13 research outputs found

    Ecology and Conservation of Bird Assemblages in Native and Afforested Environments in the Northern Campos Grasslands of Uruguay

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    Commercial forestry has expanded across the Rio de la Plata Grasslands (RPG) of South America in recent decades. I conducted a resource-use based study on bird communities during the 2013-2014 austral breeding season in northern Uruguay. I assessed relationships between habitat types and bird abundance as a function of vegetation structure. To compare avian responses to treatments, I included native environments, pine and eucalyptus plantations of different ages and thinning regimes. I detected differences in species richness and composition and species-specific responses in abundance along structural gradients sampled. Although poorer in species than native habitat types, tree plantations were extensively used by birds. Birds associated with plantations were primarily habitat generalists and forest dependent species, with low incidence of grassland specialists. Results of my study provide baseline information for stand-level management and future landscape design of timber plantations to benefit conservation of bird communities in afforested landscapes in the RPG

    Insights for policy-based conservation strategies for the Rio de la Plata Grasslands through the IPBES framework

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    The Río de la Plata Grasslands (RPG) are one of the most modified biomes in the world. Changes in land use and cover affect the RPG’s rich biodiversity. In particular, the expansion of crops, overgrazing, afforestation, and the introduction of exotic species pose a major threat to the conservation of biodiversity and ecosystem services (BES). In this study, we applied the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) conceptual framework as a new lens to approach biodiversity conservation enactments in the RPG. First, we systematically reviewed published scientific literature to identify direct and indirect drivers that affect the RPG’s BES. Further, we conducted an extensive analysis of management policies affecting the BES directly in the region, at a national and international level. We conclude by offering recommendations for policy and praxis under the umbrella of the IPBES framework

    High extinction risk and limited habitat connectivity of Muñoa's pampas cat, an endemic felid of the Uruguayan Savanna ecoregion

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    Muñoa´s pampas cat (recently proposed to be a distinct species, Leopardus munoai) is a small felid that is endemic to the Uruguayan Savanna ecoregion (encompassing southern Brazil, north-eastern Argentina and Uruguay). Previous studies have suggested that it is threatened, but its conservation assessment has been hampered by the scarcity of data on its ecology, including spatial distribution, population size, and connectivity. To address these issues, we developed current spatial distribution models and used them to: (i) identify the environmental variables affecting L. munoai habitat suitability; (ii) generate estimates of population size to assess its conservation status based on IUCN criteria; (iii) estimate habitat suitability in protected areas; (iv) identify potential paths of connectivity among protected areas and sites of confirmed occurrence; and (v) assess the proportion of the estimated connectivity paths that overlap with threatened areas (based on future threat projections). Our results indicated higher habitat suitability in the central area of the species? distribution. All estimates (based on different demographic assumptions) indicated that L. munoai should be categorized in one of the IUCN threatened categories. Worryingly, several estimates indicated that it may be Critically Endangered. Only 0.73 % of its high-suitability landscape is presently protected, and connectivity among most protected areas and occurrence records was low. Additionally, areas with estimated connectivity among occurrence records mostly overlapped with regions with a high level of future habitat loss threat (92.46 %), highlighting the urgent need for an international approach to ensure the long-term survival of this elusive felid.Fil: Tirelli, Flávia P.. Pontificia Universidade Católica do Rio Grande do Sul; Brasil. University of Oxford; Reino Unido. Universidade Federal do Rio Grande do Sul; Brasil. Instituto Pró-Carnívoros; BrasilFil: Trigo, Tatiane C.. Instituto Pró-Carnívoros; Brasil. Secretariat of Environment and Infrastructure, Department of Biodiversity, Mammalogy Sector, Museum of Natural Sciences; BrasilFil: Queirolo, Diego. Universidad de la República; UruguayFil: Kasper, Carlos Benhur. Universidade Federal do Pampa; BrasilFil: Bou, Nadia. Instituto de Investigaciones Biológicas "Clemente Estable"; UruguayFil: Peters, Felipe. Instituto Pró-Carnívoros; BrasilFil: Mazim, Fábio D.. Instituto Pró-Carnívoros; BrasilFil: Martínez Lanfranco, Juan Andrés. University of Alberta; CanadáFil: González, Enrique M.. National Museum of Natural History, Mammalogy Section; UruguayFil: Espinosa, Caroline. Universidade Federal do Rio Grande; BrasilFil: Favarini, Mariana. Instituto Pró-Carnívoros; BrasilFil: Gonçalves da Silva, Lucas. University of Brasília; BrasilFil: Macdonald, David W.. University of Oxford; Reino UnidoFil: Lucherini, Mauro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias Biológicas y Biomédicas del Sur. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia. Instituto de Ciencias Biológicas y Biomédicas del Sur; ArgentinaFil: Eizirik, Eduardo. Instituto Pró-Carnívoros; Brasi

    Four principles for improved statistical ecology

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    1. Increasing attention has been drawn to the misuse of statistical methods over recent years, with particular concern about the prevalence of practices such as poor experimental design, cherry picking and inadequate reporting. These failures are largely unintentional and no more common in ecology than in other scientific disciplines, with many of them easily remedied given the right guidance. 2. Originating from a discussion at the 2020 International Statistical Ecology Conference, we show how ecologists can build their research following four guiding principles for impactful statistical research practices: (1) define a focussed research question, then plan sampling and analysis to answer it; (2) develop a model that accounts for the distribution and dependence of your data; (3) emphasise effect sizes to replace statistical significance with ecological relevance; and (4) report your methods and findings in sufficient detail so that your research is valid and reproducible. 3. These principles provide a framework for experimental design and reporting that guards against unsound practices. Starting with a well-defined research question allows researchers to create an efficient study to answer it, and guards against poor research practices that lead to poor estimation of the direction, magnitude, and uncertainty of ecological relationships, and to poor replicability. Correct and appropriate statistical models give sound conclusions. Good reporting practices and a focus on ecological relevance make results impactful and replicable. 4. Illustrated with two examples—an experiment to study the impact of disturbance on upland wetlands, and an observational study on blue tit colouring—this paper explains the rationale for the selection and use of effective statistical practices and provides practical guidance for ecologists seeking to improve their use of statistical methods.Publisher PDFPeer reviewe

    Insights for policy-based conservation strategies for the Rio de la Plata Grasslands through the IPBES framework

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    NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

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    Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

    NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

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    Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data
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