An integration of niche and demographic concepts to unravel range-wide population dynamics under climate change

Climate change poses a great threat to species' populations and their distribution. Species distribution models (SDMs) have become key in predicting and managing these impacts. SDMs rely on the ecological niche concept, which defines niches as conditions enabling species to persist indefinitely. However, SDMs rarely consider vital demographic processes-such as survival, growth, and reproduction-that drive population dynamics. Conversely, population ecology often overlooks how vital rates vary across niche space, hindering range-wide predictions of climate change impacts on species populations. DemographicNiches will deepen our mechanistic understanding of the niche by building on the innovative Demographic Niche concept. This concept views a species' niche as comprised of multiple, separate demographic niche components: separate conditions enabling survival, growth, and reproduction. I will integrate existing niche and demographic principles while testing novel hypotheses to advance this concept. I will identify patterns of vital rate variation across niche space and uncover the roles of genetic differences and phenotypic plasticity in driving such variation, revealing the intricate factors shaping demographic niches. I will then introduce the concept of demographic niche syndromes-the relations among separate demographic niches-as part of a framework to describe and assess species' extinction risks and management options. Applying this framework to plant species worldwide, I will quantify trends in species' susceptibility to climate change. Leveraging extensive demographic datasets, I will unravel the complexities behind vital rate variation among populations across environments and their consequence for species' persistence under climate change. Through DemographicNiches, I will bridge the gap between key biogeographic and demographic concepts, offering a novel and comprehensive approach to understand and predict range-wide population responses to climate change.