Joseph Mascaro

Don't judge species on their origins

Conservationists should assess organisms on environmental impact rather than on whether they are natives, argue Mark Davis and 18 other ecologists.

High-resolution forest carbon stocks and emissions in the Amazon

Efforts to mitigate climate change through the Reduced Emissions from Deforestation and Degradation (REDD) depend on mapping and monitoring of tropical forest carbon stocks and emissions over large geographic areas. With a new integrated use of satellite imaging, airborne light detection and ranging, and field plots, we mapped aboveground carbon stocks and emissions at 0.1-ha resolution over 4.3 million ha of the Peruvian Amazon, an area twice that of all forests in Costa Rica, to reveal the determinants of forest carbon density and to demonstrate the feasibility of mapping carbon emissions for REDD. We discovered previously unknown variation in carbon storage at multiple scales based on geologic substrate and forest type. From 1999 to 2009, emissions from land use totaled 1.1% of the standing carbon throughout the region. Forest degradation, such as from selective logging, increased regional carbon emissions by 47% over deforestation alone, and secondary regrowth provided an 18% offset against total gross emissions. Very high-resolution monitoring reduces uncertainty in carbon emissions for REDD programs while uncovering fundamental environmental controls on forest carbon storage and their interactions with land-use change.

Managing the whole landscape: historical, hybrid, and novel ecosystems

The reality confronting ecosystem managers today is one of heterogeneous, rapidly transforming landscapes, particularly in the areas more affected by urban and agricultural development. A landscape management framework that incorporates all systems, across the spectrum of degrees of alteration, provides a fuller set of options for how and when to intervene, uses limited resources more effectively, and increases the chances of achieving management goals. That many ecosystems have departed so substantially from their historical trajectory that they defy conventional restoration is not in dispute. Acknowledging novel ecosystems need not constitute a threat to existing policy and management approaches. Rather, the development of an integrated approach to management interventions can provide options that are in tune with the current reality of rapid ecosystem change.

Novel forests maintain ecosystem processes after the decline of native tree species

The positive relationship between species diversity (richness and evenness) and critical ecosystem functions, such as productivity, carbon storage, and nutrient cycling, is often used to predict the consequences of extinction. At regional scales, however, plant species richness is mostly increasing rather than decreasing because successful plant species introductions far outnumber extinctions. If these regional increases in richness lead to local increases in diversity, a reasonable prediction is that productivity, carbon storage, and nutrient cycling will increase following invasion, yet this prediction has rarely been tested empirically. We tested this prediction in novel forest communities dominated by introduced species (;90% basal area) in lowland Hawaiian rain forests by comparing their functionality to that of native forests. We conducted our comparison along a natural gradient of increasing nitrogen availability, allowing for a more detailed examination of the role of plant functional trait differences (specifically, N2 fixation) in driving possible changes to ecosystem function. Hawaii is emblematic of regional patterns of species change; it has much higher regional plant richness than it did historically, due to .1000 plant species introductions and only ;71 known plant extinctions, resulting in an ;100% increase in richness. At local scales, we found that novel forests had significantly higher tree species richness and higher diversity of dominant tree species. We further found that aboveground biomass, productivity, nutrient turnover (as measured by soil-available and litter-cycled nitrogen and phosphorus), and belowground carbon storage either did not differ significantly or were significantly greater in novel relative to native forests. We found that the addition of introduced N2-fixing tree species on N-limited substrates had the strongest effect on ecosystem function, a pattern found by previous empirical tests. Our results support empirical predictions of the functional effects of diversity, but they also suggest basic ecosystem processes will continue even after dramatic losses of native species diversity if simple functional roles are provided by introduced species. Because large portions of the Earths surface are undergoing similar transitions from native to novel ecosystems, our results are likely to be broadly applicable.

High-fidelity national carbon mapping for resource management and REDD+

BackgroundHigh fidelity carbon mapping has the potential to greatly advance national resource management and to encourage international action toward climate change mitigation. However, carbon inventories based on field plots alone cannot capture the heterogeneity of carbon stocks, and thus remote sensing-assisted approaches are critically important to carbon mapping at regional to global scales. We advanced a high-resolution, national-scale carbon mapping approach applied to the Republic of Panama – one of the first UN REDD + partner countries.ResultsIntegrating measurements of vegetation structure collected by airborne Light Detection and Ranging (LiDAR) with field inventory plots, we report LiDAR-estimated aboveground carbon stock errors of ~10% on any 1-ha land parcel across a wide range of ecological conditions. Critically, this shows that LiDAR provides a highly reliable replacement for inventory plots in areas lacking field data, both in humid tropical forests and among drier tropical vegetation types. We then scale up a systematically aligned LiDAR sampling of Panama using satellite data on topography, rainfall, and vegetation cover to model carbon stocks at 1-ha resolution with estimated average pixel-level uncertainty of 20.5 Mg C ha-1 nationwide.ConclusionsThe national carbon map revealed strong abiotic and human controls over Panamanian carbon stocks, and the new level of detail with estimated uncertainties for every individual hectare in the country sets Panama at the forefront in high-resolution ecosystem management. With this repeatable approach, carbon resource decision-making can be made on a geospatially explicit basis, enhancing human welfare and environmental protection.

High‐resolution carbon mapping on the million‐hectare Island of Hawaii

Current markets and international agreements for reducing emissions from deforestation and forest degradation (REDD) rely on carbon (C) monitoring techniques. Combining field measurements, airborne light detection and ranging (LiDAR)-based observations, and satellite-based imagery, we developed a 30-meter-resolution map of aboveground C density spanning 40 vegetation types found on the million-hectare Island of Hawaii. We estimate a total of 28.3 teragrams of C sequestered in aboveground woody vegetation on the island, which is 56% lower than Intergovernmental Panel on Climate Change estimates that do not resolve C variation at fine spatial scales. The approach reveals fundamental ecological controls over C storage, including climate, introduced species, and land-use change, and provides a fourfold decrease in regional costs of C measurement over field sampling alone.

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.

A Tale of Two “Forests”: Random Forest Machine Learning Aids Tropical Forest Carbon Mapping

Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.

Human and environmental controls over aboveground carbon storage in Madagascar

BackgroundAccurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar.ResultsWe found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67% of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR.ConclusionsHigh-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy.

Lianas in gaps reduce carbon accumulation in a tropical forest

Treefall gaps are the “engines of regeneration” in tropical forests and are loci of high tree recruitment, growth, and carbon accumulation. Gaps, however, are also sites of intense competition between lianas and trees, whereby lianas can dramatically reduce tree carbon uptake and accumulation. Because lianas have relatively low biomass, they may displace far more biomass than they contribute, a hypothesis that has never been tested with the appropriate experiments. We tested this hypothesis with an 8-yr liana removal experiment in central Panama. After 8 years, mean tree biomass accumulation was 180% greater in liana-free treefall gaps compared to control gaps. Lianas themselves contributed only 24% of the tree biomass accumulation they displaced. Scaling to the forest level revealed that lianas in gaps reduced net forest woody biomass accumulation by 8.9% to nearly 18%. Consequently, lianas reduce whole-forest carbon uptake despite their relatively low biomass. This is the first study to demonstrate experimentally that plant–plant competition can result in ecosystem-wide losses in forest carbon, and it has critical implications for recently observed increases in liana density and biomass on tropical forest carbon dynamics.