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Modelos de distribuição de espécies são constituídos principalmente de dados ambientais (em sua maioria climáticos) e de distribuição das espécies para predizer a distribuição potencial das espécies. Neste sentido, a dispersão das espécies (i.e., movimento) é por muitas vezes ignorada nas predições. Em ambientes aquáticos, a dispersão não é restrita somente às barreiras físicas, mas também se dá pelo movimento direcional das espécies através da malha hidrográfica, que por sua vez pode ser incluída nos modelos por meio de preditores espaciais. Neste trabalho, nós buscamos avaliar o efeito da inclusão de preditores de dispersão assimétrica na distribuição geográfica potencial de um peixe de água doce da bacia Tocantins-Araguaia, Brasil. Além disso, nós estimamos se as predições usando preditores climáticos e de dispersão assimétrica variam dependendo da distribuição e amplitude de múltiplas espécies, e dependendo da inclusão de hidrelétricas como barreiras de dispersão nas predições. Para isso, nós geramos modelos usando sete conjunto de variáveis representando modelos climáticos e de dispersão, assim como suas interações. As métricas de avaliação dos modelos foram usadas para comparar a performance dos diferentes conjuntos de modelos (e.g., assimétrico e simétrico, e ambiental), a performance de modelos de múltiplas espécies baseando-se na distribuição das ocorrências entre sub-bacias e amplitude de distribuição, além do efeito da inclusão de barreiras de dispersão nos modelos. Primeiramente, os modelos com maiores performances foram os gerados usando preditores de dispersão assimétrica, tanto sozinhos como em conjunto com variáveis ambientais. Em segundo, espécies mais restritas tiveram modelos com maior performance quando modeladas usando preditores de dispersão assimétrica, especialmente quando distribuídas em diferentes sub-bacias. Por último, predições incluindo hidrelétricas como barreiras de dispersão mostraram uma maior perda de riqueza e composição de espécies, especialmente para as áreas com o maior número de barragens. Portanto, a inclusão de variáveis de dispersão assimétricas, considerando limites de dispersão das espécies, reduziu a extrapolação de predições para áreas climaticamente adequáveis, porém desconectadas pelos rios. Ademais, os modelos usando dispersão assimétrica melhor representaram espécies restritas em ambas sub-bacias e também o efeito de barreiras de dispersão na riqueza e composição de espécies ao longo da bacia. Sendo assim, futuros trabalhos usando modelos de distribuição de espécies, especialmente usando grupos com dispersão assimétrica, deveriam considerar a inclusão de preditores de dispersão assimétrica de forma a melhorar a performance dos modelos e realidade ecológica das predições. Species distribution models are based mainly on environmental (mostly climatic) and species distribution data to predict the potential distribution of species. In this sense, the species dispersal (i.e., movement) is often ignored in their predictions. In freshwater habitats, species dispersal is not restricted only by physical barriers but also by the directional movement of the hydrographic network, which can be considered through spatial predictors. Here, we aim to evaluate the effect of including asymmetrical dispersal predictors in the potential geographic distribution of a freshwater fish in the Tocantins-Araguaia River basin, Brazil. Furthermore, we aim to assess if the predictions using climatic and asymmetrical dispersal vary depending on multiple species occurrence distribution and range, and on the inclusion of hydropower plants as dispersal barriers in the predictions. For this, we built models with seven variable sets representing environmental (climatic) and dispersal models, as well as their interactions. The models’ accuracy metrics were then used to compare the performance of different model sets (e.g., asymmetrical and symmetrical dispersal and environmental predictors), the performance of multiple species models based on their occurrence distribution among sub-basins and range, and the effect of including dispersal barriers into the models. First, we found that the models with higher performance are those built using asymmetrical dispersal predictors, either solo or combined with environmental variables. Second, species more restricted had models with higher performance when modeled using asymmetrical dispersal predictors, especially when distributed in different sub-basins. Third, predictions including the hydropower plants as dispersal barriers showed a higher loss of species richness and composition, especially for the areas with the highest number of dams. Therefore, the inclusion of asymmetrical dispersal variables, taking into account dispersal limitations of species, decreased the overprediction to climatically suitable but disconnected areas through rivers. Furthermore, those models using asymmetrical dispersal better represented restricted species distributed in both sub-basins of the basin and also the effect of dispersal barriers in the fish species richness and composition along the basin. Therefore, future SDM studies, especially those using species groups with asymmetrical dispersal, should consider the inclusion of asymmetrical dispersal predictors to increase the model’s accuracy and ecological reality of predictions. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES Fundação de Amparo à Pesquisa do Estado de Goiás

Made available in DSpace on 2020-12-10T19:45:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-12-31 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) University of Florida Foundation COTEC IBAMA/ICMBio Contemporary and historical factors influence assemblage structure. The environmental and spatial influences acting on fish organization of rain forest coastal streams in the Atlantic rain forest of Brazil were examined. Fish (and functional traits such as morphology, diet, velocity preference, body size), environmental variables (pH, water conductivity, dissolved oxygen, temperature, stream width, flow, depth, substrate), and altitude were measured from 59 stream reaches. Asymmetric eigenvector maps were used to model the spatial structure considering direction of fish movements. Elevation played an important role-fish abundance, biomass, and richness all decrease with increasing elevation. Fish communities are influenced by both environmental and spatial factors, but downstream movements were shown to be more important in explaining the observed spatial variation than were bidirectional and upstream movements. Spatial factors, as well as environmental variables influenced by the spatial structure, explained most of the variation in fish assemblages. The strong spatial structuring is probably attributable to asymmetric dispersal limitation along the altitudinal profile: Dispersal is likely to be more limiting moving upstream than downstream. These fish assemblages reflect scale-dependent processes: At the stream-reach scale, fish respond to local environmental filters (habitat structure, water chemistry, and food supply), which are in turn influenced by a larger scale, namely the altitudinal gradient expected in steep coastal mountains. Thus, environmental drivers are not independent of spatial factors, and the effects of local factors can be confounded across the altitudinal gradient. These results may have implications for conservation, because downstream reaches are often neglected in management and conservation plans. in Portuguese is available with online material. Univ Estadual Paulista, Dept Zool & Bot, Lab Ictiol, Sao Jose Do Rio Preto, SP, Brazil Univ Florida, Dept Biol, Arthur R Marshall Jr Ecol Sci Lab, Gainesville, FL USA Univ Estadual Paulista, Dept Zool & Bot, Lab Ictiol, Sao Jose Do Rio Preto, SP, Brazil CNPq: 301755/2013-2 FAPESP: 2012/19723-0 FAPESP: 2013/20794-1 FAPESP: 2008/55029-5 COTEC: 260108-015.708/2012 COTEC: 260108000.197/2008 IBAMA/ICMBio: 37489-1/2 IBAMA/ICMBio: 15744

The River Continuum Concept (RCC) and the Riverine Ecosystem Synthesis (RES) are two different theories proposed by river ecologists to describe the response of biotic communities to environmental variability. River network directional patterns are conveniently described by asymmetric eigenvector maps, an eigenfunction-based spatial filtering method specifically proposed for situations where a hypothesized directional spatial process influences the species distribution. In this work asymmetric eigenvector maps are used in conjunction with canonical redundancy analysis and variation partitioning analysis to describe the distribution of macroinvertebrate communities of a river system in Northern Italy and to test the link between the river theories and the available data. Benthic macrofauna data were collected during the summer of 2009–2013 in 16 rivers, for a total of 283 replicates. We investigate the effects of some measured environmental factors on the benthic macrofauna community, accounting for directional effects intrinsic to the river network structure. The proposed protocol allows to highlight and discuss some of the features relevant to the two river theories. According to the RCC theory, altitude and temperature were relevant factors affecting the macrozoobenthic community, together with the distance from the spring and water depth. Environmental factors representing local and lateral dimensions were less relevant for explaining the variability of the community composition. Nonetheless a role of the surrounding land use was also found, suggesting the presence of lateral effects due to human activities. Overall, the results demonstrated that RCC is a reliable model to describe the distribution of macrobenthic communities in river networks. In socio-ecological systems, the local and lateral dimensions postulated by the RES theory could be mainly related to surrounding land use and naturalness degree.

In this study, we investigate the processes that influence the diversity of planktonic communities in space and time. We split the research into two approach. In the first, we evaluated the effect of different temporal scales on the structure of planktonic communities (ciliates, zooplankton and phytoplankton). We used as model two lakes located at the Upper Paraná River floodplain, and a data time series of 15 years. The results suggested that community variation in both fine (months) and broad (years) temporal scales had a high importance for plankton diversity in floodplain lakes. However, the processes that influenced the composition changes varied among communities. Phytoplankton and zooplankton seem to respond to deterministic processes (resource availability and grazing), while variation of ciliates seems to be influenced mainly by stochastic processes. In the second approach, we evaluated the effect of the construction of a reservoir on the spatial and temporal patterns of plankton (zooplankton and phytoplankton). In this study, we were also interested in analyzing how the influence of dispersion and the environment on these communities changes over time. The results suggested that the construction of a reservoir adversely affects the regional diversity of the plankton by reducing the variation in the space and time of the communities. Also, that the spatial variation of the communities was controlled primarily by environmental processes before the reservoir construction, and by spatial processes associated with high dispersion after the damming because the increased connectivity. Investigou-se os processos que influenciam a diversidade de comunidades planctônicas no espaço e no tempo. Avaliou-se na primeira abordagem o efeito de diferentes escalas temporais sobre a estrutura de comunidades planctônicas (ciliados, zooplâncton e fitoplâncton). Utilizou-se como modelo duas lagoas da planície de inundação do alto rio Paraná e uma série de dados de 15 anos. Os resultados obtidos indicaram que a variação da comunidade em escalas temporais finas (meses) e amplas (anos) tem grande importância para a diversidade de plâncton em lagos de planície de inundação. No entanto, os processos que influenciam as mudanças na composição variam entre as comunidades. O fitoplâncton e o zooplâncton parecem responder a processos deterministas (disponibilidade de recursos e herbivoria), enquanto que a variação dos ciliados parece ser influenciada principalmente por processos estocásticos. Na segunda abordagem, avaliou-se o efeito da construção de um barramento sobre os padrões espaciais e temporais do plâncton (zooplâncton e fitoplâncton). Analisou-se também, como a influência da dispersão e o ambiente sobre essas comunidades muda no tempo. Os resultados obtidos indicaram que a construção de um reservatório afeta negativamente a diversidade regional do plâncton por diminuir a variação no espaço e no tempo das comunidades. E também, que a variação espacial das comunidades foi controlada principalmente por processos ambientais antes do barramento, e por processos espaciais associados com alta dispersão após o barramento devido ao aumento da conectividade. 77 f

International audience; This review focuses on the analysis of temporal beta diversity, which is the variation in community composition along time in a study area. Temporal beta diversity is measured by the variance of the multivariate community composition time series and that variance can be partitioned using appropriate statistical methods. Some of these methods are classical, such as simple or canonical ordination, whereas others are recent, including the methods of temporal eigenfunction analysis developed for multiscale exploration (i.e. addressing several scales of variation) of univariate or multivariate response data, reviewed, to our knowledge for the first time in this review. These methods are illustrated with ecological data from 13 years of benthic surveys in Chesapeake Bay, USA. The following methods are applied to the Chesapeake data: distance-based Moran's eigenvector maps, asymmetric eigenvector maps, scalogram, variation partitioning, multivariate correlogram, multivariate regression tree, and two-way MANOVA to study temporal and space-time variability. Local (temporal) contributions to beta diversity (LCBD indices) are computed and analysed graphically and by regression against environmental variables, and the role of species in determining the LCBD values is analysed by correlation analysis. A tutorial detailing the analyses in the R language is provided in an appendix.

Time-series modelling techniques are powerful tools for studying temporal scaling structures and dynamics present in ecological and other complex systems and are gaining popularity for assessing resilience quantitatively. Among other methods, canonical ordinations based on redundancy analysis are increasingly used for determining temporal scaling patterns that are inherent in ecological data. However, modelling outcomes and thus inference about ecological dynamics and resilience may vary depending on the approaches used. In this study, we compare the statistical performance, logical consistency and information content of two approaches: (i) asymmetric eigenvector maps (AEM) that account for linear trends and (ii) symmetric distance-based Moran's eigenvector maps (MEM), which requires detrending of raw data to remove linear trends prior to analysis. Our comparison is done using long-term water quality data (25 years) from three Swedish lakes. This data set therefore provides the opportunity for assessing how the modelling approach used affects performance and inference in time series modelling. We found that AEM models had consistently more explanatory power than MEM, and in two out of three lakes AEM extracted one more temporal scale than MEM. The scale-specific patterns detected by AEM and MEM were uncorrelated. Also individual water quality variables explaining these patterns differed between methods, suggesting that inferences about systems dynamics are dependent on modelling approach. These findings suggest that AEM might be more suitable for assessing dynamics in time series analysis compared to MEM when temporal trends are relevant. The AEM approach is logically consistent with temporal autocorrelation where earlier conditions can influence later conditions but not vice versa. The symmetric MEM approach, which ignores the asymmetric nature of time, might be suitable for addressing specific questions about the importance of correlations in fluctuation patterns where there are no confounding elements of linear trends or a need to assess causality.