Knowledge on mesoclimatic zonation and microclimatic variations within mountain forest ecosystems is crucial for understanding regional species turnover and effects of climate change on these systems. The temperate mountain forests in the Andean region of South America are among the largest and contiguous natural deciduous forest areas in the world. Due to their pronounced disturbance regime and different successional stages, a climatic zonation combined with the characterisation of its microclimatic variation is important to identify thresholds of species occurrences.We used micro-loggers to measure air temperature and relative humidity for one year at 40 measurement locations along longitudinal and elevation gradients in mountain forests in Northern Patagonia, Argentina. Our results unveil mesoclimatic patterns within these forests characterised by variations in temperature and vapour pressure deficit along the elevational gradient in general, but also at different times of the year. For example,Austrocedrus chilensisandNothofagus dombeyiforests differed mainly by temperature and its diurnal range in the warmest months of the year. Also, differences between forest stands and gaps were more pronounced in the warmest months of the year and at lower elevations, with up to 2.5 K higher temperatures in the second half of the day in gaps. We found clear indications that shrubland ofNothofagus antarcticarepresenting a successional stage after disturbances alters the mesoclimatic pattern, favouring forest fire ignition. Such mesoclimatic variations have a major influence on tree species turnover and ecological processes within these forest ecosystems.The findings contribute to our understanding of the complex interplay between topography, climate, and vegetation in shaping the spatial patterns of species occurrences.

Climate change is reshaping forest ecosystems, presenting urgent and complex challenges that demand attention. In this context, research that quantifies interactions between climate and forests is substantial. However, modelling at a spatial resolution relevant for ecological processes presents a significant challenge, especially given the diverse geographical contexts in which it is applied. In our study, we aimed to assess the effects of applying CHELSA v.2.1 and WorldClim v2.1 data on bioclimatic analysis within the Río Puelo catchment area in northern Patagonia. To achieve this, we inter-compared and evaluated present and future bioclimates, drawing on data from both climate datasets. Our findings underscore substantial consistency between both datasets for temperature variables, confirming the reliability of both for temperature analysis. However, a strong contrast emerges in precipitation predictions, with significant discrepancies highlighted by minimal overlap in bioclimatic classes, particularly in steep and elevated terrains. Thus, while CHELSA and WorldClim provide valuable temperature data for northern Patagonia, their use for precipitation analysis requires careful consideration of their limitations and potential inaccuracies. Nevertheless, our bioclimatic analyses of both datasets under different scenarios reveal a uniform decline in mountain climates currently occupied by N. pumilio, with projections suggesting a sharp decrease in their coverage under future climate scenarios.

Aims: To explore the relationship between plant communities and key environmental drivers in the Andes of northwest Patagonia, Argentina, and to evaluate the applicability of traditional phytosociological definitions to this region. Methods: We conducted 141 vegetation samples using a stratified systematic sampling design. This was done along two steep gradients of aridity and temperature, which are further modified by local factors that include successional changes due to fire and soil variation. We employed a series of multivariate approaches, including hierarchical clustering, Indicator Species Analysis (ISA), restricted Monte Carlo permutation tests, and both constrained and unconstrained ordinations, to identify (a) the main plant community types, (b) their representative species, and (c) the primary drivers of variation in species composition. Finally, we compared the obtained groups and species to associations described by earlier expert-based classifications. Results: From the set of analyses, we identified six different plant community types with 241 recorded species. We found significant differences across communities’ species composition and their environmental indicators. Among the considered environmental variables, elevation and annual precipitation had the strongest effect on species composition. Additionally, variation in composition was significantly related to forest structure, land use and soil characteristics. We further outlined the influence of locally biased classifications based on a predominance of sampling in areas western to the Andes in classification systems developed in the region. Conclusion: Our analysis allowed us to identify the most relevant environmental drivers and indicator species of the six classified plant communities based on numerical methods. The findings highlight the importance of considering full ecological gradients and communities’ responses for developing stable classification approaches. Taxonomic reference: Anton and Zuloaga (2023). Abbreviations: db-RDA = distance-based Redundancy Analysis; ISA = Indicator Species Analysis; NMDS = Non-metric Multi-Dimensional Scaling.