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climate_flow_2022_1_20 (Map Service)


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Current Version: 10.81

Service Description:
For our final climate flow model, we weighted the regional anthropogenic flow model with the upslope and downslope models to simulate species populations could flow through the natural landscape finding climate refuge both by moving up or down slopes and mostly in a northward direction. Note: unlike other study regions in the US, Hawaii is close to the equator, so northward flow has no effect on cooler temperatures. It was not included in our climate flow model. 

When combining the factors, a challenge was how to weight the influence of each factor in a way that most closely approximates the real world. We wanted to keep the emphasis on the areas that are important for regional flow, while boosting slightly the areas that channel slope-based and northward movements. We accomplished this by using the anthropogenic regional flow map as our based dataset and boosted the score of cells if they were important for upslope or downslope movement. For each of the two factors we took the areas that were above-average with respect to their factor. 

We overlaid each factor on the regional flow map and replaced the cell score if the cell score for the factor was higher (figure 26 and 27). For example, a cell score of 1.2 for Upslope would replace a Anthropogenic Regional Flow score of 1.0, giving a slight bump-up to the cell reflecting its slope. If both factors had scores higher than the northward regional flow score we replaced the latter with the highest score. This had the effect of raising the scores in areas with above-average current flow for upslope, downslope movement but still retaining the northward regional flow score, and thus not penalizing areas for not having slopes. 


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For our final climate flow model, we weighted the regional anthropogenic flow model with the upslope and downslope models to simulate species populations could flow through the natural landscape finding climate refuge both by moving up or down slopes and mostly in a northward direction. Note: unlike other study regions in the US, Hawaii is close to the equator, so northward flow has no effect on cooler temperatures. It was not included in our climate flow model. 

When combining the factors, a challenge was how to weight the influence of each factor in a way that most closely approximates the real world. We wanted to keep the emphasis on the areas that are important for regional flow, while boosting slightly the areas that channel slope-based and northward movements. We accomplished this by using the anthropogenic regional flow map as our based dataset and boosted the score of cells if they were important for upslope or downslope movement. For each of the two factors we took the areas that were above-average with respect to their factor. 

We overlaid each factor on the regional flow map and replaced the cell score if the cell score for the factor was higher (figure 26 and 27). For example, a cell score of 1.2 for Upslope would replace a Anthropogenic Regional Flow score of 1.0, giving a slight bump-up to the cell reflecting its slope. If both factors had scores higher than the northward regional flow score we replaced the latter with the highest score. This had the effect of raising the scores in areas with above-average current flow for upslope, downslope movement but still retaining the northward regional flow score, and thus not penalizing areas for not having slopes. 


Copyright Text: Center for Resilient Conservation Science, The Nature Conservancy.

Spatial Reference:
102100

Single Fused Map Cache: true

Capabilities: Map,TilesOnly,Tilemap

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Min Scale: 0.0
Max Scale: 0.0

Min LOD: 0
Max LOD: 13

Units: esriMeters

Supported Image Format Types: PNG

Export Tiles Allowed: false
Max Export Tiles Count: 100000

Resampling: true

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