Deep soils modify environmental consequences of increased nitrogen fertilizer use in intensifying Amazon agriculture

Agricultural intensification offers potential to grow more food while reducing the conversion of native ecosystems to croplands. However, intensification also risks environmental degradation through emissions of the greenhouse gas nitrous oxide (N2O) and nitrate leaching to ground and surface waters. Intensively-managed croplands and nitrogen (N) fertilizer use are expanding rapidly in tropical regions. We quantified fertilizer responses of maize yield, N2O emissions, and N leaching in an Amazon soybean-maize double-cropping system on deep, highly-weathered soils in Mato Grosso, Brazil. Application of N fertilizer above 80 kg N ha−1 yr−1 increased maize yield and N2O emissions only slightly. Unlike experiences in temperate regions, leached nitrate accumulated in deep soils with increased fertilizer and conversion to cropping at N fertilization rates \u3e80 kg N ha−1, which exceeded maize demand. This raises new questions about the capacity of tropical agricultural soils to store nitrogen, which may determine when and how much nitrogen impacts surface waters

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Amazonia Camtrap: a data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest.

Abstract : The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scatteredacross the published, peer-reviewed, and gray literature and in unpublishedraw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazonregions to compile the most extensive data set of inventories of mammal,bird, and reptile species ever assembled for the area. The complete data setcomprises 154,123 records of 317 species (185 birds, 119 mammals, and13 reptiles) gathered from surveys from the Amazonian portion of eightcountries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru,Suriname, and Venezuela). The most frequently recorded species per taxawere: mammals:Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles:Tupinambis teguixin(716 records). The infor-mation detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a moreaccurate evaluation of the effects of habitat loss, fragmentation, climatechange, and other human-mediated defaunation processes in one of themost important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when usingits data in publications and we also request that researchers and educator sinform us of how they are using these data

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Effects of soil and space on the woody species composition and vegetation structure of three Cerrado phytophysiognomies in the Cerrado-Amazon transition

Abstract The Cerrado Biome is considered one of the world's biodiversity hotspots because of its rich biodiversity, the high level of endemism and the increasing threat. The Cerrado is composed by a mosaic of different vegetation types, including physiognomies that vary from grasslands (campo limpo) to savannas (typical cerrado or cerrado sensu stricto) and cerrado woodlands (cerradão). However, the factors that determine the composition of the Cerrado’s flora and the structure of the physiognomies that compose this biome are still poorly understood. Here, we investigate the influence of the chemical and granulometric properties of the soil and the effect of geographic distance on the occurrence and abundance of woody species in three Cerrado phytophysiognomies – cerrado woodland (cerradão), dense cerrado savanna and typical cerrado savanna – in the Cerrado-Amazon transition. We tested the hypothesis that the edaphic characteristics and geographic space determine the species composition and the structure of the woody vegetation of these three phytophysiognomies. We demonstrate that the dissimilarities in the structure and composition of the three sites were determined more by space (13% of explanation) than edaphic properties (1%), but primarily by the interaction between these two factors (26%). We conclude that, in situations where the chemical and granulometric properties of the soil are relatively homogeneous, as we found in the present study, geographic distance between sites has a greater influence than variation in the substrate’s properties on modelling the occurrence and abundance of the woody plant species in the Cerrado