SummaryThe available tools and approaches to inform conservation decisions commonly assume detailed distribution data. We examine how well-established ecological concepts about patterns in local richness and community turnover can help overcome data limitations when planning future protected areas. To inform our analyses, we surveyed tree species in protected areas in the southern Appalachian Mountains in the eastern USA. We used the survey data to construct predictive models for alpha and beta diversity based on readily observed biophysical variables and combined them to create a heuristic that could predict among-site richness in trees (gamma diversity). The predictive models suggest that site elevation and latitude in this montane system explain much of the variation in alpha and beta diversity in tree species. We tested how well resulting protected areas would represent species if a conservation planner lacking detailed species inventories for candidate sites were to rely only on our alpha, beta and gamma diversity predictions. Our approach selected sites that, when aggregated, covered a large proportion of the overall species pool. The combined gamma diversity models performed even better when we also accounted for the cost of protecting sites. Our results demonstrate that classic community biogeography concepts remain highly relevant to conservation practice today.

中文翻译：

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划分树木多样性模式以优先考虑保护投资

摘要为保护决策提供信息的可用工具和方法通常假设详细的分布数据。我们研究了关于当地丰富度和社区营业额模式的成熟生态概念如何在规划未来保护区时帮助克服数据限制。为了进行分析，我们调查了美国东部阿巴拉契亚山脉南部保护区的树种。我们使用调查数据基于容易观察到的生物物理变量构建了 alpha 和 beta 多样性的预测模型，并将它们结合起来创建了一个可以预测树木的站点间丰富度（伽马多样性）的启发式方法。预测模型表明，该山地系统中的场地海拔和纬度解释了树种中α和β多样性的大部分变化。如果缺乏候选地点详细物种清单的保护规划者仅依赖我们的 alpha、beta 和 gamma 多样性预测，我们测试了由此产生的保护区将如何代表物种。我们的方法选择的地点在聚合时覆盖了整个物种库的很大一部分。当我们还考虑保护站点的成本时，组合的伽马多样性模型表现更好。我们的研究结果表明，经典的社区生物地理学概念仍然与今天的保护实践高度相关。覆盖了整个物种库的很大一部分。当我们还考虑保护站点的成本时，组合的伽马多样性模型表现更好。我们的研究结果表明，经典的社区生物地理学概念仍然与今天的保护实践高度相关。覆盖了整个物种库的很大一部分。当我们还考虑保护站点的成本时，组合的伽马多样性模型表现更好。我们的研究结果表明，经典的社区生物地理学概念仍然与今天的保护实践高度相关。