Ongoing global climate change is driving widespread shifts in species distributions. Trends show frequent upwards shifts of treelines, but information on changes in montane forest below the treeline and in the tropics and subtropics is limited, despite the importance of these areas for biodiversity and ecosystem function. Patterns of species shifts in tropical and subtropical regions are likely to be more complex and individualistic than global averages suggest due to high species diversity and strong influence of competition, alongside direct climatic limitations on distributions. To address the question of how subtropical montane tree species are likely to move as climate changes, we used an extensive national forest inventory to estimate distribution shifts of 75 tree species in Taiwan by comparing the optimum elevation and range edges of adults and juveniles within species. Overall there was a significant difference in optimum elevation of adults and juveniles. Life stage mismatches suggested upward shifts in 35% of species but downward shifts of over half (56%), while 8% appeared stable. Upward elevation shifts were disproportionately common in high elevation species, whilst mid to low elevation species suggested greater variation in shift direction. Whilst previous research on mountain forest range shifts has been dominated by work addressing changes in treeline position, we show that although high elevation species shift up, below the treeline species may shift individualistically, heralding widespread changes in forest communities over coming decades. The wide variation of responses indicated is likely driven by individual species responses to interacting environmental factors such as competition, topography and anthropogenic influences across the broad range of forest types investigated. As global environmental changes continue, more detailed understanding of tree range shifts across a wide spectrum of forests will allow us to prepare for the implications of such changes for biodiversity, ecosystem function and dependent human populations.
Aim: Plant functional traits are broadly used to quantify and predict impacts of climate change on vegetation. However, high intraspecific trait variation can bias mean values when few measurements are available. Here, we determine the extent of individual leaf trait variation and covariation across a highly heterogeneous environmental gradient for a widely distributed subtropical pine. We demonstrate the implications of trait variation for characterising species by assessing data availability and variability across the Pinus genus.Location: Central Mountain Range, Taiwan.Taxon: Pinus taiwanensis Hayata (Pinaceae). Methods:We measured eight functional traits suggested to reflect plant strategies: needle length, area, thickness, dry and fresh mass, stomatal row density (SD), leaf dry matter content (LDMC) and specific leaf area (SLA). We examined trait variation in response to climatic and physiographic factors across an elevational gradient of 495-3106 m a.s.l. using linear mixed effects models (LMMs). Intraspecific trait covariation was explored using principal component analyses (PCAs) and LMMs. Descriptive statistics were calculated for Pinus records in the global TRY plant trait database.Results: Intraspecific variability among traits was high (CV 20%-44%) and predictable with elevation (generally p < 0.05, with declining needle size and LDMC with elevation and increasing SD). However, 41%-92% of variance was un-explained by topography. Sixty-five percent of variation was explained by two trait covariation axes, with predictable changes with elevation (p < 0.001). Pinus data availability in TRY was low.Across traits, only 12.5%-53% of species had sufficient sample sizes for intraspecific analyses. Main conclusions:We show substantial trait variation for a single species, here likely driven by temperature differences and additional biotic and abiotic drivers across the elevational range. Improved understanding of the extent and implications of intraspecific variability is necessary for reliable quantifications and predictions of the impacts of environmental change, especially in understudied, hyper-diverse ecosystems such as tropical forests.
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