Predictive mapping of abalone fishing grounds using remotely-sensed LiDAR and commercial catch data

Defining the geographic extent of suitable fishing grounds at a scale relevant to resource exploitation for commercial benthic species can be problematic. Bathymetric light detection and ranging (LiDAR) systems provide an opportunity to enhance ecosystem-based fisheries management strategies for coastally distributed benthic fisheries. In this study we define the spatial extent of suitable fishing grounds for the blacklip abalone (Haliotis rubra) along 200 linear kilometers of coastal waters for the first time, demonstrating the potential for integration of remotely-sensed data with commercial catch information. Variables representing seafloor structure, generated from airborne bathymetric LiDAR were combined with spatially-explicit fishing event data, to characterize the geographic footprint of the western Victorian abalone fishery, in south-east Australia. A MaxEnt modeling approach determined that bathymetry, rugosity and complexity were the three most important predictors in defining suitable fishing grounds (AUC = 0.89). Suitable fishing grounds predicted by the model showed a good relationship with catch statistics within each sub-zone of the fishery, suggesting that model outputs may be a useful surrogate for potential catch.

Modeling the spatial and temporal heterogeneity of deforestation-driven carbon emissions: the INPE-EM framework applied to the Brazilian Amazon

We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation (INPE-EM). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 similar to Pg similar to C similar to yr-1. (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years, from 27 similar to Mkm2 in 2004 to 7 similar to Mkm2 in 2010. INPE-EM process-based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non-process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 similar to Pg similar to C similar to yr-1 in 2009; the non-process model estimates a decrease from 0.33 to 0.10 similar to Pg similar to C similar to yr-1. We conclude that the INPE-EM is a powerful tool for representing deforestation-driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD+. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.

Socio-climatic hotspots in Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Impacts of Climate Change and the End of Deforestation on Land Use in the Brazilian Legal Amazon

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

How individual movement response to habitat edges affects population persistence and spatial spread

How individual-level movement decisions in response to habitat edges influence population-level patterns of persistence and spread of a species is a major challenge in spatial ecology and conservation biology. Here, we integrate novel insights into edge behavior, based on habitat preference and movement rates, into spatially explicit growth-dispersal models. We demonstrate how crucial ecological quantities (e.g., minimal patch size, spread rate) depend critically on these individual-level decisions. In particular, we find that including edge behavior properly in these models gives qualitatively different and intuitively more reasonable results than those of some previous studies that did not consider this level of detail. Our results highlight the importance of new empirical work on individual movement response to habitat edges. © 2013 by The University of Chicago.

A vulnerabilidade da ictiofauna à invasão por espécies de peixes: um modelo baseado no indivíduo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Modelagem matemática para a simulação de estratégias de controle biológico da mosca-do-mediterrâneo C. capitata (Diptera : Tephritidae), em plantações de citrus: utilização de variáveis temporais e espaciais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A mathematical approach to simulate spatio-temporal patterns of an insect-pest, the corn rootworm Diabrotica speciosa (Coleoptera: Chrysomelidae) in intercropping systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Feedbacks between vegetation and disturbance processes promote long-term persistence of forest-grassland mosaics in south Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Simulating Population Genetics of Pathogen Vectors in Changing Landscapes: Guidelines and Application with Triatoma brasiliensis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

High Levels of Diversity Uncovered in a Widespread Nominal Taxon: Continental Phylogeography of the Neotropical Tree Frog Dendropsophus minutus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Site Selection for Restoration Planning: A Protocol With Landscape and Legislation Based Alternatives

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Community-wide spatial and temporal discordances of seed-seedling shadows in a tropical rainforest

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Model-Based Approach for Making Ecological Inference from Distance Sampling Data

We consider a fully model-based approach for the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study area. There is, however, no readily available method of making statistical inference on the relationships between abundance and environmental covariates. Spatial Poisson process likelihoods can be used to simultaneously estimate detection and intensity parameters by modeling distance sampling data as a thinned spatial point process. A model-based spatial approach to distance sampling data has three main benefits: it allows complex and opportunistic transect designs to be employed, it allows estimation of abundance in small subregions, and it provides a framework to assess the effects of habitat or experimental manipulation on density. We demonstrate the model-based methodology with a small simulation study and analysis of the Dubbo weed data set. In addition, a simple ad hoc method for handling overdispersion is also proposed. The simulation study showed that the model-based approach compared favorably to conventional distance sampling methods for abundance estimation. In addition, the overdispersion correction performed adequately when the number of transects was high. Analysis of the Dubbo data set indicated a transect effect on abundance via Akaike’s information criterion model selection. Further goodness-of-fit analysis, however, indicated some potential confounding of intensity with the detection function.

Plant invasions research in Latin America: fast track to a more focused agenda

While many developed countries have invested heavily in research on plant invasions over the last 50 years, the immense region of Latin America has made little progress. Recognising this, a group of scientists working on plant invasions in Latin America met in Chile in late 2010 to develop a research agenda for the region based on lessons learned elsewhere. Our three main findings are as follows. (1) Globalisation is inevitable, but the resultant plant introductions can be slowed or prevented by effective quarantine and early intervention. Development of spatially explicit inventories, research on the invasion process and weed risk assessments can help prioritise and streamline action. (2) Eradication has limited application for plants and control is expensive and requires strict prioritisation and careful planning and evaluation. (3) Accepting the concept of novel ecosystems, new combinations of native and introduced species that no longer depend on human intervention, may help optimise invasive species management. Our vision of novel ecosystem management is through actions that: (a) maintain as much native biodiversity and ecosystem functionality as possible, (b) minimise management intervention to invasives with known impact, and (c) maximise the area of intervention. We propose the creation of a Latin American Invasive Plants Network to help focus the new research agenda for member countries. The network would coordinate research and training and establish funding priorities, develop and strengthen tools to share knowledge, and raise awareness at the community, governmental and intergovernmental levels about the social, economic and environmental costs of plant invasions.