ABSTRACT. In the Río de la Plata grasslands (RPG) biogeographical region of South America, agricultural activities have undergone important changes during the last 15-18 years because of technological improvements and new national and international market conditions. We characterized changes in the landscape structure between 1985-1989 and 2002-2004 for eight pilot areas distributed across the main regional environmental gradients. These areas incorporated approximately 35% of the 7.5 × 10 5 km² of the system. Our approach involved the generation of land-use and land cover maps, the analysis of landscape metrics, and the computation of annual transition probabilities between land cover types. All of the information was summarized in 3383 cells of 8 × 8 km. The area covered by grassland decreased from 67.4 to 61.4% between the study periods. This decrease was associated with an increase in the area of annual crops, mainly soybean, sunflower, wheat, and maize. In some subunits of the RPG, i.e., Flat Inland Pampa, the grassland-to-cropland transition probability was high (p G→C = 3.7 × 10 −2 ), whereas in others, i.e., Flooding Pampa, this transition probability was low (p G→C = 6.7 × 10 −3 ). Our description of the magnitude, direction, and spatial distribution of land-use and land cover changes provides a basis from which to develop spatially explicit scenarios of land cover change.

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conclusions E. granulosus s. s. (G1) accounts for most of the global burden followed by E. canadensis (G6 and G7) in South America and worldwide. This information should be taken into account to suit local cystic echinococcosis control and prevention programmes according to each molecular epidemiological situation.

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In the last decades, South American ecosystems underwent important functional modifications due to climate alterations and direct human intervention on land use and land cover. Among remotely sensed data sets, NOAA-AVHRR “Normalized Difference Vegetation Index” (NDVI) represents one of the most powerful tools to evaluate these changes thanks to their extended temporal coverage. In this paper we explored the possibilities and limitations of three commonly used NOAA-AVHRR NDVI series (PAL, GIMMS and FASIR) to detect ecosystem functional changes in the South American continent. We performed pixel-based linear regressions for four NDVI variables (average annual, maximum annual, minimum annual and intra-annual coefficient of variation) for the 1982-1999 period and (1) analyzed the convergences and divergences of significant multi-annual trends identified across all series, (2) explored the degree of aggregation of the trends using the O-ring statistic, and (3) evaluated observed trends using independent information on ecosystem functional changes in five focal regions. Several differences arose in terms of the patterns of change (the sign, localization and total number of pixels with changes). FASIR presented the highest proportion of changing pixels (32.7%) and GIMMS the lowest (16.2%). PAL and FASIR data sets showed the highest agreement, with a convergence of detected trends on 71.2% of the pixels. Even though positive and negative changes showed substantial spatial aggregation, important differences in the scale of aggregation emerged among the series, with GIMMS showing the smaller scale (≤11 pixels). The independent evaluations suggest higher accuracy in the detection of ecosystem changes among PAL and FASIR series than with GIMMS, as they detected trends that match expected shifts. In fact, this last series eliminated most of the long term patterns over the continent. For example, in the “Eastern Paraguay” and “Uruguay River margins” focal regions, the extensive changes due to land use and land cover change expansion were detected by PAL and FASIR, but completely ignored by GIMMS. Although the technical explanation of the differences remains unclear and needs further exploration, we found that the evaluation of this type of remote sensing tools should not only be focused at the level of assumptions (i.e. physical or mathematical aspects of image processing), but also at the level of results (i.e. contrasting observed patterns with independent proofs of change). We finally present the online collaborative initiative “Land ecosystem change utility for South America”, which facilitates this type of evaluations and helps to identify the most important functional changes of the continent.

Abstract. Few field studies examine greenhouse gas (GHG) emissions from African agricultural systems, resulting in high uncertainty for national inventories. This lack of data is particularly noticeable in smallholder farms in sub-Saharan Africa, where low inputs are often correlated with low yields, often resulting in food insecurity as well. We provide the most comprehensive study in Africa to date, examining annual soil CO2, CH4 and N2O emissions from 59 smallholder plots across different vegetation types, field types and land classes in western Kenya. The study area consists of a lowland area (approximately 1200 m a.s.l.) rising approximately 600 m to a highland plateau. Cumulative annual fluxes ranged from 2.8 to 15.0 Mg CO2-C ha−1, −6.0 to 2.4 kg CH4-C ha−1 and −0.1 to 1.8 kg N2O-N ha−1. Management intensity of the plots did not result in differences in annual GHG fluxes measured (P = 0.46, 0.14 and 0.67 for CO2, CH4 and N2O respectively). The similar emissions were likely related to low fertilizer input rates (≤ 20 kg N ha−1). Grazing plots had the highest CO2 fluxes (P = 0.005), treed plots (plantations) were a larger CH4 sink than grazing plots (P = 0.05), while soil N2O emissions were similar across vegetation types (P = 0.59). This study is likely representative for low fertilizer input, smallholder systems across sub-Saharan Africa, providing critical data for estimating regional or continental GHG inventories. Low crop yields, likely due to low fertilization inputs, resulted in high (up to 67 g N2O-N kg−1 aboveground N uptake) yield-scaled emissions. Improvement of crop production through better water and nutrient management might therefore be an important tool in increasing food security in the region while reducing the climate footprint per unit of food produced.

The Gran Chaco harbors high biodiversity, including many endemic species (3, 6, 7). This region is also a global deforestation hotspot (8) due to the recently accelerated expansion of cattle ranching and soybean cultivation there (9, 10). Given the agricultural potential of the region and the growing global demands for agricultural products, the pressure to convert additional natural ecosystems into agricultural land remains very high. Yet, only 9% of the Gran Chaco is currently protected (6). For these reasons, the Gran Chaco is one of the most threatened ecoregions worldwide. Various definitions of dry forests exist, but the Gran Chaco should not be neglected when raising awareness to the urgent conservation needs in the often forgotten neotropical dry forests.