952 resultados para MPAs, marine conservation, quotas, taxes, penalties, bonds, protected species


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Tropical marginal seas (TMSs) are natural subregions of tropical oceans containing biodiverse ecosystems with conspicuous, valued, and vulnerable biodiversity assets. They are focal points for global marine conservation because they occur in regions where human populations are rapidly expanding. Our review of 11 TMSs focuses on three key ecosystems—coral reefs and emergent atolls, deep benthic systems, and pelagic biomes—and synthesizes, illustrates, and contrasts knowledge of biodiversity, ecosystem function, interaction between adjacent habitats, and anthropogenic pressures. TMSs vary in the extent that they have been subject to human influence—from the nearly pristine Coral Sea to the heavily exploited South China and Caribbean Seas—but we predict that they will all be similarly complex to manage because most span multiple national jurisdictions. We conclude that developing a structured process to identify ecologically and biologically significant areas that uses a set of globally agreed criteria is a tractable first step toward effective multinational and transboundary ecosystem management of TMSs.

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High level environmental screening study for offshore wind farm developments – marine habitats and species This report provides an awareness of the environmental issues related to marine habitats and species for developers and regulators of offshore wind farms. The information is also relevant to other offshore renewable energy developments. The marine habitats and species considered are those associated with the seabed, seabirds, and sea mammals. The report concludes that the following key ecological issues should be considered in the environmental assessment of offshore wind farms developments: • likely changes in benthic communities within the affected area and resultant indirect impacts on fish, populations and their predators such as seabirds and sea mammals; • potential changes to the hydrography and wave climate over a wide area, and potential changes to coastal processes and the ecology of the region; • likely effects on spawning or nursery areas of commercially important fish and shellfish species; • likely effects on mating and social behaviour in sea mammals, including migration routes; • likely effects on feeding water birds, seal pupping sites and damage of sensitive or important intertidal sites where cables come onshore; • potential displacement of fish, seabird and sea mammals from preferred habitats; • potential effects on species and habitats of marine natural heritage importance; • potential cumulative effects on seabirds, due to displacement of flight paths, and any mortality from bird strike, especially in sensitive rare or scarce species; • possible effects of electromagnetic fields on feeding behaviour and migration, especially in sharks and rays, and • potential marine conservation and biodiversity benefits of offshore wind farm developments as artificial reefs and 'no-take' zones. The report provides an especially detailed assessment of likely sensitivity of seabed species and habitats in the proposed development areas. Although sensitive to some of the factors created by wind farm developments, they mainly have a high recovery potential. The way in which survey data can be linked to Marine Life Information Network (MarLIN) sensitivity assessments to produce maps of sensitivity to factors is demonstrated. Assessing change to marine habitats and species as a result of wind farm developments has to take account of the natural variability of marine habitats, which might be high especially in shallow sediment biotopes. There are several reasons for such changes but physical disturbance of habitats and short-term climatic variability are likely to be especially important. Wind farm structures themselves will attract marine species including those that are attached to the towers and scour protection, fish that associate with offshore structures, and sea birds (especially sea duck) that may find food and shelter there. Nature conservation designations especially relevant to areas where wind farm might be developed are described and the larger areas are mapped. There are few designated sites that extend offshore to where wind farms are likely to be developed. However, cable routes and landfalls may especially impinge on designated sites. The criteria that have been developed to assess the likely marine natural heritage importance of a location or of the habitats and species that occur there can be applied to survey information to assess whether or not there is anything of particular marine natural heritage importance in a development area. A decision tree is presented that can be used to apply ‘duty of care’ principles to any proposed development. The potential ‘gains’ for the local environment are explored. Wind farms will enhance the biodiversity of areas, could act as refugia for fish, and could be developed in a way that encourages enhancement of fish stocks including shellfish.

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Science-based approaches to support the conservation of marine biodiversity have been developed in recent years. They include measures of ‘rarity’, ‘diversity’, ‘importance’, biological indicators of water ‘quality’ and measures of ‘sensitivity’. Identifying the sensitivity of species and biotopes, the main topic of this contribution, relies on accessing and interpreting available scientific data in a structured way and then making use of information technology to disseminate suitably presented information to decision makers. The Marine Life Information Network (MarLIN) has achieved that research for a range of environmentally critical species and biotopes over the past four years and has published the reviews on the MarLIN Web site (www.marlin.ac.uk). Now, by linking the sensitivity database and databases of survey information, sensitivity mapping approaches using GIS are being developed. The methods used to assess sensitivity are described and the approach is advocated for wider application in Europe.

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Pelagic longliners targeting swordfish and tunas in oceanic waters regularly capture sharks as bycatch, including currently protected species as the bigeye thresher, Alopias superciliosus. Fifteen bigeye threshers were tagged with pop-up satellite archival tags (PSATs) in 2012-2014 in the tropical northeast Atlantic, with successful transmissions received from 12 tags for a total of 907 tracking days. Marked diel vertical movements were recorded on all specimens, with most of the daytime spent in deeper colder water (mean depth = 353 m, SD = 73; mean temperature = 10.7 °C, SD = 1.8) and nighttime spent in warmer water closer to the surface (mean depth = 72 m, SD = 54; mean temperature = 21.9 °C, SD = 3.7). The operating depth of the pelagic longline gear was measured with Minilog Temperature and Depth Recorders (TDRs), and the overlap with habitat utilization was calculated. Overlap is taking place mainly during the night and is higher for juveniles. The results presented herein can be used as inputs for Ecological Risk Assessments for bigeye threshers captured in oceanic tuna fisheries, and serve as a basis for efficient management and conservation of this vulnerable shark species.

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The White-headed Vulture Trigonoceps occipitalis (WhV) is uncommon and largely restricted to protected areas across its range in sub-Saharan Africa. We used the World Database on Protected Areas to identify protected areas (PAs) likely to contain White-headed Vultures. Vulture occurrence on road transects in Southern, East, and West Africa was adjusted to nests per km2 using data from areas with known numbers of nests and corresponding road transect data. Nest density was used to calculate the number of WhV nests within identified PAs and from there extrapolated to estimate the global population. Across a fragmented range, 400 PAs are estimated to contain 1893 WhV nests. Eastern Africa is estimated to contain 721 nests, Central Africa 548 nests, Southern Africa 468 nests, and West Africa 156 nests. Including immature and nonbreeding birds, and accounting for data deficient PAs, the estimated global population is 5475 - 5493 birds. The identified distribution highlights are alarming: over 78% (n = 313) of identified PAs contain fewer than five nests. A further 17% (n = 68) of PAs contain 5 - 20 nests and 4% (n = 14) of identified PAs are estimated to contain >20 nests. Just 1% (n = 5) of PAs are estimated to contain >40 nests; none is located in West Africa. Whilst ranging behavior of WhVs is currently unknown, 35% of PAs large enough to hold >20 nests are isolated by more than 100 km from other PAs. Spatially discrete and unpredictable mortality events such as poisoning pose major threats to small localized vulture populations and will accelerate ongoing local extinctions. Apart from reducing the threat of poisoning events, conservation actions promoting linkages between protected areas should be pursued. Identifying potential areas for assisted re-establishment via translocation offers the potential to expand the range of this species and alleviate risk.

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Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions.

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There has been a dramatic increase in the area that is within the National Reserve System since 2000 – from around 60 million hectares to around 100 million in 2008. This dramatic increase can be attributed to Indigenous Protected Areas and the acquisition of private or leasehold land for either addition to the public protected area estate or management as private protected areas. This growth has also been strategic, increasingly the reservation status of the most underreserved bioregions. However, the reality is the land acquisition has slowed since the global financial crisis of the late 2000s and this has led to new models with different partners coming to the fore. This chapter highlights one of those new models – the acquisition of Fish River Station in the Northern Territory for conservation.

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Australia has seen a rapid growth in the establishment of networks of lands managed for connectivity conservation across tenures, at landscape and sub-continental scales. Such networks go under a variety of names, including biosphere reserves, biolinks, wildlife corridors and conservation management networks. Their establishment has varied from state government-led initiatives to those initiated by non-government organizations and interested landholders. We surveyed existing major landscape scale conservation initiatives for successes, failures and future directions and synthesized common themes. These themes included scale, importance of social and economic networks, leadership, governance, funding, conservation planning, the role of protected areas and communication. We discuss the emergence of national policy relating to National Wildlife Corridors in Australia and the relationship of this policy to the long standing commitment to build a comprehensive, adequate and representative National Reserve System. Finally we outline areas for further research for connectivity conservation projects in Australia.

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The application of the 'ecosystem approach' to marine conservation management demands knowledge of the distribution patterns of the target species or communities. This information is commonly obtained from species distribution models (SDMs). This article explores an important but rarely acknowledged assumption in these models: almost all species may be present, but simply not detected by the particular survey method. However, nearly all of these SDM approaches neglect this important characteristic. This leads to the violation of a fundamental assumption of these models, which presuppose the detection of a species is equal to one (i.e. at each survey locality, a species is perfectly detected). In this article, the concept of imperfect detection is discussed, how it potentially influences the prediction of species' distributions is examined, and some statistical methods that could be used to incorporate the detection probability of species in estimates of their distribution are suggested. The approaches discussed here could improve the collection and interpretation of marine biological survey data and provide a coherent way to incorporate detection probability estimates in the modelling of species distributions. This will ultimately lead to an unbiased and more rigorous understanding of the distribution of species in the marine environment.

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In recent years, marine predator and seabird tracking studies have become ever more popular. However, they are often conducted without first considering how many individuals should be tracked and for how long they should be tracked in order to make reliable predictions of a population's home-range area. Home-range area analysis of two seabird-tracking data sets was used to define the area of active use (where birds spent 100% of their time) and the core foraging area (where birds spent 50% of their time). Analysis was conducted on the first foraging trip undertaken by the birds and then the first two, three and four foraging trips combined. Appropriate asymptotic models were applied to the data, and the calculated home-range areas were plotted as a function of an increasing number of individuals and trips included in the sample. Data were extrapolated from these models to predict the area of active use and the core foraging area of the colonies sampled. Significant variability was found in the home-range area predictions made by analysis of the first foraging trip and the first four foraging trips combined. For shags, the first foraging trip predicted a 56% smaller area of active use when compared to the predictions made by combining the first four foraging trips. For kittiwakes, a 43% smaller area was predicted when comparing the first foraging trip with the four combined trips. The number of individuals that would be required to predict the home range area of the colony depends greatly on the number of trips included in the analysis. This analysis predicted that 39 (confidence interval 29-73) shags and 83 (CI: 109-161) kittiwakes would be required to predict 95% of the area of active use when the first four foraging trips are included in the sample compared with 135 (CI 96-156) shags and 248 (164-484) kittiwakes when only the first trip is included in the analysis. Synthesis and applications. Seabird and marine mammal tracking studies are increasingly being used to aid the designation of marine conservation zones and to predict important foraging areas. We suggest that many studies may be underestimating the size of these foraging areas and that better estimates could be made by considering both the duration and number of data logger deployments. Researchers intending to draw conclusions from tracking data should conduct a similar analysis of their data as used in this study to determine the reliability of their home-range area predictions.

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Despite global declines in the abundance of marine predators, knowledge of foraging ecology, necessary to predict the ecological consequences of large changes in marine predator abundance, remains enigmatic for many species. Given that populations suffering severe declines are of conservation concern, we examined the foraging ecology of southern sea lions (SSL) (Otaria flavescens)-one of the least studied otariids (fur seal and sea lions)-which have declined by over 90 % at the Falkland Islands since the 1930s. Using a combination of biologging devices and stable isotope analysis of vibrissae, we redress major gaps in the knowledge of SSL ecology and quantify patterns of individual specialization. Specifically, we revealed two discrete foraging strategies, these being inshore (coastal) and offshore (outer Patagonian Shelf). The majority of adult female SSL (72 % or n = 21 of 29 SSL) foraged offshore. Adult female SSL that foraged offshore travelled further (92 ± 20 vs. 10 ± 4 km) and dived deeper (75 ± 23 vs. 21 ± 8 m) when compared to those that foraged inshore. Stable isotope analysis revealed long-term fidelity (years) to these discrete foraging habitats. In addition, we found further specialization within the offshore group, with adult female SSL separated into two clusters on the basis of benthic or mixed (benthic and pelagic) dive behavior (benthic dive proportion was 76 ± 9 vs. 51 ± 8 %, respectively). We suggest that foraging specialization in depleted populations such as SSL breeding at the Falkland Islands, are influenced by foraging site fidelity, and could be independent of intraspecific competition. Finally, the behavioral differences we describe are crucial to understanding population-level dynamics, impediments to population recovery, and threats to population persistence.

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 Aim: The purpose of this study was to create predictive species distribution models (SDMs) for temperate reef-associated fish species densities and fish assemblage diversity and richness to aid in marine conservation and spatial planning. Location: California, USA. Methods: Using generalized additive models, we associated fish species densities and assemblage characteristics with seafloor structure, giant kelp biomass and wave climate and used these associations to predict the distribution and assemblage structure across the study area. We tested the accuracy of these predicted extrapolations using an independent data set. The SDMs were also used to estimate larger scale abundances to compare with other estimates of species abundance (uniform density extrapolation over rocky reef and density extrapolations taking into account variations in geomorphic structure). Results: The SDMs successfully modelled the species-habitat relationships of seven rocky reef-associated fish species and showed that species' densities differed in their relationships with environmental variables. The predictive accuracy of the SDMs ranged from 0.26 to 0.60 (Pearson's r correlation between observed and predicted density values). The SDMs created for the fish assemblage-level variables had higher prediction accuracies with Pearson's r values of 0.61 for diversity and 0.71 for richness. The comparisons of the different methods for extrapolating species densities over a single marine protected area varied greatly in their abundance estimates with the uniform extrapolation (density values extrapolated evenly over the rocky reef) always estimating much greater abundances. The other two methods, which took into account variation in the geomorphic structure of the reef, provided much lower abundance estimates. Main conclusions: Species distribution models that combine geomorphic, oceanographic and biogenic habitat variables can reliably predict spatial patterns of species density and assemblage attributes of temperate reef fishes at spatial scales of 50 m. Thus, SDMs show great promise for informing spatial and ecosystem-based approaches to conservation and fisheries management. © 2015 John Wiley

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

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The jacutinga Pipile jacutinga was formerly one of the most abundant game bird cracids in the Atlantic forest of Brazil. Nowadays this species is vulnerable to extinction due to hunting and habitat loss. The ecology of the jacutinga was studied at Parque Estadual Intervales, Sao Paulo, Brazil from October 1993 to December 1995 and in adjacent areas. Jacutingas were observed to feed mainly on the sugar-rich fruit of 41 species. We recorded a low index of abundance for the jacutinga (0.018) or c.1.7 birds/km2 at Intervales, one of the best protected areas within their range. Surveys carried out in the Atlantic forest of Sao Paulo found jacutinga populations in 14 localities. Probably < 1500 birds survive in the best protected areas. The species' stronghold in southeastern Brazil is in the mountains of Serra de Paranapiacaba, an area protected by several parks suffering from hunting and palm heart harvesting and threatened by a hydroelectric project.

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Coarse-resolution thematic maps derived from remotely sensed data and implemented in GIS play an important role in coastal and marine conservation, research and management. Here, we describe an approach for fine-resolution mapping of land-cover types using aerial photography and ancillary GIs and ground data in a large (100 x 35 km) subtropical estuarine system (Moreton Bay, Queensland, Australia). We have developed and implemented a classification scheme representing 24 coastal (subtidal, intertidal. mangrove, supratidal and terrestrial) cover types relevant to the ecology of estuarine animals, nekton and shorebirds. The accuracy of classifications of the intertidal and subtidal cover types, as indicated by the agreement between the mapped (predicted) and reference (ground) data, was 77-88%, depending on the zone and level of generalization required. The variability and spatial distribution of habitat mosaics (landscape types) across the mapped environment were assessed using K-means clustering and validated with Classification and Regression Tree models. Seven broad landscape types could be distinguished and ways of incorporating the information on landscape composition into site-specific conservation and field research are discussed. This research illustrates the importance and potential applications of fine-resolution mapping for conservation and management of estuarine habitats and their terrestrial and aquatic wildlife. (c) 2005 Elsevier Ltd. All rights reserved.