Inferring space from time: On the relationship between demography and environmental suitability in the desert plant O. rastrera.

• Main Authors: Carolina Ureta, Carlos Martorell, Ángela P Cuervo-Robayo, María C Mandujano, Enrique Martínez-Meyer
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2018-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC6084933?pdf=render

Demographic analyses and ecological niche modeling (ENM) are two popular tools that address species persistence in relation to environmental conditions. Classic demography provides detailed information about the mechanisms that allow a population to grow or remain stable at a local scale, while ENM infers distributions from conditions suitable for species persistence at geographic scales by relating species' occurrences with environmental variables. By integrating these two tools, we may better understand population processes that determine species persistence at a geographic scale. To test this idea, we developed a model that relates climate to demography of the cactus Opuntia rastrera using 15 years of data from one locality. Using this model we determined the geographic area where populations would have positive growth rates given its climatic conditions. The climate-dependent demographic model showed poor performance as a distribution model, but it was helpful in defining some mechanisms that determine species' distributions. For instance, high rainfall had a negative impact on the population growth rate by increasing mortality. Rainy areas to the west of the distribution of O. rastrera were identified as unsuitable both by our climate-dependent demographic model and by a popular ENM algorithm (MaxEnt), suggesting that distribution is constrained by excessive rains due to high mortality. Areas projected to be climatically suitable by MaxEnt were not related with higher population growth rates. Instead, we found a strong correlation between environmental distance to the niche centroid (center of the niche hypervolume, where optimal conditions may occur) and population growth rate, meaning that the niche centroid approach is helpful in finding high-fitness areas.