The effects of landscape modifications on the long-term persistence of animal populations

Background: The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition. Methodology/Principal Findings: Starting with a real agricultural landscape, we progressively reduced landscape complexity by (i) homogenizing habitat patch shapes, (ii) randomizing the locations of the patches, and (iii) randomizing the size of the patches. The first two steps increased landscape fragmentation. We assessed the effects of these manipulations on the long-term persistence of animal populations by measuring equilibrium population sizes and time to recovery after disturbance. Patch rearrangement and the presence of corridors had a large effect on the population dynamics of species whose local success depends on the surrounding terrain. Landscape modifications that reduced population sizes increased recovery times in the short-dispersing species, making small populations vulnerable to increasing disturbance. The species that were most strongly affected by large disturbances fluctuated little in population sizes in years when no perturbations took place. Significance: Traditional approaches to the management and conservation of populations use either classical methods of population analysis, which fail to adequately account for the spatial configurations of landscapes, or landscape ecology, which accounts for landscape structure but has difficulty predicting the dynamics of populations living in them. Here we show how realistic and replicable individual-based models can bridge the gap between non-spatial population theory and non-dynamic landscape ecology. A major strength of the approach is its ability to identify population vulnerabilities not detected by standard population viability analyses.

Recent Glacier Retreat Exceeds Internal Variability

Glacier fluctuations exclusively due to internal variations in the climate system are simulated using downscaled integrations of the ECHAM4/OPYC coupled general circulation model (GCM). A process-based modeling approach using a mass balance model of intermediate complexity and a dynamic ice flow model considering simple shearing flow and sliding are applied. Multimillennia records of glacier length fluctuations for Nigardsbreen (Norway) and Rhonegletscher (Switzerland) are simulated using autoregressive processes determined by statistically downscaled GCM experiments. Return periods and probabilities of specific glacier length changes using GCM integrations excluding external forcings such as solar irradiation changes, volcanic, or anthropogenic effects are analyzed and compared to historical glacier length records. Preindustrial fluctuations of the glaciers as far as observed or reconstructed, including their advance during the “Little Ice Age,” can be explained by internal variability in the climate system as represented by a GCM. However, fluctuations comparable to the present-day glacier retreat exceed any variation simulated by the GCM control experiments and must be caused by external forcing, with anthropogenic forcing being a likely candidate.

Modelling fire and the terrestrial carbon balance

Four CO2 concentration inversions and the Global Fire Emissions Database (GFED) versions 2.1 and 3 are used to provide benchmarks for climate-driven modeling of the global land-atmosphere CO2 flux and the contribution of wildfire to this flux. The Land surface Processes and exchanges (LPX) model is introduced. LPX is based on the Lund-Potsdam-Jena Spread and Intensity of FIRE (LPJ-SPITFIRE) model with amended fire probability calculations. LPX omits human ignition sources yet simulates many aspects of global fire adequately. It captures the major features of observed geographic pattern in burnt area and its seasonal timing and the unimodal relationship of burnt area to precipitation. It simulates features of geographic variation in the sign of the interannual correlations of burnt area with antecedent dryness and precipitation. It simulates well the interannual variability of the global total land-atmosphere CO2 flux. There are differences among the global burnt area time series from GFED2.1, GFED3 and LPX, but some features are common to all. GFED3 fire CO2 fluxes account for only about 1/3 of the variation in total CO2 flux during 1997–2005. This relationship appears to be dominated by the strong climatic dependence of deforestation fires. The relationship of LPX-modeled fire CO2 fluxes to total CO2 fluxes is weak. Observed and modeled total CO2 fluxes track the El Niño–Southern Oscillation (ENSO) closely; GFED3 burnt area and global fire CO2 flux track the ENSO much less so. The GFED3 fire CO2 flux-ENSO connection is most prominent for the El Niño of 1997–1998, which produced exceptional burning conditions in several regions, especially equatorial Asia. The sign of the observed relationship between ENSO and fire varies regionally, and LPX captures the broad features of this variation. These complexities underscore the need for process-based modeling to assess the consequences of global change for fire and its implications for the carbon cycle.

Effects of noise and by-catch on a Danish harbour porpoise population

Ships and wind turbines generate noise, which can have a negative impact on marine mammal populations by scaring animals away. Effective modelling of how this affects the populations has to take account of the location and timing of disturbances. Here we construct an individual-based model of harbour porpoises in the Inner Danish Waters. Individuals have their own energy budgets constructed using established principles of physiological ecology. Data are lacking on the spatial distribution of food which is instead inferred from knowledge of time-varying porpoise distributions. The model produces plausible patterns of population dynamics and matches well the age distribution of porpoises caught in by-catch. It estimates the effect of existing wind farms as a 10% reduction in population size when food recovers fast (after two days). Proposed new wind farms and ships do not result in further population declines. The population is however sensitive to variations in mortality resulting from by-catch and to the speed at which food recovers after being depleted. If food recovers slowly the effect of wind turbines becomes negligible, whereas ships are estimated to have a significant negative impact on the population. Annual by-catch rates ≥10% lead to monotonously decreasing populations and to extinction, and even the estimated by-catch rate from the adjacent area (approximately 4.1%) has a strong impact on the population. This suggests that conservation efforts should be more focused on reducing by-catch in commercial gillnet fisheries than on limiting the amount of anthropogenic noise. Individual-based models are unique in their ability to take account of the location and timing of disturbances and to show their likely effects on populations. The models also identify deficiencies in the existing database and can be used to set priorities for future field research.

Nonlinear identification using orthogonal forward regression with nested optimal regularization

An efficient data based-modeling algorithm for nonlinear system identification is introduced for radial basis function (RBF) neural networks with the aim of maximizing generalization capability based on the concept of leave-one-out (LOO) cross validation. Each of the RBF kernels has its own kernel width parameter and the basic idea is to optimize the multiple pairs of regularization parameters and kernel widths, each of which is associated with a kernel, one at a time within the orthogonal forward regression (OFR) procedure. Thus, each OFR step consists of one model term selection based on the LOO mean square error (LOOMSE), followed by the optimization of the associated kernel width and regularization parameter, also based on the LOOMSE. Since like our previous state-of-the-art local regularization assisted orthogonal least squares (LROLS) algorithm, the same LOOMSE is adopted for model selection, our proposed new OFR algorithm is also capable of producing a very sparse RBF model with excellent generalization performance. Unlike our previous LROLS algorithm which requires an additional iterative loop to optimize the regularization parameters as well as an additional procedure to optimize the kernel width, the proposed new OFR algorithm optimizes both the kernel widths and regularization parameters within the single OFR procedure, and consequently the required computational complexity is dramatically reduced. Nonlinear system identification examples are included to demonstrate the effectiveness of this new approach in comparison to the well-known approaches of support vector machine and least absolute shrinkage and selection operator as well as the LROLS algorithm.

Effects of agricultural management practices on earthworm populations and crop yield: validation and application of a mechanistic modelling approach

There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.

Scientific output trends in oral health in Brazil

Objective. To describe dental research trends in Brazil (especially population-based oral health) in the early Twenty-first Century. Methods. The abstracts of studies presented at meetings of the Brazilian Society for Dental Medicine Research (Sociedade Brasileira de Pesquisa Odontologica) from 2001-2006 were assessed in terms of methodological design (aggregate or population-based and individual-based studies, observational and intervention studies, cross-sectional and longitudinal studies); general type (literature review, studies with human subjects, and laboratory studies); and classification into one of the 19 specialty categories recognized by the Brazilian Federal Dentistry Council. Of the 10 406 abstracts presented in this period, 5 203 (50%) were reviewed. Results. Concerning methodological design, 87.5% of the abstracts referred to individual-based studies, whereas 12.5% were of aggregate studies. Concerning the general category, 41.7% referred to studies with human subjects. The remaining abstracts (58.3%) described in vitro (31.1%) or in vivo (23.6%) laboratory research and literature reviews (3.6%). Concerning the Council`s specialty categories, only five had a frequency higher than 10.0%: esthetic dentistry, periodontics, endodontics, pediatric dentistry, and population-based oral health. Conclusions. Brazil`s scientific output in the field of oral health for the period 2001-2006 was balanced, with increasing interest in the area of population-based oral health.

Fragmentation drives tropical forest fragments to early successional states: A modelling study for Brazilian Atlantic forests

Land use leads to massive habitat destruction and fragmentation in tropical forests. Despite its global dimensions the effects of fragmentation on ecosystem dynamics are not well understood due to the complexity of the problem. We present a simulation analysis performed by the individual-based model FORMIND. The model was applied to the Brazilian Atlantic Forest, one of the world`s biodiversity hot spots, at the Plateau of Sao Paulo. This study investigates the long-term effects of fragmentation processes on structure and dynamics of different sized remnant tropical forest fragments (1-100 ha) at community and plant functional type (PFT) level. We disentangle the interplay of single effects of different key fragmentation processes (edge mortality, increased mortality of large trees, local seed loss and external seed rain) using simulation experiments in a full factorial design. Our analysis reveals that particularly small forest fragments below 25 ha suffer substantial structural changes, biomass and biodiversity loss in the long term. At community level biomass is reduced up to 60%. Two thirds of the mid- and late-successional species groups, especially shade-tolerant (late successional climax) species groups are prone of extinction in small fragments. The shade-tolerant species groups were most strongly affected; its tree number was reduced more than 60% mainly by increased edge mortality. This process proved to be the most powerful of those investigated, explaining alone more than 80% of the changes observed for this group. External seed rain was able to compensate approximately 30% of the observed fragmentation effects for shade-tolerant species. Our results suggest that tropical forest fragments will suffer strong structural changes in the long term, leading to tree species impoverishment. They may reach a new equilibrium with a substantially reduced subset of the initial species pool, and are driven towards an earlier successional state. The natural regeneration potential of a landscape scattered with forest fragments appears to be limited, as external seed rain is not able to fully compensate for the observed fragmentation-induced changes. Our findings suggest basic recommendations for the management of fragmented tropical forest landscapes. (C) 2011 Elsevier B.V. All rights reserved.

Redes sociais e a lógica do desvio comportamental em relação às normas de trabalho

This paper aim to check a hypothesis that assumes several behaviors related to social work norm´s obeying as a phenomenon that can be explained by actor´s social network structure and the rational choice processes related to the social norm inside that network, principally the payoff´s analysis received by the closest actors, or neighbors, at a social situation. Taking the sociological paradigm of rational action theory as a basis, the focus is on a debate about the logic of social norms, from Émile Durkheim´s method to Jon Elster´s theory, but also including social network analysis´s variables according to Robert Hanneman; and also Vilfredo Pareto´s constants related to human sociability, at the aim to detect elements that can help the scholars to develop an agent based model which could explain the sociological problem of deviance by a better way than the common sense´s view about morality and ethics at a social work environment

Antimicrobial use and incidence of multidrug-resistant Pseudomonas aeruginosa in a teaching hospital: an ecological approach

Introduction: Multidrug-resistant Pseudomonas aeruginosa is a major threat in healthcare settings. The use of antimicrobials can influence the incidence of resistant strains by direct and indirect mechanisms. The latter can be addressed by ecological studies. Methods: Our group attempted to analyze the relation between the use of antipseudomonal drugs and the incidence of MDR-PA among 18 units from a 400-bed teaching hospital. The study had a retrospective, ecological design, comprising data from 2004 and 2005. Data on the use of four antimicrobials (amikacin, ciprofloxacin, ceftazidime and imipenem) were tested for correlation with the incidence of MDR-PA (defined as isolates resistant to the four antimicrobials of interest) in clinical cultures. Univariate and multivariate linear regression analyses were performed. Results: Significant correlations were determined between use and resistance for all antimicrobials in the univariate analysis: amikacin (standardized correlation coefficient = 0.73, p = 0.001); ciprofloxacin (0.71, p = 0.001); ceftazidime (0.61, p = 0.007) and imipenem (0.87, p < 0.001). In multivariate analysis, only imipenem (0.67, p = 0.01) was independently related to the incidence of multidrug-resistant strains. Conclusions: These findings share similarities with those reported in individual-based observational studies, with possible implications for infection control.

Efeitos do estado e especificidade do treinamento aeróbio na relação %VO2max versus %FCmax durante o ciclismo

OBJETIVO: Determinar os efeitos do estado e especificidade de treinamento aeróbio na relação entre o percentual do consumo máximo de oxigênio (%VO2max) e o percentual da frequência cardíaca máxima (%FCmax) durante o exercício incremental realizado no cicloergômetro. MÉTODOS: Sete corredores, 9 ciclistas, 11 triatletas e 12 sedentários, todos do sexo masculino e aparentemente saudáveis, foram submetidos a um teste incremental até a exaustão no cicloergômetro. Regressões lineares entre %VO2max e %FCmax foram determinadas para cada indivíduo. Com base nessas regressões, foram calculados %FCmax correspondentes a determinados %VO2max (50, 60, 70, 80 e 90%) de cada participante. RESULTADOS: Não foram encontradas diferenças significantes entre todos os grupos nos %FCmax para cada um dos %VO2max avaliados. Analisando-se os voluntários como um único grupo, as médias dos %FCmax correspondentes a 50, 60, 70, 80 e 90% %VO2max foram 67, 73, 80, 87, e 93%, respectivamente. CONCLUSÃO: Nos grupos analisados, a relação entre o %VO2max e %FCmax durante o exercício incremental no ciclismo não é dependente do estado e especificidade do treinamento aeróbio.

Application of differential scanning calorimetry in hair samples as a possible tool in Forensic Science

A calorimetria Exploratória Diferencial (DSC) foi utilizada para estudar o comportamento térmico de amostras de cabelo e verificar a possibilidade de identificar um indivíduo com base nas curvas DSC de um banco de dados. Amostras de cabelo de estudantes e funcionários do Instituto de Química de Araraquara UNESP, foram obtidas para construir um banco de dados. Procurou-se assim identificar de um indivíduo sob incógnita, utilizando-se a curva DSC deste banco de dados.

Purification, sequencing and structural characterization of the phospholipase A(1) from the venom of the social wasp Polybia paulista (Hymenoptera, Vespidae)

The biochemical and functional characterization of wasp venom toxins is an important prerequisite for the development of new tools both for the therapy of the toxic reactions due to envenomation caused by multiple stinging accidents and also for the diagnosis and therapy of allergic reactions caused by this type of venom. PLA(1) was purified from the venom of the neotropical social wasp Polybia paulista by using molecular exclusion and cation exchange chromatographies; its amino acid sequence was determined by using automated Edman degradation and compared to the sequences of other vespid venom PLA(1)'s. The enzyme exists as a 33,961.40 da protein, which was identified as a lipase of the GX class, liprotein lipase superfamily, pancreatic lipases (ab20.3) homologous family and RP2 sub-group of phospholipase. P. paulista PLA(1) is 53-82% identical to the phospholipases from wasp species from Northern Hemisphere. The use restrained-based modeling permitted to describe the 3-D structure of the enzyme, revealing that its molecule presents 23% alpha-helix, 28% beta-sheet and 49% coil. The protein structure has the alpha/beta fold common to many lipases; the core consists of a tightly packed beta-sheet constituted of six-stranded parallel and one anti-parallel beta-strand, surrounded by four alpha-helices. P. paulista PLA(1) exhibits direct hemolytic action against washed red blood cells with activity similar to the Cobra cardiotoxin from Naja naja atra. In addition to this, PLA(1) was immunoreactive to specific IgE from the sera of P. paulista-sensitive patients. (c) 2007 Elsevier Ltd. All rights reserved.

The role of spatial and temporal descriptors for neotropical tadpole communities in southern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Petri nets and autonomous systems: A case study

This work presents the Petri net-based modeling of an autonomous robot's navigation system used for the application of supplies in agriculture. The model was developed theoretically and implemented through the CPNTools software. It simulates the behavior of the robot, capturing environmental characteristics by means of sensors, making appropriate decisions, and forwarding them to the corresponding actuators. By exciting the model using CPNTools it is possible to simulate situations that the robot might undergo, without the need to expose it to real potentially dangerous situations. ©2009 IEEE.