Connor Bernard

Jun 27, 2024 | besjournals.onlinelibrary.wiley.com | Connor Bernard |Charlotte de Vries |Owen Jones |Roberto Salguero-Gómez

Supported by the emergence of multiple demographic datasets (e.g. Gaillard et al., 2021; Levin et al., 2022; Salguero-Gómez et al., 2015, 2016) and long-term studies (e.g. Clutton-Brock & Pemberton, 2004; Festa-Bianchet et al., 2017; Nussey et al., 2013; Pemberton et al., 2022), ageing research and comparative demography have undusted (Colchero et al., 2016; Gaillard & Lemaître, 2020; Wrycza et al., 2015), and developed (Baudisch & Stott, 2019) new metrics to quantify actuarial senescence—the...

Apr 10, 2024 | biorxiv.org | Connor Bernard |Michael B. Bonsall |Roberto Salguero-Gómez

AbstractEcology has been surprisingly slow to address the uncertainty and bias that results from using short-term time series to draw long-term inference. To improve our understanding of assumptions around the temporal structure of vital rates (e.g., survival, reproduction), we need tools that are feasible and capture longer-term, state-structured population dynamics.

Mar 23, 2023 | besjournals.onlinelibrary.wiley.com | Charlotte de Vries |Roberto Salguero-Gómez |Connor Bernard

2.4 Comparing the metrics in real species using the COM(P)ADRE databases To compare how the two discrete-time entropy measures perform in the context of biologically realistic models, we calculated entropies for age-structured matrix population models. We evaluated both animal and plant population models from the COMADRE (version 4.21.8.0) and COMPADRE (version 6.22.5.0) matrix population databases (both available from https://www.compadre-db.org).