Trait-based modelling of temperate forests in Western Himalaya, India

A central goal of ecology is to understand how ecological communities assemble and how species assemblages determine ecosystem functioning ( reflected in ’ effect traits ’ ) in response to environmental factors ( reflected in ’ response traits ’ ). In this study, we aim to characterize the spatial variability of major plant functional traits along an environmental gradient in temperate forests of western Himalaya, and to assess the extent to which this variability differs between broad-leaved and conifer tree species. Further, to analyze the effect of traits on vegetation dynamics mechanistically, we calibrated the Plant and Plant-FATE vegetation models. Four functional traits were selected to incorporate information on both the leaf and the wood economic spectra: maximum tree height, wood density, leaf mass per area and leaf phosphorous content. We found that environmental filtering shapes local species composition and associated functional characteristics in the region – particularly, elevation, light intensity, and soil texture are the most important determinants of vegetation dynamics which affect plant functional trait variation and determine vegetation carbon storage in the temperate forests of Western Himalaya. Moreover, most of the plant functional trait variability was determined at the level of individual plants, thus suggesting higher trait variation within species than between species. To further investigate how these environmental drivers affect the size distribution of trees, we calibrated trait-based eco-evolutionary vegetation models (Plant and Plant-FATE) capable of predicting species-specific size distributions. We found that predicted height and DBH distributions of trees successfully match with field observations, suggesting that inclusion of the mechanistic factors driving intraspecific trait variation is crucial for linking environmental variation to changes in community assemblage processes and emergent ecosystem functioning. Our approach has the potential to improve the prediction of ecosystem services under future climate change scenarios for the Himalayan region. traits on vegetation carbon storage; and iv) Calibrate the Plant and Plant-FATE models to predict the effect of plant functional traits on forest dynamics across environmental gradients. if covariation among traits varies depending on the ecological scale considered, we performed a principal components analysis (PCA) for both broad-leaved and conifer species (ggfortify package). We performed variance partitioning to separate different components driving trait variation across three nested ecological scales: species, population and individual level (lme4 package). We further used structural equation modeling (SEM) to study the influence of environmental gradients and plant traits on carbon stocks (piecewiseSEM package). The best model was selected based on lowest AIC value and significant p-value. We applied principal component analysis (PCA) to reduce multicollinearity among soil variables across environmental gradients and thus computed principal components of soil variables (PC1) for SEM analysis. PC1 accounted for 24.58% of variation among the variables Sand content, pH and Bulk Density. All statistical analyses were conducted using R version 3.5. 0 (R Core Team 2018). topographical heterogeneity and environmental conditions in the at class level, we conclude that intra-specific variation results from management activities at lower elevation zones. Variance partitioning for the leaf economic spectrum (LMA and LPC) shows low differentiation between species, suggesting that external factors such management activities are affecting the trait distribution at different ecological levels. study Environmental shapes local species composition and associated plant functional traits in the study site and we found elevation, light intensity and soil texture to be the most important environmental factors affecting plant functional trait distribution. Contrary to our expectations, we found higher intra-specific variation than inter-specific trait variation for both broad-leaved and conifer tree species. While inter-specific variation typically results from changes in species composition between study sites located in different elevations along environmental gradients in resource availability, intra-specific variation results form individual adaptation to local site conditions. we and trait is crucial for linking environmental changes to changes in species distribution and ecosystem functions and We found plant functional traits are important predictors of vegetation storage suggesting that differences in species composition determine vegetation carbon storage in the region. Eventually, using our results to calibrate a trait-based eco-evolutionary model, we successfully predicted the size distribution of two species at our sites. The calibrated models can thus be used to project crucial ecosystem services under future climate change scenarios. Overall, our study findings indicate that species with more conservative ecological strategies would be more prone to continued disturbance intensity, and therefore highly fragile temperate forests in the Himalaya should be sustainably managed to maintain crucial ecosystem services and avoid further loss of biodiversity in the region.