Landscape-scale benefits of protected areas for tropical biodiversity

Nature, Journal Year: 2023, Volume and Issue: 620(7975), P. 807 - 812

Published: Aug. 23, 2023

Language: Английский

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Citizen science needs a name change

Trends in Ecology & Evolution, Journal Year: 2023, Volume and Issue: 38(6), P. 485 - 489

Published: April 21, 2023

Language: Английский

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Spatially Explicit Capture-Recapture Through Camera Trapping: A Review of Benchmark Analyses for Wildlife Density Estimation

Frontiers in Ecology and Evolution, Journal Year: 2020, Volume and Issue: 8

Published: Dec. 18, 2020

Camera traps have become an important research tool for both conservation biologists and wildlife managers. Recent advances in spatially explicit capture-recapture (SECR) methods increasingly put camera at the forefront of population monitoring programs. These allow benchmark analysis species density without need invasive fieldwork techniques. We conducted a review SECR studies using to summarize current focus these investigations, as well provide recommendations future identify areas investigation. Our shows strong bias preference, with large proportion focusing on felids, many which only baseline estimates species. Furthermore, we found that majority produced may not be precise enough long-term monitoring. recommend simulation power before initiating any particular study design examples readily available software. show precision can increased by including larger area will subsequently increase number individuals photo-captured. As lack resources or manpower accomplish such effort, researchers incorporate new technologies machine-learning, web-based data entry, online deployment management into their design. also cautiously potential citizen science help address concerns. In addition, modifications model development include subset individual identification (often called mark-resight models), extend process estimation through trapping individually identifiable.

Language: Английский

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Ecological Correlates of Elevational Range Shifts in Tropical Birds

Frontiers in Ecology and Evolution, Journal Year: 2021, Volume and Issue: 9

Published: April 12, 2021

Globally, birds have been shown to respond climate change by shifting their elevational distributions. This phenomenon is especially prevalent in the tropics, where gradients are often hotspots of diversity and endemism. Empirical evidence has suggested that range shifts far from uniform across species, varying greatly direction (upslope vs. downslope) rate (speed shift). However, little known about drivers these variable responses change, limiting our ability accurately project changes future. Here, we compile empirical estimates shift rates (m/yr) for 421 bird species eight study sites tropics. On average, shifted mean elevations upslope 1.63 ± 0.30 m/yr, upper limits 1.62 m 0.38 lower 2.81 0.42 m/yr. Upslope increased smaller-bodied, less territorial whereas larger were more likely downslope. When considering absolute rates, fastest with high dispersal ability, low foraging strata, wide ranges. Our results indicate associated species’ traits, particularly body size, territoriality. effects vary substantially sites, suggesting tropical montane communities complex best predicted within local or regional context.

Language: Английский

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Turning observations into biodiversity data: Broadscale spatial biases in community science

Ecosphere, Journal Year: 2023, Volume and Issue: 14(6)

Published: June 1, 2023

Abstract Biodiversity community science projects are growing rapidly in popularity. The enormous amounts of data generated by these programs transforming how we conduct ecological research and conservation management. However, as with other biodiversity surveys, datasets suffer from biases time locations observations. To better use data, modeled the spatial present popular platform, iNaturalist. iNaturalist uses crowdsourcing to collect georeferenced time‐stamped observations all taxa worldwide. With its wealth is now being used answer a broad range questions ecology conservation, but little known about platform's biases. We focus on more than 1.75 million available (as December 2021) British Columbia, Canada, region strong presence diversity ecosystems. Using machine learning species distribution modeling, examined which landscape factors (e.g., protected areas, roads, human population density, habitat zones, elevation) were most important determining where taken, created predicted probability map revealing likely different regions be sampled scientists. found road for iNaturalist, over 94% within 1 km roads. In addition, density ecosystem zones played large role predicting occur across landscape. These methods demonstrate tools modeling effects opportunistic that can then produce accurate models data.

Language: Английский

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Effects of input data sources on species distribution model predictions across species with different distributional ranges

Journal of Biogeography, Journal Year: 2022, Volume and Issue: 49(7), P. 1299 - 1312

Published: May 17, 2022

Abstract Aim A major source of uncertainty in the application species distribution models (SDMs) is related to input data quality. Citizen‐collected occurrence are often used for fitting SDMs when from standardized and expert‐supported surveys unavailable. Macroclimate variables much more commonly as predictors than other sources coming remote sensing data. Here, we assess effects using different (in both response predictor variables) on SDM performance across a wide range with contrasting distributional ranges. Location Iberian Peninsula. Taxon Birds. Methods ensemble‐forecasting approach was implemented bird two sources: eBird project Atlases. We fitted three types: macroclimate, remotely sensed ecosystem functional attributes (EFAs) their combination. Species were grouped four size classes. assessed model predictions by evaluation metrics. Generalized linear mixed‐effects tested effect sizes while accounting accuracy Pairwise comparisons between projections spatial similarity. Results Data source, class, metric showed significant performance. eBird‐based outperformed those built Atlas less widespread species. Climate yielded best performance, especially combined EFAs. However, contribution consistent datasets, being mostly driven range. Main Conclusions Our demonstrated usefulness complementarity modelling These findings highlight need integrate improve at regional scale. framework also underlines that should be examined exhaustively early stages process.

Language: Английский

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Estimating sampling biases in citizen science datasets

Ibis, Journal Year: 2024, Volume and Issue: unknown

Published: June 28, 2024

The rise of citizen science (also called community science) has led to vast quantities species observation data collected by members the public. Citizen tend be unevenly distributed across space and time, but treatment sampling bias varies between studies, interactions different biases are often overlooked. We present a method for conceptualizing estimating spatial temporal biases, them. use this estimate in an example ornithological dataset from eBird Brisbane City, Australia. then explore effects these on subsequent model inference population trends, using both simulation study application same trend models dataset. find varying levels scales, evidence biases. Several we identified differ those described literature other datasets, with protected areas being undersampled city, only limited seasonal bias. demonstrate variable performance under scenarios, more complex associated typically poorer estimates. Sampling important consider when analysing ecological analysts can ensure that any biologically relevant detected given due consideration during analysis. With appropriate specification, reduced yield reliable information about biodiversity.

Language: Английский

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Methods for Monitoring Large Terrestrial Animals in the Wild

Forests, Journal Year: 2020, Volume and Issue: 11(8), P. 808 - 808

Published: July 26, 2020

Reliable information about wildlife is absolutely important for making informed management decisions. The issues with the effectiveness of control and monitoring both large small wild animals are relevant to assess protect world’s biodiversity. Monitoring becomes part methods in ecology observation, assessment, forecasting human environment. World practice reveals potential joint application proven traditional modern technologies using specialized equipment organize environmental processes. terrestrial require an individual approach due their low density larger habitat. Elk/moose such animals. This work aims evaluate animals, suitable controlling number elk/moose framework nature conservation activities. Using different models allows determining population size without affecting significant financial costs. Although, accuracy each model determined by its postulates implementation initial conditions that need statistical data. Depending on geographical, climatic, economic territory, it possible use tools (e.g., cameras, GPS sensors, unmanned aerial vehicles), a flexible variation which will allow reaching golden mean between desires capabilities researchers.

Language: Английский

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Spatiotemporal Distribution of Photographic Records of Brazilian Birds Available in the WikiAves Citizen Science Database

Birds, Journal Year: 2023, Volume and Issue: 4(1), P. 28 - 45

Published: Jan. 22, 2023

About four million photographic records of Brazilian birds are deposited in the WikiAves database. The objective this study was to examine spatiotemporal distribution available Searches were performed database 2022. Record numbers produced by citizens obtained selecting states and municipalities different periods. annual record production Brazil has increased substantially since 2009, reaching about 400,000 per year 2020–2021. Most Sudeste Sul geopolitical regions. Seasonal variations Cerrado Atlantic Forest comparable, with more July–October. In Amazonia, a substantial decrease occurred between November April. monthly uniform Caatinga. When compared, similar seasonal variation observed for ecosystems (Amazonia, Forest, Pampa). However, differences Pantanal results indicate that high human density, individual income breeding season potential factors leading production. On other hand, heavy rainfall, flooding, remoteness environmental harshness pointed out as potentially relatively fewer records. Further, article discusses implications availability ornithological studies use

Language: Английский

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Removing Human Bottlenecks in Bird Classification Using Camera Trap Images and Deep Learning

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(10), P. 2638 - 2638

Published: May 18, 2023

Birds are important indicators for monitoring both biodiversity and habitat health; they also play a crucial role in ecosystem management. Declines bird populations can result reduced services, including seed dispersal, pollination pest control. Accurate long-term of birds to identify species concern while measuring the success conservation interventions is essential ecologists. However, time-consuming, costly often difficult manage over long durations at meaningfully large spatial scales. Technology such as camera traps, acoustic monitors drones provide methods non-invasive monitoring. There two main problems with using traps monitoring: (a) cameras generate many images, making it process analyse data timely manner; (b) high proportion false positives hinders processing analysis reporting. In this paper, we outline an approach overcoming these issues by utilising deep learning real-time classification automated removal trap data. Images classified Faster-RCNN architecture. transmitted 3/4G processed Graphical Processing Units (GPUs) conservationists key detection metrics, thereby removing requirement manual observations. Our models achieved average sensitivity 88.79%, specificity 98.16% accuracy 96.71%. This demonstrates effectiveness automatic

Language: Английский

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