High‐resolution data are necessary to understand the effects of climate on plant population dynamics of a forest herb

Abstract

Climate is assumed to strongly influence species distribution and abundance.Although the performance of many organisms is influenced by the climate intheir immediate proximity, the climate data used to model their distributionsoften have a coarse spatial resolution. This is problematic because the local cli-mate experienced by individuals might deviate substantially from the regionalaverage. This problem is likely to be particularly important for sessile organ-isms like plants and in environments where small-scale variation in climate islarge. To quantify the effect of local temperature on vital rates and populationgrowth rates, we used temperature values measured at the local scale (in situlogger measures) and integral projection models with demographic data from37 populations of the forest herbLathyrus vernusacross a wide latitudinal gra-dient in Sweden. To assess how the spatial resolution of temperature datainfluences assessments of climate effects, we compared effects from modelsusing local data with models using regionally aggregated temperature data atseveral spatial resolutions (≥1 km). Using local temperature data, we foundthat spring frost reduced the asymptotic population growth rate in the first oftwo annual transitions and influenced survival in both transitions. Only one ofthe four regional estimates showed a similar negative effect of spring frost onpopulation growth rate. Our results for a perennial forest herb show that ana-lyses using regionally aggregated data often fail to identify the effects of cli-mate on population dynamics. This emphasizes the importance of usingorganism-relevant estimates of climate when examining effects on individualperformance and population dynamics, as well as when modeling species dis-tributions. For sessile organisms that experience the environment over smallspatial scales, this will require climate data at high spatial resolutions.