Point Blue Conservation Science, 3820 Cypress Drive #11 Petaluma, CA, 94954, U.S.A.
American Bird Conservancy, 4249 Loudon Avenue, The Plains, VA, 20198, U.S.A.
Conserv Biol. 2015 Aug;29(4):1217-1227. doi: 10.1111/cobi.12499. Epub 2015 Apr 14.
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.
系统保护规划旨在设计保护区域网络，以满足大景观范围内的保护目标。这些保护网络的最佳设计通常基于物种的栖息地适宜性或出现概率的模型，尽管有证据表明模型预测可能与物种密度相关性不高。我们假设，使用物种密度分布设计的保护网络比使用出现概率模型设计的网络更有效地保护所有考虑物种的种群。为了验证这一假设，我们使用分区保护优先排序算法（Zonation），根据美国太平洋西北地区 26 种陆地鸟类的出现概率与密度模型，评估保护网络设计。我们根据预测物种密度和预测物种多样性来评估每个保护网络的效果。当网络保护景观最高优先级的 10-40%时，高密度模型的分区排名保护了更多的物种个体。与基于密度的模型相比，基于出现的模型在景观最低优先级的 50%区域保护了更多的个体。这两种方法以相似的方式保护了物种多样性：在两个保护网络中，较高优先级的位置预测多样性更高。我们得出的结论是，密度和出现概率模型都可以用于确定保护优先级，但基于密度的模型最适合确定最高优先级区域。开发汇总来自不同监测工作的物种计数数据的方法，并通过像鸟类知识网络这样的生态信息学门户广泛提供这些数据，将使物种计数数据更广泛地纳入系统保护规划工作中。
