293 resultados para Hotspots
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Due to its extraordinary biodiversity and rapid deforestation, north-eastern Madagascar is a conservation hotspot of global importance. Reducing shifting cultivation is a high priority for policy-makers and conservationists; however, spatially explicit evidence of shifting cultivation is lacking due to the difficulty of mapping it with common remote sensing methods. To overcome this challenge, we adopted a landscape mosaic approach to assess the changes between natural forests, shifting cultivation and permanent cultivation systems at the regional level from 1995 to 2011. Our study confirmed that shifting cultivation is still being used to produce subsistence rice throughout the region, but there is a trend of intensification away from shifting cultivation towards permanent rice production, especially near protected areas. While large continuous forest exists today only in the core zones of protected areas, the agricultural matrix is still dominated by a dense cover of tree crops and smaller forest fragments. We believe that this evidence makes a crucial contribution to the development of interventions to prevent further conversion of forest to agricultural land while improving local land users' well-being.
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The spectrum of immunogenic epitopes presented by the H2-IAb MHC class II molecule to CD4+ T cells has been defined for two different (clade B and clade D) HIV envelope (gp140) glycoproteins. Hybridoma T cell lines were generated from mice immunized by a sequential prime and boost regime with DNA, recombinant vaccinia viruses, and protein. The epitopes recognized by reactive T cell hybridomas then were characterized with overlapping peptides synthesized to span the entire gp140 sequence. Evidence of clonality also was assessed with antibodies to T cell receptor Vα and Vβ chains. A total of 80 unique clonotypes were characterized from six individual mice. Immunogenic peptides were identified within only four regions of the HIV envelope. These epitope hotspots comprised relatively short sequences (≈20–80 aa in length) that were generally bordered by regions of heavy glycosylation. Analysis in the context of the gp120 crystal structure showed a pattern of uniform distribution to exposed, nonhelical strands of the protein. A likely explanation is that the physical location of the peptide within the native protein leads to differential antigen processing and consequent epitope selection.
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High-density mutational spectra have been established for exon 3 of the gene encoding adenine phosphoribosyltransferase (APRT) of the Chinese hamster ovary (CHO) cell line derivative D422 and closely related and/or modified lines by using the mutagen ethyl methanesulfonate (EMS). The total number of selectable sites (GC-->AT transitions yielding a selectable APRT- phenotype) was estimated at 31 based on our own accumulated data base of 136 sequenced exon 3 mutations and on literature reports. D422 and two other APRT hemizygous lines each yielded very similar spectra and showed two populations of mutable sites: (i) 24 "baseline" sites that followed the Poisson distribution and therefore were equally susceptible to mutation and (ii) two hotspots, one comprising a cluster at nucleotides 1293-1309 and the other at nucleotide 1365. Collectively, the latter sites were about 10-fold more frequently mutated than the others. CHO cells are mer- as they lack the repair enzyme O6-methylguanidine methyltransferase (EC 2.1.1.63). In modified repair-proficient CHO cells, the distribution of mutations among all of the 31 sites was random, with only 3 of the 19 GC-->AT transitions in the above hotspots. To determine whether the distribution was locus-dependent, two independent lines carrying single copies of transfected APRT genes were generated from a derivative of D422 carrying a deletion in the endogenous APRT gene. Nucleotides 1293-1309 were again no longer preferentially mutated, but the site at nucleotide 1365 was still a hotspot. We conclude that mutational spectra in mer- cells are at least in part locus dependent and that some sequences are particularly susceptible to EMS mutagenesis and perhaps also to methyltransferase repair.
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The high rate of amphibian endemism and the severe habitat modification in the Caribbean islands make them an ideal place to test if the current protected areas network might protect this group. In this study, we model distribution and map species richness of the 40 amphibian species from eastern Cuba with the objectives of identify hotspots, detect gaps in species representation in protected areas, and select additional areas to fill these gaps. We used two modeling methods, Maxent and Habitat Suitability Models, to reach a consensus distribution map for each species, then calculate species richness by combining specific models and finally performed gap analyses for species and hotspots. Our results showed that the models were robust enough to predict species distributions and that most of the amphibian hotspots were represented in reserves, but 50 percent of the species were incompletely covered and Eleutherodactylus rivularis was totally uncovered by the protected areas. We identified 1441 additional km2 (9.9% of the study area) that could be added to the current protected areas, allowing the representation of every species and all hotspots. Our results are relevant for the conservation planning in other Caribbean islands, since studies like this could contribute to fill the gaps in the existing protected areas and to design a future network. Both cases would benefit from modeling amphibian species distribution using available data, even if they are incomplete, rather than relying only in the protection of known or suspected hotspots.
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Different measures are used to define concentrations of biodiversity — so-called 'hotspots'. More rigorous, global-scale analyses of how they compare will be essential for efficient resource allocation to conservation.
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Acknowledgements This work received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (Grant reference HR09011) and contributing institutions.
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Acknowledgements This work received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (Grant reference HR09011) and contributing institutions.
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Habitat loss, fragmentation, and degradation threaten the World’s ecosystems and species. These, and other threats, will likely be exacerbated by climate change. Due to a limited budget for conservation, we are forced to prioritize a few areas over others. These places are selected based on their uniqueness and vulnerability. One of the most famous examples is the biodiversity hotspots: areas where large quantities of endemic species meet alarming rates of habitat loss. Most of these places are in the tropics, where species have smaller ranges, diversity is higher, and ecosystems are most threatened.
Species distributions are useful to understand ecological theory and evaluate extinction risk. Small-ranged species, or those endemic to one place, are more vulnerable to extinction than widely distributed species. However, current range maps often overestimate the distribution of species, including areas that are not within the suitable elevation or habitat for a species. Consequently, assessment of extinction risk using these maps could underestimate vulnerability.
In order to be effective in our quest to conserve the World’s most important places we must: 1) Translate global and national priorities into practical local actions, 2) Find synergies between biodiversity conservation and human welfare, 3) Evaluate the different dimensions of threats, in order to design effective conservation measures and prepare for future threats, and 4) Improve the methods used to evaluate species’ extinction risk and prioritize areas for conservation. The purpose of this dissertation is to address these points in Colombia and other global biodiversity hotspots.
In Chapter 2, I identified the global, strategic conservation priorities and then downscaled to practical local actions within the selected priorities in Colombia. I used existing range maps of 171 bird species to identify priority conservation areas that would protect the greatest number of species at risk in Colombia (endemic and small-ranged species). The Western Andes had the highest concentrations of such species—100 in total—but the lowest densities of national parks. I then adjusted the priorities for this region by refining these species ranges by selecting only areas of suitable elevation and remaining habitat. The estimated ranges of these species shrank by 18–100% after accounting for habitat and suitable elevation. Setting conservation priorities on the basis of currently available range maps excluded priority areas in the Western Andes and, by extension, likely elsewhere and for other taxa. By incorporating detailed maps of remaining natural habitats, I made practical recommendations for conservation actions. One recommendation was to restore forest connections to a patch of cloud forest about to become isolated from the main Andes.
For Chapter 3, I identified areas where bird conservation met ecosystem service protection in the Central Andes of Colombia. Inspired by the November 11th (2011) landslide event near Manizales, and the current poor results of Colombia’s Article 111 of Law 99 of 1993 as a conservation measure in this country, I set out to prioritize conservation and restoration areas where landslide prevention would complement bird conservation in the Central Andes. This area is one of the most biodiverse places on Earth, but also one of the most threatened. Using the case of the Rio Blanco Reserve, near Manizales, I identified areas for conservation where endemic and small-range bird diversity was high, and where landslide risk was also high. I further prioritized restoration areas by overlapping these conservation priorities with a forest cover map. Restoring forests in bare areas of high landslide risk and important bird diversity yields benefits for both biodiversity and people. I developed a simple landslide susceptibility model using slope, forest cover, aspect, and stream proximity. Using publicly available bird range maps, refined by elevation, I mapped concentrations of endemic and small-range bird species. I identified 1.54 km2 of potential restoration areas in the Rio Blanco Reserve, and 886 km2 in the Central Andes region. By prioritizing these areas, I facilitate the application of Article 111 which requires local and regional governments to invest in land purchases for the conservation of watersheds.
Chapter 4 dealt with elevational ranges of montane birds and the impact of lowland deforestation on their ranges in the Western Andes of Colombia, an important biodiversity hotspot. Using point counts and mist-nets, I surveyed six altitudinal transects spanning 2200 to 2800m. Three transects were forested from 2200 to 2800m, and three were partially deforested with forest cover only above 2400m. I compared abundance-weighted mean elevation, minimum elevation, and elevational range width. In addition to analyzing the effect of deforestation on 134 species, I tested its impact within trophic guilds and habitat preference groups. Abundance-weighted mean and minimum elevations were not significantly different between forested and partially deforested transects. Range width was marginally different: as expected, ranges were larger in forested transects. Species in different trophic guilds and habitat preference categories showed different trends. These results suggest that deforestation may affect species’ elevational ranges, even within the forest that remains. Climate change will likely exacerbate harmful impacts of deforestation on species’ elevational distributions. Future conservation strategies need to account for this by protecting connected forest tracts across a wide range of elevations.
In Chapter 5, I refine the ranges of 726 species from six biodiversity hotspots by suitable elevation and habitat. This set of 172 bird species for the Atlantic Forest, 138 for Central America, 100 for the Western Andes of Colombia, 57 for Madagascar, 102 for Sumatra, and 157 for Southeast Asia met the criteria for range size, endemism, threat, and forest use. Of these 586 species, the Red List deems 108 to be threatened: 15 critically endangered, 29 endangered, and 64 vulnerable. When ranges are refined by elevational limits and remaining forest cover, 10 of those critically endangered species have ranges < 100km2, but then so do 2 endangered species, seven vulnerable, and eight non-threatened ones. Similarly, 4 critically endangered species, 20 endangered, and 12 vulnerable species have refined ranges < 5000km2, but so do 66 non-threatened species. A striking 89% of these species I have classified in higher threat categories have <50% of their refined ranges inside protected areas. I find that for 43% of the species I assessed, refined range sizes fall within thresholds that typically have higher threat categories than their current assignments. I recommend these species for closer inspection by those who assess risk. These assessments are not only important on a species-by-species basis, but by combining distributions of threatened species, I create maps of conservation priorities. They differ significantly from those created from unrefined ranges.
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Proliferation of invasive aquatic weeds has developed into a major ecological and socio economic issue for many regions of the world. As a consequence, inference on where to target control and other management efforts is critical in the management of aquatic weeds (Ibáñez et al., 2009). Notwithstanding, aquatic systems in Uganda in general and in the basins of Lakes Victoria and Kyoga in particular, have fallen victims to aquatic weeds invasion and subsequent infestation. If these aquatic weeds infestations are to be minimized and their impacts mitigated, management decisions ought to be based on up-to-date data and information in relation to location of infestation hotspots. Aquatic systems in the basins of the two production systems are important sources of livelihoods especially from fish production and trade yet they are prone to infestation by aquatic weeds. Thus, the invasion and subsequent infestation of aquatic ecosystems by aquatic weeds pose a major conservation threat to various aquatic resources (Catford et al., 2011; Kayanja, 2002). This paper examines the extent to which aquatic weeds have infested aquatic ecosystems in the basins of Lakes Victoria and Kyoga. The information is expected to guide management of major aquatic weeds through rational allocation of the scarce resources by targeting hotspots.
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Live animal trade is considered a major mode of introduction of viruses from enzootic foci into disease-free areas. Due to societal and behavioural changes, some wild animal species may nowadays be considered as pet species. The species diversity of animals involved in international trade is thus increasing. This could benefit pathogens that have a broad host range such as arboviruses. The objective of this study was to analyze the risk posed by live animal imports for the introduction, in the European Union (EU), of four arboviruses that affect human and horses: Eastern and Western equine encephalomyelitis, Venezuelan equine encephalitis and Japanese encephalitis. Importation data for a five-years period (2005-2009, extracted from the EU TRACES database), environmental data (used as a proxy for the presence of vectors) and horses and human population density data (impacting the occurrence of clinical cases) were combined to derive spatially explicit risk indicators for virus introduction and for the potential consequences of such introductions. Results showed the existence of hotspots where the introduction risk was the highest in Belgium, in the Netherlands and in the north of Italy. This risk was higher for Eastern equine encephalomyelitis (EEE) than for the three other diseases. It was mainly attributed to exotic pet species such as rodents, reptiles or cage birds, imported in small-sized containments from a wide variety of geographic origins. The increasing species and origin diversity of these animals may have in the future a strong impact on the risk of introduction of arboviruses in the EU.
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Influenza A virus is an important human pathogen causative of yearly epidemics and occasional pandemics. The ability to replicate within the host cell is a determinant of virulence, amplifying viral numbers for host-to-host transmission. This process requires multiple rounds of entering permissive cells, replication, and virion assembly at the plasma membrane, the site of viral budding and release. The assembly of influenza A virus involves packaging of several viral (and host) proteins and of a segmented genome, composed of 8 distinct RNAs in the form of viral ribonucleoproteins (vRNPs). The selective assembly of the 8-segment core remains one of the most interesting unresolved problems in virology. The recycling endosome regulatory GTPase Rab11 was shown to contribute to the process, by transporting vRNPs to the periphery, giving rise to enlarged cytosolic puncta rich in Rab11 and the 8 vRNPs. We recently reported that vRNP hotspots were formed of clustered vesicles harbouring protruding electron-dense structures that resembled vRNPs. Mechanistically, vRNP hotspots were formed as vRNPs outcompeted the cognate effectors of Rab11, the Rab11-Family-Interacting-Proteins (FIPs) for binding, and as a consequence impair recycling sorting at an unknown step. Here, we speculate on the impact that such impairment might have in host immunity, membrane architecture and viral assembly.
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Nineteen areas on the island of Hispaniola (Haiti and the Dominican Republic) were studied with the aim of determining the distribution pattern of the endemic flora in these areas, and their variability with altitude. The main concentration of endemic species occurs in mountains with a medium altitude and in certain mountain sites (palaeo-islands), which coincide with hotspots; a lower number of endemics are found in low-lying areas (coldspots), due to the degradation of their habitats. A total of 1,582 endemic species were studied and were distributed in 19 areas. The whole island is of outstanding interest for its richness in endemics; it has 2,050 endemic species, representing 34.16% of its total flora. The territory in the study is home to 1,284 genera of which 31 are endemic to the island, including monotypical genera such as Tortuella abietifolia Urb. & Ekman, and endemic genera such as Hottea, containing seven endemic species. The sites with the highest rate of endemics are area A16 in the central range with a total of 440 endemic species, of which 278 are exclusive to the territory; and the Sierra de Bahoruco, la Selle, La Hotte and Tibur on in area A12, where we found 699 plants of which 482 are endemic and exclusive to the area; and A13 with 173 and 129 respectively. This work highlights the exceptional floristic diversity in endemic species and genera and analyses their distribution patterns as a tool for conservation in this area of the world, whose high endemicity rate makes it one of the most significant hotspots in the Caribbean.
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Key resource areas (KRAs), defined as dry season foraging zones for herbivores, were studied relative to the more extensive outlying rangeland areas (non-KRAs) in Kenya. Field surveys with pastoralists, ranchers, scientists and government officials delineated KRAs on the ground. Identified KRAs were mapped based on global positioning and local experts' information on KRAs accessibility and ecological attributes. Using the map of known KRAs and non-KRAs, we examined characteristics of soils, climate, topography, land use/cover attributes at KRAs relative to non-KRAs. How and why do some areas (KRAs) support herbivores during droughts when forage is scarce in other areas of the landscape? We hypothesized that KRAs have fundamental ecological and socially determined attributes that enable them to provide forage during critical times and we sought to characterize some of those attributes in this study. At the landscape level, KRAs took different forms based on forage availability during the dry season but generally occurred in locations of the landscape with aseasonal water availability and/or difficult to access areas during wet season forage abundance. Greenness trends for KRAs versus non-KRAs were evaluated with a 22-year dataset of Normalized Difference Vegetation Index (NDVI). Field surveys of KRAs provided qualitative information on KRAs as dry season foraging zones. At the scale of the study, soil attributes did not significantly differ for KRAs compared to non-KRAs. Slopes of KRA were generally steeper compared to non-KRAs and elevation was higher at KRAs. Field survey respondents indicated that animals and humans generally avoid difficult to access hilly areas using them only when all other easily accessible rangeland is depleted of forage during droughts. Understanding the nature of KRAs will support identification, protection and restoration of critical forage hotspots for herbivores by strengthening rangeland inventory, monitoring, policy formulation, and conservation efforts to improve habitats and human welfare. (c) 2007 Elsevier Ltd. All rights reserved.
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Identifying crash “hotspots”, “blackspots”, “sites with promise”, or “high risk” locations is standard practice in departments of transportation throughout the US. The literature is replete with the development and discussion of statistical methods for hotspot identification (HSID). Theoretical derivations and empirical studies have been used to weigh the benefits of various HSID methods; however, a small number of studies have used controlled experiments to systematically assess various methods. Using experimentally derived simulated data—which are argued to be superior to empirical data, three hot spot identification methods observed in practice are evaluated: simple ranking, confidence interval, and Empirical Bayes. Using simulated data, sites with promise are known a priori, in contrast to empirical data where high risk sites are not known for certain. To conduct the evaluation, properties of observed crash data are used to generate simulated crash frequency distributions at hypothetical sites. A variety of factors is manipulated to simulate a host of ‘real world’ conditions. Various levels of confidence are explored, and false positives (identifying a safe site as high risk) and false negatives (identifying a high risk site as safe) are compared across methods. Finally, the effects of crash history duration in the three HSID approaches are assessed. The results illustrate that the Empirical Bayes technique significantly outperforms ranking and confidence interval techniques (with certain caveats). As found by others, false positives and negatives are inversely related. Three years of crash history appears, in general, to provide an appropriate crash history duration.
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Hot spot identification (HSID) plays a significant role in improving the safety of transportation networks. Numerous HSID methods have been proposed, developed, and evaluated in the literature. The vast majority of HSID methods reported and evaluated in the literature assume that crash data are complete, reliable, and accurate. Crash under-reporting, however, has long been recognized as a threat to the accuracy and completeness of historical traffic crash records. As a natural continuation of prior studies, the paper evaluates the influence that under-reported crashes exert on HSID methods. To conduct the evaluation, five groups of data gathered from Arizona Department of Transportation (ADOT) over the course of three years are adjusted to account for fifteen different assumed levels of under-reporting. Three identification methods are evaluated: simple ranking (SR), empirical Bayes (EB) and full Bayes (FB). Various threshold levels for establishing hotspots are explored. Finally, two evaluation criteria are compared across HSID methods. The results illustrate that the identification bias—the ability to correctly identify at risk sites--under-reporting is influenced by the degree of under-reporting. Comparatively speaking, crash under-reporting has the largest influence on the FB method and the least influence on the SR method. Additionally, the impact is positively related to the percentage of the under-reported PDO crashes and inversely related to the percentage of the under-reported injury crashes. This finding is significant because it reveals that despite PDO crashes being least severe and costly, they have the most significant influence on the accuracy of HSID.