953 resultados para Ecological processes


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Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.

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Oribatid mites are one of the most abundant and species rich group in soil mesofauna. In spite of this, we have limited knowledge on the role they play in ecological processes. Since they are small like other mesofauna members and live a hidden life, their observation is difficult. Their life style, interactions with other organisms and role in soil decomposition processes can be investigated with laboratory experiments more exactly and effectively. While the literature of microcosm studies is very extensive, relatively few review papers have been written about the methodology of microcosm studies. The present review summarizes details of techniques that have been applied laboratory microcosms involving oribatid mites. It is shown what one should keep in mind in planning, composing and setting up a microcosm. Our comparative evaluation reveals how the laboratory experiments were maintained and manipulated and what kind of information was extracted. This methodological review can be useful in preparing microcosm experiments applied to other animal groups as well.

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Biological diversity is threatened worldwide and it is a priority to generate more information that can be used both for understanding ecological processes and determining conservation strategies. For my dissertation, I focused on amphibian diversity patterns in lowland rainforests of southwestern Amazonia to evaluate the importance of habitat heterogeneity in the region. My main purpose was to test the hypothesis that amphibian communities in different forest types differ in species richness, composition, and abundance. I used standardized visual encounter surveys to quantify the species composition and abundance of amphibians at four sites, each containing four forest types (floodplain, terra firme, bamboo, and palm swamp). I used leaf-litter plots to evaluate the effect of soil and leaf-litter characteristics on species richness and abundance of leaf-litter frogs. I intensively sampled at one site and then sampled three other sites (distance among sites varied 3.5–105 km) to evaluate whether the patterns observed at one site were similar elsewhere. I also updated the information on threatened and potentially threatened amphibians in Peru and my study region. I found that no species appears to have experienced population declines in southeastern Peru, suggesting that the region still contains the original species pool. My results support the hypothesis that amphibian communities differ across forest types and that patterns observed at the local scale (one site) are similar at the regional scale (four sites). My data also indicate that there is no correlation between species composition and geographic distance among sites. Instead, an important proportion of the gamma diversity is represented by habitat-related beta diversity. My leaf-litter plot data showed that part of the variation in the leaf-litter community structure is explained by soil and litter characteristics. I found that soil total phosphorus and, to a lesser extent, humidity, leaf-litter mass, and pH is linked to species presence/absence and abundance. My study provides the first standardized, quantitative comparison of amphibian community structure across four major forest types in southwestern Amazonia and highlights the fact that forest types are complementary and necessary for maintaining high species richness in the region.

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The freshwater Everglades is a complex system containing thousands of tree islands embedded within a marsh-grassland matrix. The tree island-marsh mosaic is shaped and maintained by hydrologic, edaphic and biological mechanisms that interact across multiple scales. Preserving tree islands requires a more integrated understanding of how scale-dependent phenomena interact in the larger freshwater system. The hierarchical patch dynamics paradigm provides a conceptual framework for exploring multi-scale interactions within complex systems. We used a three-tiered approach to examine the spatial variability and patterning of nutrients in relation to site parameters within and between two hydrologically defined Everglades landscapes: the freshwater Marl Prairie and the Ridge and Slough. Results were scale-dependent and complexly interrelated. Total carbon and nitrogen patterning were correlated with organic matter accumulation, driven by hydrologic conditions at the system scale. Total and bioavailable phosphorus were most strongly related to woody plant patterning within landscapes, and were found to be 3 to 11 times more concentrated in tree island soils compared to surrounding marshes. Below canopy resource islands in the slough were elongated in a downstream direction, indicating soil resource directional drift. Combined multi-scale results suggest that hydrology plays a significant role in landscape patterning and also the development and maintenance of tree islands. Once developed, tree islands appear to exert influence over the spatial distribution of nutrients, which can reciprocally affect other ecological processes.

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Seascape ecology provides a useful framework from which to understand the processes governing spatial variability in ecological patterns. Seascape context, or the composition and pattern of habitat surrounding a focal patch, has the potential to impact resource availability, predator-prey interactions, and connectivity with other habitats. For my dissertation research, I combined a variety of approaches to examine how habitat quality for fishes is influenced by a diverse range of seascape factors in sub-tropical, back-reef ecosystems. In the first part of my dissertation, I examined how seascape context can affect reef fish communities on an experimental array of artificial reefs created in various seascape contexts in Abaco, Bahamas. I found that the amount of seagrass at large spatial scales was an important predictor of community assembly on these reefs. Additionally, seascape context had differing effects on various aspects of habitat quality for the most common reef species, White grunt Haemulon plumierii. The amount of seagrass at large spatial scales had positive effects on fish abundance and secondary production, but not on metrics of condition and growth. The second part of my dissertation focused on how foraging conditions for fish varied across a linear seascape gradient in the Loxahatchee River estuary in Florida, USA. Gray snapper, Lutjanus griseus, traded food quality for quantity along this estuarine gradient, maintaining similar growth rates and condition among sites. Additional work focused on identifying major energy flow pathways to two consumers in oyster-reef food webs in the Loxahatchee. Algal and microphytobenthos resource pools supported most of the production to these consumers, and body size for one of the consumers mediated food web linkages with surrounding mangrove habitats. All of these studies examined a different facet of the importance of seascape context in governing ecological processes occurring in focal habitats and underscore the role of connectivity among habitats in back-reef systems. The results suggest that management approaches consider the surrounding seascape when prioritizing areas for conservation or attempting to understand the impacts of seascape change on focal habitat patches. For this reason, spatially-based management approaches are recommended to most effectively manage back-reef systems.

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Dissolved organic matter (DOM) is an essential component of the carbon cycle and a critical driver in controlling variety of biogeochemical and ecological processes in wetlands. The quality of this DOM as it relates to composition and reactivity is directly related to its sources and may vary on temporal and spatial scales. However, large scale, long-term studies of DOM dynamics in wetlands are still scarce in the literature. Here we present a multi-year DOM characterization study for monthly surface water samples collected at 14 sampling stations along two transects within the greater Everglades, a subtropical, oligotrophic, coastal freshwater wetland-mangrove-estuarine ecosystem. In an attempt to assess quantitative and qualitative variations of DOM on both spatial and temporal scales, we determined dissolved organic carbon (DOC) values and DOM optical properties, respectively. DOM quality was assessed using, excitation emission matrix (EEM) fluorescence coupled with parallel factor analysis (PARAFAC). Variations of the PARAFAC components abundance and composition were clearly observed on spatial and seasonal scales. Dry versus wet season DOC concentrations were affected by dry-down and re-wetting processes in the freshwater marshes, while DOM compositional features were controlled by soil and higher plant versus periphyton sources respectively. Peat-soil based freshwater marsh sites could be clearly differentiated from marl-soil based sites based on EEM–PARAFAC data. Freshwater marsh DOM was enriched in higher plant and soil-derived humic-like compounds, compared to estuarine sites which were more controlled by algae- and microbial-derived inputs. DOM from fringe mangrove sites could be differentiated between tidally influenced sites and sites exposed to long inundation periods. As such coastal estuarine sites were significantly controlled by hydrology, while DOM dynamics in Florida Bay were seasonally driven by both primary productivity and hydrology. This study exemplifies the application of long term optical properties monitoring as an effective technique to investigate DOM dynamics in aquatic ecosystems. The work presented here also serves as a pre-restoration condition dataset for DOM in the context of the Comprehensive Everglades Restoration Plan (CERP).

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Biological diversity is threatened worldwide and it is a priority to generate more information that can be used both for understanding ecological processes and determining conservation strategies. For my dissertation, I focused on amphibian diversity patterns in lowland rainforests of southwestern Amazonia to evaluate the importance of habitat heterogeneity in the region. My main purpose was to test the hypothesis that amphibian communities in different forest types differ in species richness, composition, and abundance. I used standardized visual encounter surveys to quantify the species composition and abundance of amphibians at four sites, each containing four forest types (floodplain, terra firme, bamboo, and palm swamp). I used leaf-litter plots to evaluate the effect of soil and leaf-litter characteristics on species richness and abundance of leaf-litter frogs. I intensively sampled at one site and then sampled three other sites (distance among sites varied 3.5-105 km) to evaluate whether the patterns observed at one site were similar elsewhere. I also updated the information on threatened and potentially threatened amphibians in Peru and my study region. I found that no species appears to have experienced population declines in southeastern Peru, suggesting that the region still contains the original species pool. My results support the hypothesis that amphibian communities differ across forest types and that patterns observed at the local scale (one site) are similar at the regional scale (four sites). My data also indicate that there is no correlation between species composition and geographic distance among sites. Instead, an important proportion of the gamma diversity is represented by habitat-related beta diversity. My leaf-litter plot data showed that part of the variation in the leaf-litter community structure is explained by soil and litter characteristics. I found that soil total phosphorus and, to a lesser extent, humidity, leaf-litter mass, and pH is linked to species presence/absence and abundance. My study provides the first standardized, quantitative comparison of amphibian community structure across four major forest types in southwestern Amazonia and highlights the fact that forest types are complementary and necessary for maintaining high species richness in the region.

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There are several abiotic factors reported in the literature as regulators of the distribution of fish species in marine environments. Among them stand out structural complexity of habitat, benthic composition, depth and distance from the coast are usually reported as positive influencers in the diversity of difentes species, including reef fish. These are dominant elements in reef systems and considered high ecological and socioeconomic importance. Understanding how the above factors influence the distribution and habitat use of reef fish communities are important for their management and conservation. Thus, this study aims to evaluate the influence of these variables on the community of reef fishes along an environmental gradient of depth and distance from shore base in sandstone reefs in the coast of state of Rio Grande do Norte, Brazil. These variables are also used for creating a simple predictive model reef fish biomass for the environment studied. Data collection was performed through visual surveys in situ, and recorded environmental data (structural complexity of habitat, type of coverage of the substrate, benthic invertebrates) and ecological (wealth, abundance and reef fish size classes). As a complement, information on the diet were raised through literature and the biomass was estimated from the length-weight relationship of each species. Overall, the reefs showed a low coverage by corals and the Shallow reefs, Intermediate I and II dominated by algae and the Funds by algae and sponges. The complexity has increased along the gradient and positively influenced the species richness and abundance. Both attributes influenced in the structure of the reef fish community, increasing the richness, abundance and biomass of fish as well as differentiating the trophic structure of the community along the depth gradient and distance from the coast. Distribution and use of habitat by recifas fish was associated with food availability. The predictor model identified depth, roughness and coverage for foliose algae, calcareous algae and soft corals as the most significant variables influencing in the biomass of reef fish. In short, the description and understanding of these patterns are important steps to elucidate the ecological processes. In this sense, our approach provides a new understanding of the structure of the reef fish community of Rio Grande do Norte, allowing understand a part of a whole and assist future monitoring actions, evaluation, management and conservation of these and other reefs of Brazil.

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Physiological responses of larval stages can differ from those of the adults, affecting key ecological processes. Therefore, developing a mechanistic understanding of larval responses to environmental conditions is essential vis-à-vis climate change. We studied the thermal tolerance windows, defined by lower and upper pejus (Tp) and critical temperatures (Tc), of zoea I, II, and megalopa stages of the Chilean kelp crab Taliepus dentatus. Tp limits determine the temperature range where aerobic scope is maximal and functioning of the organism is unrestrained and were estimated from direct observations of larval activity. Tc limits define the transition from aerobic to anaerobic metabolism, and were estimated from the relationship between standard metabolic rate and temperature. Zoea I showed the broadest, Zoea II an intermediate, and megalopae the narrowest tolerance window (Tp). Optimum performance in megalopae was limited to Tp between 11 and 15°C, while their Tc ranged between 7 and 19°C. Although Tc may be seldom encountered by larvae, the narrower Tp temperatures can frequently expose larvae to unfavorable conditions that can drastically constrain their performance. Temperatures beyond the Tp range of megalopae have been observed in most spring and summer months in central Chile, and can have important consequences for larval swimming performance and impair their ability to avoid predators or settle successfully. Besides the well-documented effects of temperature on development time, variability in field temperatures beyond Tp can affect performance of particular larval stages, which could drive large-scale variability in recruitment and population dynamics of T. dentatus and possibly other invertebrate species.

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The distribution, abundance, behaviour, and morphology of marine species is affected by spatial variability in the wave environment. Maps of wave metrics (e.g. significant wave height Hs, peak energy wave period Tp, and benthic wave orbital velocity URMS) are therefore useful for predictive ecological models of marine species and ecosystems. A number of techniques are available to generate maps of wave metrics, with varying levels of complexity in terms of input data requirements, operator knowledge, and computation time. Relatively simple "fetch-based" models are generated using geographic information system (GIS) layers of bathymetry and dominant wind speed and direction. More complex, but computationally expensive, "process-based" models are generated using numerical models such as the Simulating Waves Nearshore (SWAN) model. We generated maps of wave metrics based on both fetch-based and process-based models and asked whether predictive performance in models of benthic marine habitats differed. Predictive models of seagrass distribution for Moreton Bay, Southeast Queensland, and Lizard Island, Great Barrier Reef, Australia, were generated using maps based on each type of wave model. For Lizard Island, performance of the process-based wave maps was significantly better for describing the presence of seagrass, based on Hs, Tp, and URMS. Conversely, for the predictive model of seagrass in Moreton Bay, based on benthic light availability and Hs, there was no difference in performance using the maps of the different wave metrics. For predictive models where wave metrics are the dominant factor determining ecological processes it is recommended that process-based models be used. Our results suggest that for models where wave metrics provide secondarily useful information, either fetch- or process-based models may be equally useful.

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River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950 - December 2015) on a 0.5° x 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

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River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first collect an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 11) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950-December 2014) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

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Ecosystem reconfigurations arising from climate-driven changes in species distributions are expected to have profound ecological, social, and economic implications. Here we reveal a rapid climate-driven regime shift of Australian temperate reef communities, which lost their defining kelp forests and became dominated by persistent seaweed turfs. After decades of ocean warming, extreme marine heat waves forced a 100-kilometer range contraction of extensive kelp forests and saw temperate species replaced by seaweeds, invertebrates, corals, and fishes characteristic of subtropical and tropical waters. This community-wide tropicalization fundamentally altered key ecological processes, suppressing the recovery of kelp forests.

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Ecosystem reconfigurations arising from climate-driven changes in species distributions are expected to have profound ecological, social, and economic implications. Here we reveal a rapid climate-driven regime shift of Australian temperate reef communities, which lost their defining kelp forests and became dominated by persistent seaweed turfs. After decades of ocean warming, extreme marine heat waves forced a 100-kilometer range contraction of extensive kelp forests and saw temperate species replaced by seaweeds, invertebrates, corals, and fishes characteristic of subtropical and tropical waters. This community-wide tropicalization fundamentally altered key ecological processes, suppressing the recovery of kelp forests.

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General knowledge of the small, invisible, or hidden organisms that make soil one of the most biodiverse habitats on Earth is thought to be scarce, despite their importance in food systems and agricultural production. We provide the first worldwide review of high-quality research that reports on farmers’ knowledge of soil organisms in agriculture. The depth of farmers’ knowledge varied; some farming communities held detailed local taxonomies and observations of soil biota, or used soil biological activity as indicators of soil fertility, while others were largely unaware of soil fauna. Elicitation of soil biota knowledge was often incidental to the main research goal in many of the reviewed studies. Farmers are rarely deliberately or deeply consulted by researchers on their existing knowledge of soil biota, soil ecology, or soil ecological processes. Deeper understanding of how farmers use and value soil life can lead to more effective development of collaborative extension programs, policies, and management initiatives directed at maintaining healthy, living soils.