Data from: Biological traits, rather than environment, shape detection curves of large vertebrates in neotropical rainforests

Line transect surveys are widely used in neotropical rainforests to estimate the population abundance of medium- and large-sized vertebrates. The use of indices such as Encounter Rate has been criticized because the probability of animal detection may fluctuate due to the heterogeneity of environmental conditions among sites. In addition, the morphological and behavioral characteristics (biological traits) of species affect their detectability. In this study, we compared the extent to which environmental conditions and species’ biological traits bias abundance estimates in terra firme rainforests in French Guiana. The selected environmental conditions included both physical conditions and forest structure covariates, while the selected biological traits included the morphological and behavioral characteristics of species. We used the distance sampling method to model the detection probability as an explicit function of environmental conditions and biological traits and implemented a model selection process to determine the relative importance of each group of covariates. Biological traits contributed to the variability of animal detectability more than environmental conditions, which had only a marginal effect. Detectability was best for large animals with uniform or disruptive markings that live in groups in the canopy top. Detectability was worst for small, solitary, terrestrial animals with mottled markings. In the terra firme rainforests which represent ~80% of the Amazonia and Guianas regions, our findings support the use of relative indices such as the encounter rate to compare population abundance between sites in species-specific studies. Even though terra firme rainforests may appear similar between regions of Amazonia and the Guianas, comparability must be ensured, especially in forests disturbed by human activity. The detection probability can be used as an indicator of species’ vulnerability to hunting and, thus, to the risk of local extinction. Only a few biological trait covariates are required to correctly estimate the detectability of the majority of medium- and large-sized vertebrates. Thus, a biological trait model could be useful in predicting the detection probabilities of rare, uncommon or localized species for which few data are available to fit the detection function.样线调查法（Line transect surveys）在新热带界雨林中被广泛应用，用于估算中大型脊椎动物的种群丰度。诸如相遇率（Encounter Rate）这类指数的应用曾备受批评，原因在于不同样地间环境条件的异质性可能导致动物探测概率出现波动。此外，物种的形态与行为特征（即生物学性状（biological traits））亦会影响其探测几率。本研究以法属圭亚那的旱地雨林（terra firme rainforests）为研究对象，对比了环境条件与物种生物学性状对种群丰度估算的偏倚程度。所选环境条件涵盖物理环境与森林结构协变量，而所选生物学性状则包含物种的形态与行为特征。本研究采用距离取样法（distance sampling method），将探测概率建模为环境条件与生物学性状的显性函数，并通过模型选择流程确定每类协变量的相对重要性。相较于仅产生微弱边际效应的环境条件，生物学性状对动物探测概率变异的贡献更为显著。体表带有均匀或破坏型斑纹、结群栖息于林冠顶层的大型动物，探测概率最高；而体型小巧、独居陆生且体表带有斑驳斑纹的动物，探测概率则最低。旱地雨林约占亚马逊与圭亚那地区总面积的80%，本研究结果支持在物种特异性研究中，采用相遇率这类相对指数开展样地间种群丰度对比。尽管亚马逊与圭亚那地区的旱地雨林外观相似，但仍需确保样地间的可比性，尤其是在受人类活动干扰的森林中。探测概率可作为物种受狩猎威胁脆弱性的指示指标，进而反映其局部灭绝风险。仅需少量生物学性状协变量，即可准确估算多数中大型脊椎动物的探测概率。因此，生物学性状模型可用于预测稀有、罕见或局域分布物种的探测概率——这类物种往往缺乏足够数据以拟合探测函数。