Marc K. Steininger

Remote sensing for biodiversity science and conservation

Remote-sensing systems typically produce imagery that averages information over tens or even hundreds of square meters – far too coarse to detect most organisms – so the remote sensing of biodiversity would appear to be a fool’s errand. However, advances in the spatial and spectral resolutions of sensors now available to ecologists are making the direct remote sensing of certain aspects of biodiversity increasingly feasible; for example, distinguishing species assemblages or even identifying species of individual trees. In cases where direct detection of individual organisms or assemblages is still beyond our grasp, indirect approaches offer valuable information about diversity patterns. Such approaches derive meaningful environmental parameters from biophysical characteristics that

Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data

Forest cover is an important input variable for assessing changes to carbon stocks, climate and hydrological systems, biodiversity richness, and other sustainability science disciplines. Despite incremental improvements in our ability to quantify rates of forest clearing, there is still no definitive understanding on global trends. Without timely and accurate forest monitoring methods, policy responses will be uninformed concerning the most basic facts of forest cover change. Results of a feasible and cost-effective monitoring strategy are presented that enable timely, precise, and internally consistent estimates of forest clearing within the humid tropics. A probability-based sampling approach that synergistically employs low and high spatial resolution satellite datasets was used to quantify humid tropical forest clearing from 2000 to 2005. Forest clearing is estimated to be 1.39% (SE 0.084%) of the total biome area. This translates to an estimated forest area cleared of 27.2 million hectares (SE 2.28 million hectares), and represents a 2.36% reduction in area of humid tropical forest. Fifty-five percent of total biome clearing occurs within only 6% of the biome area, emphasizing the presence of forest clearing “hotspots.” Forest loss in Brazil accounts for 47.8% of total biome clearing, nearly four times that of the next highest country, Indonesia, which accounts for 12.8%. Over three-fifths of clearing occurs in Latin America and over one-third in Asia. Africa contributes 5.4% to the estimated loss of humid tropical forest cover, reflecting the absence of current agro-industrial scale clearing in humid tropical Africa.

Tropical deforestation in the Bolivian Amazon

The distributions of forest and deforestation throughout the tropics are poorly known despite their importance to regional biodiversity and global climate and biodiversity. Deforestation estimates based on surveys or sampling have large errors, and high-resolution, wall-to-wall mapping of tropical forests is necessary to assess the impacts of fragmentation. Landsat satellite images from the mid-1980s and early 1990s were thus used to map closed-canopy tropical forest extent and anthropogenic deforestation in an approximately 700 000 km 2 area of Amazonian Bolivia with precipitation >1000 mm yr −1 . Total potential forest cover extent, including tropical deciduous forest, was 448 700 km 2 , while the area of natural non-forest formations was 245 100 km 2 . The area deforested was 15 500 km 2 in the mid-1980s and 24 700 km 2 by the early 1990s. The rate of tropical deforestation in the forest zone of Bolivia with >1000 mm yr −1 precipitation below 1500 m elevation and north of 19° S, was 1529 km 2 yr −1 from 1985–1986 to 1992–1994. Our estimates of deforestation are significantly lower than those reported by the Food and Agriculture Organization of the United Nations (FAO). We document a spatially-concentrated ‘deforestation zone’ in Santa Cruz where >60% of the Bolivian deforestation has occurred. These results indicate that the rate of deforestation in Bolivia has been rapid despite a relatively small human population, and, as in Brazil, clearance has concentrated in the more deciduous forests.

Biomass resilience of Neotropical secondary forests

Land-use change occurs nowhere more rapidly than in the tropics, where the imbalance between deforestation and forest regrowth has large consequences for the global carbon cycle. However, considerable uncertainty remains about the rate of biomass recovery in secondary forests, and how these rates are influenced by climate, landscape, and prior land use. Here we analyse aboveground biomass recovery during secondary succession in 45 forest sites and about 1,500 forest plots covering the major environmental gradients in the Neotropics. The studied secondary forests are highly productive and resilient. Aboveground biomass recovery after 20 years was on average 122 megagrams per hectare (Mg ha−1), corresponding to a net carbon uptake of 3.05 Mg C ha−1 yr−1, 11 times the uptake rate of old-growth forests. Aboveground biomass stocks took a median time of 66 years to recover to 90% of old-growth values. Aboveground biomass recovery after 20 years varied 11.3-fold (from 20 to 225 Mg ha−1) across sites, and this recovery increased with water availability (higher local rainfall and lower climatic water deficit). We present a biomass recovery map of Latin America, which illustrates geographical and climatic variation in carbon sequestration potential during forest regrowth. The map will support policies to minimize forest loss in areas where biomass resilience is naturally low (such as seasonally dry forest regions) and promote forest regeneration and restoration in humid tropical lowland areas with high biomass resilience.

NET PRIMARY PRODUCTION OF U.S. MIDWEST CROPLANDS FROM AGRICULTURAL HARVEST YIELD DATA

We studied crop harvested yield, as recorded in national agricultural statistics, to estimate net primary production (NPP) in agricultural regions where most of the land area is sown with a few, well-studied crops. We estimated the magnitudes and interannual variations in NPP in croplands in the U.S. Midwest using crop area and yield data obtained from the U.S. National Agricultural Statistics Service (NASS). Total NPP, including estimates of the above- and belowground components, was calculated from harvested-yield data by (1) conversion from reporting units of yield of the crop product (usually in volume) to mass, (2) conversion from fresh mass to dry mass, (3) estimation of aboveground yield using crop harvest indices, defined as the ratio of economic product (e.g., grain) dry mass to plant aboveground dry mass, and (4) estimation of belowground yield as a function of aboveground biomass. This approach is applied to corn, soybean, sorghum, sunflower, oats, barley, wheat, and hay in Illinois, Indiana, I...

Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites

Aim The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Remote sensing (RS) is currently the key tool for this purpose, but RS does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset. Location Tropical forests of the Amazon basin. The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/2014_1 Methods Two recent pantropical RS maps of vegetation carbon are compared to a unique ground-plot dataset, involving tree measurements in 413 large inventory plots located in nine countries. The RS maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons. Results The two RS carbon maps fail to capture the main gradient in Amazon forest carbon detected using 413 ground plots, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%. Main conclusions Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.

Reference scenarios for deforestation and forest degradation in support of REDD: a review of data and methods

Global climate policy initiatives are now being proposed to compensate tropical forest nations for reducing carbon emissions from deforestation and forest degradation (REDD). These proposals have the potential to include developing countries more actively in international greenhouse gas mitigation and to address a substantial share of the worlds emissions which come from tropical deforestation. For such a policy to be viable it must have a credible benchmark against which emissions reduction can be calculated. This benchmark, sometimes termed a baseline or reference emissions scenario, can be based directly on historical emissions or can use historical emissions as input for business as usual projections. Here, we review existing data and methods that could be used to measure historical deforestation and forest degradation reference scenarios including FAO (Food and Agricultural Organization of the United Nations) national statistics and various remote sensing sources. The freely available and corrected global Landsat imagery for 1990, 2000 and soon to come for 2005 may be the best primary data source for most developing countries with other coarser resolution high frequency or radar data as a valuable complement for addressing problems with cloud cover and for distinguishing larger scale degradation. While sampling of imagery has been effectively useful for pan-tropical and continental estimates of deforestation, wall-to-wall (or full coverage) allows more detailed assessments for measuring national-level reference emissions. It is possible to measure historical deforestation with sufficient certainty for determining reference emissions, but there must be continued calls at the international level for making high-resolution imagery available, and for financial and technical assistance to help countries determine credible reference scenarios. The data available for past years may not be sufficient for assessing all forms of forest degradation, but new data sources will have greater potential in 2007 and after. This paper focuses only on the methods for measuring changes in forest area, but this information must be coupled with estimates of change in forest carbon stocks in order to quantify emissions from deforestation and forest degradation.

Subpixel forest cover in central Africa from multisensor, multitemporal data☆

Abstract Seven Landsat Multispectral Scanner (MSS) scenes in central Africa were coregistered with 8 km resolution data from the 1987 AVHRR Pathfinder Land data set. Percent forest cover in each 8 km grid cell was derived from the classified MSS scenes. Linear relationships between percent forest cover and 30 multitemporal metrics derived from all AVHRR optical and thermal channels were determined. Correlations were strongest for the mean annual normalized difference vegetation index (NDVI) and mean annual brightness temperature (AVHRR Channel 3) and weakest for those metrics, besides NDVI, based on near-infrared reflectances (AVHRR Channel 2). The relationships were used to estimate percent forest cover in various locations in the study area using multiple linear regression and regression trees. Overall, the multiple linear regression provided more accurate results. Predicted percent forest cover estimates were within 20% of the “actual” percent forest cover (derived from the MSS data) for approximately 90% of the grid cells. The RMS error for the prediction was 12% forest cover. RMS errors above 18% forest cover were obtained when using AVHRR data from a single month to derive predictive relationships. The results demonstrate that multitemporal data reflecting vegetation phenology can be used to estimate subpixel forest cover at coarse spatial resolutions.

Total Historical Land-Use Change in Eastern Bolivia: Who, Where, When, and How Much?

We documented the history of land-use change and migration in eastern Bolivia in five temporal periods: pre-1976, 1976-1986, 1986-1991, 1991-2001, and 2001-2004. We included all land- cover types located below the natural montane tree line (~3000 m), including forest, savanna, scrubland, seasonal wetland, second-growth forest, pasture, and cropland. The rate of land-use change has increased from approximately 4.7 × 104 ha/yr in the 1960s to > 2.9 × 10 5 ha/yr in the most recent period. Land-use change was quantified for 10 groups within which cultural traditions and production systems are shared, including three nonmechanized indigenous groups, four mechanized farming groups, two cattle ranching groups, and the forest products sector. Mechanized Cruceno farmers and Andean indigenous colonists were responsible for most land-use change in the 1960s and 1970s; deforestation by the latter group increased to twice that by all other groups during 1986-1991, declined in the 1990s, and then increased again in the most recent period. In the last 15 years, land-use change by agro-industrialists specializing in soybean has become important, and cattle ranching based on cultivated pastures has surpassed land use by all other groups. When the rates of change increased for the three indigenous nonmechanized groups, they tended to decrease for the four nonindigenous mechanized groups, and vice versa.

Thirty Years of Land-cover Change in Bolivia

Abstract Land-cover change in eastern lowland Bolivia was documented using Landsat images from five epochs for all landscapes situated below the montane tree line at approximately 3000 m, including humid forest, inundated forest, seasonally dry forest, and cloud forest, as well as scrublands and grasslands. Deforestation in eastern Bolivia in 2004 covered 45 411 km2, representing ∼9% of the original forest cover, with an additional conversion of 9042 km2 of scrub and savanna habitats representing 17% of total historical land-cover change. Annual rates of land-cover change increased from ∼400 km2 y−1 in the 1960s to ∼2900 km2 y−1 in the last epoch spanning 2001 to 2004. This study provides Bolivia with a spatially explicit information resource to monitor future land-cover change, a prerequisite for proposed mechanisms to compensate countries for reducing carbon emissions as a result of deforestation. A comparison of the most recent epoch with previous periods shows that policies enacted in the late 1990s to promote forest conservation had no observable impact on reducing deforestation and that deforestation actually increased in some protected areas. The rate of land-cover change continues to increase linearly nationwide, but is growing faster in the Santa Cruz department because of the expansion of mechanized agriculture and cattle farms.