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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.
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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.
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The Influence of Taxonomy and Environment on Leaf Trait Variation Along Tropical Abiotic Gradients
(Frontiers Media S.A., 2020-03-03)
Deconstructing functional trait variation and co-variation across a wide range of environmental conditions should increase the mechanistic understanding of community assembly processes and improve current parameterization of dynamic vegetation models. Here, we present a study that deconstructs leaf trait variation and co-variation to iithin-species, taxonomic-interspecific, and plot-environment components comparing three tropical environmental gradients in Peru, Brazil and Ghana. We measured photosynthetic, chemical and structural leaf traits using a standardized sampling protocol, totalling more than 1,000 individuals belonging to 367 species sampled. Variation associated with the whole interspecific taxonomic component (species+genus+family) for most traits was relatively consistent across environmental gradients, but intra-specificwithin-species variation and the plot-environment variation was strongly dependent on the environmental gradient. Trait-trait co-variation was also strongly linked to the environmental gradient where the traits were measured, although some traits had consistent co-variation components irrespective of environmental gradient. Our results demonstrate that filtering along gradients is mostly expressed through trait intra- and interspecifictaxonomic variation, but that trait co-variation is strongly dependent on the local environment, and thus global trait co-variation relationships might not always apply at smaller scales.
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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.
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Changes in oak (Quercus robur) photosynthesis after winter moth (Operophtera brumata) herbivory are not explained by changes in chemical or structural leaf traits
(Public Library of Science, 2020-01-01)
Insect herbivores have the potential to change both physical and chemical traits of their host plant. Although the impacts of herbivores on their hosts have been widely studied, experiments assessing changes in multiple leaf traits or functions simultaneously are still rare. We experimentally tested whether herbivory by winter moth (Operophtera brumata) caterpillars and mechanical leaf wounding changed leaf mass per area, leaf area, leaf carbon and nitrogen content, and the concentrations of 27 polyphenol compounds on oak (Quercus robur) leaves. To investigate how potential changes in the studied traits affect leaf functioning, we related the traits to the rates of leaf photosynthesis and respiration. Overall, we did not detect any clear effects of herbivory or mechanical leaf damage on the chemical or physical leaf traits, despite clear effect of herbivory on photosynthesis. Rather, the trait variation was primarily driven by variation between individual trees. Only leaf nitrogen content and a subset of the studied polyphenol compounds correlated with photosynthesis and leaf respiration. Our results suggest that in our study system, abiotic conditions related to the growth location, variation between tree individuals, and seasonal trends in plant physiology are more important than herbivory in determining the distribution and composition of leaf chemical and structural traits.
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Covariance of Sun and Shade Leaf Traits Along a Tropical Forest Elevation Gradient
(Frontiers Media S.A., 2020-01-31)
Foliar trait adaptation to sun and shade has been extensively studied in the context of photosynthetic performance of plants, focusing on nitrogen allocation, light capture and use via chlorophyll pigments and leaf morphology; however, less is known about the potential sun-shade dichotomy of other functionally important foliar traits. In this study, we measured 19 traits in paired sun and shade leaves along a 3,500-m elevation gradient in southern Peru to test whether the traits differ with canopy position, and to assess if relative differences vary with species composition and/or environmental filters. We found significant sun-shade differences in leaf mass per area (LMA), photosynthetic pigments (Chl ab and Car), and δ13C. Sun-shade offsets among these traits remained constant with elevation, soil substrates, and species compositional changes. However, other foliar traits related to structure and chemical defense, and those defining general metabolic processes, did not differ with canopy position. Our results suggest that whole-canopy function is captured in many traits of sun leaves; however, photosynthesis-related traits must be scaled based on canopy light extinction. These findings show that top-of-canopy measurements of foliar chemistry from spectral remote sensing approaches map directly to whole-canopy foliar traits including shaded leaves that cannot be directly observed from above.
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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.
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The multiple viewpoints for the Amazon: geographic limits and meanings
(2021-09-20)
The geographic term “Amazon” describes several distinct but overlapping hydrological, geological, biological, and geopolitical entities located in northern South America (Albert et al. 2018). It is therefore useful to distinguish the Amazon as a drainage basin, a sedimentary basin, a biodiversity province, and a geopolitical unit. This report describes the multiple boundaries and definitions of the geographical area called "the Amazon".
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The Global Ecosystems Monitoring network: monitoring ecosystem productivity and carbon cycling across the tropics
(Elsevier, 2021-01-01)
A rich understanding of the productivity, carbon and nutrient cycling of terrestrial ecosystems is essential in the context of understanding, modelling and managing the future response of the biosphere to global change. This need is particularly acute in tropical ecosystems, home to over 60% of global terrestrial productivity, over half of planetary biodiversity, and hotspots of anthropogenic pressure. In recent years there has been a surge of activity in collecting data on the carbon cycle, productivity, and plant functional traits of tropical ecosystems, most intensively through the Global Ecosystems Monitoring network (GEM). The GEM approach provides valuable insights by linking field-based ecosystem ecology with the needs of Earth system science. In this paper, we review and synthesize the context, history and recent scientific output from the GEM network. Key insights have emerged on the spatial and temporal variability of ecosystem productivity and on the role of temperature and drought stress on ecosystem function and resilience. New work across the network is now linking carbon cycling to nutrient cycling and plant functional traits, and subsequently to airborne remote sensing. We discuss some of the novel emerging patterns and practical and methodological challenges of this approach, and examine current and possible future directions, both within this network and as lessons for a more general terrestrial ecosystem observation scheme.
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Variation of non-structural carbohydrates across the fast-slow continuum in Amazon forest canopy trees
(Wiley, 2021-11-20)
Tropical tree species span a range of life‐history strategies within a fast–slow continuum. The position of a species within this continuum is thought to reflect a negative relationship between growth and storage, with fast‐growing species allocating more carbon to growth and slow‐growing species investing more in storage. For tropical species, the relationship between storage and life‐history strategies has been largely studied on seedlings and less so in adult trees. We evaluated how stored non‐structural carbohydrates (NSC) vary across adult trees spanning the fast–slow continuum in the Peruvian Amazon by: (a) analysing whole‐tree NSC in two species of contrasting growth and (b) investigating the relationships with key life‐history traits across a broader set of species. Our results are consistent with a growth–storage trade‐off. The analysis of whole‐tree NSC revealed that the slow‐growing Eschweilera coriacea stored about 2.7 times as much NSC as the fast‐growing Bixa arborea due to markedly higher storage in woody stems and roots. B. arborea also had higher seasonality in NSC, reflecting its strong seasonality in stem growth. Across a range of species, stem starch was negatively related to species growth rate and positively related to wood density. Given the role of NSC in mediating plants' response to stress, our results suggest that slow‐growing species with greater storage reserves may be more resilient to drought than fast‐growing species.

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