Solar energy-driven land cover change could alter landscapes critical to animal movement in the continental United States

The United States may produce as much as 45% of its electricity using solar energy technology by 2050, which could require more than 40,000 km2 of land to be converted to large-scale solar energy production facilities. Little is known about how such development may impact animal movement. Here, we use five spatially-explicit projections of solar energy development through 2050 to assess the extent to which ground-mounted photovoltaic solar energy expansion in the continental United States may impact land cover and alter areas important for animal movement. Our results suggest that there could be a substantial overlap between solar energy development and land important for animal movement: across projections, 7-17% of total development is expected to occur on land with high value for movement between large protected areas, while 27-33% of total development is expected to occur on land with high value for climate-change-induced migration. We also found substantial variation in the potenti..., Data was collected from the Net-Zero America Project's spatial projects of renewable energy development, accessible at https://maps.princeton.edu/?bbox=-138.955078+-3.425692+-27.861328+62.995158&q=netzeroamerica&search_field=all_fields&utf8=%E2%9C%93
Data describing corridors between large protected areas was collected from 'Identifying Corridors among Large Protected Areas in the United States' by Belote et al. 2016, and is accessible at http://www.conservationgateway.org/ConservationByGeography/NorthAmerica/UnitedStates/edc/reportsdata/terrestrial/resilience/Pages/Downloads.aspx
Resilisnt and Connected Landscapes was collected from The Nature Conservancy, and is accessible at http://www.conservationgateway.org/ConservationByGeography/NorthAmerica/UnitedStates/edc/reportsdata/terrestrial/resilience/Pages/Downloads.aspx
National Land Cover Database data was collected within Google Earth Engine, which is where all data were processed and analyses took place. , All spatial analyses were conducted in Google Earth Engine, and spatial visualization was conducted in QGIS. All data manipulation and visualization was conducted in R Studio., # Solar energy-driven land cover change could alter landscapes critical to animal movement in the continental United States

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This dataset contains results from an analysis of the extent to which solar energy development in the continental United States may drive land-cover change and alteration of landscapes with high value for animal movement. It contains JavaScript code from a spatial analysis within Google Earth Engine to derive initial results, and R code to parse, manipulate, and synthesize inital results into more accessible dataframes.

## Packages Used

This workflow uses the packages 'tidyverse' (version 2.0.0) and 'ggpubr' (version 0.6.0).

## Description of the Data and file structure

The file structure is contained in the R Project folder entitled '[Revised] Solar Development Driven LCC'. The folder contains the R project file as well as seven folders, eight R Markdown files, and a text file containing JavaScript code for Google Earth Engine. The folders hold all raw ....

到2050年，美国太阳能发电装机占比最高可达总发电量的45%，该发展规模或将需要超过4万平方千米的土地用于建设大型太阳能发电设施。目前学界对这类太阳能开发项目如何影响动物迁徙活动仍知之甚少。本研究基于5项截至2050年的太阳能开发空间显式预测模型，评估美国本土陆地区域地面安装式光伏（photovoltaic, PV）太阳能扩张对土地覆被的影响，以及对动物迁徙关键区域的改变程度。

研究结果显示，太阳能开发区域与动物迁徙关键用地存在大量重叠：在所有预测情景中，7%~17%的太阳能开发区域将位于大型保护区间高价值迁徙通道用地范围内，27%~33%的开发区域则位于气候变化驱动下的高价值迁徙通道用地范围内。此外，研究还发现潜在影响的空间差异亦十分显著……

本研究数据来源于净零美国计划（Net-Zero America Project）的可再生能源开发空间项目，可通过以下链接获取：https://maps.princeton.edu/?bbox=-138.955078+-3.425692+-27.861328+62.995158&q=netzeroamerica&search_field=all_fields&utf8=%E2%9C%93

大型保护区间迁徙通道的相关数据来自Belote等人2016年发表的《Identifying Corridors among Large Protected Areas in the United States》，可通过以下链接获取：http://www.conservationgateway.org/ConservationByGeography/NorthAmerica/UnitedStates/edc/reportsdata/terrestrial/resilience/Pages/Downloads.aspx

“韧性与连通性景观（Resilient and Connected Landscapes）”数据集来自大自然保护协会（The Nature Conservancy），获取链接同上。

国家土地覆被数据库（National Land Cover Database）数据通过谷歌地球引擎（Google Earth Engine）采集，所有数据处理与分析均在此平台完成。所有空间分析均在谷歌地球引擎中进行，空间可视化则通过QGIS完成。所有数据处理与可视化工作均在R Studio中完成。

# 美国本土太阳能开发驱动的土地覆被变化或将改变动物迁徙关键景观

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本数据集包含针对美国本土太阳能开发对土地覆被变化及动物迁徙关键景观改变程度的分析结果。数据集包含用于在谷歌地球引擎中开展空间分析以生成初始结果的JavaScript代码，以及用于解析、处理并将初始结果整合为更易访问数据框的R代码。

## 所用软件包
本分析流程使用了"tidyverse"（版本2.0.0）与"ggpubr"（版本0.6.0）软件包。

## 数据与文件结构说明
文件结构存储于名为“[修订版]太阳能开发驱动的土地覆被变化”的R项目文件夹中，该文件夹包含R项目文件、7个子文件夹、8个R Markdown文件以及一份包含谷歌地球引擎JavaScript代码的文本文件。各子文件夹存储所有原始……