Landscape-scale predictions of future grassland conversion to cropland or development.

IF 5.2 1区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION
Kevin W Barnes, Neal D Niemuth, Rich Iovanna
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引用次数: 0

Abstract

Grassland conservation planning often focuses on high-risk landscapes, but many grassland conversion models are not designed to optimize conservation planning because they lack multidimensional risk assessments and are misaligned with ecological and conservation delivery scales. To aid grassland conservation planning, we developed landscape-scale models at relevant scales that predict future (2021-2031) total and proportional loss of unprotected grassland to cropland or development. We developed models for 20 ecoregions across the contiguous United States by relating past conversion (2011-2021) to a suite of covariates in random forest regression models and applying the models to contemporary covariates to predict future loss. Overall, grassland loss models performed well, and explanatory power varied spatially across ecoregions (total loss model: weighted group mean R2 = 0.89 [range: 0.83-0.96], root mean squared error [RMSE] = 9.29 ha [range: 2.83-22.77 ha]; proportional loss model: weighted group mean R2 = 0.74 [range: 0.64-0.87], RMSE = 0.03 [range: 0.02-0.06]). Amount of crop in the landscape and distance to cities, ethanol plants, and concentrated animal feeding operations had high variable importance in both models. Total grass loss was greater when there were moderate amounts of grass, crop, or development (∼50%) in the landscape. Proportional grass loss was greater when there was less grass (∼<30%) and more crop or development (∼>50%). Some variables had a large effect on only a subset of ecoregions, for example, grass loss was greater when ∼>70% of the landscape was enrolled in the Conservation Reserve Program. Our methods provide a simple and flexible approach for developing risk layers well suited for conservation that can be extended globally. Our conversion models can support conservation planning by enabling prioritization as a function of risk that can be further optimized by incorporating biological value and cost.

未来草地转为耕地或开发的景观尺度预测。
草地保护规划通常侧重于高风险景观,但许多草地转化模型并不是为优化保护规划而设计的,因为它们缺乏多维风险评估,与生态和保护交付尺度不一致。为了帮助草地保护规划,我们开发了相关尺度的景观尺度模型,预测未来(2021-2031 年)未受保护的草地因耕地或开发而损失的总量和比例。我们为美国毗连地区的 20 个生态区域开发了模型,将过去的转化(2011-2021 年)与随机森林回归模型中的一系列协变量联系起来,并将模型应用于当代协变量以预测未来的损失。总体而言,草地损失模型表现良好,其解释力在不同生态区之间存在空间差异(总损失模型:加权组平均 R2 = 0.89 [范围:0.83-0.96],均方根误差 [RMSE] = 9.29 公顷 [范围:2.83-22.77 公顷];比例损失模型:加权组平均 R2 = 0.74 [范围:0.64-0.87],均方根误差 = 0.03 [范围:0.02-0.06])。在这两个模型中,地貌中的作物数量以及与城市、乙醇厂和集中饲养场的距离都具有很高的变量重要性。当草地、农作物或土地开发程度处于中等水平(∼50%)时,草地总损失量较大。当草地较少时(∼50%),草地损失比例较大。一些变量仅对部分生态区域有较大影响,例如,当 70% 的地貌被纳入保护储备计划时,草地损失更大。我们的方法提供了一种简单而灵活的方法,可用于开发适合全球保护的风险层。我们的转换模型可以支持保护规划,根据风险的函数确定优先次序,并通过纳入生物价值和成本进一步优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Conservation Biology
Conservation Biology 环境科学-环境科学
CiteScore
12.70
自引率
3.20%
发文量
175
审稿时长
2 months
期刊介绍: Conservation Biology welcomes submissions that address the science and practice of conserving Earth's biological diversity. We encourage submissions that emphasize issues germane to any of Earth''s ecosystems or geographic regions and that apply diverse approaches to analyses and problem solving. Nevertheless, manuscripts with relevance to conservation that transcend the particular ecosystem, species, or situation described will be prioritized for publication.
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