133 research outputs found

    Community motivations to engage in conservation behaviour to conserve the Sumatran orangutan

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    Community-based conservation programs in developing countries often assume that heteronomous motivation (e.g. extrinsic incentives such as economic rewards and pressure or coercion to act) will motivate local communities to adopt conservation behaviors. However, this may not be as effective or sustainable as autonomous motivations (e.g. an intrinsic desire to act due to inherent enjoyment or self-identification with a behavior and through freedom of choice). This paper analyses the comparative effectiveness of heteronomous versus autonomous approaches to community-based conservation programs, using the example of Sumatran orangutan (Pongo abelii) conservation in Indonesia. Comparing three case study villages employing differing program designs, we found that heteronomous motivations (e.g. income from tourism) led to a change in self-reported behavior towards orangutan protection. However, they were ineffective in changing self reported behavior towards forest (i.e. orangutan habitat) protection. The most effective approach to creating self-reported behavior change throughout the community was with a combination of autonomous and heteronomous motivations. Individuals who were heteronomously motivated to protect the orangutan were found to be more likely to have changed attitudes than their self-reported behavior. These findings demonstrate that the current paradigm of motivating communities in developing countries to adopt conservation behaviors primarily through monetary incentives and rewards should also consider integrating autonomous motivational techniques which promote the intrinsic values of conservation. Such a combination will have a greater potential to achieve sustainable and cost-effective conservation outcomes. Our results highlight the importance of in-depth socio psychological analyses to assist the design and implementation of community-based conservation programs

    Representative Landscapes in the Forested Area of Canada

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    Canada is a large nation with forested ecosystems that occupy over 60% of the national land base, and knowledge of the patterns of Canada’s land cover is important to proper environmental management of this vast resource. To this end, a circa 2000 Landsat-derived land cover map of the forested ecosystems of Canada has created a new window into understanding the composition and configuration of land cover patterns in forested Canada. Strategies for summarizing such large expanses of land cover are increasingly important, as land managers work to study and preserve distinctive areas, as well as to identify representative examples of current land-cover and land-use assemblages. Meanwhile, the development of extremely efficient clustering algorithms has become increasingly important in the world of computer science, in which billions of pieces of information on the internet are continually sifted for meaning for a vast variety of applications. One recently developed clustering algorithm quickly groups large numbers of items of any type in a given data set while simultaneously selecting a representative—or “exemplar”—from each cluster. In this context, the availability of both advanced data processing methods and a nationally available set of landscape metrics presents an opportunity to identify sets of representative landscapes to better understand landscape pattern, variation, and distribution across the forested area of Canada. In this research, we first identify and provide context for a small, interpretable set of exemplar landscapes that objectively represent land cover in each of Canada’s ten forested ecozones. Then, we demonstrate how this approach can be used to identify flagship and satellite long-term study areas inside and outside protected areas in the province of Ontario. These applications aid our understanding of Canada’s forest while augmenting its management toolbox, and may signal a broad range of applications for this versatile approach

    A review of elliptical and disc galaxy structure, and modern scaling laws

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    A century ago, in 1911 and 1913, Plummer and then Reynolds introduced their models to describe the radial distribution of stars in `nebulae'. This article reviews the progress since then, providing both an historical perspective and a contemporary review of the stellar structure of bulges, discs and elliptical galaxies. The quantification of galaxy nuclei, such as central mass deficits and excess nuclear light, plus the structure of dark matter halos and cD galaxy envelopes, are discussed. Issues pertaining to spiral galaxies including dust, bulge-to-disc ratios, bulgeless galaxies, bars and the identification of pseudobulges are also reviewed. An array of modern scaling relations involving sizes, luminosities, surface brightnesses and stellar concentrations are presented, many of which are shown to be curved. These 'redshift zero' relations not only quantify the behavior and nature of galaxies in the Universe today, but are the modern benchmark for evolutionary studies of galaxies, whether based on observations, N-body-simulations or semi-analytical modelling. For example, it is shown that some of the recently discovered compact elliptical galaxies at 1.5 < z < 2.5 may be the bulges of modern disc galaxies.Comment: Condensed version (due to Contract) of an invited review article to appear in "Planets, Stars and Stellar Systems"(www.springer.com/astronomy/book/978-90-481-8818-5). 500+ references incl. many somewhat forgotten, pioneer papers. Original submission to Springer: 07-June-201

    deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data

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    Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes

    Web-based tools can be used reliably to detect patients with major depressive disorder and subsyndromal depressive symptoms

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    BACKGROUND: Although depression has been regarded as a major public health problem, many individuals with depression still remain undetected or untreated. Despite the potential for Internet-based tools to greatly improve the success rate of screening for depression, their reliability and validity has not been well studied. Therefore the aim of this study was to evaluate the test-retest reliability and criterion validity of a Web-based system, the Internet-based Self-assessment Program for Depression (ISP-D). METHODS: The ISP-D to screen for major depressive disorder (MDD), minor depressive disorder (MinD), and subsyndromal depressive symptoms (SSD) was developed in traditional Chinese. Volunteers, 18 years and older, were recruited via the Internet and then assessed twice on the online ISP-D system to investigate the test-retest reliability of the test. They were subsequently prompted to schedule face-to-face interviews. The interviews were performed by the research psychiatrists using the Mini-International Neuropsychiatric Interview and the diagnoses made according to DSM-IV diagnostic criteria were used for the statistics of criterion validity. Kappa (κ) values were calculated to assess test-retest reliability. RESULTS: A total of 579 volunteer subjects were administered the test. Most of the subjects were young (mean age: 26.2 ± 6.6 years), female (77.7%), single (81.6%), and well educated (61.9% college or higher). The distributions of MDD, MinD, SSD and no depression specified were 30.9%, 7.4%, 15.2%, and 46.5%, respectively. The mean time to complete the ISP-D was 8.89 ± 6.77 min. One hundred and eighty-four of the respondents completed the retest (response rate: 31.8%). Our analysis revealed that the 2-week test-retest reliability for ISP-D was excellent (weighted κ = 0.801). Fifty-five participants completed the face-to-face interview for the validity study. The sensitivity, specificity, positive, and negative predictive values for major depressive disorder were 81.8% and 72.7%, 66.7%, and 85.7% respectively. The overall accuracy was 76.4%. CONCLUSION: The evidence indicates the ISP-D is a reliable and valid online tool for assessing depression. Further studies should test the ISP-D in clinical settings to increase its applications in clinical environments with different populations and in a larger sample size

    Additional records of metazoan parasites from Caribbean marine mammals, including genetically identified anisakid nematodes

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    Studies of marine mammal parasites in the Caribbean are scarce. An assessment for marine mammal endo- and ectoparasites from Puerto Rico and the Virgin Islands, but extending to other areas of the Caribbean, was conducted between 1989 and 1994. The present study complements the latter and enhances identification of anisakid nematodes using molecular markers. Parasites were collected from 59 carcasses of stranded cetaceans and manatees from 1994 to 2006, including Globicephala macrorhynchus, Kogia breviceps, Kogia sima, Lagenodelphis hosei, Mesoplodon densirostris, Peponocephala electra, Stenella longirostris, Steno bredanensis, Trichechus manatus. Tursiops truncatus, and Ziphius cavirostris. Sixteen species of endoparasitic helminthes were morphologically identified, including two species of acanthocephalans (Bolbosoma capitatum, Bolbosoma vasculosum), nine species of nematodes (Anisakis sp., Anisakis brevispiculata, Anisakis paggiae, Anisakis simplex, Anisakis typica, Anisakis ziphidarium, Crassicauda anthonyi, Heterocheilus tunicatus, Pseudoterranova ceticola), two species of cestodes (Monorygma grimaldi, Phyllobothrium delphini), and three species of trematodes (Chiorchis groschafti, Pulmonicola cochleotrema, Monoligerum blairi). The nematodes belonging to the genus Anisakis recovered in some stranded animals were genetically identified to species level based on their sequence analysis of mitochondrial DNA (629 bp of mtDNA cox 2). A total of five new host records and six new geographic records are presented.L'articolo è disponibile sul sito dell'editore http://www.springerlink.com

    The Natural Product Domain Seeker NaPDoS: A Phylogeny Based Bioinformatic Tool to Classify Secondary Metabolite Gene Diversity

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    New bioinformatic tools are needed to analyze the growing volume of DNA sequence data. This is especially true in the case of secondary metabolite biosynthesis, where the highly repetitive nature of the associated genes creates major challenges for accurate sequence assembly and analysis. Here we introduce the web tool Natural Product Domain Seeker (NaPDoS), which provides an automated method to assess the secondary metabolite biosynthetic gene diversity and novelty of strains or environments. NaPDoS analyses are based on the phylogenetic relationships of sequence tags derived from polyketide synthase (PKS) and non-ribosomal peptide synthetase (NRPS) genes, respectively. The sequence tags correspond to PKS-derived ketosynthase domains and NRPS-derived condensation domains and are compared to an internal database of experimentally characterized biosynthetic genes. NaPDoS provides a rapid mechanism to extract and classify ketosynthase and condensation domains from PCR products, genomes, and metagenomic datasets. Close database matches provide a mechanism to infer the generalized structures of secondary metabolites while new phylogenetic lineages provide targets for the discovery of new enzyme architectures or mechanisms of secondary metabolite assembly. Here we outline the main features of NaPDoS and test it on four draft genome sequences and two metagenomic datasets. The results provide a rapid method to assess secondary metabolite biosynthetic gene diversity and richness in organisms or environments and a mechanism to identify genes that may be associated with uncharacterized biochemistry

    Assessment of thrombin-activatable fibrinolysis inhibitor (TAFI) activation in acquired hemostatic dysfunction: a diagnostic challenge

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    Genomic comparisons reveal biogeographic and anthropogenic impacts in the koala (Phascolarctos cinereus): a dietary-specialist species distributed across heterogeneous environments

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    The Australian koala is an iconic marsupial with highly specific dietary requirements distributed across heterogeneous environments, over a large geographic range. The distribution and genetic structure of koala populations has been heavily influenced by human actions, specifically habitat modification, hunting and translocation of koalas. There is currently limited information on population diversity and gene flow at a species-wide scale, or with consideration to the potential impacts of local adaptation. Using species-wide sampling across heterogeneous environments, and high-density genome-wide markers (SNPs and PAVs), we show that most koala populations display levels of diversity comparable to other outbred species, except for those populations impacted by population reductions. Genetic clustering analysis and phylogenetic reconstruction reveals a lack of support for current taxonomic classification of three koala subspecies, with only a single evolutionary significant unit supported. Furthermore, similar to 70% of genetic variance is accounted for at the individual level. The Sydney Basin region is highlighted as a unique reservoir of genetic diversity, having higher diversity levels (i.e., Blue Mountains region; AvHe(corr)-0.20, PL% = 68.6). Broad-scale population differentiation is primarily driven by an isolation by distance genetic structure model (49% of genetic variance), with clinal local adaptation corresponding to habitat bioregions. Signatures of selection were detected between bioregions, with no single region returning evidence of strong selection. The results of this study show that although the koala is widely considered to be a dietary-specialist species, this apparent specialisation has not limited the koala's ability to maintain gene flow and adapt across divergent environments as long as the required food source is available
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