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Dataset of spillover effects of protected areas on the QTP

Citation

Shen, Yu et al. (2021), Dataset of spillover effects of protected areas on the QTP, Dryad, Dataset, https://doi.org/10.5061/dryad.k0p2ngf9c

Abstract

Aim: Although protected areas (PAs) are assumed to reduce threats to nature within boundaries, their spillover effects remain equivocal. It is necessary to not only determine whether PAs truly achieve conservation targets but also whether they promote or inhibit natural habitat degradation in adjacent areas by blockage or leakage spillover. This study aims to choose 54 nature reserves (NRs) focusing on forest protection as a case study to assess PA conservation effectiveness and spillover prevalence.

Location: PAs on the Qinghai-Tibet Plateau (QTP)

Methods: We used matching methods to compare deforestation rates inside PAs and their 20 km buffer zones with matched control areas based on the Global Forest Change data from 2001 to 2019. We contrasted the effects of NRs with different management levels, ages and areas. We designed 5 concentric buffer zones to assess spillover change with distance and estimated potential drivers of the spillover effect to explain its directions and magnitudes.

Results: 75.9% of the NRs were effective in preventing deforestation within their boundaries. NRs with different properties showed similar performance on forest conservation. Positive spillover value decreased with distance from NR boundary to further landscape, but the trend of spillover change varied around individual NR. Blockages slightly outnumbered leakages at different distances while leakages happened more frequently when we treated buffer zones as a whole spillover area. The linear model indicated NR age and population density of buffer zones were the most relevant predictors to spillover value.

Main conclusions: Most PAs performed well in forest conservation. Leakages could undermine or offset PA conservation efforts and were related to multiple natural or socioeconomic factors. We recommend considering the plurality of PAs as well as spillover effect and incorporating a social-ecological framework in further PA establishment and management.

Methods

The forest cover and loss data were collected from the Global Forest Change dataset (GFCD) 2000-2019 (version 1.7) (M. C. Hansen et al., 2013). This global dataset is divided into 10x10 degree tiles, consisting of seven files per tile. All files have a spatial resolution of 1 arc-second per pixel or approximately 30 m per pixel. We only collected files that cover the Tibetan Plateau. The QTP boundary was a vector data with a spatial boundary of our study area. The NR information data included basic information of 54 nature reserves in this study and was collected from the 2017 official Natural Reserve List, published by the Ministry of Ecology and Environment of China (http://www.mee.gov.cn/).  We used the matching method to calculate the deforestation rate inside nature reserves, buffer zones, and matched control areas. Then the nature reserve effectiveness and spillover effect were calculated based on deforestation value. The NR effectiveness and Spillover value dataset contain all effectiveness and spillover value of 54 nature reserves.

Usage Notes

There are three types of data included in this dataset. Raster data of forest cover and change, vector data of the QTP boundary, and tabular data of nature reserve information and statistical results.