DOI: 10.5061/dryad.q03g2
title: Data from: Quantifying past and present connectivity illuminates a rapidly changing landscape for the African elephant

description: There is widespread concern about impacts of land-use change on
 connectivity among animal and plant populations, but those impacts are
 difficult to quantify. Moreover, lack of knowledge regarding ecosystems
 before fragmentation may obscure appropriate conservation targets. We use
 occurrence and population genetic data to contrast connectivity for a
 long-lived mega-herbivore over historical and contemporary time frames. We
 test whether (i) historical gene flow is predicted by persistent landscape
 features rather than human settlement, (ii) contemporary connectivity is
 most affected by human settlement and (iii) recent gene flow estimates
 show the effects of both factors. We used 16 microsatellite loci to
 estimate historical and recent gene flow among African elephant (Loxodonta
 africana) populations in seven protected areas in Tanzania, East Africa.
 We used historical gene flow (FST and G'ST) to test and optimize
 models of historical landscape resistance to movement. We inferred
 contemporary landscape resistance from elephant resource selection,
 assessed via walking surveys across ~15 400 km2 of protected and
 unprotected lands. We used assignment-based recent gene flow estimates to
 optimize and test the contemporary resistance model, and to test a
 combined historical and contemporary model. We detected striking changes
 in connectivity. Historical connectivity among elephant populations was
 strongly influenced by slope but not human settlement, whereas
 contemporary connectivity was influenced most by human settlement. Recent
 gene flow was strongly influenced by slope but was also correlated with
 contemporary resistance. Inferences across multiple timescales can better
 inform conservation efforts on large and complex landscapes, while
 mitigating the fundamental problem of shifting baselines in conservation.
description: Genetic data- genepop
 formatGenetic data for 7
 elephant populations in Tanzania, at 16 microsatellite loci, in GENEPOP
 format. Populations are reported in the following order: Katavi, Ruaha,
 Muhesi, Mikumi, Selous, Tarangire, UdzungwaElephantData_GenepopFileCombined Resistance MatrixCumulative resistance matrix from the combined model (maximum value from slope^1.5 and (1/RSPF^0.33 resistance surfaces)Contemporary CubeRoot_1overRSPF Resistance MatrixCumulative resistance matrix from "contemporary" resistance model, (1/RSPF)^0.33Geographic Distance MatrixDistance in kilometers between the edges of the elephant sampling polygonsSlope^1.5 Resistance MatrixCumulative resistance matrix from the optimized historical model (slope^1.5)Water^1 Resistance MatrixCumulative resistance matrix for distance to water, untransformed:(distance to water)^1Ele_RSPF_DataElephant and random locations, with covariates scored from GIS, as employed in the habitat modelRSPF model GIS raster layerZipped file containing RSPF model as a raster dataset, Albers Equal Area (Africa) projection. This is the output from the RSPF model, it has NOT been inverted and transformed to create a resistance layer (as done for the contemporary resistance model).RSPF.zipDistance to Water GIS raster layerAlbers Equal Area (Africa) projection. Distance to water (untransformed) in kilometers, based on Africover Rivers layer with modifications.DistWater.zipSlope GIS raster layerSlope (in degrees), untransformed (i.e., slope^1); Albers Equal Area projection (Africa)Slope.zipElephant Genetic Sampling GIS PolygonsGIS polygons describing the extent of genetic sample locations for each population, Albers Equal Area (Africa)SamplingPolygons.zip