3. Producción
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Item type:Publication, Quantifying productivity at landscape scale using remotely-sensed foliar traits and canopy structure(Research Square, 2020-11-02)Abstract Forests are integral to global carbon cycling but are threatened by anthropogenic degradation and climate change. Assessing this global threat has been hindered by a lack of clear, flexible, and easy-to-use productivity models along with a lack of functional trait and productivity data for parameterizing and testing those models. Current productivity models are either extremely complex requiring up to hundreds of parameters, many sub-models, and considerable computational expense or rely on statistical trait-growth relationships that can be hard to extrapolate to new systems or climates. Here we provide a simple alternative: a remote sensing canopy functional model (RS-CFM) that uses remotely-sensed foliar traits and canopy structure data to efficiently map productivity at high-resolution and large spatial scales. We test this model by quantifying net primary productivity (NPP) at 0.01-ha resolution in 30,040 hectares of Peruvian tropical rainforest along a 3,322-m Amazon-to-Andes elevation gradient. Our model predicts local NPP and elevational shifts in NPP much more accurately and in greater detail than a prominent alternative method—NASA’s MODIS NPP product. Furthermore, we show how NPP estimates depend on light competition and identify the appropriate spatial resolution for remote productivity estimation. Our framework opens up possibilities to fully harness remote sensing data and reliably scale up from traits to map regional or global productivity in a more direct, efficient, and cost-effective manner. - Some of the metrics are blocked by yourconsent settings
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, The Influence of Ecosystem and Phylogeny on Tropical Tree Crown Size and Shape(Frontiers Media S.A., 2020-10-09)The sizes and shapes of tree crowns are of fundamental importance in ecology, yet understanding the forces that determine them remains elusive. A cardinal question facing ecologists is the degree to which general and non-specific versus ecological and context-dependent processes are responsible for shaping tree crowns. Here, we test this question for the first time across diverse tropical ecosystems. Using trees from 20 plots varying in elevation, precipitation, and ecosystem type (savanna-forest transitions) across the paleo- and neo-tropics, we test the relationship between crown dimensions and tree size. By analyzing these scaling relationships across environmental gradients, biogeographic regions, and phylogenetic distance, we extend Metabolic Scaling Theory (MST) predictions to include how local selective pressures shape variation in crown dimensions. Across all sites, we find strong agreement between mean trends and MST predictions for the scaling of crown size and shape, but large variation around the mean. While MST explained approximately half of the observed variation in tree crown dimensions, we find that local, ecosystem, and phylogenetic predictors account for the half of the residual variation. Crown scaling does not change significantly across regions, but does change across ecosystem types, where savanna tree crowns grow more quickly with tree girth than forest tree crowns. Crowns of legumes were wider and more voluminous than those of other taxa. Thus, while MST can accurately describe the central tendency of tree crown size, local ecological conditions and evolutionary history appear to modify the scaling of crown shape. Importantly, our extension of MST incorporating these differences accounts for the mechanisms driving variation in the scaling of crown dimensions across the tropics. We present allometric equations for the prediction of crown dimensions across tropical ecosystems. These results are critical when scaling the function of individual trees to larger spatial scales or incorporating the size and shape of tree crowns in global biogeochemical models. - 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, Pantropical modelling of canopy functional traits using Sentinel-2 remote sensing data(Elsevier, 2020-10-14)Tropical forest ecosystems are undergoing rapid transformation as a result of changing environmental conditions and direct human impacts. However, we cannot adequately understand, monitor or simulate tropical ecosystem responses to environmental changes without capturing the high diversity of plant functional characteristics in the species-rich tropics. Failure to do so can oversimplify our understanding of ecosystems responses to environmental disturbances. Innovative methods and data products are needed to track changes in functional trait composition in tropical forest ecosystems through time and space. This study aimed to track key functional traits by coupling Sentinel-2 derived variables with a unique data set of precisely located in-situ measurements of canopy functional traits collected from 2434 individual trees across the tropics using a standardised methodology. The functional traits and vegetation censuses were collected from 47 field plots in the countries of Australia, Brazil, Peru, Gabon, Ghana, and Malaysia, which span the four tropical continents. The spatial positions of individual trees above 10 cm diameter at breast height (DBH) were mapped and their canopy size and shape recorded. Using geo-located tree canopy size and shape data, community-level trait values were estimated at the same spatial resolution as Sentinel-2 imagery (i.e. 10 m pixels). We then used the Geographic Random Forest (GRF) to model and predict functional traits across our plots. We demonstrate that key plant functional traits can be accurately predicted across the tropicsusing the high spatial and spectral resolution of Sentinel-2 imagery in conjunction with climatic and soil information. Image textural parameters were found to be key components of remote sensing information for predicting functional traits across tropical forests and woody savannas. Leaf thickness (R2 = 0.52) obtained the highest prediction accuracy among the morphological and structural traits and leaf carbon content (R2 = 0.70) and maximum rates of photosynthesis (R2 = 0.67) obtained the highest prediction accuracy for leaf chemistry and photosynthesis related traits, respectively. Overall, the highest prediction accuracy was obtained for leaf chemistry and photosynthetic traits in comparison to morphological and structural traits. Our approach offers new opportunities for mapping, monitoring and understanding biodiversity and ecosystem change in the most species-rich ecosystems on Earth. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evolutionary heritage shapes tree distributions along an Amazon‐to‐Andes elevation gradient(Wiley, 2020-10-06)Understanding how evolutionary constraints shape the elevational distributions of tree lineages provides valuable insight into the future of tropical montane forests under global change. With narrow elevational ranges, high taxonomic turnover, frequent habitat specialization, and exceptional levels of endemism, tropical montane forests and trees are predicted to be highly sensitive to environmental change. Using plot census data from a gradient traversing > 3,000 m in elevation on the Amazonian flank of the Peruvian Andes, we employ phylogenetic approaches to assess the influence of evolutionary heritage on distribution trends of trees at the genus‐level. We find that closely related lineages tend to occur at similar mean elevations, with sister genera pairs occurring a mean 254 m in elevation closer to each other than the mean elevational difference between non‐sister genera pairs. We also demonstrate phylogenetic clustering both above and below 1,750 m a.s.l, corresponding roughly to the cloud‐base ecotone. Belying these general trends, some lineages occur across many different elevations. However, these highly plastic lineages are not phylogenetically clustered. Overall, our findings suggest that tropical montane forests are home to unique tree lineage diversity, constrained by their evolutionary heritage and vulnerable to substantial losses under environmental changes, such as rising temperatures or an upward shift of the cloud‐base. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evolutionary diversity peaks at mid-elevations along an Amazon-to-Andes elevation gradient(Frontiers Media S.A., 2021-08-24)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. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The evolutionary assembly of forest communities along environmental gradients: recent diversification or sorting of pre-adapted clades?(John Wiley and Sons Inc, 2021-12-01)Recent studies have demonstrated that ecological processes that shape community structure and dynamics change along environmental gradients. However, much less is known about how the emergence of the gradients themselves shape the evolution of species that underlie community assembly. In this study, we address how the creation of novel environments leads to community assembly via two nonmutually exclusive processes: immigration and ecological sorting of pre-adapted clades (ISPC), and 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 tree communities across elevations.1 - 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.