Amazon forest structure generates diurnal and seasonal variability in light utilization.

The complex three-dimensional (3-D) structure of tropical forests generates a diversity of light environments for canopy and understory trees. Understanding diurnal and seasonal changes in light availability is critical for interpreting measurements of net ecosystem exchange and improving ecosystem models. Here, we used the Discrete Anisotropic Radiative Transfer (DART) model to simulate leaf absorption of photosynthetically active radiation (lAPAR) for an Amazon forest. The 3-D model scene was developed from airborne lidar data, and local measurements of leaf reflectance, aerosols, and PAR were used to model lAPAR under direct and diffuse illumination conditions. Simulated lAPAR under clear-sky and cloudy conditions was corrected for light saturation effects to estimate light utilization, the fraction of lAPAR available for photosynthesis. Although the fraction of incoming PAR absorbed by leaves was consistent throughout the year (0.80?0.82), light utilization varied seasonally (0.67?0.74), with minimum values during the Amazon dry season. Shadowing and light saturation effects moderated potential gains in forest productivity from increasing PAR during dry-season months when the diffuse fraction from clouds and aerosols was low. Comparisons between DART and other models highlighted the role of 3-D forest structure to account for seasonal changes in light utilization. Our findings highlight how directional illumination and forest 3-D structure combine to influence diurnal and seasonal variability in light utilization, independent of further changes in leaf area, leaf age, or environmental controls on canopy photosynthesis. Changing illumination geometry constitutes an alternative biophysical explanation for observed seasonality in Amazon forest productivity without changes in canopy phenology.

Parasite communities of the predatory fish, Acestrorhynchus falcatus and Acestrorhynchus falcirostris, living in sympatry in Brazilian Amazon.

This study investigated the parasite communities of wild Acestrorhynchus falcatus and Acestrorhynchus falcirostris populations living in sympatry in Brazilian Amazon. In these two hosts, a total of 12 parasite species e 1-9 parasite species were found per fish, and 10 of these species are metazoans. Eight species of parasites were common to both host species and four of them exhibited differences in abundance and/or prevalence. Parasite communities of the hosts were taxonomically similar (83%) and composed of both ectoparasites and endoparasites, and characterized by high prevalence and high abundance of endoparasites and an aggregated dispersion pattern. For A. falcirostris, the dominant parasite was Ichthyophthirius multifiliis, and for A. falcatus, it was Piscinoodinium pillulare. Shannon diversity and Berger-Parker dominance were similar for both hosts, while the parasites species richness and evenness showed differences influenced by the ectoparasites species. These two populations of hosts that inhabited the same geographical area had different sizes, but were exposed to the same infective stages, and acquired qualitatively and quantitatively similar endoparasites community, thus indicating that the amounts and types of prey congeneric that they were eating were similar. Therefore, the overlap in the same occurrence area play an important role in the parasite communities to these phylogenetically related hosts.

High spatial resolution land use and land cover mapping of the Brazilian Legal Amazon in 2008 using Landsat-5/TM and MODIS data.

Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation of area occupied by different land use classes. The results showed that the four classes of Pasture covered 62% of the deforested areas of the Brazilian Legal Amazon, followed by Secondary Vegetation with 21%. The area occupied by Annual Agriculture covered less than 5% of deforested areas; the remaining areas were distributed among six other land use classes. The maps generated from this project ? called TerraClass - are available at INPE?s web site (http://www.inpe.br/cra/projetos_pesquisas/terraclass2008.php)

Agriculture and forest: A sustainable strategy in the Brazilian Amazon.

Large-scale agriculture is increasing in anthropogenically modified areas in the Amazon Basin. Crops such as soybean, maize, oil palm, and others are being introduced to supply the world demand for food and energy. However, the current challenge is to enhance the sustainability of these areas by increasing efficiency of production chains and to improve environmental services. The Amazon Basin has experienced a paradigm shift away from the traditional slash-and-burn agricultural practices, which offers decision makers the opportunity to make innovative interventions to enhance the productivity in previously degraded areas by using trees to ecological advantage. This study describes a successful experiment integrating the production of soybean and paricá (Glycine max L. and Schizolobium amazonicum) based on previous research that indicated potential topoclimatic zones for planting paricá in the Brazilian state of Pará. This paper shows that a no-tillage system reduces the effects of drought compared to conventional tillage still used by many farmers in the region. The integrated system was implemented during the 2014/2015 season in 234.6 ha in the high-potential zone in the municipality of Ulianópolis, Pará. Both soybean and paricá were planted simultaneously. Paricá was planted in 5 m x 2 m inter-tree spacing totaling 228x103 trees per hectare and soybean, in 4 m x 100 m spacing, distributed in nine rows with a 0.45 m inter-row distance, occupying 80% of the area. The harvested soybean production was 3.4 t ha-1, higher than other soybean monocultures in eastern Pará. Paricá benefited from soybean fertilization in the first year: It exhibited rapid development in height (3.26 m) and average diameter (3.85 cm). Trees and crop rotation over the following years is six years for forest species and one year for each crop. Our results confirm there are alternatives to the current production systems able to diminish negative impacts resulting from monoculture. In addition, the system provided environmental services such as reduced soil erosion and increased carbon stock by soil cover with no-tillage soybean cultivation. The soybean cover contributes to increased paricá thermal regulation and lower forestry costs. We concluded that innovative interventions are important to show local farmers that it is possible to adapt an agroforest system to large-scale production, thus changing the Amazon.

Spatial scale effects of sampling on the interpolation of species distribution models in the southwestern Amazon.

Knowledge of the geographical distribution of timber tree species in the Amazon is still scarce. This is especially true at the local level, thereby limiting natural resource management actions. Forest inventories are key sources of information on the occurrence of such species. However, areas with approved forest management plans are mostly located near access roads and the main industrial centers. The present study aimed to assess the spatial scale effects of forest inventories used as sources of occurrence data in the interpolation of potential species distribution models. The occurrence data of a group of six forest tree species were divided into four geographical areas during the modeling process. Several sampling schemes were then tested applying the maximum entropy algorithm, using the following predictor variables: elevation, slope, exposure, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). The results revealed that using occurrence data from only one geographical area with unique environmental characteristics increased both model overfitting to input data and omission error rates. The use of a diagonal systematic sampling scheme and lower threshold values led to improved model performance. Forest inventories may be used to predict areas with a high probability of species occurrence, provided they are located in forest management plan regions representative of the environmental range of the model projection area.