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Rangeland vulnerability to state transition under global climate change

机译：兰兰脆弱州的全球气候变化下的过渡

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The rapid pace of global climate change necessitates tools for prioritizing limited climate-adaptation resources in the face of imperfect knowledge regarding plant community responses to changing climate. In addition, global climate change often leads to novel shifts in plant communities which are difficult to anticipate with detailed models based on current system dynamics, which are often greatly altered under novel climates. In order to identify nonforested plant communities that are highly susceptible to state transitions under global climate change, we examined differences between the historical climate envelopes and end-of-century projections. We developed a vulnerability index based on the realized climate envelope for a given plant community relative to future climate exposure under two different climate-forcing models. To provide an approach to prioritizing climate-change adaptation resources at smaller scales, we used scenario analysis to determine the probability of falling outside of the historical climate envelope for each vegetation type present in a given management unit. The large-scale index consistently identified several areas as highly vulnerable to ecosystem state transition under future global climate change. South and north central Texas, the northwestern Great Plains and Rocky Mountain regions, eastern Kansas, and large portions of central and western Texas appear most vulnerable under both climate models. Scenarios identified thresholds of potential state shift for every vegetation type in the small-scale management areas investigated. Our study identifies a simple method for determining the relative vulnerability of nonforested plant communities to state shifts, providing a robust approach for prioritizing limited climate-adaptation resources at multiple scales.
机译：全球气候变化的快速速度需要在面对不完美的植物社区对变化气候的响应的知识面前优先考虑有限的气候适应资源的工具。此外，全球气候变化往往导致植物社区的新型转变，这难以基于当前系统动态的详细模型来预测，这通常在小说中大大改变。为了识别在全球气候变化下高度易受国家转型的非敏感的植物社区，我们研究了历史气候信封和世纪末预测之间的差异。我们基于在两个不同气候迫使模型下的未来气候曝光的给定植物界的实现气候包络的漏洞指数。为了在更小的尺寸下优先考虑气候变化适应资源的方法，我们使用场景分析来确定在给定管理单元中存在的每个植被类型的历史气候包络外面落下的概率。大规模指数一致地确定了在未来的全球气候变化下对生态系统州过渡的几个领域。德克萨斯州南部和北部德克萨斯州西北部大平原和岩石山区，东堪萨斯州和德克萨斯州中西部和西部的大部分似乎在气候模型中都很脆弱。场景确定了在调查的小规模管理区域中每种植被类型的潜在状态转变的阈值。我们的研究确定了一种简单的方法，用于确定非摩杠工厂社区与状态换档的相对漏洞，提供了一种以多种尺度优先排序有限的气候适应资源的稳健方法。

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