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\begin{document}

\title{Detecting climate signals in populations across life histories}



\author[1]{Stephanie Jenouvrier}%
\author[2]{Matthew C.  Long}%
\author[3]{Christophe Coste}%
\author[2]{Marika Holland}%
\author[4]{Marlène Gamelon}%
\author[5]{Nigel Yoccoz}%
\author[4]{Bernt-Erik Sæther}%
\affil[1]{Woods Hole Oceanographic Institution}%
\affil[2]{NCAR}%
\affil[3]{NTNU}%
\affil[4]{Centre for Biodiversity Dynamics}%
\affil[5]{University of Tromsø}%


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  \date{May 21, 2024}


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\begin{abstract}
Climate impacts are not always easily discerned in wild populations as
climate change occurs in the context of natural variability.
Furthermore, species responses to climate change and variability differ
among life histories. The time of emergence (ToE) identifies when the
signal of anthropogenic climate change can be quantitatively
distinguished from noise associated with natural variability. This
concept has been applied extensively in the climate sciences, but has
not yet formally been explored in the context of population dynamics.
Here, we present a theoretical assessment of the ToE of climate-driven
signals in population dynamics (ToEpop) to detect climate signals in
populations. We identify the dependence of ToEpop on the magnitude of
climate trends and variability and explore the demographic controls on
ToEpop. We demonstrate that different life histories (fast species vs.
slow species), demographic processes (survival, reproduction) and
functional relationships between climate and demographic rates, yield
population dynamics that filter trends and variability in climate
differently. We illustrate empirically how to detect the point in time
when anthropogenic signals in populations emerge from the envelope of
natural variability for a species threatened by climate change: the
emperor penguin. Finally, we propose six testable hypotheses and a road
map for future research.%
\end{abstract}%



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