of achieving lower average coverage across all indicators. Additional Connectivity Methods To increase the overall aggregation of the priorities, we included each indicator twice in each zone. The first version of the indicator in the input file is just the indicator layer as-is. For the second version, we have Zonation do a connectivity transformation. This approach of using both regular and connectivity transformed versions of indicators is described in the Zonation manual. It helps balance locally important places and nearby connectivity. For the connectivity transformation, we used the negative exponential dispersal kernal. This is commonly used in modeling animal movements (Moilanen et al. 2024). We used a parameter of 1, which aligns with a mean dispersal distance of 1 pixel. For the cut parameter, which sets a distance to stop the connectivity transformation, we used a value of 5 pixels. Beyond that distance, the distribution already has only a minimal impact on values anyway. Zonation Weights for Each Zone To see the weights used for each indicator in each zone, see the Zonation feature list files available [in the Southeast Blueprint 2025 Data Download] under > 6_Code. CARIBBEAN Zonation Inputs To create the inputs for the two Caribbean Zonation runs, clip the Caribbean indicators to the two Caribbean zones (Puerto Rico and U.S. Virgin Islands). Note: For more details on the mapping steps, code used to create this layer is available [in the Southeast Blueprint 2025 Data Download] or [Caribbean-only Southeast Blueprint 2025 Data Download] under > 6_Code. The Puerto Rico and U.S. Virgin Islands Zones serve as the boundaries of each Zonation run. Each Zonation run in the Caribbean geography includes all indicators that occur in a given zone, clipped to that zone. Subregions are not used as inputs in the Caribbean because the Caribbean zones are not subdivided into multiple subregions. Zonation Run Settings Determining Indicator Weights We developed indicator weighting rules to ensure that: * Spatially limited indicators were not overprioritized Spatially limited indicators With equal weights, the entire area of many indicators that cover a limited part of either the Puerto Rico or U.S. Virgin Island Zone (e.g., Caribbean beach habitat, Caribbean greenways and trails) is identified as a high priority. To address this issue, we weighted indicators based on the proportion of their total area with values ≥1. For indicators where the proportion of ≥1 values was between 0.1 and 0.5, we set their weights equal to that proportion. For example, we set the Caribbean karst habitat indicator weight to approximately 0.228 because that was the proportion of pixels analyzed by Zonation in the Puerto Rico Zone with a value ≥1. For indicators where the proportion of ≥1 values was ≤0.1, we set their weights equal to that proportion multiplied by 3. We found that indicators in this range began to be underprioritized when only using the unadjusted proportion. For indicators where the proportion of ≥1 values was 0.5 and higher, we set their weight to 1.0. Other exceptions Spatially limited Indicators on the edge of weighting thresholds In the Puerto Rico zone, Caribbean habitat patch size (large Islands) was just over the 0.5 weighting threshold. It was being overprioritized, so we kept the weight equal to the proportion of ≥1 values and did not increase the weight 1. The U.S. Virgin Islands imperiled terrestrial species indicator was being underprioritized and was close to a 0.3 threshold we used in previous versions of the Blueprint. We doubled the weight of this indicator to compensate. Marginal Loss Rule CAZMAX: This setting is consistent with basic core-area Zonation (commonly CAZ) in Zonation 4, which was used in previous versions of the Blueprint. It tries to always cover high-value locations for all indicators, even if this comes with the cost of achieving lower average coverage across all indicators. Zonation Weights for Each Zone To see the weights used for each indicator in each zone, see the Zonation feature list files available [in the Southeast Blueprint 2025 Data Download] or [Caribbean-only Southeast Blueprint 2025 Data Download] under > 6_Code. COMBINING CARIBBEAN & CONTINENTAL RESULTS Next, we mosaiced together the Zonation results for all the inland continental zones, the Continental Marine Zone, and the two Caribbean zones. In this mosaiced Zonation results layer, each pixel in the Southeast Blueprint geography has a continuous value ranging from 0 to 100 according to its rank by the Zonation prioritization. The output of this step, the [combined Zonation results for the Southeast Blueprint], is available on [the Blueprint page of the SECAS Atlas]. The continuous Zonation results are also available for download in the [Southeast Blueprint 2025 Ancillary Data Download], but are provided as separate files for the continental and Caribbean geographies to reduce file size. Note: For more details on the mapping steps, code used to create this layer is available [in the Southeast Blueprint 2025 Data Download] or [Caribbean-only Southeast Blueprint 2025 Data Download] under > 6_Code. LITERATURE CITED Moilanen, A., I. Kohonen, P. Lehtinen, I. Kivistö, J. Jalkanen, E. Virtanen, H. Kujala. March 2024. Zonation 5 v2.0 User Manual. [[https://github.com/zonationteam/Zonation5/releases/download/v2.0/manual_and_example_setups.zip]]. Moilanen A, Lehtinen P, Kohonen I, Virtanen E, Jalkanen J, Kujala H. 2022. Novel methods for spatial prioritization with applications in conservation, land use planning and ecological impact avoidance. Methods in Ecology and Evolution. [[https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13819]].