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Made available in DSpace on 2022-04-28T19:42:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-10-01 The Tocantins-Araguaia Basin is one of the largest river systems in South America, located entirely within Brazilian territory. In the last decades, capital-concentrating activities such as agribusiness, mining, and hydropower promoted extensive changes in land cover, hydrology, and environmental conditions. These changes are jeopardizing the basin’s biodiversity and ecosystem services. Threats are escalating as poor environmental policies continue to be formulated, such as environmentally unsustainable hydropower plants, large-scale agriculture for commodity production, and aquaculture with non-native fish. If the current model persists, it will deepen the environmental crisis in the basin, compromising broad conservation goals and social development in the long term. Better policies will require thought and planning to minimize growing threats and ensure the basin’s sustainability for future generations. Núcleo de Estudos Ambientais Universidade Federal do Tocantins (UFT) Programa de Pós Graduação em Ecologia de Ambientes Aquaticos Continentais (PEA) Universidade Estadual de Maringá (UEM) Museu Paraense Emílio Goeldi Grupo de Estudos em Leishmanioses Instituto René Rachou Fundação Oswaldo Cruz (FIOCRUZ) Universidade Estadual Paulista “Júlio de Mesquita Filho” Museu de Zoologia e Taxidermia José Hidasi Universidade Estadual do Tocantins (Unitins) Departamento de Ecologia Universidade Federal de Goiás (UFG) Laboratório de Ictiologia Departamento de Biologia Universidade Federal de Sergipe (UFS) Laboratório de Paleontologia e Evolução Curso de Geologia Universidade Federal de Goiás (UFG) Departamento de Ecologia Universidade Federal do Rio de Janeiro (UFRJ) Universidade Federal de Goiás (UFG) Laboratório de Biogeografia e Ecologia Aquática Universidade Estadual de Goiás Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Herbário do Tocantins Núcleo de Estudos Ambientais Universidade Federal do Tocantins (UFT) Laboratório de Ictiologia Sistemática Núcleo de Estudos Ambientais Universidade Federal do Tocantins (UFT) Departamento de Zoologia Universidade de Brasília Researcher Departamento de Ecologia Universidade de Brasília (UnB) Instituto Nacional de Pesquisas da Amazônia (INPA) Laboratório de Ecologia de Peixes e Invasões Biológicas Universidade Estadual de Londrina (UEL) Laboratório de Entomologia Universidade Federal do Tocantins (UFT) Universidade Federal de Pelotas (UFPel) Environmental Sciences Program-CIAMB Universidade Federal de Goiás (UFG) Universidade Federal de Mato Grosso (UFMT) Campus Universitário do Araguaia Laboratório de Microbiologia Universidade Federal do Tocantins (UFT) Fundação Brasileira para o Desenvolvimento Sustentável (FBDS) & Universidade Federal de Goiás (UFG) Laboratório de Ecologia e Zoologia (LABECZ) Universidade Federal do Tocantins (UFT) Laboratório de Ecologia de Peixes Departamento de Ecologia Universidade do Estado do Rio de Janeiro (UERJ) Laboratório de Análise e Síntese em Biodiversidade Departamento de Botânica Universidade Federal do Paraná (UFPR) Secretaria de Estado da Educação de Goiás-(Seduc-GO) UNISANTA PPGECOMAR Universidade Federal do Tocantins (UFT) Laboratório de Paleobiologia Universidade Federal do Tocantins (UFT) Departamento de Ecologia e Conservação Universidade Federal de Lavras (UFLA) Laboratório de Caracterização de Impactos Ambientais (LCIA) Universidade Federal do Tocantins (UFT) Embrapa Cerrado Instituto de Biodiversidade e Sustentabilidade Universidade Federal do Rio de Janeiro Programa de Pós-Graduação em Ecologia Universidade Federal do Pará (UFPA) Laboratório de Análises Geoambientais (LGA) Universidade Federal do Tocantins (UFT) Centro de Biologia Aquática Pontifícia Universidade Católica de Goiás Laboratório de Biodiversidade Universidade Evangélica de Goiás Escola de Ciências Agrárias e Biológicas Pontifícia Universidade Católica (PUC) Laboratório de Genética & Biodiversidade - ICB/UFG Núcleo de Pesquisas em Limnologia Ictiologia e Aquicultura (Nupelia) Universidade Estadual de Maringá (UEM) Departamento de Direito Universidade Federal do Tocantins (UFT) Núcleo de Estudos e Pesquisas Ambientais e Limnológicas (Nepal) Universidade de Brasília (UnB) Laboratório de Ecologia e Conservação (LEC) Universidade Federal do Paraná (UFPR) Coordenação de Biodiversidade Instituto Nacional de Pesquisas da Amazônia (INPA) Universidade Estadual Paulista “Júlio de Mesquita Filho”

Predicting the geographic distribution of plants that provide ecosystem services is essential to understand the adaptation of communities and conserve that group toward climate change. Predictions can be more accurate if changes in physiological characteristics of species due to those changes are included. Thus, we aimed to evaluate the impacts of climate change on the different hierarchical levels of Apuleia leiocarpa (Vogel) J. F. Macbr. (Fabaceae). Therefore, we experimentally evaluate the effect of different temperatures on the initial development (vigor) and estimate the impact of climate change on the potential geographic distribution of the species, using ecological niche approaches. For the experiment, we used 11 temperature intervals of 2 °C ranging from 21 to 41 °C. We used ecological niche modeling techniques (ENM) to predict the species' environmental suitability in future climate scenarios. The association between the experiment and niche models was obtained by testing the relationships of temperature increase on the species vigor and geographic distribution. This conceptual model to determine the direct and indirect effects of temperature was generated using the methodological framework of structural equation models. The experiment showed that the seeds had the highest growth at 31 °C. ENMs indicated that due to climate change, there is a tendency for the plant to migrate to regions with milder temperatures. However, such regions may be unsuitable for the plant since they do not have ideal temperatures to germinate, which may cause a drastic reduction in their availability in a future climate change scenario. The inclusion of seed germination through experimental research allowed us to detect an area that is less suitable for germination despite being climatically suitable for the species. Thus, research that integrates the effect of climate on the different stages of the organism's development is essential to understand the impact of climate change on biodiversity.

It is essential to predict areas of losses or exchanges of ecosystem services to adapt communities to the impacts caused by climate change. Particularly for provisioning ecosystem services provided by economically important plant species, understanding the association between climate change impacts and deforestation of native vegetation increases the accuracy of those predictions. Thus, we aim to (i) map the richness of provisioning ecosystem services from economically important native plants; (ii) use forecasts (present and future) of the distribution of ecosystem services to assess areas of changes in the number and type of provisioning ecosystems services. We evaluated provisioning ecosystem services from 110 Cerrado native species of economic importance for the local population. We determined the potential distribution of these plants using ecological niche modeling techniques, which were grouped according to the 21 different services provided. The forecasts for variation in richness and type of service used four future climate change scenarios (RCPs 4.5 and 8.5 in 2050 and 2070). The service losses detected in our models were associated with variables representing the progress of native vegetation deforestation in the biome due to agricultural expansion. Currently, ecosystem services can be found simultaneously in practically the entire biome. However, changes in the global climate will impact the potential geographic distribution of those plants, causing many areas in the biome to have reduced availability of potential ecosystem services. Moreover, due to the association between exposure to climate change and deforestation of native vegetation, the northern region of the biome will likely have the distribution of ecosystem services severely affected.

It is important to predict how phytoplankton will respond to global warming, as changes in their composition can affect ecosystem functions. We evaluated the effect of water warming on the taxonomic and functional composition of phytoplankton and on chemical characteristics that affect their occurrence, such as dissolved oxygen, pH and conductivity. Microcosms were constructed outdoors and monitored over time. The temperature was manipulated to simulate different scenarios predicted for the future. Warming caused a reduction in dissolved oxygen, while the pH and conductivity remained unchanged. We found a joint effect of temperature and time on chlorophyll-a as well as on the species and functional groups. The substitution of species and groups occurred in a similar way between treatments. However, a greater number of Cyanophyceae individuals were found at higher temperatures, while Bacillariophyceae and Euglenophyceae species were found more commonly in the lower warming treatments. These results indicate that warming altered the taxonomic and functional composition of phytoplankton, causing species substitution as well as a change in their functional characteristics, which led to the predominance of small organisms. Thus, contribute to predicting how an increase in temperature might alter the patterns of dominance, homogenization and community dynamics in future warming scenarios.

Different biological groups can be used for monitoring aquatic ecosystems because they can respond to variations in the environment. However, the evaluation of different bioindicators may demand multiple financial resources and time, especially when abundance quantification and species-level identification are required. In this study, we evaluated whether taxonomic, numerical resolution and cross-taxa can be used to optimize costs and time for stream biomonitoring in Central Brazil (Cerrado biome). For this, we sampled different biological groups (fish, zooplankton, phytoplankton, and periphyton) in stream stretches distributed in a gradient of land conversion dominated by agriculture and livestock. We used the Mantel and Procrustes analyses to test the association among different taxonomic levels (species to class), the association between incidence and abundance data (numerical resolution), and biological groups. We also assessed the relative effect of local environmental and spatial predictors on different groups. The taxonomic levels and numerical resolutions were strongly correlated in all taxonomic groups (r > 0.70). We found no correlations among biological groups. Different sets of environmental variables were the most important to explain the variability in species composition of distinct biological groups. Thus, we conclude that monitoring the streams in this region using bioindicators is more informative through higher taxonomic levels with occurrence data than abundance. However, different biological groups provide complementary information, reinforcing the need for a multi-taxa approach in biomonitoring.

In recent years, the Cerrado deforestation has increased considerably, reaching rates higher than in the Amazonian realm. Although the effects of deforestation are well known, the understanding of its drives at regional levels is incipient. Most studies consider that a driver influences deforestation likewise in all regions. However, deforestation has a strong spatial structure that can lead drivers to vary their influence on deforestation in different regions. Here, we evaluated the spatial variability in the relationship between the recent Cerrado deforestation and socioeconomic, environmental, and structural drivers at a regional scale. We used a geographically weighted regression (GWR) to assess the spatial variability of predictor variables. We identified regions that respond similarly to the drivers by grouping municipalities, considering their GWR coefficients through hierarchical clustering. The analyses that consider the spatial variability of predictors are more appropriated to assess the causes of recent deforestation. Remnant natural vegetation influenced the recent deforestation in all defined regions. Greater access to rural credit concession was the main driving force of deforestation in the northeast region defined here. Distance to roads increased deforestation in the northeast and north regions, while it inhibited deforestation in the central-east and southeast regions. Rainfall inhibited deforestation in the northeast, north, and southwest regions. Steep slope prevented deforestation mainly in the northeast, north, and southwest regions. Our results highlight that, to effectively reduce Cerrado deforestation, public policies should integrate strategies focusing not only at national and biome levels but also at the regional spatial level.

The aquatic microbiota is involved in crucial ecosystem functions. Thus, investigating the effects of global warming on these organisms is highly relevant, especially given the numerous climatic changes expected by the end of the century. In this study, we used an experimental approach and high-throughput sequencing to evaluate the shortterm effect of warming predicted by different future scenarios in the composition of the planktonic freshwater bacteria and microeukaryotes, and to verify if the same effects occur for each trophic level separately (autotrophic, heterotrophic and mixotrophic). Our experiment demonstrated that the composition for eukaryotes and prokaryotes based on DNA metabarcoding is affected by the increase in temperature and these have a similar pattern of response to warming. This highlights the temperature importance in structuring the communities of different groups. Modifications in the communities were observed through the substitution of specific taxa, which occurred mainly in warmer levels. Changes in community composition were also identified when trophic levels were assessed separately. Mixotrophic eukaryotes organisms are more sensitive to warming, modifying the patterns of composition with an increase in temperature of 2 °C. Microeukaryotes and heterotrophic bacteria were more resistant, with alterations in the communities composition visualized only in higher warming levels. The composition of autotrophic organisms was not affected by the increase in water temperature in any of the biological classifications evaluated, although the richness of eukaryotic autotrophic has decreased with warming. Our results contribute to predict how different biological levels and trophic groups of the aquatic microbiota respond to global warming. This approach is relevant because warming leads to changes in community composition and affects ecosystem processes essentials to the aquatic environment.

The global Climate change may affect biodiversity and the functioning of ecosystems by changing the appropriate locations for the development and establishment of the species. The Hancornia speciosa, popularly called Mangaba, is a plant species that has potential commercial value and contributes to rural economic activities in Brazil. The aim of this study was to evaluate the impact of global climate change on the potential geographic distribution, productivity, and value of production of H. speciosa in Brazil. We used MaxEnt to estimate the potential geographic distribution of the species in current and future (2050) climate scenarios. We obtained the productivity and value of production for 74 municipalities in Brazil. Moreover, to explain the variation the productivity and value of production, we constructed 15 models based on four variables: two ecological (ecological niche model and the presence of Unity of conservation) and two socio-economic (gross domestic product and human developed index). The models were selected using Akaike Information Criteria. Our results suggest that municipalities currently harvesting H. speciosa will have lower harvest rates in the future (mainly in northeastern Brazil). The best model to explain the productivity was ecological niche model; thus, municipalities with higher productivity are inserted in regions with higher environmental suitability (indicated by niche model). Thus, in the future, the municipalities harvesting H. speciosa will produce less because there will be less suitable habitat for H. speciosa, which in turn will affect the H. speciosa harvest and the local economy.

Recently, ecological niche models have been employed to investigate the potential geographical distribution of species. However, it is necessary to analyze the vast number of publications on this topic to understand the trends and biases of research using ecological niche models (ENMs). Therefore, this study aims to investigate trends in the scientific literature regarding studies on ENMs. For the quantitative analysis of the literature on ENMs, we performed a search in the Thomson ISI (Web of Science) database between 1991 and 2013. The search identified 3042 papers containing preselected keywords in either the title or abstract. The results showed that the number of papers has increased over the years (r=0.77, P

The impacts of global climate change have been a worldwide concern for several research areas, including those dealing with resources essential to human well being, such as agriculture, which directly impact economic activities and food security. Here we evaluate the relative effect of climate (as indicated by the Ecological Niche Model-ENM) and agricultural technology on actual soybean productivity in Brazilian municipalities and estimate the future geographic distribution of soybeans using a novel statistical approach allowing the evaluation of partial coefficients in a non-stationary (Geographically Weighted Regression; GWR) model. We found that technology was more important than climate in explaining soybean productivity in Brazil. However, some municipalities are more dependent on environmental suitability (mainly in Southern Brazil). The future environmental suitability for soybean cultivation tends to decrease by up 50% in the central region of Brazil. Meanwhile, southern-most Brazil will have more favourable conditions, with an increase of ca. 25% in environmental suitability. Considering that opening new areas for cultivation can degrade environmental quality, we suggest that, in the face of climate change impacts on soybean cultivation, the Brazilian government and producers must invest in breeding programmes and more general ecosystem-based strategies for adaptation to climate change, including the development of varieties tolerant to climate stress, and strategies to increase productivity and reduce costs (social and environmental).

The hindcast of shifts in the geographical ranges of species as estimated by ecological niche modelling (ENM) has been coupled with phylogeographical patterns, allowing the inference of past processes that drove population differentiation and genetic variability. However, more recently, some studies have suggested that maps of environmental suitability estimated by ENM may be correlated to species' abundance, raising the possibility of using environmental suitability to infer processes related to population demographic dynamics and genetic variability. In both cases, one of the main problems is that there is a wide variation in ENM development methods and climatic models. In this study, we analyse the relationship between heterozygosity (He) and environmental suitability from multiple ENMs for 25 population estimates for Dipteryx alata, a widely distributed, endemic tree species of the Cerrado region of central Brazil. We propose a new approach for generating a statistical distribution of correlations under randomly generated ENM. The confidence intervals from these distributions indicate how model selection with different properties affects the ability to detect a correlation of interest (e.g. the correlation between He and suitability). Additionally, our approach allows us to explore which particular ensemble of ENMs produces the better result for finding an association between environmental suitability and He. Caution is necessary when choosing a method or a climatic data set for modelling geographical distributions, but the new approach proposed here provides a conservative way to evaluate the ability of ensembles to detect patterns of interest.

Predictive models for chlorophyll-a concentration are the most common ecological tools for water-quality management. However, the interactions among factors driving eutrophication processes remain poorly understood. In addition to nutrient concentrations, other variables such as, for instance, hydrology, land use and biotic interactions may also be included as explanatory variables. Here, we compared a set of a priori models (which included local, morphological, and landscape variables) with respect to their power to predict chlorophyll-a concentration in 21 reservoirs of central Brazil. The best model, selected according to the Akaike information criterion, explained 67.7% of the variation in chlorophyll-a concentration, and indicated a positive relationship with total phosphorus concentration (the main predictor in our model) and depth. Turbidity was negatively correlated with chlorophyll-a concentration. Contrary to recent studies indicating the importance of landscape predictors, our results suggested a preponderance of local factors in determining chlorophyll-a concentration, and that the control of phosphorus sources in tropical reservoirs is as important as it is in temperate ecosystems. We also detected a substantial uncertainty regarding the best model, suggesting that further studies should focus on explicitly modeling the variation in the strength of the relationships between chlorophyll-a and explanatory variables.

The ability of high school students to know endangered species can vary among species (e.g., large body size can influence people's interest) or among municipalities (e.g., more contact with biodiversity can influence people's interest). Thus, in the present paper, we evaluated high school students' knowledge about the endangered and non-endangered mammalian species of the Brazilian Cerrado. We tested whether the recognition of the endangered and non-endangered species varied in a cross-species analysis (twelve total species) according to species characteristics, such as body size, popularity, endangered status and the length of time of inclusion on the endangered species list. Moreover, we tested whether the recognition of the endangered mammal species varied between municipalities (spatial analysis). We interviewed 366 students in their first year of high school in 21 schools (one in each municipality). Our results indicated that the proportion of correctly identified endangered species varied according to species (cross-species). The endangered species that were most often correctly identified were Myrmecophaga tridactyla (known by its popular name, Tamanduá-bandeira, in Brazil), Priodontes maximus (Tatu canastra) and Panthera onca (onça-pintada), with more than 80% correct answers. Thus, students tended to recognize the more popular species and the endangered species more than the non-endangered species. The analysis of student knowledge according to municipality demonstrated that the students' ability to recognize endangered species followed a spatial pattern. Finally, the cross-species and spatial variation patterns detected in the present study indicated the importance of formal education in increasing high school students' knowledge about endangered species and suggested that education should also promote less well-known species, species with smaller body sizes, and other groups of vertebrates and invertebrates and consider local and regional biodiversity whenever possible.

Genetic effects of habitat fragmentation may be undetectable because they are generally a recent event in evolutionary time or because of confounding effects such as historical bottlenecks and historical changes in species' distribution. To assess the effects of demographic history on the genetic diversity and population structure in the Neotropical tree Dipteryx alata (Fabaceae), we used coalescence analyses coupled with ecological niche modeling to hindcast its distribution over the last 21 000 years. Twenty-five populations (644 individuals) were sampled and all individuals were genotyped using eight microsatellite loci. All populations presented low allelic richness and genetic diversity. The estimated effective population size was small in all populations and gene flow was negligible among most. We also found a significant signal of demographic reduction in most cases. Genetic differentiation among populations was significantly correlated with geographical distance. Allelic richness showed a spatial cline pattern in relation to the species' paleodistribution 21 kyr BP (thousand years before present), as expected under a range expansion model. Our results show strong evidences that genetic diversity in D. alata is the outcome of the historical changes in species distribution during the late Pleistocene. Because of this historically low effective population size and the low genetic diversity, recent fragmentation of the Cerrado biome may increase population differentiation, causing population decline and compromising long-term persistence.