Raul Tupayachi

Elevated rates of gold mining in the Amazon revealed through high-resolution monitoring

Significance Commodity gold prices increased substantially following the 2008 global financial crisis. Gold demand has fueled a massive increase in mining activity, some of which is centered in the Amazon basin. Western Amazonian forests of Peru have become an epicenter for mostly illegal gold mining, but the clandestine nature of mining activities has made monitoring and reporting of forest losses extremely challenging. We combined high-resolution satellite and aircraft-based imaging with field surveys to address this issue in one of the highest biodiversity regions on Earth: Madre de Dios, Peru. We found the gold mining extent and rates are far higher than previously reported, with critically important implications for the ecology and environmental policy of this unique tropical rainforest region. Gold mining has rapidly increased in western Amazonia, but the rates and ecological impacts of mining remain poorly known and potentially underestimated. We combined field surveys, airborne mapping, and high-resolution satellite imaging to assess road- and river-based gold mining in the Madre de Dios region of the Peruvian Amazon from 1999 to 2012. In this period, the geographic extent of gold mining increased 400%. The average annual rate of forest loss as a result of gold mining tripled in 2008 following the global economic recession, closely associated with increased gold prices. Small clandestine operations now comprise more than half of all gold mining activities throughout the region. These rates of gold mining are far higher than previous estimates that were based on traditional satellite mapping techniques. Our results prove that gold mining is growing more rapidly than previously thought, and that high-resolution monitoring approaches are required to accurately quantify human impacts on tropical forests.

Amazonian functional diversity from forest canopy chemical assembly

Significance Canopy trees are keystone organisms that create habitat for an enormous array of flora and fauna and dominate carbon storage in tropical forests. Determining the functional diversity of tree canopies is, therefore, critical to understanding how tropical forests are assembled and predicting ecosystem responses to environmental change. Across the megadiverse Andes-to-Amazon corridor of Peru, we discovered a large-scale nested pattern of canopy chemical assembly among thousands of trees. This nested geographic and phylogenetic pattern within and among forest communities provides a different perspective on current and future alterations to the functioning of western Amazonian forests resulting from land use and climate change. Patterns of tropical forest functional diversity express processes of ecological assembly at multiple geographic scales and aid in predicting ecological responses to environmental change. Tree canopy chemistry underpins forest functional diversity, but the interactive role of phylogeny and environment in determining the chemical traits of tropical trees is poorly known. Collecting and analyzing foliage in 2,420 canopy tree species across 19 forests in the western Amazon, we discovered (i) systematic, community-scale shifts in average canopy chemical traits along gradients of elevation and soil fertility; (ii) strong phylogenetic partitioning of structural and defense chemicals within communities independent of variation in environmental conditions; and (iii) strong environmental control on foliar phosphorus and calcium, the two rock-derived elements limiting CO2 uptake in tropical forests. These findings indicate that the chemical diversity of western Amazonian forests occurs in a regionally nested mosaic driven by long-term chemical trait adjustment of communities to large-scale environmental filters, particularly soils and climate, and is supported by phylogenetic divergence of traits essential to foliar survival under varying environmental conditions. Geographically nested patterns of forest canopy chemical traits will play a role in determining the response and functional rearrangement of western Amazonian ecosystems to changing land use and climate.

Taxonomy and remote sensing of leaf mass per area (LMA) in humid tropical forests

Leaf mass per area (LMA) is a trait of central importance to plant physiology and ecosystem function, but LMA patterns in the upper canopies of humid tropical forests have proved elusive due to tall species and high diversity. We collected top-of-canopy leaf samples from 2873 individuals in 57 sites spread across the Neotropics, Australasia, and Caribbean and Pacific Islands to quantify environmental and taxonomic drivers of LMA variation, and to advance remote-sensing measures of LMA. We uncovered strong taxonomic organization of LMA, with species accounting for 70% of the global variance and up to 62% of the variation within a forest stand. Climate, growth habit, and site conditions are secondary contributors (1-23%) to the observed LMA patterns. Intraspecific variation in LMA averages 16%, which is a fraction of the variation observed between species. We then used spectroscopic remote sensing (400-2500 nm) to estimate LMA with an absolute uncertainty of 14-15 g/m2 (r2 = 0.85), or approximately 10% of the global mean. With radiative transfer modeling, we demonstrated the scalability of spectroscopic remote sensing of LMA to the canopy level. Our study indicates that remotely sensed patterns of LMA will be driven by taxonomic variation against a backdrop of environmental controls expressed at site and regional levels.

Targeted carbon conservation at national scales with high-resolution monitoring

Significance Land use is a principal driver of carbon emissions, either directly through land change processes such as deforestation or indirectly via transportation and industries supporting natural resource use. To minimize the effects of land use on the climate system, natural ecosystems are needed to offset gross emissions through carbon sequestration. Managing this critically important service must be achieved tactically if it is to be cost-effective. We have developed a high-resolution carbon mapping approach that can identify biogeographically explicit targets for carbon storage enhancement among all landholders within a country. Applying our approach to Perú reveals carbon threats and protections, as well as major opportunities for using ecosystems to sequester carbon. Our approach is scalable to any tropical forest country. Terrestrial carbon conservation can provide critical environmental, social, and climate benefits. Yet, the geographically complex mosaic of threats to, and opportunities for, conserving carbon in landscapes remain largely unresolved at national scales. Using a new high-resolution carbon mapping approach applied to Perú, a megadiverse country undergoing rapid land use change, we found that at least 0.8 Pg of aboveground carbon stocks are at imminent risk of emission from land use activities. Map-based information on the natural controls over carbon density, as well as current ecosystem threats and protections, revealed three biogeographically explicit strategies that fully offset forthcoming land-use emissions. High-resolution carbon mapping affords targeted interventions to reduce greenhouse gas emissions in rapidly developing tropical nations.

Amazonian landscapes and the bias in field studies of forest structure and biomass

Significance Although tropical forests absorb more carbon dioxide as biomass than any other terrestrial ecosystem, biomass estimates disagree substantially at landscape-to-regional scales. Current biomass maps rely upon field plots for extrapolations to larger scales, yet whether field plots accurately represent landscape-scale variables has not been assessed. To our knowledge, this is the first study to compare forest structural variables and aboveground biomass derived from field plots to those derived from their host landscapes using airborne 3D remote sensing. We found that typical field plots can produce substantially biased estimates and the number of plots needed to reduce this bias is impractical, positioning airborne remote sensing as a core tool for mapping forest structure and biomass across tropical landscapes. Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9–98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy.

Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation

Airborne spectroscopy for forest traits The development of conservation priorities in the tropics is often hampered by the sparseness of ground data on biological diversity and the relative crudeness of larger-scale remote sensing data. Asner et al. developed airborne instrumentation to make large-scale maps of forest functional diversity across 72 million hectares of the Peruvian Andes and Amazon basin (see the Perspective by Kapos). They generated a suite of forest canopy functional trait maps from laser-guided imaging spectroscopy and used them to define distinct forest functional classes. These were then compared with government deforestation and land allocation data, which enabled an analysis of conservation threats and opportunities across the region. Science, this issue p. 385; see also p. 347 Large-scale mapping of tropical forest trait diversity offers an approach for conservation. Functional biogeography may bridge a gap between field-based biodiversity information and satellite-based Earth system studies, thereby supporting conservation plans to protect more species and their contributions to ecosystem functioning. We used airborne laser-guided imaging spectroscopy with environmental modeling to derive large-scale, multivariate forest canopy functional trait maps of the Peruvian Andes-to-Amazon biodiversity hotspot. Seven mapped canopy traits revealed functional variation in a geospatial pattern explained by geology, topography, hydrology, and climate. Clustering of canopy traits yielded a map of forest beta functional diversity for land-use analysis. Up to 53% of each mapped, functionally distinct forest presents an opportunity for new conservation action. Mapping functional diversity advances our understanding of the biosphere to conserve more biodiversity in the face of land use and climate change.

Functional and biological diversity of foliar spectra in tree canopies throughout the Andes to Amazon region

Spectral properties of foliage express fundamental chemical interactions of canopies with solar radiation. However, the degree to which leaf spectra track chemical traits across environmental gradients in tropical forests is unknown. We analyzed leaf reflectance and transmittance spectra in 2567 tropical canopy trees comprising 1449 species in 17 forests along a 3400-m elevation and soil fertility gradient from the Amazonian lowlands to the Andean treeline. We developed quantitative links between 21 leaf traits and 400-2500-nm spectra, and developed classifications of tree taxa based on spectral traits. Our results reveal enormous inter-specific variation in spectral and chemical traits among canopy trees of the western Amazon. Chemical traits mediating primary production were tightly linked to elevational changes in foliar spectral signatures. By contrast, defense compounds and rock-derived nutrients tracked foliar spectral variation with changing soil fertility in the lowlands. Despite the effects of abiotic filtering on mean foliar spectral properties of tree communities, the spectra were dominated by phylogeny within any given community, and spectroscopy accurately classified 85-93% of Amazonian tree species. Our findings quantify how tropical tree canopies interact with sunlight, and indicate how to measure the functional and biological diversity of forests with spectroscopy.

Scale dependence of canopy trait distributions along a tropical forest elevation gradient

Average responses of forest foliar traits to elevation are well understood, but far less is known about trait distributional responses to elevation at multiple ecological scales. This limits our understanding of the ecological scales at which trait variation occurs in response to environmental drivers and change. We analyzed and compared multiple canopy foliar trait distributions using field sampling and airborne imaging spectroscopy along an Andes-to-Amazon elevation gradient. Field-estimated traits were generated from three community-weighting methods, and remotely sensed estimates of traits were made at three scales defined by sampling grain size and ecological extent. Field and remote sensing approaches revealed increases in average leaf mass per unit area (LMA), water, nonstructural carbohydrates (NSCs) and polyphenols with increasing elevation. Foliar nutrients and photosynthetic pigments displayed little to no elevation trend. Sample weighting approaches had little impact on field-estimated trait responses to elevation. Plot representativeness of trait distributions at landscape scales decreased with increasing elevation. Remote sensing indicated elevation-dependent increases in trait variance and distributional skew. Multiscale invariance of LMA, leaf water and NSC mark these traits as candidates for tracking forest responses to changing climate. Trait-based ecological studies can be greatly enhanced with multiscale studies made possible by imaging spectroscopy.

Seasonal Variation in Spectral Signatures of Five Genera of Rainforest Trees

Recent technological and methodological advances in the field of imaging spectroscopy (or hyperspectral imaging) make possible new approaches to studying regional ecosystem processes and structure. We use Earth Observing-1 Hyperion satellite hyperspectral imagery to test our ability to identify tree species in a lowland Peruvian Amazon forest, and to investigate seasonal variation in species detections related to phenology. We obtained four images from 2006-2008, and used them to spectrally differentiate crowns of 42 individual trees of 5 taxa using linear discriminant analysis. Temporal variation of tree spectra was assessed using three methods, based on 1) position of spectra in a two-dimensional canonical variable space, 2) a broadband, multispectral dataset derived from sets of narrow bands identified as informative to spectrally separate taxa, and 3) narrow band vegetation indices (photochemical reflectance index and anthocyanin reflectance index) sensitive to leaf pigments. We obtained high classification success with a reduced set of trees (28 individuals) whose crowns were well represented on Hyperion 30 m resolution pixels. Temporal variability of spectra was confirmed by each of the three methods employed. Understanding seasonality of spectral characteristics of tropical tree crowns has implications in spectral based multi-seasonal species mapping and studying ecosystem processes.

Regional-scale drivers of forest structure and function in northwestern Amazonia.

Field studies in Amazonia have found a relationship at continental scales between soil fertility and broad trends in forest structure and function. Little is known at regional scales, however, about how discrete patterns in forest structure or functional attributes map onto underlying edaphic or geological patterns. We collected airborne LiDAR (Light Detection and Ranging) data and VSWIR (Visible to Shortwave Infrared) imaging spectroscopy measurements over 600 km2 of northwestern Amazonian lowland forests. We also established 83 inventories of plant species composition and soil properties, distributed between two widespread geological formations. Using these data, we mapped forest structure and canopy reflectance, and compared them to patterns in plant species composition, soils, and underlying geology. We found that variations in soils and species composition explained up to 70% of variation in canopy height, and corresponded to profound changes in forest vertical profiles. We further found that soils and plant species composition explained more than 90% of the variation in canopy reflectance as measured by imaging spectroscopy, indicating edaphic and compositional control of canopy chemical properties. We last found that soils explained between 30% and 70% of the variation in gap frequency in these forests, depending on the height threshold used to define gaps. Our findings indicate that a relatively small number of edaphic and compositional variables, corresponding to underlying geology, may be responsible for variations in canopy structure and chemistry over large expanses of Amazonian forest.