Mountain ecosystems are sensitive and reliable indicators of climate change. Long-term studies may be extremely useful in assessing the responses of high-elevation ecosystems to climate change and other anthropogenic drivers from a broad ecological perspective. Mountain research sites within the LTER (Long-Term Ecological Research) network are representative of various types of ecosystems and span a wide bioclimatic and elevational range. Here, we present a synthesis and a review of the main results from ecological studies in mountain ecosystems at 20 LTER sites in Italy, Switzerland and Austria covering in most cases more than two decades of observations. We analyzed a set of key climate parameters, such as temperature and snow cover duration, in relation to vascular plant species composition, plant traits, abundance patterns, pedoclimate, nutrient dynamics in soils and water, phenology and composition of freshwater biota. The overall results highlight the rapid response of mountain ecosystems to climate change, with site-specific characteristics and rates. As temperatures increased, vegetation cover in alpine and subalpine summits increased as well. Years with limited snow cover duration caused an increase in soil temperature and microbial biomass during the growing season. Effects on freshwater ecosystems were also observed, in terms of increases in solutes, decreases in nitrates and changes in plankton phenology and benthos communities. This work highlights the importance of comparing and integrating long-term ecological data collected in different ecosystems for a more comprehensive overview of the ecological effects of climate change. Nevertheless, there is a need for (i) adopting co-located monitoring site networks to improve our ability to obtain sound results from cross-site analysis, (ii) carrying out further studies, in particular short-term analyses with fine spatial and temporal resolutions to improve our understanding of responses to extreme events, and (iii) increasing comparability and standardizing protocols across networks to distinguish local patterns from global patterns.
Community-weighted-mean (CWM) and functional diversity (FD) describe two aspects of plant communities' functional structure. While they have been often used separately to infer assembly processes, their covariation can actually provide useful insights into the prevalence of a particular 2 assembly process over the other. We propose a framework where positive or negative covariation of these indices can be related to different assembly processes along an environmental gradient. We tested this framework in grassland communities along elevation gradient in Central Apennines by collecting species cover and traits of the most abundant species and calculating the effect size CWM and FD. We performed major axis regression for each effect size CWM-FD relationship for different belts along the elevation gradient. The observation that Plant Height showed a positive CWM-FD relationship only under more stressful conditions indicates that there may be a tendency towards habitat filtering. Seed Mass showed positive covariation in each belt may indicate the presence of both habitat filtering and limiting similarity acting with different intensity depending on the environmental stress level. Negative covariation between CWM-Plant Height and Seed Mass-FD under less stress suggest biotic filter, while positive covariation between CWM-Plant Height and both Seed Mass and SLA FD under stressful conditions suggest the presence of habitat filtering.Ultimately, the relationship of CWM and FD may provide information on how different communities assemble along an environmental gradient. Moreover, combining the information of CWM with the FD and environmental stress level might help to identify the processes behind the same functional pattern.
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