Rosa Giacomo, Schmidt Benedikt R, Léna Jean-Paul, Monod-Broca Benjamin, Vignoli Leonardo, Tournier Emilie, Bonnaire Eric, Buschmann Holger, Kinet Thierry, Laudelout Arnaud, Fonters Remi, Biancardi Carlo, Di Cerbo Anna R, Langlois Dominique, Thirion Jean-Marc, Morin Lucy, Pichenot Julian, Moquet Julien, Cayuela Hugo, Canessa Stefano
Department for the Earth, Environment and Life Sciences (DISTAV), University of Genoa, Genoa, Italy.
Conservation Biology, Institute for Ecology and Evolution, University of Bern, Bern, Switzerland.
J Anim Ecol. 2025 Mar;94(3):436-448. doi: 10.1111/1365-2656.14243. Epub 2025 Jan 19.
Population matrix models are routinely used to study the demography of wild populations and to guide management choices. When vital rates are unknown for a specific population or life history stage, researchers often replace them with estimates from other populations of the same species. Such 'hybrid' matrices might ignore among-population life history variation and lead to incorrect inferences. In this study, we examined the real-world effect of using hybrid matrices on demographic inference and management decisions, using a large dataset on yellow-bellied toad (Bombina variegata) populations, an amphibian species whose life history depends on human land use. We estimated stage-specific survival and recruitment for 18 populations across different habitat types. We then assessed how estimated population growth rates and elasticities changed when population-specific vital rates were replaced by estimates from other populations, chosen randomly or based on habitat, demographic or geographic proximity. The use of hybrid matrices mixing demographic estimates from different populations and habitats biased predictions. The mean bias was relatively minor even when sampling randomly across all populations, because our large dataset represented the whole range of life histories and errors cancelled out on average. However, borrowing estimates from geographically close or demographically similar populations substantially reduced the risk of extreme errors. Borrowing from populations from similar habitat types could also reduce bias, but results varied depending on the exact habitat types concerned. Our study illustrates how habitat-specific among-population variation in life history affects the reliability of population matrices commonly used in evolutionary demography, ecology and conservation. When the use of hybrid population matrices cannot be avoided, their creation can be informed by additional information about ecological or demographic patterns, helping reduce bias. When such information is not available, we recommend that studies should consider the whole space of parameter estimates (the complete range of estimates available), thus transparently describing the true uncertainty surrounding demographic estimates.
种群矩阵模型通常用于研究野生种群的人口统计学特征，并指导管理决策。当特定种群或生活史阶段的生命率未知时，研究人员通常会用同一物种其他种群的估计值来替代它们。这种“混合”矩阵可能会忽略种群间的生活史差异，并导致错误的推断。在本研究中，我们利用一个关于黄腹蟾蜍（Bombina variegata）种群的大型数据集，研究了使用混合矩阵对人口统计学推断和管理决策的实际影响。黄腹蟾蜍是一种两栖动物，其生活史依赖于人类土地利用。我们估计了18个不同栖息地类型种群的特定阶段生存率和补充率。然后，我们评估了当用随机选择或基于栖息地、人口统计学或地理邻近性从其他种群获得的估计值替代特定种群的生命率时，估计的种群增长率和弹性是如何变化的。使用混合不同种群和栖息地人口统计学估计值的矩阵会使预测产生偏差。即使在所有种群中随机抽样，平均偏差也相对较小，因为我们的大型数据集代表了整个生活史范围，误差平均相互抵消。然而，从地理上接近或人口统计学上相似的种群借用估计值，大大降低了出现极端误差的风险。从相似栖息地类型的种群借用估计值也可以减少偏差，但结果因具体涉及的栖息地类型而异。我们的研究说明了生活史中特定栖息地的种群间差异如何影响进化人口统计学、生态学和保护中常用的种群矩阵的可靠性。当无法避免使用混合种群矩阵时，可以通过有关生态或人口统计学模式的额外信息来创建它们，这有助于减少偏差。当此类信息不可用时，我们建议研究应考虑参数估计的整个空间（可用估计值的完整范围），从而透明地描述围绕人口统计学估计值的真实不确定性。
