Richter Aline, Nakamura Gabriel, Agra Iserhard Cristiano, da Silva Duarte Leandro
Departamento de Ecologia Universidade Federal do Rio Grande do Sul Porto Alegre Brazil.
Departamento de Biologia Universidade Federal do Ceará Fortaleza Brazil.
Ecol Evol. 2021 Aug 10;11(18):12508-12519. doi: 10.1002/ece3.7995. eCollection 2021 Sep.
Studies on ecological communities often address patterns of species distribution and abundance, but few consider uncertainty in counts of both species and individuals when computing diversity measures.We evaluated the extent to which imperfect detection may influence patterns of taxonomic, functional, and phylogenetic diversity in ecological communities.We estimated the true abundance of fruit-feeding butterflies sampled in canopy and understory strata in a subtropical forest. We compared the diversity values calculated by observed and estimated abundance data through the hidden diversity framework. This framework evaluates the deviation of observed diversity when compared with diversities derived from estimated true abundances and whether such deviation represents a bias or a noise in the observed diversity pattern.The hidden diversity values differed between strata for all diversity measures, except for functional richness. The taxonomic measure was the only one where we observed an inversion of the most diverse stratum when imperfect detection was included. Regarding phylogenetic and functional measures, the strata showed distinct responses to imperfect detection, despite the tendency to overestimate observed diversity. While the understory showed noise for the phylogenetic measure, since the observed pattern was maintained, the canopy had biased diversity for the functional metric. This bias occurred since no significant differences were found between strata for observed diversity, but rather for estimated diversity, with the canopy being more clustered.We demonstrate that ignore imperfect detection may lead to unrealistic estimates of diversity and hence to erroneous interpretations of patterns and processes that structure biological communities. For fruit-feeding butterflies, according to their phylogenetic position or functional traits, the undetected individuals triggered different responses in the relationship of the diversity measures to the environmental factor. This highlights the importance to evaluate and include the uncertainty in species detectability before calculating biodiversity measures to describe communities.
对生态群落的研究通常关注物种分布和丰度模式，但在计算多样性指标时，很少有人考虑物种和个体数量的不确定性。我们评估了不完全检测可能影响生态群落中分类、功能和系统发育多样性模式的程度。我们估计了在亚热带森林的林冠层和林下层采样的食果蝴蝶的真实丰度。我们通过隐藏多样性框架比较了根据观察到的和估计的丰度数据计算出的多样性值。该框架评估观察到的多样性与从估计的真实丰度得出的多样性相比的偏差，以及这种偏差是否代表观察到的多样性模式中的偏差或噪声。除功能丰富度外，所有多样性指标的隐藏多样性值在不同层次间存在差异。分类学指标是唯一一个在纳入不完全检测时我们观察到最多样化层次发生反转的指标。关于系统发育和功能指标，尽管有高估观察到的多样性的趋势，但不同层次对不完全检测表现出不同的反应。虽然林下层在系统发育指标上表现出噪声，因为观察到的模式得以维持，但林冠层在功能指标上存在有偏差的多样性。出现这种偏差是因为观察到的多样性在不同层次间没有显著差异，而是估计的多样性存在差异，林冠层更为聚集。我们证明，忽略不完全检测可能导致对多样性的不切实际估计，从而对构建生物群落的模式和过程产生错误解释。对于食果蝴蝶，根据它们的系统发育位置或功能特征，未被检测到的个体在多样性指标与环境因素的关系中引发了不同的反应。这凸显了在计算描述群落的生物多样性指标之前评估并纳入物种可检测性不确定性的重要性。
