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Landslides are a central component of tropical montane forest disturbance regimes, including in the tropical Andes biodiversity hotspot, one of the most biodiverse ecosystems in the world. Technological developments in remote sensing have made landscape-scale landslide studies possible, unlocking new avenues for understanding montane biodiversity, ecosystem functioning, and the future effects of climate change. Here, we outline three axes of inquiry for future landslide ecology research in Andean tropical montane forest. We focus exclusively on the Andes due to the vast floral diversity and high endemicity of the tropical Andes biodiversity hotspot, and its importance for global biodiversity and regional ecosystem service provisioning; the broad elevational, latitudinal, and topographic gradients across which landslide dynamics play out; and the existence of long-term plot networks that provide the necessary baseline data on mature forest structure, composition, and functioning to contextualize disturbance impacts. The three lines of study we outline, which draw heavily on remote sensing data and techniques, will deepen scientific understanding of tropical montane forest biodiversity and ecosystem functioning, and the potential impacts of climate change on both. They are: (1) tracking landslide biodiversity dynamics across time and space with high spatial and temporal resolution satellite and unoccupied aerial vehicle imagery; (2) assessing the ecological influence of landslides through the lens of plant functional diversity with imaging spectroscopy; and (3) understanding current and predicting future landslide regimes at scale by building a living landslide inventory spanning the tropical Andes. The research findings from these three axes of inquiry will shed light on the role of landslides and the process of forest recovery from them in both the Andes and worldwide. 

Abstract Alpine grassland vegetation supports globally important biodiversity and ecosystems that are increasingly threatened by climate warming and other environmental changes. Trait-based approaches can support understanding of vegetation responses to global change drivers and consequences for ecosystem functioning. In six sites along a 1314 m elevational gradient in Puna grasslands in the Peruvian Andes, we collected datasets on vascular plant composition, plant functional traits, biomass, ecosystem fluxes, and climate data over three years. The data were collected in the wet and dry season and from plots with different fire histories. We selected traits associated with plant resource use, growth, and life history strategies (leaf area, leaf dry/wet mass, leaf thickness, specific leaf area, leaf dry matter content, leaf C, N, P content, C and N isotopes). The trait dataset contains 3,665 plant records from 145 taxa, 54,036 trait measurements (increasing the trait data coverage of the regional flora by 420%) covering 14 traits and 121 plant taxa (ca. 40% of which have no previous publicly available trait data) across 33 families. 

Elevation gradients present enigmatic diversity patterns, with trends often dependent on the dimension of diversity considered. However, focus is often on patterns of taxonomic diversity and interactions between diversity gradients and evolutionary factors, such as lineage age, are poorly understood. We combine forest census data with a genus level phylogeny representing tree ferns, gymnosperms, angiosperms, and an evolutionary depth of 382 million years, to investigate taxonomic and evolutionary diversity patterns across a long tropical montane forest elevation gradient on the Amazonian flank of the Peruvian Andes. We find that evolutionary diversity peaks at mid-elevations and contrasts with taxonomic richness, which is invariant from low to mid-elevation, but then decreases with elevation. We suggest that this trend interacts with variation in the evolutionary ages of lineages across elevation, with contrasting distribution trends between younger and older lineages. For example, while 53% of young lineages (originated by 10 million years ago) occur only below ∼1,750 m asl, just 13% of old lineages (originated by 110 million years ago) are restricted to below ∼1,750 m asl. Overall our results support an Environmental Crossroads hypothesis, whereby a mid-gradient mingling of distinct floras creates an evolutionary diversity in mid-elevation Andean forests that rivals that of the Amazonian lowlands. 

Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotely sensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivity could be predicted by remotely sensed functional diversity. Functional richness of the community decreased with increasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play an important role in explaining the range of trait variation within each site and along elevation. Single- and multitrait remotely sensed measures of functional diversity were important predictors of variation in rates of net and gross primary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests. 

Liverworts and mosses are a major component of the epiphyte flora of tropical montane forest ecosystems. Canopy access was used to analyse the distribution and vertical stratification of bryophyte epiphytes within tree crowns at nine forest sites across a 3400 m elevational gradient in Peru, from the Amazonian basin to the high Andes. The stable isotope compositions of bryophyte organic material ( 13 C/ 12 C and 18 O/ 16 O) are associated with surface water diffusive limitations and, along with C/N content, provide a generic index for the extent of cloud immersion. From lowland to cloud forest δ 13 C increased from −33‰ to −27‰, while δ 18 O increased from 16.3‰ to 18.0‰. Epiphytic bryophyte and associated canopy soil biomass in the cloud immersion zone was estimated at up to 45 t dry mass ha −1 , and overall water holding capacity was equivalent to a 20 mm precipitation event. The study emphasizes the importance of diverse bryophyte communities in sequestering carbon in threatened habitats, with stable isotope analysis allowing future elevational shifts in the cloud base associated with changes in climate to be tracked. 

Abstract Landslides are common natural disturbances in tropical montane forests. While the geomorphic drivers of landslides in the Andes have been studied, factors controlling post‐landslide forest recovery across the steep climatic and topographic gradients characteristic of tropical mountains are poorly understood.Here we use a LiDAR‐derived canopy height map coupled with a 25‐year landslide time‐series map to examine how landslide, topographic and biophysical factors, along with residual vegetation, affect canopy height and heterogeneity in regenerating landslides. We also calculate above‐ground biomass accumulation rates and estimate the time for landslides to recover to mature forest biomass levels.We find that age and elevation are the biggest determinants of forest recovery, and that the jump‐start in regeneration that residual vegetation provides lasts for at least 18 years. Our estimates of time to biomass recovery (31.6–37.1 years) are surprisingly rapid, and as a result we recommend that future research pair LiDAR with hyperspectral imagery to estimate forest above‐ground biomass in frequently disturbed landscapes.Synthesis. Using a high‐resolution LiDAR dataset and a time‐series inventory of 608 landslides distributed across a wide elevational gradient in Andean montane forest, we show that age and elevation are the most influential predictors of forest canopy height and canopy variability. Other features of landslides, in particular the presence of residual vegetation, shape post‐landslide regeneration trajectories. LiDAR allows for a detailed analysis of forest structural recovery across large landscapes and numbers of disturbances, and provides a reasonable upper bound on above‐ground biomass accumulation rates. However, because this method does not capture the effect of compositional change through succession on above‐ground biomass, wherein high‐wood density species gradually replace light‐wooded pioneer species, it overestimates above‐ground biomass. Given previously estimated stem turnover rates along this elevational gradient, we posit that above‐ground biomass recovery takes at least three times as long as our recovery time estimates based on LiDAR‐derived structure alone.