Department of Conservation and Science, Lincoln Park Zoo, 2001 N. Clark St., Chicago, IL 60614, U.S.A.
Department of Ecology and Evolution, Stony Brook University, 113 Life Sciences Building, Stony Brook, NY 11794, U.S.A.
Conserv Biol. 2018 Dec;32(6):1290-1300. doi: 10.1111/cobi.13135. Epub 2018 Aug 29.
Lack of demographic data for most of the world's threatened species is a widespread problem that precludes viability-based status assessments for species conservation. A commonly suggested solution is to use data from species that are closely related or biologically similar to the focal species. This approach assumes similar species and populations of the same species have similar demographic rates, an assumption that has yet to be thoroughly tested. We constructed a Bayesian hierarchical model with data on 425 plant species to predict demographic rates (intrinsic rate of population growth, recruit survival, juvenile survival, adult survival, and fecundity) based on biological traits and phylogenetic relatedness. Generally, we found small effects of species-level traits (except woody polycarpic species tended to have high adult survival rates that increased with plant height) and a weak phylogenetic signal for 4 of the 5 demographic parameters examined. Patterns were stronger in adult survival and fecundity than other demographic rates; however, the unexplained variances at both the species and population levels were high for all demographic rates. For species lacking demographic data, our model produced large, often inaccurate, prediction intervals that may not be useful in a management context. Our findings do not support the assumption that biologically similar or closely related species have similar demographic rates and provide further evidence that direct monitoring of focal species and populations is necessary for informing conservation status assessments.
缺乏世界上大多数受威胁物种的人口统计数据是一个普遍存在的问题,这使得基于生存能力的物种保护状况评估无法进行。一个常见的解决方案是使用与焦点物种密切相关或具有相似生物学特性的物种的数据。这种方法假设相似的物种和同一物种的种群具有相似的人口统计率,而这一假设尚未得到彻底验证。我们构建了一个贝叶斯层次模型,使用 425 种植物的数据,根据生物学特征和系统发育关系来预测人口统计率(种群增长率、幼体存活率、幼体存活率、成体存活率和繁殖力)。一般来说,我们发现物种水平特征的影响很小(除了木质多果物种的成体存活率往往较高,且随植物高度的增加而增加),而在我们研究的 5 个人口统计参数中,有 4 个参数的系统发育信号较弱。在成体存活率和繁殖力方面的模式比其他人口统计率更强;然而,所有人口统计率在物种和种群水平上的未解释方差都很高。对于缺乏人口统计数据的物种,我们的模型产生了大的、往往不准确的预测区间,在管理方面可能没有用处。我们的研究结果不支持生物学相似或密切相关的物种具有相似的人口统计率的假设,并进一步证明,直接监测焦点物种和种群对于告知保护状况评估是必要的。