Enriquecimento semântico de modelos ecológicos baseados em raciocínio qualitativo : um estudo de caso sobre a dinâmica de comunidades de vegetação lenhosa no cerrado brasileiro

Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Biológicas, Programa de Pós-Graduação em Ecologia, 2015.

Assessment of catches, landings and fishing effort as useful tools for MPA management

Marine protected areas (MPAs) have been widely recognized as a tool to achieve both fisheries management and conservation goals. Simultaneously achieving these multiple goals is difficult due to conflicts between conservation (often long-term) and economic (often short-term) objectives. MPA implementation often includes additional control measures on fisheries (e.g. vessel size restrictions, gear exclusion, catch controls) that in the short-term may have impacts on local fishers' communities. Thus, monitoring fisheries catches before, during and after MPA implementation is essential to document changes in fisheries activities and to evaluate the impact of MPAs in fishers' communities. Remarkably, in contrast with standard fisheries-independent biological surveys, these data are rarely measured at appropriate spatial scales following MPA implementation. Here, the effects of MPA implementation on local fisheries are assessed in a temperate MPA (Arrabida Marine Park, Portugal), using fisheries monitoring methods combining spatial distribution of fishing effort, on-board observations and official landings statistics at scales appropriate to the Marine Park. Fisheries spatial distribution, fishing effort, on-board data collection and official landings registered for the same vessels over time were analysed between 2004 and 2010. The applicability and reliability of using landings statistics alone was tested (i.e. when no sampling data are available) and we conclude that landings data alone only allow the identification of general patterns. The combination of landings information (which is known to be unreliable in many coastal communities) with other methods, provides an effective tool to evaluate fisheries dynamics in response to MPA implementation. As resources for monitoring socio-ecological responses to MPAs are frequently scarce, the use of landings data calibrated with fisheries information (from vessels, gear distribution and on-board data) is a valuable tool applicable to many worldwide coastal small-scale fisheries. (C) 2015 Elsevier B.V. All rights reserved.

Species richness and composition of butterfly assemblages (Lepidoptera:Rhopalocera) along the altitudinal gradient of Serra da Estrela

Os gradientes altitudinais são importantes modelos em ecologia pois permitem, numa escala reduzida, estudar a influência da variação de diversas variáveis ambientais nos padrões de biodiversidade existentes. Estes padrões são influenciados por diversos factores, desde variáveis climáticas às relacionadas com a perturbação humana. Nesta tese é estudada a variação na composição das comunidades de borboletas ao longo do gradiente altitudinal na Serra da Estrela e são testadas duas hipóteses sobre os padrões de riqueza específica ao longo do gradiente altitudinal: a regra de Rapoport e o “Mid Domain Effect” (MDE). Foram assinaladas 70 espécies de borboletas neste estudo e constatou-se que a variação na riqueza de espécies de borboletas apresenta um padrão “mid peak” apoiando o MDE. Verificou-se também que as comunidades de borboletas do mesmo nível altitudinal são mais semelhantes entre si independentemente da vertente em que se encontram e são também mais semelhantes com as comunidades dos níveis altitudinais adjacentes. Finalmente, a análise da distribuição de algumas espécies ameaçadas de borboletas torna evidente a necessidade de realização de mais estudos sobre a biologia da conservação deste grupo de animais em Portugal; Abstract: Altitudinal gradients are important ecological models because they allow us to study the influence of diverse environmental variables in the existing biodiversity patterns. These patterns are influenced by various factors, from climatic variables to variables related to human disturbance. In this thesis we studied the variations in the composition of the butterfly assemblages along the altitudinal gradient of Serra da Estrela and we tested two hypotheses regarding the species richness patterns along the altitudinal gradient: Rapoport’s rule and the Mid Domain Effect (MDE). In this study 70 butterfly species were marked recorded and it was observed that the butterfly species richness presents a mid-peak pattern supporting the MDE. It was also noted that the butterfly assemblages in the same altitudinal level show more similarity within themselves regardless of the slope they are found in, and are also more similar to the assemblages present in the adjacent altitudinal levels. Finally, the distribution of some threatened butterfly species was analyzed and it became evident the need to do more studies regarding the conservation biology of this animal group in Portugal.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Predicting loss and fragmentation of habitat of the vulnerable subtropical rainforest tree Macadamia integrifolia with models developed from compiled ecological data

Habitat models are widely used in ecology, however there are relatively few studies of rare species, primarily because of a paucity of survey records and lack of robust means of assessing accuracy of modelled spatial predictions. We investigated the potential of compiled ecological data in developing habitat models for Macadamia integrifolia, a vulnerable mid-stratum tree endemic to lowland subtropical rainforests of southeast Queensland, Australia. We compared performance of two binomial models—Classification and Regression Trees (CART) and Generalised Additive Models (GAM)—with Maximum Entropy (MAXENT) models developed from (i) presence records and available absence data and (ii) developed using presence records and background data. The GAM model was the best performer across the range of evaluation measures employed, however all models were assessed as potentially useful for informing in situ conservation of M. integrifolia, A significant loss in the amount of M. integrifolia habitat has occurred (p < 0.05), with only 37% of former habitat (pre-clearing) remaining in 2003. Remnant patches are significantly smaller, have larger edge-to-area ratios and are more isolated from each other compared to pre-clearing configurations (p < 0.05). Whilst the network of suitable habitat patches is still largely intact, there are numerous smaller patches that are more isolated in the contemporary landscape compared with their connectedness before clearing. These results suggest that in situ conservation of M. integrifolia may be best achieved through a landscape approach that considers the relative contribution of small remnant habitat fragments to the species as a whole, as facilitating connectivity among the entire network of habitat patches.

Information Behavior: A Socio-Cognitive Ability

Abstract: How has human information behavior evolved? Our paper explores this question in the form of notions, models and theories about the relationship between information behavior and human evolution. Alexander’s Ecological Dominance and Social Competition/Cooperation (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality. His model provides a basis for explaining the evolution of human socio-cognitive abilities, including ecological dominance, and social competition/cooperation. Our paper examines the human trait of information behavior as a socio-cognitive ability related to ecological dominance, and social competition/cooperation. The paper first outlines what is meant by information behavior from various interdisciplinary perspectives. We propose that information behavior is a socio-cognitive ability that is related to and enables other sociocognitive abilities such as human ecological dominance, and social competition/cooperation. The paper reviews the current state of evolutionary approaches to information behavior and future directions for this research . Keywords: information behavior, socio-cognitive ability, ecological dominance, social competition, social cooperation.

Ecosystem management along ephemeral rivers: Trading off socio-economic water supply and vegetation conservation under flood regime uncertainty

In ecosystems driven by water availability, plant community dynamics depend on complex interactions between vegetation, hydrology, and human water resources use. Along ephemeral rivers—where water availability is erratic—vegetation and people are particularly vulnerable to changes in each other's water use. Sensible management requires that water supply be maintained for people, while preserving ecosystem health. Meeting such requirements is challenging because of the unpredictable water availability. We applied information gap decision theory to an ecohydrological system model of the Kuiseb River environment in Namibia. Our aim was to identify the robustness of ecosystem and water management strategies to uncertainties in future flood regimes along ephemeral rivers. We evaluated the trade-offs between alternative performance criteria and their robustness to uncertainty to account for both (i) human demands for water supply and (ii) reducing the risk of species extinction caused by water mining. Increasing uncertainty of flood regime parameters reduced the performance under both objectives. Remarkably, the ecological objective (species coexistence) was more sensitive to uncertainty than the water supply objective. However, within each objective, the relative performance of different management strategies was insensitive to uncertainty. The ‘best’ management strategy was one that is tuned to the competitive species interactions in the Kuiseb environment. It regulates the biomass of the strongest competitor and, thus, at the same time decreases transpiration, thereby increasing groundwater storage and reducing pressure on less dominant species. This robust mutually acceptable strategy enables species persistence without markedly reducing the water supply for humans. This study emphasises the utility of ecohydrological models for resource management of water-controlled ecosystems. Although trade-offs were identified between alternative performance criteria and their robustness to uncertain future flood regimes, management strategies were identified that help to secure an ecologically sustainable water supply.

Ecological and Socio Economic Assesment of Varthur Wetlnd, Bengaluru (India)

Wetlands are the most productive ecosystems, recognized globally for its vital role in sustaining a wide array of biodiversity and provide goods and services. However despite their important role in maintaining the ecology and economy, wetlands in India are endangered by inattention and lack of appreciation for their role. Increased anthropogenic activities such as intense agriculture practices, indiscriminate disposal of industrial effluents and sewage wastes have altered the physical, chemical as well as biological integrity of the ecosystem. This has resulted in the ecological degradation, which is evident from the current ecosystem valuation of Varthur wetland. Global valuation of coastal wetland ecosystem shows a total of 14,785/ha US$ annual economic value. An earlier study of relatively pristine wetland in Bangalore shows the value of Rs. 10,435/ha/day while the polluted wetland shows the value of Rs.20/ha/day. In contrast to this, Varthur, a sewage fed wetland has a value of Rs.118.9/ha/day. The pollutants and subsequent contamination of the wetland has telling effects such as disappearance of native species, dominance of invasive exotic species (such as African catfish), in addition to profuse breeding of disease vectors and pathogens. Water quality analysis revealed of high phosphates (4.22-5.76 ppm) level in addition to the enhanced BOD (119-140 ppm) and decreased DO (0-1.06 ppm). The amplified decline of ecosystem goods and services with degradation of water quality necessitates the implementation of sustainable management strategies to recover the lost wetland benefits.

Ecological and socio-economic assessment of Varthur wetland, Bengaluru (India)

Wetlands are the most productive ecosystems, recognized globally for its vital role in sustaining a wide array of biodiversity and provide goods and services. However despite their important role in maintaining the ecology and economy, wetlands in India are endangered by inattention and lack of appreciation for their role. Increased anthropogenic activities such as intense agriculture practices, indiscriminate disposal of industrial effluents and sewage wastes have altered the physical, chemical as well as biological integrity of the ecosystem. This has resulted in the ecological degradation, which is evident from the current ecosystem valuation of Varthur wetland. Global valuation of coastal wetland ecosystem shows a total of 14,785/ha US$ annual economic value. An earlier study of relatively pristine wetland in Bangalore shows the value of Rs. 10,435/ha/day while the polluted wetland shows the value of Rs.20/ha/day. In contrast to this, Varthur, a sewage fed wetland has a value of Rs.118.9/ha/day. The pollutants and subsequent contamination of the wetland has telling effects such as disappearance of native species, dominance of invasive exotic species (such as African catfish), in addition to profuse breeding of disease vectors and pathogens. Water quality analysis revealed of high phosphates (4.22-5.76 ppm) level in addition to the enhanced BOD (119-140 ppm) and decreased DO (0-1.06 ppm). The amplified decline of ecosystem goods and services with degradation of water quality necessitates the implementation of sustainable management strategies to recover the lost wetland benefits.

Annotated bibliography on socio-economic and ecological impacts of marine protected areas in Pacific Island countries

The bibliography is to highlight impacts on fisheries and livelihoods attributed to coral reef marine protected areas in Pacific Island countries and territories. Included in this collection is literature that reports various forms of reef area management practiced in Pacific Island countries: reserves, sanctuaries, permanent or temporary closed areas, community and traditional managed areas. (Document contains 36 pages)

Granularity and disaggregation in compositional modelling with applications to ecological systems

J. Keppens and Q. Shen. Granularity and disaggregation in compositional modelling with applications to ecological systems. Applied Intelligence, 25(3):269-292, 2006.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.