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Dryad

Pearson correlation tests for environmental variables, Student t-test for range shift and comparisons for habitat loss in 2070

Cite this dataset

Zhu, Bingrun (2022). Pearson correlation tests for environmental variables, Student t-test for range shift and comparisons for habitat loss in 2070 [Dataset]. Dryad. https://doi.org/10.5061/dryad.gqnk98sr3

Abstract

Habitat loss and shifts associated with climate change threaten global biodiversity, with impacts likely to be most pronounced at high latitudes. With the disappearance of the tundra breeding habitats, migratory shorebirds that breed at these high latitudes are likely to be even more vulnerable to climate change than those in temperate regions. We examined this idea using new distributional information on two subspecies of Black-tailed Godwits Limosa limosa in Asia: the northerly, bog-breeding L. l. bohaii and the more southerly, steppe-breeding L. l. melanuroides. Based on breeding locations of tagged and molecularly assayed birds, we modelled the current breeding distributions of the two subspecies with species distribution models, tested those models for robustness, and then used them to predict climatically suitable breeding ranges in 2070 according to bioclimatic variables and different climate change scenarios. Our models were robust and showed that climate change is expected to push bohaii into the northern rim of the Eurasian continent. Melanuroides is also expected to shift northward, stopping in the Yablonovyy and Stanovoy Ranges, and breeding elevation is expected to increase. Climatically suitable breeding habitat ranges would shrink to 16% and 11% of the currently estimated ranges of bohaii and melanuroides, respectively. Overall, this study provides the first predictions for the future distributions of two little-known Black-tailed Godwit subspecies and highlights the importance of factoring in shifts in bird distribution when designing climate-proof conservation strategies.

Methods

1. Pearson correlation tests for environmental variables

All variables for species distribution modelling were loaded to Qgis 3.8. We extracted the values of each variable from 101 occurrence locations (60 bohaii and 41 melanuroides) using the "raster values to points" function in Qgis 3.8. The outcome was saved as a .csv file. Next, the Pearson correlation coefficient was calculated using "tidyverse" package in R. 

2. Student t-test for range shift

see methods of the paper

3. Comparisons for habitat loss in 2070  

see methods of the paper

Funding

International Wetlands and River Beijing