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Background Different methods estimating the global anthropogenic land flux, which is dominated by forest-related activities, vary in magnitude and direction with respect to whether the land is a net source or sink. One reason for these variations is the extent to which methods consider land to be “managed”, thus contributing to the anthropogenic flux. Earth Observation (EO) datasets characterising spatio-temporal changes in land cover and carbon stocks provide an independent approach to flux estimations that can be compared against National Greenhouse Gas Inventories (NGHGIs) to support accurate and timely monitoring, reporting and verification capacity. Using Brazil as a primary case study, with additional analysis in Indonesia and Malaysia, we compare EO-based estimates of forest fluxes to NGHGIs. Results Between 2001 and 2020, the EO-derived estimates of all forest-related emissions and removals indicate that Brazil was a net sink of carbon (-0.2 GtCO2yr− 1), while Brazil’s NGHGI reports a net carbon source (+ 0.8 GtCO2yr− 1). After adjusting the Global EO estimate to accommodate the Brazilian NGHGI definition of managed forest and other assumptions used in the inventory’s methodology, the Global EO net flux became a source of + 0.6 GtCO2yr− 1, comparable to the NGHGI. Remaining discrepancies are largely due to differences in carbon removal factors and forest types considered in the two datasets. In Indonesia, Global EO and NGHGI net flux estimates were similar (+ 0.6 GtCO2 yr− 1), but in Malaysia, they differed in both magnitude and sign (NGHGI: -0.2 GtCO2 yr− 1; Global EO: +0.2 GtCO2 yr− 1). Spatially explicit datasets on forest types were not publicly available in either country, limiting the possibility of detailed analyses and adjustments. Conclusions By adjusting the Global EO dataset to improve comparability with carbon fluxes estimated for managed forests in the Brazilian NGHGI, initially diverging estimates were largely reconciled and remaining differences explained. Despite limited spatial data in Indonesia and Malaysia, our comparison indicated where differing approaches may explain uncertainties and inaccuracies. Our study highlights that comparing Global EO and NGHGIs is a useful exercise to improve both datasets towards greater accuracy and alignment, provided that sufficiently transparent and complete information is available for such detailed analyses.

The Brazilian Cerrado consists of a highly heterogeneous tropical savanna, and its biomass stocks are highly variable. Mapping and monitoring these stocks is not trivial. To address this challenge, we built an aboveground woody biomass (AGWB) model for the Cerrado biome using 30-m resolution optical satellite imagery (Landsat-5 and Landsat-8), 25-m resolution SAR imagery (ALOS and ALOS-2), and a set of plot-based and LiDAR-derived AGWB estimates. We implemented both a Classification and Regression Tree (CART) and a Random Forest (RF) algorithm to model AGWB over the native vegetation for the year 2019 in the Cerrado. The RF algorithm resulted in a slightly better result $(\mathrm{R}^{2}=53\%;\text{ rel. RMSE} =57\%)$ than, the CART model $(\mathbf{R}^{2}=45\%\ \text{ rel. RMSE} =63\% 1$ , but our map shows an underestimation of very high AGWB (negative bias over 200 t.ha-1) and a slight overestimation of low AGWB (positive bias).

The tropical savanna in Brazil known as the Cerrado covers circa 23% of the Brazilian territory, but only 3% of this area is protected. High rates of deforestation and degradation in the woodland and forest areas have made the Cerrado the second-largest source of carbon emissions in Brazil. However, data on these emissions are highly uncertain because of the spatial and temporal variability of the aboveground biomass (AGB) in this biome. Remote-sensing data combined with local vegetation inventories provide the means to quantify the AGB at large scales. Here, we quantify the spatial distribution of woody AGB in the Rio Vermelho watershed, located in the centre of the Cerrado, at a high spatial resolution of 30 metres, with a random forest (RF) machine-learning approach. We produced the first high-resolution map of the AGB for a region in the Brazilian Cerrado using a combination of vegetation inventory plots, airborne light detection and ranging (LiDAR) data, and multispectral and radar satellite images (Landsat 8 and ALOS-2/PALSAR-2). A combination of random forest (RF) models and jackknife analyses enabled us to select the best remote-sensing variables to quantify the AGB on a large scale. Overall, the relationship between the ground data from vegetation inventories and remote-sensing variables was strong (R2 = 0.89), with a root-mean-square error (RMSE) of 7.58 Mg ha−1 and a bias of 0.43 Mg ha−1. View Full-Text Made available in DSpace on 2020-12-15T09:04:29Z (GMT). No. of bitstreams: 1 SANO-WOODY-ABOVEGROUND-BIOMASS-MAPPING-OF-THE-BRAZILIAN-SAVANNA.pdf: 7895412 bytes, checksum: d5c0e21e63f6269019a19c5dfd64005a (MD5) Previous issue date: 2020

The Brazilian Savanna, known as Cerrado (Cerrado sensu lato (s.l.)), is the second largest biome in South America. It comprises different physiognomies due to variations of soil, topography and human impacts. The gradients of tree density, tree height, above ground biomass (AGB) and wood species cover vary according to the Cerrado formation, ranging from different grassland formations (Campo limpo, campo sujo), savanna intermediary formations (Campo cerrado and Cerrado sensu stricto - s.s) and forest formations (Cerradão, Mata ciliar, Mata de galeria and Mata Seca).Although the carbon stock in Cerrado is lower than in the Brazilian Amazon, the conversion of this biome to other types of land use is occurring much faster. In the last ten years, the degradation of Cerrado forest was the second largest source of carbon emissions in Brazil. Therefore, effective methods for assessing and monitoring aboveground woody biomass and carbon stocks are needed. A multi-sensor Earth observation approach and machine learning techniques have shown potential for the large-scale characterization of Cerrado forest structure.The aim of this study is to present a method to estimate the AGB of an area of the Brazilian Cerrado using ALOS-PALSAR (L-band SAR), Landsat, LIDAR (LIght Detection And Ranging) and field datasets. Field data consisted of 15 plots of 1 ha area located in Rio Vermelho watershed in Goiás-State (Brazil). We used a 2-step AGB estimation (i) from the field AGB using LIDAR metrics and (ii) from LIDAR-AGB to satellite Earth Observation scales following a Random Forest regression algorithm. The methodology to estimate ABG of Cerrado Stricto Sensu vegetation is part of the Forests 2020 project which is the largest investment by the UK Space Agency, as part of the International Partnerships Programme (IPP), to support in the improvement of the forest monitoring in six partner countries through advanced uses of satellite data.

Widespread in the subtropics and tropics of the Southern Hemisphere, savannas are highly heterogeneous and seasonal natural vegetation types, which makes change detection (natural vs. anthropogenic) a challenging task. The Brazilian Cerrado represents the largest savanna in South America, and the most threatened biome in Brazil owing to agricultural expansion. To assess the native Cerrado vegetation (NV) areas most susceptible to natural and anthropogenic change over time, we classified 33 years (1985?2017) of Landsat imagery available in the Google Earth Engine (GEE) platform. The classification strategy used combined empirical and statistical decision trees to generate reference maps for machine learning classification and a novel annual dataset of the predominant Cerrado NV types (forest, savanna, and grassland). We obtained annual NV maps with an average overall accuracy ranging from 87% (at level 1 NV classification) to 71% over the time series, distinguishing the three main NV types. This time series was then used to generate probability maps for each NV class. The native vegetation in the Cerrado biome declined at an average rate of 0.5% per year (748,687 ha yr?1), mostly affecting forests and savannas. From 1985 to 2017, 24.7 million hectares of NV were lost, and now only 55% of the NV original distribution remains. Of the remnant NV in 2017 (112.6 million hectares), 65% has been stable over the years, while 12% changed among NV types, and 23% was converted to other land uses but is now in some level of secondary NV. Our results were fundamental in indicating areas with higher rates of change in a long time series in the Brazilian Cerrado and to highlight the challenges of mapping distinct NV types in a highly seasonal and heterogeneous savanna biome. Made available in DSpace on 2020-12-15T09:03:27Z (GMT). No. of bitstreams: 1 SANO-MAPPING-THREE-DECADES-OF-CHANGES-IN-THE-BRAZILIAN-CERRADO-USING-GEE.pdf: 9748840 bytes, checksum: 8969ac0ad8657d5b696bc169a8cddf48 (MD5) Previous issue date: 2020

The relationship between environmental heterogeneity and species diversity has been one of the most studied patterns in ecology. However, some taxa and regions worldwide still lack studies to verify this relationship. Phyllostomidae is the most ecologically diverse family of mammals worldwide, encompassing a great proportion of the species of mammals and bats across the Amazon forest. Even though the Amazon seems to be a homogeneous landscape with an unlimited supply of water, it presents a high variation in vegetation types and proximity to large bodies of water. In our study, we have analyzed the relationship between environmental heterogeneity and proximity to large bodies of water in the structure of phyllostomid assemblages (Chao-estimated species richness and capture rates). We have found that an increase in landscape heterogeneity associated with large bodies of water and representative flooded forest increase species richness. In addition, more heterogeneous landscapes in the presence of water have presented a higher abundance of bats. Our findings might be related with the small niche widths of phyllostomids, which could have promoted specialization in some landscape features, while the presence of water could have promoted an increase in food availability (insects and fruits), leading to an increase in phyllostomid richness and abundance. This is important information for planning where to place protected areas in the northeastern portion of the Amazon, while taking into account the consequences of drought and deforestation close to water bodies on the local phyllostomid fauna, and the maintenance of the ecosystem services provided by a higher bat diversity.

Freshwater ecosystems across the Amazon are largely comprised of small streams and headwaters of riparian zones. These areas are legally protected within private landholdings in Brazil, but recent changes in the environmental legislation have slackened protection requirements, with unpredictable consequences to the integrity and functioning of these freshwater environments. Local drivers of riparian forest loss and degradation should be understood by considering context-dependent land management practices and pressures within a region. Here, we examine the spatial determinants of the total amount and spectral quality of both headwater and overall riparian forests within private landholdings within a highly fragmented region of southern Amazonia. We built generalized linear models to assess how the amount and spectral quality of headwater and riparian forests respond to landholding size and distance to roads and an urban center, and document landholder compliance rates according to both the current and previous Brazilian environmental legislation. Although forest loss and degradation are typically associated, forest degradation responded independently to the same drivers. Headwater forests were generally more degraded than riparian forests, and smallholders complied less often with legal requirements than largeholders. Proximity to roads and the nearest town had a detrimental effect on both headwater and riparian forest amount and quality, and distance to the nearest town affected all variables, except for headwater forest quality. Compliance with environmental legislation is the first step in protecting riparian and headwater forests, but alternative landscape management strategies must be explored, particularly focusing on smallholdings, which are most vulnerable to deforestation and forest degradation.

The Brazilian Cerrado biome consists of a highly heterogeneous tropical savanna, and is one of the world’s biodiversity hotspots. High rates of deforestation, however, place it as the second-largest source of carbon emissions in Brazil. Due to its heterogeneity, biomass and carbon stocks in the Cerrado vegetation are highly variable, and mapping and monitoring these stocks are not a trivial effort. To address this challenge, we built an aboveground woody biomass (AGWB) model for the Cerrado biome using 30-m resolution optical satellite imagery (Landsat-5 and Landsat-8), 25-m resolution SAR imagery (ALOS and ALOS-2), and a set of plot-based and LiDAR-derived AGWB estimates (n = 1858) from a wide network of researchers in Brazil. We implemented both a Classification and Regression Tree (CART) and a Random Forest (RF) algorithm to model AGWB over the native vegetation in the year 2019 (as classified by MapBiomas) in the Cerrado. The RF algorithms resulted in a slightly better result (R2 = 53%; rel. RMSE = 57%) than the CART model (R2 = 45%; rel. RMSE = 63%), but our map shows an underestimation of very high AGWB (negative bias over 200 t ha−1) and a slight overestimation of low AGWB (positive bias), especially in the RF model (bias of 1.19 t ha−1 against 0.86 t ha−1 for the CART model). We believe we have contributed to knowledge on the woody biomass stocks in the biome, especially in the predominant savanna woodlands, which is where the highest current rates of conversion take place in the Cerrado.

Carnivores face conflicts with humans, which has reduced their numbers and distribution. Carnivores compete in intraguild predation systems, Subordinate predators usually avoid top predators through spatial or temporal separation. Coexistence requires a complex combination of resources and environmental conditions. In this study, we assessed the occupancy and temporal activity during night time of the jaguar ( Panthera onca ) and puma ( Puma concolor ) in the Serra da Capivara National Park (SCNP), located in the semi-arid Caatinga biome of Brazil. Felines face biological limitations in hot environments. We used camera-traps, occupancy models and temporal analysis to evaluate their patterns of habitat use, activity and interactions in SCNP between 2009 and 2011. We considered jaguar as dominant predator and puma as subordinate, and expected to find spatial and temporal avoidance between them. We found evidence of spatial and temporal coexistence. This coexistence could be a result of a restriction of niche separation between both species, influenced by the harsh conditions in the Caatinga, represented by a combination of extreme temperatures, scarcity of refuges to thermoregulate, an environment around SCNP with a high level of human disturbance and an apparent increase in prey due conservation policies.

Xenarthrans -anteaters, sloths, and armadillos- have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. Have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become. Fil: Marques Santos, Paloma. Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas; Brasil Fil: Bocchiglieri, Adriana. Universidade Federal de Sergipe; Brasil Fil: Garcia Chiarello, Adriano. Universidade de Sao Paulo; Brasil Fil: Pereira Paglia, Adriano. Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas; Brasil Fil: Moreira, Adryelle. Amplo Engenharia e Gestão de Projetos ; Brasil Fil: Abba, Agustin Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; Argentina Fil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; Argentina Fil: Gatica, Ailin. Universidad Nacional de San Luis; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; Argentina Fil: Ochoa, Ana Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis. Universidad Nacional de San Luis. Facultad de Ciencias Físico Matemáticas y Naturales. Instituto Multidisciplinario de Investigaciones Biológicas de San Luis; Argentina Fil: de Angelo, Carlos Daniel. Universidad Nacional de Rio Cuarto. Facultad de Cs.exactas Fisicoquimicas y Naturales. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Cordoba. Instituto de Ciencias de la Tierra, Biodiversidad y Ambiente.; Argentina Fil: Tellaeche, Cintia Gisele. Universidad Nacional de Jujuy. Facultad de Ciencias Agrarias. Centro de Estudios Ambientales Territoriales y Sociales; Argentina. Universidad Nacional de Jujuy. Instituto de Ecorregiones Andinas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Ecorregiones Andinas; Argentina Fil: Varela, Diego Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Vanderhoeven, Ezequiel Andres. Ministerio de Salud. Instituto Nacional de Medicina Tropical; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Caruso, María Flavia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Administración de Parques Nacionales. Delegación Regional del Noroeste; Argentina Fil: Arrabal, Juan Pablo. Secretaria de Gobierno de Salud. Instituto Nacional de Medicina Tropical - Sede Puerto Iguazú Misiones; Argentina. Centro de Investigaciones del Bosque Atlántico; Argentina Fil: Iezzi, María Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Di Bitetti, Mario Santiago. Centro de Investigaciones del Bosque Atlántico; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Cruz, Paula Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Centro de Investigaciones del Bosque Atlántico; Argentina Fil: Reppucci, Juan Ignacio. Administración de Parques Nacionales. Delegación Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Benito Santamaria, Silvia. Centro de Investigaciones del Bosque Atlántico; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Quiroga, Verónica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; Argentina Fil: Di Blanco, Yamil Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Marás, Gustavo Arnaldo. Administración de Parques Nacionales. Delegación Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Camino, Micaela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Centro de Ecología Aplicada del Litoral. Universidad Nacional del Nordeste. Centro de Ecología Aplicada del Litoral; Argentina Fil: Perovic, Pablo Gastón. Administración de Parques Nacionales. Delegación Regional del Noroeste; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Martínez Pardo, Julia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Costa, Sebastián Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina Fil: Pinheiro, Fabiana. Universidade Federal do Rio Grande do Sul; Brasil Fil: Volkmer de Castilho, Pedro. Universidade Federal de Santa Catarina; Brasil Fil: Bercê, William. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil Fil: Camara Assis, Julia. Universidade Estadual Paulista Julio de Mesquita Filho. Faculdade de Engenharia.; Brasil Fil: Rodrigues Tonetti, Vinicius. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil Fil: Alves Eigenheer, Milene. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil Fil: Chinem, Simonne. Universidade de Sao Paulo; Brasil Fil: Honda, Laura K.. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil Fil: Bergallo, Helena de Godoy. Universidade do Estado de Rio do Janeiro; Brasil Fil: Alberici, Vinicius. Universidade de Sao Paulo; Brasil Fil: Wallace, Robert. Wildlife Conservation Society; Estados Unidos Fil: Ribeiro, Milton Cezar. Universidade de Sao Paulo; Brasil Fil: Galetti, Mauro. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil

Understanding structural variations in natural systems can help us understand their responses to disturbance and environmental changes and plan for the mitigation of human-induced impacts. Terrestrial laser scanning (TLS) is a technological solution to quickly and accurately capture and model vegetation structure. In the Brazilian Cerrado biome, characterized by highly heterogeneous plant formations and marked seasonality, TLS may help improve aboveground biomass (AGB) estimates. This study aimed to use single-scan TLS-derived metrics to predict plot-scale aboveground biomass for three vegetation types with high structural diversity and biomass content (woodland savanna, forested savanna, and gallery forest). Ten plots were scanned in each vegetation type, and variables related to point density at different strata and height distribution were extracted from the point cloud to predict AGB measured in local field inventories. The woodland savanna provided good fit models with only two metrics (rainy season: proportion of points below 1.37 m and height of the 99th percentile; adj-R2 = 0.92, RMSE (root mean square error) = 2.67 Mg/ha or 12%; and dry season: height of the 20th and the 99th percentiles; adj-R2 = 0.88, RMSE = 3.32 Mg/ha or 15%). The model for the forested savanna had relatively less explanatory power with one influential predictor (forested savanna: height of the 20th percentile; adj-R2 = 0.58, RMSE = 6.85 Mg/ha or 21%). For the gallery forest, however, the canopy structure could not be adequately characterized due to occlusion of laser returns by dense sub-canopy strata. Our study shows the strong potential of the terrestrial LiDAR technology for estimation of plot-based biomass across diverse savanna vegetation types, where the sparse tree structure allows for better laser penetration the accurate generation of height profiles.

Species persistence in fragmented landscapes is intimately related to the quality, structure, and context of remaining habitat remnants. Riparian vegetation is legally protected within private landholdings in Brazil, so we quantitatively assessed occupancy patterns of terrestrial mammals in these remnants, examining under which circumstances different species effectively use them. We selected 38 riparian forest patches and five comparable riparian sites within continuous forest, at which we installed four to five camera-traps per site (199 camera-trap stations). Terrestrial mammal assemblages were sampled for 60 days per station during the dry seasons of 2013 and 2014. We modelled species occupancy and detection probabilities within riparian forest remnants, and examined the effects of patch size, habitat quality, and landscape structure on occupancy probabilities. We then scaled-up modelled occupancies to all 1915 riparian patches throughout the study region to identify which remnants retain the greatest potential to work as habitat for terrestrial vertebrates. Of the ten species for which occupancy was modelled, six responded to forest quality (remnant degradation, cattle intrusion, palm aggregations, and understorey density) or structure (remnant width, isolation, length, and area of the patch from which it originates). Patch suitability was lower considering habitat quality than landscape structure, and virtually all riparian remnants were unsuitable to maintain a high occupancy probability for all species that responded to forest patch quality or structure. Beyond safeguarding legal compliance concerning riparian remnant amount, ensuring terrestrial vertebrate persistence in fragmented landscapes will require curbing the drivers of forest degradation within private landholdings.

Extensive 1970–2010 deforestation in the Brazilian Amazon has generated a ~ 1.5 Mha fragmented region known as the ‘arc of deforestation’. Farmers and cattle ranchers throughout Brazil are legally required to set-aside riparian forest strips within their landholdings, but recent legislative changes have relaxed the minimum mandatory conditions of these riparian forests. In this context, we assessed the functional role of riparian forest remnants as landscape connectors for medium to large-bodied terrestrial mammals in a vast fragmented landscape of southern Amazonia. We selected 38 riparian forest strips and five riparian sites within continuous forest, installed four to five camera-traps along each riparian zone (199 camera-trap stations), and sampled the terrestrial mammal assemblage for 60 days per station during the dry seasons of 2013 and 2014. We compared mammal use of riparian forests within both continuous and highly fragmented forests, and examined the effects of corridor width, corridor habitat structure, and landscape context on mammal species richness, composition, and functional diversity, all of which were higher in continuous forests than in riparian remnants. Functional diversity differences between corridor type was trait-independent and mediated by differences in species richness. Forest habitat degradation was associated with overall lower species richness, whereas forest specialists were more species-rich in increasingly wider corridors. Compositional shifts indicate that deforestation and forest degradation favours matrix-tolerant species with lower levels of forest habitat specificity. We show the potential landscape connectivity role for forest mammals of riparian corridors, whose width and forest degradation status are key predictors of community-wide responses. We provide evidence on the importance of these relict riparian strips to forest vertebrates, strengthening the scientific arguments that help justify the recently embattled legal requirements to maintain effective riparian corridors in Brazil.

Accurately estimating home range and understanding movement behavior can provide important information on ecological processes. Advances in data collection and analysis have improved our ability to estimate home range and movement parameters, both of which have the potential to impact species conservation. Fitting continuous-time movement model to data and incorporating the autocorrelated kernel density estimator (AKDE), we investigated range residency of forty-four jaguars fit with GPS collars across five biomes in Brazil and Argentina. We assessed home range and movement parameters of range resident animals and compared AKDE estimates with kernel density estimates (KDE). We accounted for differential space use and movement among individuals, sex, region, and habitat quality. Thirty-three (80%) of collared jaguars were range resident. Home range estimates using AKDE were 1.02 to 4.80 times larger than KDE estimates that did not consider autocorrelation. Males exhibited larger home ranges, more directional movement paths, and a trend towards larger distances traveled per day. Jaguars with the largest home ranges occupied the Atlantic Forest, a biome with high levels of deforestation and high human population density. Our results fill a gap in the knowledge of the species´ ecology with an aim towards better conservation of this endangered/critically endangered carnivore-the top predator in the Neotropics. Fil: Morato, Ronaldo G.. National Zoological Park. Smithsonian Conservation Biology Institute; Estados Unidos. Instituto Pró-Carnívoros; Brasil. Instituto Chico Mendes da Conservaçao da Biodiversidade; Brasil Fil: Stabach, Jared A.. National Zoological Park. Smithsonian Conservation Biology Institute; Estados Unidos Fil: Fleming, Chris H.. National Zoological Park. Smithsonian Conservation Biology Institute; Estados Unidos Fil: Calabrese, Justin M.. National Zoological Park. Smithsonian Conservation Biology Institute; Estados Unidos Fil: De Paula, Rogério C.. Instituto Chico Mendes de Conservaçao da Biodiversidade; Brasil. Instituto Pró-Carnívoros; Brasil Fil: Ferraz, Kátia M. P. M.. Instituto Pró-Carnívoros; Brasil. Universidade de Sao Paulo; Brasil Fil: Kantek, Daniel L. Z.. Instituto Chico Mendes de Conservação da Biodiversidade; Brasil Fil: Miyazaki, Selma S.. Instituto Chico Mendes de Conservação da Biodiversidade; Brasil Fil: Pereira, Thadeu D. C.. Instituto Chico Mendes de Conservação da Biodiversidade; Brasil Fil: Araujo, Gediendson R.. Universidade Federal de Viçosa; Brasil Fil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; Argentina Fil: de Angelo, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; Argentina Fil: Di Bitetti, Mario Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; Argentina Fil: Cruz, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Posadas; Argentina Fil: Lima, Fernando. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil. Instituto de Pesquisas Ecológicas; Brasil Fil: Cullen, Laury. Instituto de Pesquisas Ecológicas; Brasil Fil: Sana, Denis A.. Instituto Pró-Carnívoros; Brasil. Universidade Federal do Rio Grande do Sul; Brasil Fil: Ramalho, Emiliano E.. Instituto Pró-Carnívoros; Brasil. Instituto de Desenvolvimento Sustentável Mamirauá; Brasil Fil: Carvalho, Marina M.. Instituto de Defensa e Preservação dos Felídeos Brasieiros; Brasil Fil: Soares, Fábio H. S.. Instituto de Defensa e Preservação dos Felídeos Brasieiros; Brasil Fil: Zimbres, Barbara. Universidade do Brasília; Brasil Fil: Silva, Marina X.. Instituto Chico Mendes de Conservação da Biodiversidade; Brasil Fil: Moraes, Marcela D. F.. Instituto Chico Mendes de Conservação da Biodiversidade; Brasil Fil: Vogliotti, Alexandre. Instituto Pró-Carnívoros; Brasil. Universidade Federal da Integração Latino-Americana; Brasil Fil: May Jr., Joares A.. Projeto Onçafari Miranda; Brasil Fil: Haberfeld, Mario. Projeto Onçafari Miranda; Brasil Fil: Rampim, Lilian. Projeto Onçafari Miranda; Brasil Fil: Sartorello, Leonardo. Projeto Onçafari Miranda; Brasil Fil: Ribeiro, Milton C.. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil Fil: Leimgruber, Peter. National Zoological Park. Smithsonian Conservation Biology Institute; Estados Unidos

The impact of deforestation and fragmen- tation upon ecologically important and poorly known groups is currently an important issue for conservation biology. Herein we describe xenathran communities across the Brazilian Cerrado and study the effects of habitat fragmentation on occupancy and activity patterns on these assemblages. Our hypothesis was that larger and specialized species would be more ecologically sensitive, and likely to exhibit shifts in their activity patterns in more deforested areas as a way of dealing with the myriad of effects involved in the fragmentation process. The study was conducted by camera trapping in ten Cerrado sites. Five species were analyzed: Priodontes maximus, Euphractus sexcinctus, Dasypus novemcintus (Order Cingulata), Tamandua tetradactyla and Myrmecophaga tridactyla (Order Pilosa). Fragmentation was quantified by landscape metrics, calculated on scales that matched the species' home ranges. Occupancy and detection probability analyses were conducted to test for shifts in occupancy under different fragmentation condi- tions. A mixed-effects model analysis was conducted to test for shifts in species' frequency of records related to time of day, controlling for spatial autocor- relation by means of eigenvector-based spatial filters for the models' residuals. There were no changes in activity pattern between more and less fragmented areas, so that our behavioural plasticity hypothesis was not corroborated for this group. The lack of changes in the patterns could be explained by a species' time-lag response, or by the lack of a wide enough fragmen- tation gradient in our study.

The planning of protected areas take into consideration the current distributions of target species, disregarding possible future range shifts under climate change. This study tested potential shifts in the distribution of three xenarthran species (the giant anteater, Myrmecophaga tridactyla ; the giant armadillo, Priodontes maximus ; and the three-banded armadillo, Tolypeutes tricinctus ) due to the effects of climate change under different dispersal scenarios. In addition, we tested the adequacy of the current Brazilian protected areas in preserving these species under future climate changes (future distribution for the year 2050), under full and null dispersal scenarios. The final occurrence maps were then confronted with two Brazilian reserve systems for the year 2010: one consisting of reserves for integral protection only (IPCU), and one that included also reserves for sustainable use and indigenous reserves (SUCU). In the IPCU system, none of the species have or will have ⩾10% of their distributions protected, under neither dispersal scenario. Including SUCU, however, M. tridactyla and P. maximus already are, and will still be, adequately protected in the future. T. tricinctus , which is endemic to the Brazilian semi-arid, will not reach the 10% goal under neither dispersal scenario, even under the SUCU system. We stress the need for management actions in the northeastern and central parts of Brazil. Opportunities for the creation of more reserves are highlighted, considering the potential range shifts and the natural habitats still present in these regions.

Carnivores and their prey occurring at the extremes of their ecological niches face particular constraints in terms of habitat suitability (HS). We combined the use of camera traps and Ecological Niche Factor Analysis (ENFA) to calculate HS for jaguars (Panthera onca), pumas (Puma concolor), and 4 prey species (3-banded armadillos, Tolypeutes tricinctus; 9-banded armadillos, Dasypus novemcinctus; collared peccaries, Pecari tajacu; and gray brocket deer, Mazama gouazoubira) in Serra da Capivara National Park (SCNP), located in the semiarid Caatinga biome of Brazil. We also evaluated HS in relation to water management applied in the Park since 1994. Considering the physiological limitations of the Caatinga's species, we used an “edge of niche” habitat-suitability algorithm. For all species examined, distance to waterholes was the ecogeographical variable with the greatest contribution for the ENFA. Water management implemented in SCNP helps to ensure the persistence of predators and prey species, since the combination of topographic characteristics and location of waterholes explained most of HS for the analyzed species.

© 2012 Goulart et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Agricultural SystemS and the Conservation of Biodiversity and Ecosystems in the Tropics