HighlightsMicroclimate was monitored in primary forest, logged forest and oil palm plantation.There were strong relationships between leaf area index and diurnal climate.Logged forest is up to 2.5 °C warmer on average than primary forest.Oil palm plantations are up to 6.5 °C warmer on average than primary forest.Forest disturbance led to desiccation of the air near the forest floor.

Local‐scale microclimatic conditions in forest understoreys play a key role in shaping the composition, diversity and function of these ecosystems. Consequently, understanding what drives variation in forest microclimate is critical to forecasting ecosystem responses to global change, particularly in the tropics where many species already operate close to their thermal limits and rapid land‐use transformation is profoundly altering local environments. Yet our ability to characterize forest microclimate at ecologically meaningful scales remains limited, as understorey conditions cannot be directly measured from outside the canopy. To address this challenge, we established a network of microclimate sensors across a land‐use intensity gradient spanning from old‐growth forests to oil‐palm plantations in Borneo. We then combined these observations with high‐resolution airborne laser scanning data to characterize how topography and canopy structure shape variation in microclimate both locally and across the landscape. In the processes, we generated high‐resolution microclimate surfaces spanning over 350 km2, which we used to explore the potential impacts of habitat degradation on forest regeneration under both current and future climate scenarios. We found that topography and vegetation structure were strong predictors of local microclimate, with elevation and terrain curvature primarily constraining daily mean temperatures and vapour pressure deficit (VPD), whereas canopy height had a clear dampening effect on microclimate extremes. This buffering effect was particularly pronounced on wind‐exposed slopes but tended to saturate once canopy height exceeded 20 m—suggesting that despite intensive logging, secondary forests remain largely thermally buffered. Nonetheless, at a landscape‐scale microclimate was highly heterogeneous, with maximum daily temperatures ranging between 24.2 and 37.2°C and VPD spanning two orders of magnitude. Based on this, we estimate that by the end of the century forest regeneration could be hampered in degraded secondary forests that characterize much of Borneo's lowlands if temperatures continue to rise following projected trends.

Invertebrates are dominant species in primary tropical rainforests, where their abundance and diversity contributes to the functioning and resilience of these globally important ecosystems. However, more than one-third of tropical forests have been logged, with dramatic impacts on rainforest biodiversity that may disrupt key ecosystem processes. We find that the contribution of invertebrates to three ecosystem processes operating at three trophic levels (litter decomposition, seed predation and removal, and invertebrate predation) is reduced by up to one-half following logging. These changes are associated with decreased abundance of key functional groups of termites, ants, beetles and earthworms, and an increase in the abundance of small mammals, amphibians and insectivorous birds in logged relative to primary forest. Our results suggest that ecosystem processes themselves have considerable resilience to logging, but the consistent decline of invertebrate functional importance is indicative of a human-induced shift in how these ecological processes operate in tropical rainforests.

Logging and habitat conversion create hotter microclimates in tropical forest landscapes, representing a powerful form of localised anthropogenic climate change. It is widely believed that these emergent conditions are responsible for driving changes in communities of organisms found in modified tropical forests, although the empirical evidence base for this is lacking. Here we investigated how interactions between the physiological traits of genera and the environmental temperatures they experience lead to functional and compositional changes in communities of ants, a key organism in tropical forest ecosystems. We found that the abundance and activity of ant genera along a gradient of forest disturbance in Sabah, Malaysian Borneo, was defined by an interaction between their thermal tolerance (CTmax) and environmental temperature. In more disturbed, warmer habitats, genera with high CTmax had increased relative abundance and functional activity, and those with low CTmax had decreased relative abundance and functional activity. This interaction determined abundance changes between primary and logged forest that differed in daily maximum temperature by a modest 1.1°C, and strengthened as the change in microclimate increased with disturbance. Between habitats that differed by 5.6°C (primary forest to oil palm) and 4.5°C (logged forest to oil palm), a 1°C difference in CTmax among genera led to a 23% and 16% change in relative abundance, and a 22% and 17% difference in functional activity. CTmax was negatively correlated with body size and trophic position, with ants becoming significantly smaller and less predatory as microclimate temperatures increased. Our results provide evidence to support the widely held, but never directly tested, assumption that physiological tolerances underpin the influence of disturbance‐induced microclimate change on the abundance and function of invertebrates in tropical landscapes. A free Plain Language Summary can be found within the Supporting Information of this article.

Capturing the spatial and temporal correlation of multiple variables in a weather generator is challenging. A new massively multi-site, multivariate daily stochastic weather generator called IMAGE is presented here. It models temperature and precipitation variables as latent Gaussian variables with temporal behaviour governed by an auto-regressive model whose residuals and parameters are correlated through resampling of principle component time series of empirical orthogonal function modes. A case study using European climate data demonstrates the model's ability to reproduce extreme events of temperature and precipitation. The ability to capture the spatial and temporal extent of extremes using a modified Climate Extremes Index is demonstrated. Importantly, the model generates events covering not observed temporal and spatial scales giving new insights for risk management purposes.