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Improving effectiveness of systematic conservation planning with density data

机译：利用密度数据提高系统保护规划的有效性

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Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High-density model Zonation rankings protected more individuals per species when networks protected the highest priority 10-40% of the landscape. Compared with density-based models, the occurrence-based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density-based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.
机译：系统的保护规划旨在设计能够满足大片景观保护目标的保护区网络。尽管有证据表明模型预测可能与物种密度不高度相关，但这些保护网络的最佳设计通常是基于建模的栖息地适宜性或物种出现的概率。我们假设使用物种密度分布设计的保护网络比使用发生概率模型设计的网络更有效地保护了所考虑的所有物种的种群。为了验证这一假设，我们使用了分区保护优先排序算法，根据美国西北太平洋地区26种陆上鸟类的出现概率与密度模型，评估了保护网络设计。我们根据预测的物种密度和预测的物种多样性评估了每个保护网络的效力。当网络保护最高优先级景观的10-40％时，高密度模型分区划分可保护每个物种更多的个体。与基于密度的模型相比，基于事件的模型在景观的最低50％优先区域保护了更多的个体。两种方法以相似的方式保护物种多样性：在两个保护网络中，优先级较高的地区，预测的多样性更高。我们得出结论，密度模型和概率模型都可以用于设置保护优先级，但是基于密度的模型最适合于确定最高优先级区域。开发方法以汇总来自无关监视工作的物种计数数据，并通过诸如禽知识网络之类的生态信息门户网站广泛提供这些数据，将使物种计数数据更广泛地纳入系统的保护规划工作中。

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