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      Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves

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          Abstract

          Understanding the factors underpinning species abundance patterns in space and time is essential to implement effective cave conservation actions. Yet, the methods employed to monitor cave biodiversity still lack standardization, and no quantitative assessment has yet tried to optimize the amount and type of information required to efficiently identify disturbances in cave ecosystems. Using a comprehensive monitoring dataset for tropical iron caves, comprising abundance measurements for 33 target taxa surveyed across 95 caves along four years, here we provide the first evidence-based recommendations to optimize monitoring programs seeking to follow target species abundance through time. We found that seasonality did not influence the ability to detect temporal abundance trends. However, in most species, abundance estimates assessed during the dry season resulted in a more accurate detection of temporal abundance trends, and at least three surveys were required to identify global temporal abundance trends. Finally, we identified a subset of species that could potentially serve as short-term disturbance indicators. Results suggest that iron cave monitoring programs implemented in our study region could focus sampling efforts in the dry season, where detectability of target species is higher, while assuring data collection for at least three years. More generally, our study reveals the importance of long-term cave monitoring programs for detecting possible disturbances in subterranean ecosystems, and for using the generated information to optimize future monitoring efforts.

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          mvabund- anRpackage for model-based analysis of multivariate abundance data

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            Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine

            Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil.
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              The selection, testing and application of terrestrial insects as bioindicators

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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                16 April 2021
                2021
                : 9
                : e11271
                Affiliations
                [1 ]Biodiversity and Ecosystem Services, Instituto Tecnológico Vale , Belém, Pará, Brazil
                [2 ]Environmental Licensing and Speleology, Vale S.A. , Nova Lima, Minas Gerais, Brazil
                Author information
                http://orcid.org/0000-0001-9260-1441
                http://orcid.org/0000-0002-2101-5282
                Article
                11271
                10.7717/peerj.11271
                8054738
                33959423
                195989f5-eb97-4c21-b7e3-a90a259542d1
                © 2021 Trevelin et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 4 January 2021
                : 23 March 2021
                Funding
                Funded by: Instituto Tecnológico Vale. RJ Conselho Nacional de Desenvolvimento Científico e Tecnológico
                Award ID: 301616/2017-5
                Funding was provided by Instituto Tecnológico Vale. RJ received a research productivity grant from Conselho Nacional de Desenvolvimento Científico e Tecnológico (301616/2017-5). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Biodiversity
                Conservation Biology
                Ecology
                Zoology
                Population Biology

                iron caves,landscape ecology,mining,speleology,subterranean communities,troglobites

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