Search

Participation in authentic research in the field and online through Community and Citizen Science (CCS) has shown to bring learning benefits to volunteers. In online CCS, available platforms present distinct features, ranging from scaffolding the process of data collection, to supporting data analysis and enabling volunteers to initiate their own studies. What is yet not well understood is how best to design CCS programmes that are educational, inclusive, and accessible by diverse volunteers, including young people and those with limited prior science experiences who are rather few in CCS. In this study, we interviewed 31 young people, aged 7-20 years old, who used iNaturalist, an online biodiversity monitoring platform, and identified how different forms of participation online and in the field facilitated (or inhibited) certain forms of learning, as defined by the Environmental Science Agency framework. Findings revealed that iNaturalist enabled participation of young people including those with limited science experiences and facilitated science learning such as the development of science competence and understanding. A blended learning framework for biodiversity monitoring in CCS is presented as a means to support the development of hybrid, educational, and inclusive CCS programmes for young people.

Biodiversity loss is increasing worldwide, necessitating effective approaches to counteract negative trends. Here, we assessed aquatic macroinvertebrate biodiversity in two river catchments in Switzerland; one significantly degraded and associated with urbanisation and instream barriers, and one in a near-natural condition. Contrary to our expectations, environmental heterogeneity was lower in the near-natural stream, with enhanced productivity in the degraded system resulting in a greater range of environmental conditions. At face value, commonly employed alpha, beta and gamma biodiversity metrics suggested both catchments constituted healthy systems, with greater richness or comparable values recorded in the degraded system relative to the near-natural one. Further, functional metrics considered to be early indicators for anthropogenic disturbance, demonstrated no anticipated differences between degraded and near-natural catchments. However, investigating the identity of the taxa unique to each river system showed that anthropogenic degradation led to replacement of specialist, sensitive species indicative of pristine rivers, by generalist, pollution tolerant species. These replacements reflect a major alteration in community composition in the degraded system compared with the near-natural system. Total nitrogen and fine sediment were important in distinguishing the respective communities. We urge caution in biodiversity studies that employ numerical biodiversity metrics alone. Assessing just one aspect of diversity, such as richness, is not sufficient to track biodiversity changes associated with environmental stress. We advocate that biodiversity monitoring for conservation and management purposes must go beyond traditional richness biodiversity metrics, to include indices that incorporate detailed nuances of biotic communities that relates to taxon identity. [ABSTRACT FROM AUTHOR]

Biogeographic context, such as biome type, has a critical influence on ecological resilience, as climatic and environmental conditions impact how communities respond to anthropogenic threats. For example, land‐use change causes a greater loss of biodiversity in tropical biomes compared to temperate biomes. Furthermore, the nature of threats impacting ecosystems varies geographically. Therefore, monitoring the state of biodiversity at a high spatial resolution is crucial to capture variation in threat–responses caused by biogeographical context. However such fine‐scale ecological data collection could be prohibitively resource intensive. In this study, we aim to find the spatial scale that could best capture variation in community‐level threat responses whilst keeping data collection requirements feasible. Using a database of biodiversity records with extensive global coverage, we modelled species richness and total abundance (the responses) across land‐use types (reflecting threats), considering three different spatial scales: biomes, biogeographical realms, and regional biomes (the interaction between realm and biome). We then modelled data from three highly sampled biomes to ask how responses to threat differ between regional biomes and taxonomic group. We found strong support for regional biomes in explaining variation in species richness and total abundance compared to biomes or realms alone. Our biome case studies demonstrate that there is variation in magnitude and direction of threat responses across both regional biomes and taxonomic group, although the interpretation is limited by sampling bias in the literature. All groups in tropical forest showed a consistently negative response, whilst many taxon‐regional biome groups showed no clear response to threat in temperate forest and tropical grassland. Our results provide the first empirical evidence that the taxon‐regional biome unit has potential as a reasonable spatial unit for monitoring how ecological communities respond to threats and designing effective conservation interventions to bend the curve on biodiversity loss. [ABSTRACT FROM AUTHOR]

Over 20 years ago, ecologists were introduced to the site occupancy model (SOM) for estimating occupancy rates from detection‐nondetection data. In the ensuing decades, the SOM and its hierarchical modeling extensions have become mainstays of quantitative ecology, and estimating occupancy rates has become one of the most common applications of ecological field data. Here, we review 364 peer‐reviewed articles published between 2019–2021 that estimated occupancy. We first document broad patterns in study design and statistical methods to provide educators, developers of methodology and software, and ecologists with a clear picture of the landscape of methodologies used to estimate animal occupancy. Second, we conduct a focused review of a subset of 98 papers that applied the hierarchical SOM, drawing from methodological literature to identify discrepancies between SOM applications and methodological best practices. We discuss limits to statistical power, issues with model checking and model selection procedures, potential problems arising from unmodeled non‐independence, and reproducibility. We highlight areas of rapid advancement in interpreting animal occupancy related to animal movement, imperfect detection, and the occupancy–density relationship. We aim to help readers understand the landscape of methods available, motivate shifts toward robust and reproducible science, and inspire new software and methodological research. [ABSTRACT FROM AUTHOR]

The heat tolerance of corals is largely determined by their microbial photosymbionts, and manipulating these symbiont communities may enhance the ability of corals to survive summer heatwaves. Experimental evolution of Symbiodiniaceae cultures under elevated temperatures has been successfully used to enhance the upper thermal tolerance of both symbiont cultures in vitro and corals following inoculation. Novel culturing, upscaling, and biodiversity monitoring techniques are required to deliver experimentally evolved coral symbionts at scale, and success requires learning from, or directly utilising, adjacent industries (e.g., biotechnology for algae-based commodities). This intervention has transitioned from stakeholder engagement to regulatory approval for risk assessments via small-scale field trials, which is an essential step on the path to implementation. The heat tolerance of corals is largely determined by their microbial photosymbionts (Symbiodiniaceae, colloquially known as zooxanthellae). Therefore, manipulating symbiont communities may enhance the ability of corals to survive summer heatwaves. Although heat-tolerant and -sensitive symbiont species occur in nature, even corals that harbour naturally tolerant symbionts have been observed to bleach during summer heatwaves. Experimental evolution (i.e., laboratory selection) of Symbiodiniaceae cultures under elevated temperatures has been successfully used to enhance their upper thermal tolerance, both in vitro and, in some instances, following their reintroduction into corals. In this review, we present the state of this intervention and its potential role within coral reef restoration, and discuss the next critical steps required to bridge the gap to implementation. [ABSTRACT FROM AUTHOR]

Payments for ecosystem services (PES) are widely applied incentive‐based instruments with diverse objectives that increasingly include biodiversity conservation. Yet, there is a gap in understanding of how to best assess and monitor programs' biodiversity outcomes. We examined perceptions and drivers of engagement related to biodiversity monitoring through surveys among current PES participants in 7 communities in Mexico's Selva Lacandona. We conducted workshops among survey participants that included training and field deployment of tools used to monitor biodiversity and land cover, including visual transects, camera traps, acoustic recorders, and forest cover satellite images. We conducted pre‐ and postworkshop surveys in each community to evaluate changes in respondents' perceptions following exposure to biodiversity monitoring training and related field activities. We also reviewed existing research on participatory environmental management and monitoring approaches. One quarter of current PES participants in the study area participated in our surveys and workshops. The majority stated interest in engaging in diverse activities related to the procedural aspects of biodiversity monitoring (e.g., planning, field data collection, results dissemination) and acknowledged multiple benefits of introducing biodiversity monitoring into PES (e.g., knowledge and capacity building, improved natural resource management, and greater support for conservation). Household economic reliance on PES was positively associated with willingness to engage in monitoring. Technical expertise, time, and monetary constraints were deterrents. Respondents were most interested in monitoring mammals, birds, and plants and using visual transects, camera traps, and forest cover satellite images. Exposure to monitoring enhanced subsequent interest in monitoring by providing respondents with new insights from their communities related to deforestation and species' abundance and diversity. Respondents identified key strengths and weaknesses of applying different monitoring tools, which suggests that deploying multiple tools simultaneously can increase local engagement and produce complementary findings and data. Overall, our findings support the relevance and usefulness of incorporating participatory biodiversity monitoring into PES. [ABSTRACT FROM AUTHOR]

Background: Monitoring biodiversity is crucial in biogeography. Citizen science and biodiversity platforms have revolutionized data access across taxa, but they struggle to provide robust raw data essential for conservation decisions. Aims: This study addresses data gaps for under‐represented species and locations, observer expertise variability, and the lack of absence data and sampling effort information to improve data representation and suitability for statistical analyses. Materials & Methods: We collected, compared to IUCN‐recognized taxonomic groups, all worldwide living being (animal, plant and fungi) observations held by four major biodiversity platforms: eBird, GBIF, iNaturalist, and Observation.org. We also organized such observations by country of origin and based on their Human Development Index (HDI). Results: We found that, while GBIF, iNaturalist, and Observation.org cover all life forms, birds are the most observed (eBird is a bird‐specific platform), whereas fish, other marine organisms, arthropods, and invertebrates are dramatically underrepresented. Moreover, none of the above‐mentioned biodiversity platforms considered or directly analysed expertise variability among observers and, apart from eBird, the other three biodiversity platforms do not accommodate data on species absence and sampling effort. Discussion and Conclusion: Finally, we found that species observations on biodiversity platforms considered in this study are skewed towards high HDI countries, primarily North America and Europe. By enhancing the effectiveness of biodiversity platforms, this study has the potential to significantly advance the field of biogeography, paving the way for more informed and effective conservation strategies. Overall, our findings underscore the untapped potential of these platforms in contributing to our understanding of the spatial and temporal patterns of biodiversity. [ABSTRACT FROM AUTHOR]

Marine biodiversity monitoring in the Mediterranean's increasingly threatened ecosystems is crucial for effective ecosystem conservation and management. Here, we leveraged the Mediterranean International Trawl Survey program (MEDITS) to implement eDNA sampling through the recently tested 'metaprobe' procedure and characterize fish assemblages in three separate areas off the Italian coasts: Northern Adriatic Sea (NoAS), Ligurian and Northern Tyrrhenian Sea (LNTS), and Sardinian Sea (SaS). By combining the information from two homologous mitochondrial 12S metabarcodes––i.e., Elas02 and Tele02 targeting elasmobranchs and teleosts, respectively––we identified 108 species, over 60% of which overlapped with those caught by the trawl net. We produced an accurate reconstruction of fish community composition of the examined sites, reflecting differences in species assemblages linked with both geographic area and depth range. Metaprobe eDNA data consistently returned a biodiversity 'bonus' mostly consisting of pelagic taxa not captured through bottom trawl surveys, including rare and endangered taxa (e.g., elasmobranchs). Overall, the spatial characterisation of the assemblages across the surveyed areas was better delineated and more robust using eDNA metabarcoding than trawl data. Our results support the operationalisation of the metaprobe as a simple, inexpensive, versatile sampling tool, in association with pre-existing ship surveys, to overcome many of the limitations of marine data collection and strengthen marine management. [ABSTRACT FROM AUTHOR]

Genetic diversity is essential for maintaining healthy populations and ecosystems. Several approaches have recently been developed to evaluate population genetic trends without necessarily collecting new genetic data. Such "genetic diversity indicators" enable rapid, large-scale evaluation across dozens to thousands of species. Empirical genetic studies, when available, provide detailed information that is important for management, such as estimates of gene flow, inbreeding, genetic erosion and adaptation. In this article, we argue that the development and advancement of genetic diversity indicators is a complementary approach to genetic studies in conservation biology, but not a substitute. Genetic diversity indicators and empirical genetic data can provide different information for conserving genetic diversity. Genetic diversity indicators enable affordable tracking, reporting, prioritization and communication, although, being proxies, do not provide comprehensive evaluation of the genetic status of a species. Conversely, genetic methods offer detailed analysis of the genetic status of a given species or population, although they remain challenging to implement for most species globally, given current capacity and resourcing. We conclude that indicators and genetic studies are both important for genetic conservation actions and recommend they be used in combination for conserving and monitoring genetic diversity. [ABSTRACT FROM AUTHOR]

Coral reefs are known to be one of the most diverse marine ecosystems on earth. However, these important ecosystems are heavily stressed by natural and anthropogenic activities. Environmental DNA (eDNA) metabarcoding is an innovative approach that can provide a greater diversity of taxonomic detections, non-invasive sampling, and a lower field component cost than traditional biomonitoring methods. Taiping Island (Itu Aba Island) is one of the major coral reef islands situated in the South China Sea where underwater visual surveys documented an outbreak of Crown-of-Thorns starfish (COTS) in 2021. In our study, we used eDNA metabarcoding to investigate whether there were shifts in coral communities by comparing pre- and post-COTS outbreak communities. One metabarcoding assay targeting the 18S gene and two assays targeting the ITS2 region (one of these assays specifically targeting Acroporid corals) were applied to 42 seawater samples collected in 2019 and 2021 from 12 sites around Taiping Island. Based on these three metabarcoding assays, 52 unique hard coral species were identified, corresponding to a total of 51 species in 2019 and 26 species in 2021. Our results indicated a significant decline in coral diversity but an increase in sponge diversity from the phylum porifera at Taiping Island in 2021. We suggest that these faunal shifts may be due to active feeding and disturbance of COTS at outbreak proportions that result in habitat changes. Our findings also suggest that eDNA can continue to serve as a promising tool to monitor the change in coral as well as reef-associated taxa during devastating outbreak events. [ABSTRACT FROM AUTHOR]

Long-term biodiversity monitoring studies of restored wetland ecosystems are essential for successful conservation. We studied the bird diversity of century-old Pashan Lake (18.5344°N, 73.7853°E), Pune, Maharashtra, India, after 15 years of restoration. Pashan Lake is an overwintering site for many birds and recently went through a restoration event after eutrophication. Currently, the lake receives heavy sewage water and industrial effluents through a small river Ramnadi. The lake receives heavy monsoon rainwater, and in late winter and summer, hyacinth vegetation covers the entire lake surface. We monitored bird diversity (number of species with abundance) at Pashan Lake throughout the year (June 2021-May 2022) using the point transact method during morning and evening hours. We also recorded physicochemical parameters, including water temperature, pH, dissolved oxygen, conductivity, salt, and TDS (Total Dissolved Solids). We calculated diversity indices for each season, Monsoon (June–September), winter (October-January), and summer (February-May). We recorded a total 81 bird species with the highest bird diversity in the winter season. Omnivorous and insectivorous birds dominate the fauna. Bird community recorded every month was clustered into two groups, June-November and December-May, suggesting the influence of hyacinth vegetation. Bird community was dissimilar among seasons. The study signifies the importance of long-term biodiversity monitoring studies for wetland conservation. [ABSTRACT FROM AUTHOR]

Copyright of Methods in Ecology & Evolution is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Urban roads are known to affect wildlife fauna but most assessments of the impacts of roads have been done in cities of the developed world with comparable studies still lacking from sprawling cities of the developing countries. This gap precludes the ability of the city management authorities in designing the appropriate mitigation and conservation measures especially during this era where the road networks in African cities is expanding steadily. We surveyed 48 km of roads transcending an urban-rural gradient in Morogoro city, Tanzania to understand the patterns of road kills, taxonomic composition and used the Generalized linear modeling to determine the ecological and environmental factors mostly influencing the road kill abundances. We also assessed the conservation status of the road kills to propose measures to improve biodiversity conservation in this urban landscape bordering a global biodiversity hotspot. We found 929 killed animals belonging to 62 families and 23 orders and 5 taxa (classes) with the majority kills being insects. There was a significant difference on road kill abundance between taxa but no significant difference in kill abundance across the urban-rural gradient. Furthermore, we found that designated road speed limit was significantly positively associated with increased road kills with the insect taxon occurring most abundant in the kill. Additionally, we found three species involved in the animal-vehicle collision threatened with extinction and over 50% of the recorded road kills lacking information on their conservation status on the red list at all. These data may be useful in improving the strategies to reducing the animal-vehicle collisions and to inform the potential biodiversity monitoring in the study area and elsewhere in Africa's cities faced with similar urbanization challenges. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) serves as a valuable proxy for photosynthesis. The TROPOspheric Monitoring Instrument (TROPOMI) aboard the Copernicus Sentinel-5P mission offers nearly global coverage with a fine spectral resolution for reliable SIF retrieval. However, the present satellite-derived SIF datasets are accessible only at coarse spatial resolutions, constraining its applications at fine scales. Here, we utilized a weighted stacking algorithm to generate a high spatial resolution SIF dataset (500 m, 8-day) in China (HCSIF) from 2000 to 2022 from the TROPOMI with a spatial resolution at a nadir of 3.5 km by 5.6–7 km. Our algorithm demonstrated high accuracy on validation datasets (R2 = 0.87, RMSE = 0.057 mW/m2/nm/sr). The HCSIF dataset was evaluated against OCO-2 SIF, GOME-2 SIF tower-based measurements of SIF, and gross primary productivity (GPP) from flux towers. We expect this dataset can potentially advance the understanding of fine-scale terrestrial ecological processes, allowing for monitoring of ecosystem biodiversity and precise assessment of crop health, productivity, and stress levels in the long term. [ABSTRACT FROM AUTHOR]

Mangrove environments have garnered attention in recent years as a result of their substantial contribution to the earth's dynamic. Its function in carbon sequestration within coastal sediments helps alleviate climate change. Mangrove ecosystems, characterized by various tree species, face numerous threats and require continuous monitoring for conservation efforts, which can be facilitated by remote sensing. Biodiversity monitoring and the detection of different species demand highly specific techniques. This study introduces a comprehensive analysis of in situ spectral signatures for two mangrove species found in Egypt. We assessed these spectral signatures and organized them into a spectral library to classify high-resolution Pleiades Neo satellite images using linear unmixing techniques to differentiate the mangrove species. The results were significant, allowing us to distinguish five halophyte coastal species and accurately identify the two mangrove species, Avicennia marina and Rhizophora mucronata, with an accuracy assessment of 89.83%. [ABSTRACT FROM AUTHOR]

Simple Summary: Little attention has been paid to the efficiency of trap types in capturing bees across taxonomic and functional groups, nor their suitability under varying environmental conditions. Our study evaluated the efficiency, bias, and complementarity of four trap types: yellow, white, and blue pan traps, and blue vane traps for pollinator monitoring in monoculture and mixed forests. We found that bias in trap types was not only detected in taxonomic but also in functional groups. Differences in bee taxonomic, phylogenetic, and functional diversity were also observed, with blue pan traps yielding the highest species richness and phylogenetic diversity, while blue vane traps captured the highest functional richness. When considering the complementarity of different traps, the combination of blue pan and vane traps outperformed the other two-method combinations. Notably, the bias in trap types was most pronounced in mixed forests. The choice of trap in entomological surveys affects the composition of captured insects, though previous comparative studies have been limited in the types of composition measured, and the effects of environmental context. We assessed the sampling bias of several traps commonly used in pollinator monitoring: blue, yellow, and white pan traps, and blue vane traps, towards different taxonomic and functional groups and their efficiency in measuring taxonomic, phylogenetic, and functional diversity. Analyses were performed in monoculture and mixed forests to understand the environmental context of trap efficiency. We found that blue pan traps generally outperformed other types in bee capture and exhibited a preference for Halictidae bees. Blue pan traps yielded the highest species richness and phylogenetic diversity, while blue vane traps captured the highest functional richness. Bias differences were frequently detected in mixed forests compared with monoculture forests. We also found the combination of blue vane and pan traps consistently correlated highest with a complete survey among two-method combinations. Based on our findings, we recommend a combination of blue vane and pan traps to obtain a more comprehensive bee collection in an efficient manner. Additionally, it is crucial to consider habitat type when designing bee trapping protocols to ensure an accurate representation of bee communities. [ABSTRACT FROM AUTHOR]

Simple Summary: This study focuses on the management of the red imported fire ant (RIFA), an invasive pest in China that threatens local biodiversity. We implemented a two-step control method using three insecticides, 0.5% beta-cypermethrin dust, 1.0% hydramethylnon bait, and 0.1% indoxacarb bait, and monitored their effects on ant communities. The results showed significant reductions in RIFA populations, with the most effective insecticide being 0.1% indoxacarb bait. After treatment, there was an increase in ant species richness and diversity, indicating a positive impact on local ecosystems. The findings highlight that effective RIFA management can also restore ecological balance among native ant species, providing valuable insights for future biodiversity conservation strategies. The red imported fire ant (RIFA, Solenopsis invicta Buren) represents a significant invasive pest in China, exerting extensive negative impacts on ecosystems. The invasion of RIFA not only poses a severe threat to biodiversity within the environment; inappropriate controlling measures can also adversely affect community dynamics. Therefore, while implementing effective management strategies to control the proliferation of RIFA populations, it is imperative to evaluate the potential effects of these measures on the structure of local biological communities to safeguard native biodiversity. This study employs a "two-step method" using dust and bait formulations, respectively, to control RIFA while conducting ecological monitoring to further assess the impact of RIFA population decline on ant communities. The results of RIFA management showed that after post-treatment periods of 28 days, 35 days, and 60 days, the worker ant reduction rates for the three insecticides—0.5% beta-cypermethrin dust, 1.0% hydramethylnon bait, and 0.1% indoxacarb bait—reached approximately 72%, with their efficacy ranked as follows: 1.0% hydramethylnon bait > 0.1% indoxacarb bait > 0.5% beta-cypermethrin dust. By the 60th day of the experiment, the ant nest reduction rates reached their highest values—66.84% for 0.5% beta-cypermethrin dust, 77.89% for 1.0% hydramethylnon bait, and 87.52% for 0.1% indoxacarb bait—with the latter performing the best. Meanwhile, the occurrence level of RIFAs in all three pesticide treatment areas decreased from level III to level I 60 days post-treatment. Following the application of these three insecticides, the RIFA population significantly decreased, leading to an increase in species richness within the ant community. The reduction in RIFA numbers had a positive impact on the restoration of ant community diversity, as evidenced by significant improvements in both diversity and evenness indices. Notably, 0.1% indoxacarb bait was particularly effective in enhancing the ant community diversity and species richness, while 1.0% hydramethylnon bait was more effective in improving community evenness. These findings indicate that the controlling strategy used in this study not only effectively manages RIFA populations but also promotes recovery and contributes to the ecological balance of local ant communities, providing an important reference for future biodiversity conservation efforts. [ABSTRACT FROM AUTHOR]

There are 23 national parks in Poland, and only a few of them have been studied thoroughly with regard to acarofauna so far. One of the least-examined areas in this regard is Bory Tucholskie National Park (BTNP), established in 1996. The aim of this research study was to explore the species diversity, community structure, and spatial distribution of mites from the order Oribatida: ptyctimous mites (Acari: Oribatida) and species from the families Nothridae and Camisiidae (Acari: Oribatida: Crotonioidea) inhabiting different forests open and unstable microhabitats in the area of Bory Tucholskie National Park (BTNP). In the case of ptyctimous mites, the communities were compared to those in other Polish national parks. Based on the analysis of 285 samples collected in BTNP between 2022 and 2024, 8 species of Crotonioidea with dominant Heminothrus peltifer (C. L. Koch, 1839) and 21 species of ptyctimous mites with the most numerous Atropacarus (Atropacarus) striculus (C. L. Koch, 1835) were identified in the analyzed material. The highest species diversity was observed in different types of pine forests (25 species) and in alder forests (24 species), while the lowest diversity occurred in areas with reeds (11 species). The comparison of the number of ptyctimous mites in Polish national parks revealed that BTNP can be ranked second in terms of species diversity among 12 national parks examined in Poland so far. [ABSTRACT FROM AUTHOR]

Biodiversity loss will lead to a serious decline for ecosystem services, which will ultimately affect human well-being and survival. Monitoring the spatial and temporal dynamics of grassland biodiversity is essential for its conservation and sustainable development. This study integrated ground monitoring data, Landsat remote sensing, and environmental variables in the Three Rivers Headwater Region (TRHR) from 2000 to 2021. We established a reliable model for estimating grassland species diversity, analyzed the spatial and temporal patterns, trends of change, and the driving factors of changes in grassland species diversity over the past 22 years. Among models based on diverse variable selection and machine learning methods, the random forest (RF) combined stepwise regression (STEP) model was found to be the optimal model for estimating grassland species diversity in this study, which had an R2 of 0.44 and an RMSE of 2.56 n/m2 on the test set. The spatial distribution of species diversity showed a pattern of abundance in the southeast and scarcity in the northwest. Trend analysis revealed that species diversity was increasing in 80.46% of the area, whereas 16.59% of the area exhibited a decreasing trend. The analysis of driving factors indicated that the changes in species diversity were driven by both climate change and human activities over the past 22 years in the study area, of which temperature was the most significant driving factor. This study effectively monitors grassland species diversity on a large scale, thereby supporting biodiversity monitoring and grassland resource management. [ABSTRACT FROM AUTHOR]

More efficient methods for extensive biodiversity monitoring are required to support rapid measures to address the biodiversity crisis. While environmental DNA (eDNA) metabarcoding and quantitative PCR (qPCR) methods offer advantages over traditional monitoring approaches, their large‐scale application is limited by the time and labour required for developing assays and/or for analysis. CRISPR (clustered regularly interspaced short palindromic repeats) diagnostic technologies (Dx) may overcome some of these limitations, but they have been used solely with species‐specific primers, restricting their versatility for biodiversity monitoring. Here, we demonstrate the feasibility of designing species‐specific CRISPR‐Dx assays in silico within a short metabarcoding fragment using a general primer set, a methodology we term 'ampliscanning', for 18 of the 22 amphibian species in Switzerland. We sub‐selected nine species, including three classified as regionally endangered, to test the methodology using eDNA sampled from ponds at nine sites. We compared the ampliscanning detections to data from traditional monitoring at these sites. Ampliscanning was successful at detecting target species with different prevalences across the landscape. With only one visit, we detected more species per site than three traditional monitoring visits (visual and acoustic detections by trained experts), in particular more elusive species and previously undocumented but expected populations. Ampliscanning detected 25 species/site combinations compared to 12 with traditional monitoring. Sensitivity analyses showed that larger numbers of field visits and PCR replicates are more important for reliable detection than many technical replicates at the CRISPR‐Dx assay level. Given the reduced sampling and analysis effort, our results highlight the benefits of eDNA and CRISPR‐Dx combined with universal primers for large‐scale monitoring of multiple endangered species across landscapes to inform conservation measures. [ABSTRACT FROM AUTHOR]

The long-term monitoring of freshwater ecosystems has been globally recognized for its critical role in preserving natural biodiversity and human well-being over the past century, yet monitoring efforts remain heterogeneously distributed. The Anatolia region in Turkey is known to host three out of the world's 34 biodiversity hotspots, boasting high biodiversity, but is increasingly threatened by anthropogenic effects and invasive freshwater fish species. Although the introduction of non-native fish species and pollution has detrimental effects on different river catchments in this area, long-term biomonitoring studies in Anatolia remain scarce and inconsistent. Collecting information of the Gediz River basin, a major Anatolian river catchment as a model that has been significantly impacted by human activities, published between 1971 and 2023, a total of 21 fish species from 12 families were identified. The spatial and temporal occurrences of these species fluctuated significantly due to heterogeneous sampling efforts that did not follow a clear pattern, indicating a complex ecological and conservation scenario characterized by both spatial and temporal variability in species prevalence, endemism and abundance. The presented results emphasize the need for comprehensive long-term biodiversity monitoring for anthropogenically impacted catchments like the Gediz River basin. Only with a coherent basis of high-resolution monitoring data can the multiple stressors threatening Anatolia's freshwater biodiversity be disentangled and, subsequently, be mitigated. Using the Gediz River basin as an example, this study emphasizes the urgent need for comprehensive, long-term biodiversity monitoring in understudied regions worldwide to protect regional biodiversity and ensure ecosystem health. [ABSTRACT FROM AUTHOR]

To effectively monitor biodiversity in streams and rivers, we need to quantify species distribution accurately.Occupancy models are useful for distinguishing between the non‐detection of a species and its actual absence. While these models can account for spatial autocorrelation, they are not suited for streams and rivers due to their unique network spatial structure.Here, I propose spatial occupancy models specifically designed for data collected on stream and river networks. I present the statistical developments and illustrate their application using data on a semi‐aquatic mammal.Overall, spatial stream network occupancy models offer a robust method for assessing biodiversity in freshwater ecosystems. [ABSTRACT FROM AUTHOR]

Efficient biodiversity surveys are critical for successful restoration monitoring and management. We studied the effect of varying sampling effort on the observed species richness of surveys of small mammals (trapping transects), bats (passive acoustic detection), and medium to large mammals (trail cameras). Field studies provided mammalian biodiversity data for 4 bottomland hardwood restoration sites in northeastern Indiana. Subsampled data were used to simulate monitoring surveys with a range of levels of effort. We then used hierarchical Bayesian nonlinear mixed models to analyze how different components of sampling effort affected observed species richness, a key monitoring outcome. We found that observed small mammal richness increased with the increased number of transects in a survey, while observed bat and medium to large mammal richness increased with the increased duration of sampling. Variation between sites was important for the observed richness of small mammals and bats but not for medium to large mammals. The key driver of richness observed in simulated surveys was related to the spatial scale at which target fauna interact with the habitat, with decreasing richness accompanied by a greater spatial scale of animal–habitat interactions. Our findings suggest taxon‐specific recommendations for efficiently quantifying the mammalian diversity of managed sites. Integr Environ Assess Manag 2024;20:1969–1981. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC) Key Points: Hierarchical subsampling was used to simulate how different levels of sampling effort affected the observed biodiversity of mammals.Observed small mammal species richness increased with number of samples (i.e., transects).For bats and medium to large mammals the duration of sampling, not number of samples, had the greatest effect on observed species richness.The spatial scale at which a species interacts with the habitat determined which component of sampling effort had the greatest effect. [ABSTRACT FROM AUTHOR]

Butterflies and plant species are widely used as model systems in biodiversity and conservation research. However, little is known about spatial patterns of butterfly diversity linked to plant communities across coastal dune ecotones. We explored the relation between butterfly and vegetation diversity in a Mediterranean protected dune system in Central Italy. We sampled butterfly and plant communities on shifting and fixed dunes and investigated their distribution patterns by diversity indexes and Species Abundance Diversity models (SADs). We also computed species beta-diversity and analyzed the relation between butterfly communities and vegetation by correlation analyses. Cross-taxon congruence in species richness, composition and abundance was assessed using Mantel correlation tests. Both butterfly and plant diversity were higher on the fixed dunes than on the shifting dunes. In both communities, SADs were adequately described by the geometric series model, which is typical of harsh environments with simple communities dominated by few species. Among both butterflies and plants, we identified species found only on either the shifting or the fixed dunes. Correlation between plant and butterfly diversity was higher for entomophilous plant species than for the more abundant anemophilous ones. Our results indicate that both plant and butterfly communities respond to the sea-inland environmental gradient, forming distinct communities with specialized taxa. Our findings also provide evidence of the importance of butterfly-plant relations for preserving biological diversity and ecosystem functioning in Mediterranean coastal areas. [ABSTRACT FROM AUTHOR]

Reconstructing past ecological population dynamics and demographic events is crucial for understanding the dynamics of ecological processes, evaluating the impact of environmental changes and making informed conservation decisions. In forest ecosystems, retrodiction (i.e. the backward projection of ecological populations) plays a pivotal role in understanding historical forest carbon levels and the factors that have influenced their variation over time, because forest demography is a major determinant of the amount of carbon stored in forest ecosystems. The persistent lack of quantitative methods has been a significant obstacle in retrodicting forest demography, especially in applications of a broad geographical scale. While there is a wealth of models for predicting future forest conditions, models that can project these conditions backward in time are scarce.This study presents reverse matrix model (RMM), an innovative retrodiction modelling approach grounded in the principles of transition matrix models. RMM is designed to deduce past demographic characteristics of ecological populations using current data, making it one of the first models capable of projecting the fine‐scale dynamics of forest demography into the past.We assessed the retrodictive performance of RMM by fitting it to a dataset of a disturbed tropical rainforest in French Guiana in 2001–2023, then comparing the retrodictions to observations back to 1983 when the disturbance occurred. We further empirically evaluated the viability of retrodiction over a defined duration by inverting the density‐dependent matrix model by Lin et al. (1996), which predicts the dynamics of northern hardwoods in the United States.The case studies demonstrate significant potential for RMM application in various domains of forestry and conservation, including ecosystem management and conservation planning, global change impact assessment and biodiversity monitoring. [ABSTRACT FROM AUTHOR]

This study thoroughly examines biodiversity and aquatic ecosystems across 14 sampled sites within the Shitou River basin by utilizing environmental DNA technology. Through integrated analysis and high‐throughput sequencing, the study elucidates a diverse array of biodiversity, encompassing 27 fish species and 341 freshwater benthic macroinvertebrates (FBM) species. Using various biodiversity indices, we found significant differences in diversity and stability across different environments. Regions with more complex habitats had higher species richness and evenness. Further analyses showed complex relationships between diversity metrics for FBM and fish, indicating potential interactions between these groups. The standardized mean score (SMS) was developed to aid in the assessment of water quality. Specifically, SMS scoring revealed that sites STH3, STH4, and STH14 excelled across multiple dimensions, earning an “Excellent” rating, while site STH12 was rated as “Poor” due to subpar performance across several metrics. This project not only enhances current understanding regarding aquatic ecological dynamics but also establishes a strong foundation for detailed environmental evaluation and monitoring, aligned with the priorities of contemporary ecological management and caution. [ABSTRACT FROM AUTHOR]

Citizen science platforms like iNaturalist play a crucial role in biodiversity monitoring. However, the identification of plants from the genus Castilleja (Indian Paintbrush), which comprises about 200 species with often similar features and frequent introgression, presents considerable challenges. Our study examines the agreement between initial identifications (often made by computer vision algorithms), subsequent identifications, and the final Research-Grade identifications for Castilleja species on iNaturalist. We focus on prevalent identification problems within this genus, particularly noting that Castilleja densiflora and Castilleja exserta are most frequently confused. This study highlights the need for improved algorithms to enhance initial species identification accuracy, especially for complex genera like Castilleja. Our findings have implications for the efficiency of the identification process on citizen science platforms and underscore the importance of expert verification in challenging taxonomic groups. [ABSTRACT FROM AUTHOR]

In recent years, the need to protect and conserve biodiversity has become more critical than ever before, as a prerequisite for both sustainable development and the very survival of the human species. This has made it a priority for the scientific community to develop technological solutions that provide data and information for monitoring, directly or indirectly, biodiversity and the drivers of change. A new era of satellite earth observation upgrades the potential of Remote Sensing (RS) to support, at relatively low cost, but with high accuracy the extraction of information over large areas, at regular intervals, and over extended periods of time. Also, the recent development of the Earth Observation Data Cubes (EODC) framework facilitates EO data management and information extraction, enabling the mapping and monitoring of temporal and spatial patterns on the Earth's surface. This submission presents the ELBIOS EODC, specifically developed to support the biodiversity management and conservation over Greece. Based on the Open Data Cube (ODC) framework, it exploits multi-spectral optical Copernicus Sentinel-2 data and provides a series of Satellite Earth Observation (SEO) biodiversity products and spectral indices nationwide. [ABSTRACT FROM AUTHOR]

The use of environmental DNA (eDNA) to assess the presence of biological communities has emerged as a promising monitoring tool in the marine conservation landscape. Moreover, advances in Next-Generation Sequencing techniques, such as DNA metabarcoding, enable multi-species detection in mixed samples, allowing the study of complex ecosystems such as oceanic ones. We aimed at using these molecular-based techniques to characterize cetacean communities, as well as potential prey on the northern coast of Mainland Portugal. During four seasonal campaigns (summer 2021 to winter 2022/2023), seawater samples were collected along with visual records of cetacean occurrence. The eDNA isolated from 64 environmental samples was sequenced in an Illumina platform, with universal primers targeting marine vertebrates. Five cetacean species were identified by molecular detection: common dolphin (Delphinus delphis), bottlenose dolphin (Tursiops truncatus), Risso's dolphin (Grampus griseus), harbor porpoise (Phocoena phocoena) and fin whale (Balaenoptera physalus). Overall, except for the latter (not sighted during the campaigns), this cetacean community composition was similar to that obtained through visual monitoring, and the complementary results suggest their presence in the region all year round. In addition, the positive molecular detections of Balaenoptera physalus are of special relevance since there are no records of this species reported on scientific bibliography in the area. The detection of multiple known prey of the identified dolphins indicates an overlap between predator and prey in the study area, which suggests that these animals may use this coastal area for feeding purposes. While this methodological approach remains in a development stage, the present work highlights the benefits of using eDNA to study marine communities, with specific applications for research on cetacean distribution and feeding ecology. [ABSTRACT FROM AUTHOR]

As anthropogenic pressures continue to increase, generalist species tend to be more resilient than specialised species. Specialisation can take various forms, among else dependence on other species through biotic interactions. Some Lycaenid butterflies (gossamer‐winged butterflies: blues, coppers and hairstreaks; Lycaenidae Leach, 1815)) rely on host ants for larval care and survival (myrmecophily). This dependence may pose an additional threat. To investigate whether myrmecophily is associated with the long‐term trends of Lycaenids, we compared 40‐year occupancy trends derived from occupancy‐detection models of ant‐independent, facultative and obligate myrmecophile Lycaenidae in a central European model region. Contrary to our expectations, obligate myrmecophile butterflies did not show more declines compared to ant‐independent ones. Five out of seven obligate myrmecophile butterflies increased, while five out of eight ant‐independent Lycaenids decreased. Trends among facultative butterflies were highly ambiguous. The differences between the groups were not significant. Although obligate myrmecophile butterflies are protected significantly more often under stricter rules, the degree of protection did not affect Lycaenid long‐term trends. European obligate myrmecophile butterflies interact with several ant species within widespread genera (primarily Myrmica Latreille, 1804, also Formica Linnaeus, 1758 and Lasius Fabricius, 1804) potentially protecting the larvae against environmental impacts and thus mitigating the effects of changing conditions on the butterflies. Incomplete understanding of the varying degrees of ant affiliation hinders the identification of specific interactions that may require increased conservation efforts. In our rapidly changing world, monitoring changes in the opportunities and strengths of species interactions is needed to prevent coupled species' extinctions and improve conservation outcomes. [ABSTRACT FROM AUTHOR]

Mitigating ongoing losses of insects and their key functions (e.g. pollination) requires tracking large‐scale and long‐term community changes. However, doing so has been hindered by the high diversity of insect species that requires prohibitively high investments of time, funding and taxonomic expertise when addressed with conventional tools. Here, we show that these concerns can be addressed through a comprehensive, scalable and cost‐efficient DNA metabarcoding workflow. We use 1815 samples from 75 Malaise traps across Germany from 2019 and 2020 to demonstrate how metabarcoding can be incorporated into large‐scale insect monitoring networks for less than 50 € per sample, including supplies, labour and maintenance. We validated the detected species using two publicly available databases (GBOL and GBIF) and the judgement of taxonomic experts. With an average of 1.4 M sequence reads per sample we uncovered 10,803 validated insect species, of which 83.9% were represented by a single Operational Taxonomic Unit (OTU). We estimated another 21,043 plausible species, which we argue either lack a reference barcode or are undescribed. The total of 31,846 species is similar to the number of insect species known for Germany (~35,500). Because Malaise traps capture only a subset of insects, our approach identified many species likely unknown from Germany or new to science. Our reproducible workflow (~80% OTU‐similarity among years) provides a blueprint for large‐scale biodiversity monitoring of insects and other biodiversity components in near real time. [ABSTRACT FROM AUTHOR]

Biodiversity monitoring is key for understanding the delivery of ecosystem functions and services. Mediterranean forests and woodlands harbor many characteristic species of the Mediterranean vascular flora, and hence, they are a good surrogate for detecting changes in biodiversity linked to global change. In this work, we present a database resulting from the study of vascular plant diversity in multi-scale plots of 0.1 ha, measured around the first decade of this century and located in Mediterranean forest environments. Diversity profiles are calculated from Hill numbers (0, 1 and 2) for local (α) and regional (ϒ) diversity, as well as a multiplicative calculation of differential diversity (β). The main Mediterranean forests sampled had a medium coverage of 51% and stand dominant height of 10.6 m, and they were monospecific in two-thirds of cases. Local diversity reaches its highest values (around 78 species per 0.1 ha) in Holm oak dehesas, with values below 50 species for the most productive forest stands dominated by species of the genus Pinus. As regards the contribution to regional diversity, broadleaf formations contribute the most, with stone pine forests and dehesas in an intermediate position, and pine forests contributing the lowest in species richness terms. [ABSTRACT FROM AUTHOR]

Urban trees support vital ecological functions and help with the mitigation of and adaption to climate change. Yet, their monitoring and management require significant public resources. remote sensing could facilitate these tasks. Recent hyperspectral satellite programs such as PRISMA have enabled more advanced remote sensing applications, such as species classification. However, PRISMA data's spatial resolution (30 m) could limit its utility in urban areas. Improving hyperspectral data resolution with pansharpening using the PRISMA coregistered panchromatic band (spatial resolution of 5 m) could solve this problem. This study addresses the need to improve hyperspectral data resolution and tests the pansharpening method by classifying exemplative urban tree species in Naples (Italy) using a convolutional neural network and a ground truths dataset, with the aim of comparing results from the original 30 m data to data refined to a 5 m resolution. An evaluation of accuracy metrics shows that pansharpening improves classification quality in dense urban areas with complex topography. In fact, pansharpened data led to significantly higher accuracy for all the examined species. Specifically, the Pinus pinea and Tilia x europaea classes showed an increase of 10% to 20% in their F1 scores. Pansharpening is seen as a practical solution to enhance PRISMA data usability in urban environments. [ABSTRACT FROM AUTHOR]

The article discusses the need for improved monitoring of plants and pollinators in response to the challenges posed by pollution, climate change, and habitat loss. The current methods of collecting occurrence data are limited in their ability to detect short-term trends and monitor conservation efforts. The symposium held in Paris aimed to assess existing monitoring schemes, identify gaps, and propose guidelines for improvement. The article emphasizes the importance of coordinated efforts, technological innovations, and international collaboration in monitoring and conserving plant and pollinator populations. [Extracted from the article]

Preserving biodiversity is a paramount global concern and, in this regard, monitoring urban biodiversity has increasingly taken on a significant role. Citizen science has emerged as a resource for addressing this challenge, offering a cost-effective approach capable of producing extensive data while promoting public engagement. In this work, a Lisbon university campus was used to determine the effectiveness of a citizen science project launched on the BioDiversity4All/iNaturalist platform to monitor urban biodiversity and analyse the influence of different engagement actions on biodiversity observations. The data analysis was based on biodiversity observations, including the temporal evolution of observations, the most frequently observed taxonomic groups, and the impact of promotional actions on project data. Additionally, the profiles of the observers were analyzed to assess their level of engagement and continued involvement in citizen science. The project had an effect on the increase in the number of observers and observations, and it was also possible to see a positive effect of the organized activities. The two indices used showed that Researchers and Students were the observer categories responding the most to the project, followed by Naturalists and Others. The results highlighted the capacity of citizen science to increase interest in biodiversity among both the university community and the general public. Furthermore, this work underlines the role of different strategies such as BioBlitzes, social media campaigns, and formal education activities to reduce the impact of relevant limitations associated with citizen science, namely taxonomic, aesthetic, and temporal biases. [ABSTRACT FROM AUTHOR]

With increasing demands for biodiversity monitoring, the integration of camera trapping (CT) and deep learning automation holds significant promise. However, few studies have addressed the application potential of this approach in urban areas in Asia. 4064 CT images targeting 18 species of urban wildlife in South Korea were collected and used to fine-tune a pre-trained object detection model. The performance of the custom model was evaluated across three levels: animal filtering, mammal and bird classification, and species classification, to assess its applicability. A comparison with existing universal models was conducted to test the utility of the custom model. The custom model demonstrated approximately 94% and 85% accuracy in animal filtering and species classification, respectively, outperforming universal models in some aspects. In addition, recommendations regarding CT installation distances and the acquisition of nighttime data were provided. Importantly, these results have practical implications for terrestrial monitoring, especially focusing on the analysis of local species. Automating image filtering and species classification facilitates efficient analysis of large CT datasets and enables broader participation in wildlife monitoring. [ABSTRACT FROM AUTHOR]

To effectively protect the marine environment, it is crucial to establish effective environ mental monitoring platforms. Traditional marine environmental monitoring methods heavily rely on morphological identification and field expertise, with the sampling process being disruptive and potentially destructive to vulnerable marine environments. In light of emerging biomonitoring needs and biodiversity declines, we reviewed the urgently needed, ongoing advances in developing effective, noninvasive, and innovative monitoring methods and systems to examine the complex marine environment for better strategic conservation and protection, using the coral ecosystem as one of the representative forefront examples in marine protection. This review summarizes current trends and efforts in transitioning into more standardizable and automatable utilizations of environmental DNA metabarcoding-based monitoring strategies and high-resolution underwater optical imaging monitoring systems as two of the promising pillars for the next generation of noninvasive biomonitoring and associated applications. The assistance of artificial intelligence for environmental DNA metabarcoding and high-resolution underwater optical imaging into an empowered, all-rounded monitoring platform for enhanced monitoring capacity is discussed as a highly potent direction for future research exploration. This review will be a cornerstone reference for the future development of artificial intelligence-assisted, noninvasive, and innovative marine environmental monitoring systems. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) metabarcoding has emerged as a promising approach to assess biodiversity and derive ecological status classes from water samples. However, a limitation of eDNA surveys is that detected DNA molecules may originate from other places or even dead organisms, distorting local biodiversity assessments. Environmental RNA (eRNA) metabarcoding has recently been proposed as a complementary tool for more localized assessments of the biological community. In this study, we evaluated the effectiveness of eDNA and eRNA metabarcoding for inferring the richness and species distribution patterns of vertebrates and invertebrates in a Central European lowland river. We collected water samples and analyzed them using a 12S marker for vertebrates and a COI marker for invertebrates. We detected 31 fish, 16 mammal, 10 bird and one lamprey species in the vertebrate dataset. While results were largely consistent, we detected a higher number of species when analysing eRNA (mean = 30.89) than eDNA (mean = 26.16). Also, eRNA detections had a stronger local signature than eDNA detections when compared against species distribution patterns from traditional fish monitoring data. For invertebrates, we detected 109 arthropod, 22 annelid, 12 rotiferan, eight molluscan and four cnidarian species. In contrast to the pattern of vertebrate richness, we detected a higher richness using eDNA (mean = 41.37) compared to eRNA (mean = 22.42). Our findings primarily show that eDNA and eRNA-based detections are comparable for vertebrate and invertebrate taxa. Biological replication was important for both template molecules studied. Signal detections for vertebrates were more localized for eRNA compared to eDNA. Overall, the advantages of the extra steps needed for eRNA analyses depend on the study question but both methods provide important data for biodiversity monitoring and research. [ABSTRACT FROM AUTHOR]

Sampling and sequencing marine environmental DNA (eDNA) provides a tool that can increase our ability to monitor biodiversity, but movement and mixing of eDNA after release from organisms before collection could affect our inference of species distributions. To assess how conditions at differing spatial scales influence the inferred species richness and compositional turnover, we conducted a paired eDNA metabarcoding and capture (beach seining) survey of fishes on the coast of British Columbia. We found more taxa were typically detected using eDNA compared to beach seining. eDNA identified more taxa with alternative habitat preferences, and this richness difference was greater in areas of high seawater movement, suggesting eDNA has a larger spatial grain influenced by water motion. By contrast, we found that eDNA consistently missed low biomass species present in seining surveys. Spatial turnover of communities surveyed using beach seining differed from that of the eDNA and was better explained by factors that vary at small (10–1000s meters) spatial scales. Specifically, vegetation cover and shoreline exposure explained most species turnover from seining, while eDNA turnover was not explained by those factors and showed a distance decay pattern (a change from 10% to 25% similarity from 2 km to 10 km of distance), suggesting unmeasured environmental variation at larger scales drives its turnover. Our findings indicate that the eDNA sample grain is larger than that of capture surveys. Whereas seining can detect differences in fish distributions at scales of 10s–100s of meters, eDNA can best summarize fish biodiversity at larger scales possibly more relevant to regional biodiversity assessments. [ABSTRACT FROM AUTHOR]

The dataset presents a 43 year-long reanalysis of pollen seasons for three major allergenic genera of trees in Europe: alder (Alnus), birch (Betula), and olive (Olea). Driven by the meteorological reanalysis ERA5, the atmospheric composition model SILAM predicted the flowering period and calculated the Europe-wide dispersion pattern of pollen for the years 1980–2022. The model applied an extended 4-dimensional variational data assimilation of in-situ observations of aerobiological networks in 34 European countries to reproduce the inter-annual variability and trends of pollen production and distribution. The control variable of the assimilation procedure was the total pollen release during each flowering season, implemented as an annual correction factor to the mean pollen production. The dataset was designed as an input to studies on climate-induced and anthropogenically driven changes in the European vegetation, biodiversity monitoring, bioaerosol modelling and assessment, as well as, in combination with intra-seasonal observations, for health-related applications. [ABSTRACT FROM AUTHOR]

Context. Indigenous people influenced fire in Australia's deserts for millennia, until colonisation interrupted traditional fire practices. Many groups are reinvigorating those practices to achieve inter-linked biodiversity, cultural, and social benefits. Contemporary fire management integrates modern planning and delivery approaches with cultural process. However, deserts have changed since colonisation (e.g. invasive species, biodiversity loss, climate change) and fire-management outcomes for Country are less certain. Some Indigenous groups are integrating scientific methods into their programs, to examine biodiversity outcomes and refine management. Aims. Karajarri and Ngurrara Traditional Owners wanted to understand how fire affects Kuwi (mammals, reptiles) on their Country, to guide fire management. Karajarri and Ngurrara Rangers worked together on this project, exchanging skills and knowledge with each other, and with scientists. Methods. We established 32 monitoring sites at four locations on Karajarri and Ngurrara Country. We undertook 11 survey trips from 2018 to 2022, gathering data from 81 site visits. Using Landsat satellite imagery we described fire patterns around each site, focussing on seral stage (as defined by Traditional Owners), patch size, and seral diversity at small (500 m), medium (1 km), and large (5 km) spatial scales. Results. There were 378 mammal captures (11 species) and 3392 reptile captures (66 species). Mammal species richness and captures were lowest in Wuntara (recently burnt) and highest in Nyirrinyanu (mature) spinifex. Mammal species richness increased with seral diversity within 1 km around the trapping site. Reptile species richness and captures were unaffected by seral stage. However, many species were caught significantly more often in specific seral stages. Neither reptile richness nor capture rate were related to patch size or seral diversity. Conclusions. Retaining a mix of seral stages can maintain diverse reptile and mammal assemblages. The management challenge will be increasing the extent of mature/long-unburnt spinifex, currently the rarest seral stage. Ranger fire management has already reduced mean fire size by 40–52%, and further reductions are possible. Implications. Our work improves the understanding of fire effects on northern desert fauna, guides management, provides important ecological information from a little-studied region of Australia's deserts, and increases the recognition of Indigenous conservation management of Country. [ABSTRACT FROM AUTHOR]

Wildlife monitoring is key for the effective management of natural resources. Hunting-based data (e.g., hunting bag statistics) is an important source of information to overcome the financial constraints imposed to long-term monitoring. Here, taking advantage of three decades (1989–2022) of hunting bag statistics of wild mammals in Portugal, we present the trends and discuss the issues regarding nine game species (five wild ungulates, two carnivores and two lagomorphs). Our results show that hunting bag statistics mirror the general population trends of wild mammal populations at a national scale. The data reflects the increase in number and distribution of roe deer, red deer and wild boar, and the recent expansion experienced by the Egyptian mongoose. The decline in the numbers of European wild rabbit and Iberian hare harvested are also noticeable. Hunting-based data have been used in several research contexts; however, this information is usually affected by geographical, temporal and recording bias. Portugal is no exception. Engaging the interested stakeholders is pivotal to ensure data quality. By reporting reliable and systematically collected hunting data, game managers and wildlife researchers will be able to better understand the main drivers of population dynamics, adjust hunting bags towards sustainable yield and assess the ecological and socio-economic relevance of the hunting sector. [ABSTRACT FROM AUTHOR]

Abstract We need comprehensive information to manage and protect biodiversity in the face of global environmental challenges, and artificial intelligence is required to generate that information from vast amounts of biodiversity data. Currently, vision‐based monitoring methods are heterogenous; they poorly cover spatial and temporal dimensions, overly depend on humans, and are not reactive enough for adaptive management. To mitigate these issues, we present a portable, modular, affordable and low‐power device with embedded vision for biodiversity monitoring of a wide range of terrestrial taxa. Our camera uses interchangeable lenses to resolve barely visible and remote targets, as well as customisable algorithms for blob detection, region‐of‐interest classification and object detection to automatically identify them. We showcase our system in six use cases from ethology, landscape ecology, agronomy, pollination ecology, conservation biology and phenology disciplines. Using the same devices with different setups, we discovered bats feeding on durian tree flowers, monitored flying bats and their insect prey, identified nocturnal insect pests in paddy fields, detected bees visiting rapeseed crop flowers, triggered real‐time alerts for waterfowl and tracked flower phenology over months. We measured classification accuracies (i.e. F1‐scores) between 55% and 95% in our field surveys and used them to standardise observations over highly resolved time scales. Our cameras are amenable to situations where automated vision‐based monitoring is required off the grid, in natural and agricultural ecosystems, and in particular for quantifying species interactions. Embedded vision devices such as this will help addressing global biodiversity challenges and facilitate a technology‐aided agricultural systems transformation.

Cryptofauna are an overlooked faunal group due to their hidden nature and the use of conventional survey methods, despite playing a significant role in the ecosystem complex as keystone taxa. In this study, a structural framework, viz. cryptofauna monitoring structure (CMS) was developed to assess cryptofauna living in the lagoon reef environment and their preference to various substrates. The efficiency of CMS modules was tested by deploying them in coral lagoons in Agatti and Kavaratti of the Lakshadweep Archipelago, India. A total of 24 CMS units, sets of four, were deployed in these islands at live coral, dead coral and sandy habitat sites. Retrieval of CMS units revealed a total of 424 individuals of motile and sessile organisms representing 12 different taxonomic groups collected. Among the habitats, the sandy area had a high taxa number while the dead coral area had a high taxa abundance. Polychaetes and gastropods were the dominant faunal groups regardless of habitat and island. The present study suggests that CMS can be an efficient tool to assess cryptofauna diversity, which could make monitoring cryptobionts more affordable and environment-friendly. In addition, this study lays the foundation for research into cryptic reef benthos in India. [ABSTRACT FROM AUTHOR]

Introduction: Coastal marine ecosystems are among the most ecologically and socio-economically dynamic regions on Earth, and the study of eukaryotic planktonic communities is an important aspect of aquatic ecology. It is essential to monitor plankton biodiversity and identify influencing factors in order to measure human effects on coastal waters and help contribute to ecosystem preservation. Environmental DNA (eDNA) metabarcoding analysis is an advanced toolfor detecting the presence of aquatic organisms, which has revolutionary significance for biodiversity monitoring and real-time detection of wild environments. Methods: In this study, eDNA metabarcoding was used to study seasonal changes in eukaryotic plankton communities in subtropical coastal waters of the northern South China Sea, to explore how various trophic groups affect the complexity and stability of the species network. Results: The results showed that the summer interaction network is looser and had has reduce biodiversitycompared to the spring interaction network. As an important part of the planktonic community, the abundance and diversity of algae reflect the interactions between different species and the influence of environmental factors on the dominant species, particularly temperature and nutrients. In addition, producer diversity set the basis for species network complexity and indirectly affected network stability, while consumer diversity and its flexible predation strategies may directly lead to differences in network stability across seasons. There were close correlations among species interaction, environmental factors and species diversity. Discussion: This study can help us understand the ecosystemfunctions throughout the year and the complex interactions of planktonic communities from a multiple trophic level perspective, and provide effective methods for sustainable resource utilization and ecological environmental protection in the future. [ABSTRACT FROM AUTHOR]

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model--Deepbiosphere--not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data, Deepbiosphere can detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide. [ABSTRACT FROM AUTHOR]

Biological monitoring using environmental DNA (eDNA) technology has expanded from micro- to macro-organisms. In aquatic eDNA studies, large volumes of water need to be filtered rapidly in the field, which requires development of effective eDNA collection devices. In this study, we introduce a novel portable eDNA collection system containing a GM dual-channel water filter and a DNA extraction kit adapted to large filter membranes (ø 100 mm). The water filter is powered by a high-capacity lithium battery (9,000 mA), which operates two peristaltic pumps and maintains a continuous filtration rate of up to 1 L/min for 5 h in outdoor settings. For sample collection, the optimum conditions are still water and turbidity below 8 nephelometric turbidity units. This allows for the filtration of 10 L of water within 10 min by use of a 0.22-µm filter. Metagenomic and 12S metabarcoding sequencing showed that the DNA extraction quality and species annotation accuracy of our custom DNA extraction kit, which was tailored for this system, rivaled the performance of established kits. The GM water filter's enrichment mode gave consistent results with vacuum filtration, which greatly reduced the filtration time for large water samples, while accurately reproducing species annotations. This innovation streamlines the eDNA collection and annotation process and offers substantial benefits for biodiversity monitoring and conservation efforts. [ABSTRACT FROM AUTHOR]

Ecoacoustics—or acoustic ecology—aids in monitoring elusive and protected species in several ecological contexts. For example, passive acoustic monitoring (PAM), which involves autonomous acoustic sensors, is widely used to detect various taxonomic groups in terrestrial and aquatic ecosystems, from birds and bats to fish and cetaceans. Here, we illustrate the potential of ecoacoustics to monitor soil biodiversity (specifically fauna)—a crucial endeavour given that 59% of species live in soil yet 75% of soils are affected by degradation. We describe the sources of sound in the soil (e.g. biological, geological and anthropogenic) and the ability of acoustic technology to detect and differentiate between these sounds, highlighting opportunities and current gaps in knowledge. We also propose a roadmap for the future development of optimized hardware, analytical pipelines and experimental approaches. Soil ecoacoustics is an emerging field with considerable potential to improve soil biodiversity monitoring and 'soil health' diagnostics. Indeed, early studies suggest soil ecoacoustics can be successfully applied in various ecosystems (e.g. grasslands, temperate, tropical and arid forests) and land uses (e.g. agriculture, viticulture, natural and restored ecosystems). Given the low cost, minimal intrusiveness, and effectiveness in supporting soil biodiversity assessments and biosecurity risks, we advocate for the advancement of soil ecoacoustics for future land management applications. [ABSTRACT FROM AUTHOR]

The Caspian Sea, the world's largest inland body of water, supports a highly diverse community of phytoplankton species that play a crucial role in its ecosystem and overall food web dynamics. This unique, enclosed environment, which spans several countries, is subject to various ecological pressures, including climate change and anthropogenic activities, making it a critical area for biodiversity research. In this study, a comprehensive checklist of these species has been compiled based on an extensive literature review, revealing a total of 970 species and subspecies from 242 genera across 7 phyla. Bacillariophyceae was identified as the dominant class, comprising 347 species (36.37%), followed by Chlorophyta with 289 species (30.29%) and Cyanobacteria with 190 species (19.92%). Other notable groups include Myzozoa with 72 species (7.55%), Ochrophyta with 56 species (5.87%), Cryptophyta with 13 species (1.36%), and Haptophyta with 3 species (0.31%). This detailed inventory provides essential data on the phytoplankton biodiversity in the Caspian Sea, contributing to a deeper understanding of its ecological complexity. The checklist not only highlights the diversity within each phylum but also emphasizes the dominance of diatoms and chlorophytes, which are key to the sea's primary productivity. These findings serve as a critical resource for future ecological and environmental assessments, offering a baseline for monitoring biodiversity changes, potential threats to the ecosystem, and the impacts of climate change and human activities. The rich phytoplankton diversity outlined in this study shows the ecological significance of the Caspian Sea and its importance for regional and global biodiversity conservation efforts. [ABSTRACT FROM AUTHOR]

This introduction presents the context in which digital participatory biodiversity science has developed. After describing its basic operating model and how it is affecting scientific practice, the text suggests that a science and technology studies perspective may shed light on some of the issues raised by new ways of doing biodiversity science. It highlights issues of authority and expertise, different modes of representation and visibility, and the importance of infrastructure. Finally, the introduction briefly describes each of the four papers in the special section and draws parallels among them. Digital technologies blur previous clear-cut dichotomies between producers and users of data and reconfigure the distribution of agency among living beings and technologies. They connect local practices and achievements of biodiversity monitoring with extended outcomes, produced by the transposition, and adaptation of practices or the interoperability of data in larger infrastructures. [ABSTRACT FROM AUTHOR]