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Item type:Publication, The evolutionary assembly of forest communities along environmental gradients: recent diversification or sorting of pre-adapted clades?(Cold Spring Harbor Laboratory, 2020-12-22)Summary Biogeographic events occurring in the deep past can contribute to the structure of modern ecological communities. However, little is known about how the emergence of environmental gradients shape the evolution of species that underlie community assembly. In this study, we address how the creation of novel environments lead to community assembly via two non-mutually exclusive processes: 1) the immigration and ecological sorting of pre-adapted clades (ISPC), and 2) recent adaptive diversification (RAD). We study these processes in the context of the elevational gradient created by the uplift of the Central Andes. We develop a novel approach and method based on the decomposition of species turnover into within- and among-clade components, where clades correspond to lineages that originated before mountain uplift. Effects of ISPC and RAD can be inferred from how components of turnover change with elevation. We test our approach using data from over 500 Andean forest plots. We found that species turnover between communities at different elevations is dominated by the replacement of clades that originated before the uplift of the Central Andes. Our results suggest that immigration and sorting of clades pre-adapted to montane habitats is the primary mechanism shaping communities across elevations.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Reduced tree density and basal area in Andean forests are associated with bamboo dominance(Elsevier, 2020-10-13)Forest structure and composition play an essential role in determining the carbon storage capacity of tropical forests. Andean forests, with great potential for carbon accumulation, include large expanses of high-density woody bamboo communities. Woody bamboos can potentially alter forest structure, composition and dynamics and thus can affect carbon storage capacity; however, they are commonly excluded from forest monitoring and modelling. With the aim of documenting patterns of bamboo abundance and disentangling its association with forest structure, we carried out a bamboo census in seven 1-ha long-term forest monitoring plots situated across a large elevation gradient (1000–3600 m a.s.l.) in the Peruvian Andes. We determined that bamboo is a dominant plant group in the study area. In every plot, bamboos were the most common genera in terms of number of stems, and in two of the plots bamboo species were among those with the greatest basal area. We used a combination of Generalized linear mixed models (GLMM) and structural equation modelling (SEM) to hypothesize a causal framework and determine the direction and size of the effects of bamboo abundance (basal area) on number of individual trees, total tree basal area, mean tree basal area, mean tree growth rate and tree mortality rate. We found an overall negative association between bamboo abundance and total tree basal area driven mainly by reduced tree density (directly and indirectly mediated by an increase in tree mortality). However, the decrease in tree density and the increase in tree mortality are also associated with a small increase in tree diameter (mean tree basal area). Overall, the negative association between bamboo abundance and tree basal area suggests a lower biomass accumulation and thus a lower carbon storage capacity of trees in Andean forests where bamboo is dominant. Our results, which show the importance of bamboo in determining forest function, highlight the need for including bamboo in monitoring efforts and modeling studies. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Functional susceptibility of tropical forests to climate change(Nature Research, 2022-07-01)Tropical forests are some of the most biodiverse ecosystems in the world, yet their functioning is threatened by anthropogenic disturbances and climate change. Global actions to conserve tropical forests could be enhanced by having local knowledge on the forestsʼ functional diversity and functional redundancy as proxies for their capacity to respond to global environmental change. Here we create estimates of plant functional diversity and redundancy across the tropics by combining a dataset of 16 morphological, chemical and photosynthetic plant traits sampled from 2,461 individual trees from 74 sites distributed across four continents together with local climate data for the past half century. Our findings suggest a strong link between climate and functional diversity and redundancy with the three trait groups responding similarly across the tropics and climate gradient. We show that drier tropical forests are overall less functionally diverse than wetter forests and that functional redundancy declines with increasing soil water and vapour pressure deficits. Areas with high functional diversity and high functional redundancy tend to better maintain ecosystem functioning, such as aboveground biomass, after extreme weather events. Our predictions suggest that the lower functional diversity and lower functional redundancy of drier tropical forests, in comparison with wetter forests, may leave them more at risk of shifting towards alternative states in face of further declines in water availability across tropical regions. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Improving landscape-scale productivity estimates by integrating trait-based models and remotely-sensed foliar-trait and canopy-structural data(John Wiley and Sons Inc, 2022-08-01)Assessing the impacts of anthropogenic degradation and climate change on global carbon cycling is hindered by a lack of clear, flexible and easy-to-use productivity models along with scarce trait and productivity data for parameterizing and testing those models. We provide a simple solution: a mechanistic framework (RS-CFM) that combines remotely-sensed foliar-trait and canopy-structural data with trait-based metabolic theory to efficiently map productivity at large spatial scales. We test this framework by quantifying net primary productivity (NPP) at high-resolution (0.01-ha) in hyper-diverse Peruvian tropical forests (30040 hectares) along a 3322-m elevation gradient. Our analysis captures hotspots and elevational shifts in productivity more accurately and in greater detail than alternative empirical- and process-based models that use plant functional types. This result exposes how high-resolution, location-specific variation in traits and light competition drive variability in productivity, opening up possibilities to fully harness remote sensing data and reliably scale up from traits to map global productivity in a more direct, efficient and cost-effective manner.