--------Data files--------
Naming conventions across columns in all files
- Scenarios: Present, RCP45_2055 (1.5 C warming), RCP85_2055 (2.0 C warming), RCP85_2085 (3.0 C warming)
- Scenario comparisons columns: `SCENARIO1`_`SCENARIO2` in column name indicates comparison between SCENARIO1 and SCENARIO2
				(e.g. Present_RCP45_2055B_Shift(km) indicates breeding range shift from present to 2.0 C warming)
- Habitat_Group: determined based on NACBI 2010 State of the Birds Report, from Bateman et al. (2020)

RangeOverlapComparisons.csv
- overlap metrics for each possible pair of species in each scenario
- column format: `SCENARIO `_`SPP#`_`METRIC`
- `_Spp1_` or `_Spp2_` in col indicates metrics for specified species 
- columns...
- `SCENARIO`_Total_Area: total breeding range area (in km)
- `SCENARIO`_Proportion_Overlap: proportional overlap between breeding ranges
- `SCENARIO`_Total_Area_Overlap: total area overlap between breeding ranges (in km)
- Allopatric_or_Sympatric: allopatric or sympatric based on 10% threshold for determining sympatry

RangeOverlapData.csv
- summary of overlap metrics for each species (average overlap areas, number of sympatric species, etc.)
- column format: `SCENARIO `_`METRIC`
- columns...
- `SCENARIO`_Number_Species_Overlapping: number of sympatric species based on 10% threshold for determining sympatry
- `SCENARIO`_Total_Area: total breeding range area (in km)
- `SCENARIO`_Mean_Proportion_Overlap: average proportional overlap with present sympatric species
- `SCENARIO`_Mean_Total_Area_Overlap: average total area overlap with present sympatric species (in km)
- `SCENARIO`_Sample Size: number of sympatric species in the present based on 10% threshold used to calculate averages
- `SCENARIO`_Overlapping Species: 4 letter codes of overlapping species
- AlloToSym_`SCENARIO`: number of gained sympatry in given scenario
- SpeciesAlloToSym_`SCENARIO`: 4 letter codes of gained sympatric species in given scenario
- SymToAllo_`SCENARIO`: number of lost sympatry in given scenario
- SpeciesSymToAllo_`SCENARIO`: 4 letter codes of lost sympatric species in given scenario

BreedingRangeShiftData.csv
- breeding range shift distances in each warming scenario
- columns...
- `SCENARIO1`_`SCENARIO2`_Shift(km): breeding range shift distance (in km)

ScenarioComparisons_pValues.csv
- p-values and t-statistics from paired t-tests comparing metrics in each scenario
- column format: `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`_`METRIC`
- columns...
- `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`_NumSppOlap: t-test values for comparison of number of sympatric species
- `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`_MeanPropOlap: t-test values for comparison of mean proportional overlap
- `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`_MeanAreaOlap: t-test values for comparison of mean total area of overlap
- `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`_TotalArea: t-test values for comparison of total area 
- `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`_AlloToSym: t-test values for comparison of number of gained sympatric species
- `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`_SymToAllo: t-test values for comparison of number of lost sympatric species
- `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`_AlloToSymVSSymToAllo: t-test values for comparison of gained to lost sympatric species
- `TESTMETRIC`_``SCENARIO1`_`SCENARIO2`Shift: t-test values for comparison of breeding range shifts (measured by shift of weighted centroid)


--------Data Analyses Code--------
IMPORTANT NOTE) For users of this script, the filepaths leading up to the name of the file 
("'C:/Users/codyp/Desktop/UMich REU Stuff/GIS Project Work/Results Tables/") will need to be changed to the specific
location on the user's local directory either containing the referred to file or specifying the location the 
user would like to save the output file to.

OverlapCalculations.ipynb
- takes original rasters for each warming scenario and calculates overlap metrics between each possible pair of species

DataSummary.ipynb
- takes output file of OverlapCalculations.ipynb (overlap metrics for each species pair) and calculates summary of overlap metrics for each species

ShiftDistanceCalcs.ipynb
- takes original rasters for each warming scenario, gets location of weighted centroids, calculates distance of range shifts

GetPvalues.ipynb
- takes values from output file of DataSummary.ipynb and runs paired t-tests comparing metrics in across warming scenarios, outputs statistical test values

SppWarmingCompareDataClean.Rmd
- takes data summary file and extracts most useful metrics to compare what is happening to each species under each warming scenario

--------Spreadsheets--------
Breeding_Threshold_values.csv: threshold values for extracting suitable range areas from original raster files

Species_4lettercodes.csv: common and scientific names that correspond to each of the species 4-letter codes used throughout the work

--------Shapefiles--------
present_suit_weightcentroid: weighted centroids for present ranges calculated using habitat suitability rasters

rcp45_2055_weightcentroid: weighted centroids under 1.5 C warming calculated using habitat suitability rasters

rcp85_2055_weightcentroid: weighted centroids under 2.0 C warming calculated using habitat suitability rasters

rcp85_2085_weightcentroid: weighted centroids under 3.0 C warming calculated using habitat suitability rasters

--------Referenced Datasets--------
Bateman, B.L., C.B. Wilsey, L. Taylor, J. Wu, G.S. LeBaron, and G. Langham. 2020. North American birds require mitigation and adaptation to reduce vulnerability to climate change. Conservation Science and Practice, 2(8) e242.
(https://conbio.onlinelibrary.wiley.com/doi/full/10.1111/csp2.242)
- We extract raster files for warblers from the datasets "Boreal Forests", "Eastern Forests", "Subtropical Forests", "Western Forests", "Aridlands", and "Generalists" datasets for the scenarios and "Current Time Period (2010)", "RCP 4.5", and "RCP 8.5"

--------Methodology--------
All data in this project derived from model outputs produced by Bateman et al. (2020; https://adaptwest.databasin.org/pages/audubon-survival-by-degrees/). These model outputs included projections for the breeding ranges of 47 wood-warbler species under greenhouse gas Representative Concentration Pathways (RCPs) 4.5 and 8.5 in 2041-2070 (2050s) and 2071-2100 (2080s). The RCPs in different decades corresponded with specific levels of average global warming, with RCP 4.5 in the 2050s corresponding to 1.5°C of average global warming, RCP 8.5 in the 2050s to 2.0°C, and RCP 8.5 in the 2080s to 3.0°C (IPCC 2014). To predict species ranges under each warming scenario, the SDMs incorporated current species occurrence, dispersal limitation, climate, vegetation, and land cover data to create continuous projections of suitable habitat for 1 km2 “pixels” across North America. We used thresholding approaches recommended by Bateman et al. (2020) to eliminate pixels that species are unlikely to occupy before creating predicted range maps for each model projection. We then used current and predicted range maps to quantify predicted changes in overall range area, geographic range shifts, and co-occurrence among all warbler species pairs. 
	We further compared changes in overall breeding range area and patterns of sympatry among warbler species in four habitat affinity groups defined by Bateman et al. (2020): boreal forest (n = 14 species), eastern forest (n = 19), subtropical forest (n = 4), and western forest (n = 8). We did not include 2 of the 47 study species in these comparisons: one that was the only member of its habitat affinity group (Lucy’s Warbler, Oreothlypis luciae: aridlands) and one generalist species that did not belong to a specific habitat affinity group (Common Yellowthroat, Geothlypis trichas).
Range shift distance calculations
To calculate distances of species range shifts, we measured the distance between the centroid of a species’ current breeding range and the centroid of that range under each warming scenario. We weighted our centroid calculations in each warming scenario based on habitat suitability to place less emphasis on less climatically suitable areas where site fidelity will likely prevent occupation (Warkentin and Hernández 1996). We calculated the distance by which species ranges are predicted to shift between each pairwise comparison of warming scenarios by converting the coordinates of each range centroid pair into a World Geodetic System 1984 (WGS84) projection.
To assess changes in sympatry among species, we compared range overlap between species’ current breeding ranges to future overlap under each warming scenario. For each possible pair of species (n = 2,162 pairs) in each warming scenario, we used Python for ArcGIS to overlay the range maps of each species in an Albers equal area conic projection and calculate the area of range overlap between the two species. Using these results, we calculated overlap area as a proportion of the overall breeding range of each species. We then calculated, for each species under each warming scenario, the total number of other warbler species with which it is predicted to be sympatric over at least some of its breeding range. We considered a species as sympatric with another if it shared at least 10% of its total breeding range with the other species, based on uncertainties about range boundaries in our models and a conservative assumption that species pairs with range overlaps below this 10% threshold are less likely to have appreciable ecological effects on each other. 
Species range overlap analysis
	To assess changes in community composition, we calculated the number of sympatric species gained and lost (currently allopatric species becoming sympatric and vice versa) for each species under each warming scenario, again defining the threshold between sympatric and allopatric as 10% of breeding range overlap. In practice we found that the placement of this threshold had little effect on relative changes in co-occurrence among taxa. We calculated gains and losses of sympatry as changes in proportional breeding range overlap between species and as changes in absolute numbers of sympatric species, both overall and within each of the four habitat affinity groups.
	We compared our estimates of range shift, range area, range area overlap, proportional range overlap, number of sympatric species, and gains and losses of sympatry under each warming scenario to current values and to each other using paired t-tests, treating each species as an independent replicate.

Reference:
Warkentin, I.G., D. Hernández. 1996. The conservation implications of site fidelity: A case study involving nearctic-neotropical migrant songbirds wintering in a Costa Rican mangrove. Biological Conservation, 77(2-3). (https://doi.org/10.1016/0006-3207(95)00146-8)