DOI: 10.5061/dryad.2280gb60d
title: Data from: Ecological and anthropogenic drivers of local extinction and colonization of giant pandas over the past 30 years

description: Understanding the patterns and drivers of species range shifts is
 essential to disentangle mechanisms driving species’ responses to global
 change. Here, we quantified local extinction and colonization dynamics of
 giant pandas (Ailuropoda melanoleuca) using occurrence data collected by
 harnessing the labor of &gt;1,000 workers and &gt;60,000 worker
 days for each of the three periods (TP1: 1985-1988, TP2: 1998-2002, and
 TP3: 2011-2014), and evaluated how these patterns were associated with (1)
 protected area, (2) local rarity/abundance, and (3) abiotic factors (i.e.,
 climate, land-use and topography). We documented a decreased rate (from
 0.433 during TP1-TP2 to 0.317 during TP2-TP3) of local extinction and a
 relatively stable rate (from 0.060 during TP1-TP2 to 0.056 during TP2-TP3)
 of local colonization through time. Furthermore, the occupancy gains have
 exceeded losses by a ratio of approximately 1.5 to 1, illustrating an
 expanding of panda’s range at a rate of 1408.3 km2/decade. We also found
 that pandas were more likely to become locally extinct outside protected
 areas, when locally rare in surrounding areas, and when certain biotic
 conditions were not met (e.g., increased forest cover). Local colonization
 was less likely in areas with high local rarity, challenging biotic
 conditions and unprotected area status. As the network of panda reserves
 expanded and the forest matured, the relative importance of other factors
 such as climate, biotic factors, and land-use became more influential in
 determining patterns of local extinction and colonization. Our findings
 provide insights into the factors governing the expansion of panda’s
 range, illustrate how the relative influence of biotic and abiotic factors
 can change over time, indicating that effective conservation intervention
 may be able to mitigate some of the negative impacts of climate change and
 habitat degradation. This insight extends beyond pandas, and highlights
 the role conservation interventions can play in building resilience under
 a changing climate.
description: # Data from: Ecological and anthropogenic drivers of local extinction and
 colonization of giant pandas over the past 30 years
 [https://doi.org/10.5061/dryad.2280gb60d](https://doi.org/10.5061/dryad.2280gb60d) ## Description of the data and file structure **Data from: Ecological and anthropogenic drivers of local extinction and colonization of giant pandas over the past 30 years** Datasets used to identify ecological and anthropogenic drivers of local extinction and colonization of giant pandas over the past 30 years ### Files and variables: #### File: **R script**—Script to run spatial generalized additive models in the programming language R **TP12_5km_ext.csv** — local extinction (loss [1] and persistence [0]), local rarity, local abundance, protected area status, 19 future bioclimatic variables and 10 land use variables during TP1-TP2 at 5 km X ![](file:///C:/Users/junfe/AppData/Local/Temp/msohtmlclip1/01/clip_image002.gif)5 km grid cell **TP12_5km_col.csv** — local colonization (gain [1] vs absence [0]), local rarity, protected area status, 19 future bioclimatic variables and 10 land use variables during TP1-TP2 at 5 km X ![](file:///C:/Users/junfe/AppData/Local/Temp/msohtmlclip1/01/clip_image002.gif)5 km grid cell **TP23_5km_ext.csv** — local extinction (loss [1] and persistence [0]), local rarity, local abundance, protected area status, 19 future bioclimatic variables and 10 land use variables during TP2-TP3 at 5 km X ![](file:///C:/Users/junfe/AppData/Local/Temp/msohtmlclip1/01/clip_image002.gif)5 km grid cell **TP23_5km_col.csv** — local colonization (gain [1] vs absence [0]), local rarity, protected area status, 19 future bioclimatic variables and 10 land use variables during TP2-TP3 at 5 km X ![](file:///C:/Users/junfe/AppData/Local/Temp/msohtmlclip1/01/clip_image002.gif)5 km grid cell **Description:**  All file folders include 35 variables, the details are provided as follows: gx and gy — the x-y coordinate of centroids of each 5km X 5km grid cell ft — Local extinction (loss [1] and persistence [0]) or local colonization (gain [1] vs absence [0]) lr — Local rarity ABUND – Local abundance PA — Protected area status BIO1 — Mean annual temperature (℃) BIO2 — Mean diurnal range (℃) BIO3 — Isothermality (Bio2/Bio7) (* 100) BIO4 — Temperature seasonality (standard deviation *100) ( ℃) BIO5 — Maximal temperature of the warmest month (℃) BIO6 — Minimal temperature of coldest month (℃) BIO7 — Temperature annual range (Bio5-Bio6) (℃) BIO8 — Mean temperature of the wettest quarter (℃) BIO9 — Mean temperature of the driest quarter (℃) BIO10 — Mean temperature of the warmest quarter (℃) BIO11 — Mean temperature of the coldest quarter (℃) BIO12 — Total annual precipitation (mm) BIO13 — Precipitation of the wettest month (mm) BIO14 — Precipitation of the driest month (mm) BIO15 — Precipitation seasonality (coefficient of variation) BIO16 — Precipitation of the wettest quarter (mm) BIO17 — Precipitation of the driest quarter (mm) BIO18 — Precipitation of the warmest quarter l (mm) BIO19 — Precipitation of the coldest quarter (mm) FAL— The proportion of farmland area (%) FOL — The proportion of forest land area (%) GL — The proportion of grassland area (%) WL — The proportion of water area (%) RL — The proportion of resident area (%) OL — The proportion of other area (%) ME — Mean elevation (m) MA — Mean aspect MS — Mean slope RE — Range of elevation (m)