Indicator Species Research Articles

Food ethnobotany of forest resource in the high-altitude Himalaya Mountains: Enhancing the food sovereignty of ethnic groups

The vital knowledge of traditional foraging techniques used in indigenous peoples' cuisines may be preserved through gastronomical field studies before it is lost forever. Certain plants are appreciated for their gastronomic, social, economic and ecological importance in the High Himalaya because they play such a significant role in the daily life of the local indigenous populations. To determine the plant cultural indicators for each ethnic group, the data were analyzed using an indicator species analysis. Semi-structured interviews of 167 participants, focus group discussion, and field observations were used to gather information from February 2019 to August 2022 for a comprehensive and systematic gastronomical survey. Across four ethnic groups, a total of (N = 99) wild edible plant species and (N = 9) fungi species from 38 families were documented. Tender leaves were the most commonly used, while tubers were the least commonly used. The majority of the species reported were used as vegetables, followed by species used as fruits and herbal tea. For the first time, we examined cross-cultural similarity and dissimilarity for gastronomic usage: vegetables and savoring plants,fruits, and herbal tea across the cultures studied from the perspective of food ethnobotany. We discovered a clear difference in how different cultures used forest resources, with Gujjar and Pahari showing the most species similarity. This is because these ethic groups are culturally linked with one another and share a common social structure, geography, and language. We calculated plant cultural markers for each species, and 19 of them had significant p-values among the four ethnic groups. The findings revealed a positive relationship between the Gujjar and Pahari ethnic groups and the gastronomical indicator values, while the Kashmiri ethnic group had a negative relationship. The Kashmiri ethnic group experienced the loss of traditional knowledge because of the economic transition that caused people to prefer purchasing vegetables from the market rather than foraging for them in the wild. Traditional knowledge was also dwindling between the Gujjar and Pahari ethnic groups because of social changes brought on by developmental activities that changed their way of life. The identified plant cultural markers were significant to local residents and frequently had adaptations to extremely harsh climatic and environmental conditions. Our finding that 47% of species had market value suggests that these species have a sizable market demand and a promising economic value. They have the potential to boost food security, local community sovereignty, and people's living standards. Food production systems may become more resilient and sustainable by incorporating these indicator species into conventional agriculture. The current study raises awareness about forest resources and enables ethnic groups to live in a natural environment without food scarcity.

Dry grasslands and thorn-cushion communities of Armenia: a first syntaxonomic classification

Aim: To provide the first syntaxonomic, plot-based classification of the dry grasslands and thorn-cushion communities in Armenia. Study area: Armenia. Methods: We sampled 111 vegetation plots (10 m2) and recorded environmental and structural parameters. We collected additional 487 relevés from surrounding countries for a broad-scale comparison. We used modified TWINSPAN to derive a syntaxonomic classification system, whose units were then compared among each other regarding species composition, structure, site conditions and distribution. Results: The classification of Armenian vegetation plots resulted in a 12-cluster solution. Unsupervised classification of the broad-scale dataset yielded five main groups, which were used for the high-level syntaxonomic assignments of the Armenian data. We assigned about half of the plots of the Armenian dataset to the Festuco-Brometea, while the remaining represented a potential new class, preliminarily called “Ziziphora tenuior-Stipa arabica grasslands”. Most of the syntaxa below class level are new to science, therefore we provide formal descriptions of three orders (Plantagini atratae-Bromopsietalia variegatae, Onobrychido transcaucasicae-Stipetalia pulcherrimae, Cousinio brachypterae-Stipetalia arabicae), four alliances (Acantholimono caryophyllacei-Stipion holosericeae, Artemision fragrantis, Onobrychido michauxii-Stipion capillatae, Onobrychido transcaucasicae-Stipion pulcherrimae) and six associations. We found significant differences in the topographic, climatic and soil characteristics, and structural parameters, species life forms and distribution range types between the grassland types at different syntaxonomic levels. The mean species richness was 47.3 (vascular plants: 46.8, bryophytes: 0.4, lichens: 0.1). Conclusions: We found remarkable differences of the Armenian dry grasslands from the previously known units and described most of the higher syntaxa and all the associations as new to science. Our study provides arguments for a potential new class of Ziziphora tenuior-Stipa arabica grasslands separate both from the Euro-Siberian Festuco-Brometea and the Anatolian Astragalo-Brometea. Finally, we found plot scale richness of vascular plants clearly above the Palaearctic average of dry grasslands and that of non-vascular plants clearly below, which calls for further biodiversity analyses. Taxonomic reference: Euro+Med (2023) for vascular plants, Hodgetts et al. (2020) for bryophytes, Nimis et al. (2018) for lichens except for Xanthoparmelia camtschadalis (Ach.) Hale. Abbreviations: EDGG = Eurasian Dry Grassland Group; DCA = detrended correspondence analysis; ICPN = International Code of Phytosociological Nomenclature (Theurillat et al. 2021); TWINSPAN = two-way indicator species analysis.

Assessing landscape-level effects of permanent grassland management and landscape configuration on open-land butterflies based on national monitoring data

AbstractHalting and reversing the ongoing insect decline requires in-depth knowledge on key drivers. Due to their sensitivity to habitat quality, butterflies are valuable indicators for grassland management intensity, including mowing. However, most studies examining mowing regime impacts on butterflies are limited to small spatial extents. Here, we tested the potential of citizen science butterfly monitoring data for assessing landscape-level effects of mowing regimes (number of mowing events and timing of the first event) and edge density (density of boundaries between different land-cover types) on butterfly richness, abundance, and community composition. We used generalised linear mixed-effects models to relate nationwide data from the German Butterfly Monitoring Scheme (DEBMS) to high-resolution satellite imagery on mowing events in permanent grasslands (grasslands excluded from crop rotation). As butterfly transects may not consistently be located within grasslands, we ran our models for different thresholds from 0 to 50%, representing increasing shares of the transect route situated within permanent grasslands (10% intervals). We did not find significant associations between mowing regimes and butterflies when focussing on species richness and abundance of all species inhabiting open land. However, we found strong positive associations of delayed mowing with the abundance of grassland specialists with increasing grassland shares per transect. Further, we found negative associations of delayed mowing with the annual number of generations and of more frequent mowing with the abundance of specialists, depending on the share of grassland per transect. Edge density had a positive association with species richness and abundance of species inhabiting open land, as well as abundance of grassland indicator species and grassland specialists in landscapes with a low grassland share per transect. Our findings underscore the importance of low-intensity managed permanent grasslands at the landscape scale for specialised butterflies. Additionally, we highlight the importance of a high density of boundaries for open-land and specialised butterflies, particularly in landscapes with highly fragmented permanent grasslands. To improve future analyses of grassland management impacts, we recommend expanding DEBMS monitoring sites to cover a larger grassland management intensity gradient and to place more transects within grasslands.

New insights into biodiversity-disease relationships: the importance of the host community network characterization

Camera-trapping-based social network analysis (SNA) is a valuable tool to characterize communities and identify species with an outstanding role in pathogen maintenance. This study provides new insights into the contentious debate on the effect of biodiversity on disease risk by combining SNA with the assessment of host diversity indicators and pathogen richness in Spain. The apparent species richness detected by camera traps at each study site ranged from 10 to 33 species (mean ± standard error (SE): 20.73 ± 1.94) and their apparent diversity rates (i.e., Shannon index) ranged from 0.57 to 2.55 (mean ± SE: 1.97 ± 0.16). At the community level, vertebrate host diversity had a marginal dilution effect on the disease risk and was negatively correlated to pathogen richness. The exposure to multiple pathogens, as a proxy of disease risk, was negatively associated with apparent host diversity. The disease risk was driven by the interaction of apparent biodiversity with the presence of livestock and with the centrality of the indicator species (i.e., the wild boar). The maximum risk of co-exposure to pathogens was reached when the lowest apparent biodiversity rates coincided with the highest wild boar centrality in the host community or with the presence of livestock, respectively. The highest confluence of pathogens occurred at lower apparent diversity indexes, higher wild boar relative abundances and predominance of agricultural lands. Our results suggest that the diversity-disease relationship is not linear and depends on the environment and host community characteristics, thereby opening avenues for designing new prevention strategies.

Multi-omics reveal the gut microbiota-mediated severe foraging environment adaption of small wild ruminants in the Three-River-Source National Park, China.

The Tibetan antelope (Pantholops hodgsonii), blue sheep (Pseudois nayaur), and Tibetan sheep (Ovis aries) are the dominant small ruminants in the Three-River-Source National Park (TRSNP). However, knowledge about the association between gut microbiota and host adaptability remains poorly understood. Herein, multi-omics sequencing approaches were employed to investigate the gut microbiota-mediated forage adaption in these ruminants. The results revealed that although wild ruminants (WR) of P. hodgsoni and P. nayaur were faced with severe foraging environments with significantly low vegetation coverage and nutrition, the apparent forage digestibility of dry matter, crude protein, and acid detergent fiber was significantly higher than that of O. aries. The 16s rRNA sequencing showed that the gut microbiota in WR underwent convergent evolution, and alpha diversity in these two groups was significantly higher than that in O. aries. Moreover, indicator species, including Bacteroidetes and Firmicutes, exhibited positive relationships with apparent forage digestibility, and their relative abundances were enriched in the gut of WR. Enterotype analysis further revealed that enterotype 1 belonged to WR, and the abundance of fatty acid synthesis metabolic pathway-related enzyme genes was significantly higher than enterotype 2, represented by O. aries. Besides, the metagenomic analysis identified 14 pathogenic bacterial species, among which 10 potentially pathogenic bacteria were significantly enriched in the gut microbiota of O. aries. Furthermore, the cellulolytic strains and genes encoding cellulase and hemicellulase were significantly enriched in WR. In conclusion, our results provide new evidence of gut microbiota to facilitate wildlife adaption in severe foraging environments of the TRSNP, China.

Deficiency of IL-22–binding protein enhances the ability of the gut microbiota to protect against enteric pathogens

Interleukin 22 (IL-22) promotes intestinal barrier integrity, stimulating epithelial cells to enact defense mechanisms against enteric infections, including the production of antimicrobial peptides. IL-22 binding protein (IL-22BP) is a soluble decoy encoded by the Il22ra2 gene that decreases IL-22 bioavailability, attenuating IL-22 signaling. The impact of IL-22BP on gut microbiota composition and functioning is poorly understood. We found that Il22ra2-/- mice are better protected against Clostridioides difficile and Citrobacter rodentium infections. This protection relied on IL-22-induced antimicrobial mechanisms before the infection occurred, rather than during the infection itself. Indeed, the gut microbiota of Il22ra2-/- mice mitigated infection of wild-type (WT) mice when transferred via cohousing or by cecal microbiota transplantation. Indicator species analysis of WT and Il22ra2-/- mice with and without cohousing disclosed that IL22BP deficiency yields a gut bacterial composition distinct from that of WT mice. Manipulation of dietary fiber content, measurements of intestinal short-chain fatty acids and oral treatment with acetate disclosed that resistance to C. difficile infection is related to increased production of acetate by Il22ra2-/--associated microbiota. Together, these findings suggest that IL-22BP represents a potential therapeutic target for those at risk for or with already manifest infection with this and perhaps other enteropathogens.

Improving the knowledge base of Vulnerable Marine Ecosystems’ distribution in the Amendolara Bank (Ionian Sea)

The Amendolara Bank was recently designated as a Site of Community Importance; however, information on its ecosystems remains limited, with a particular dearth of knowledge regarding the deeper zone (>100 m). Previous studies have discovered the existence of Vulnerable Marine Ecosystems (VMEs) within the bank, underscoring the necessity for more comprehensive data and its significance in terms of conservation in the Ionian Sea. This study aims to investigate various aspects of the bank using Remotely Operated Vehicles (ROVs) to shed light on the possible presence of VME indicator species, their relationship with environmental variables, their connection with the observed fish, and to assess anthropogenic impact via the identification of fishing gear within the study area. This present research provides new information on the biodiversity of the Amendolara Bank, revealing the presence of four VME indicator species including the first sightings of black coral Antipathella subpinnata and the precious red coral Corallium rubrum. Moreover, it provides evidence on the interaction between fish fauna and VME indicator species as well as signs of anthropogenic impact from abandoned, lost, or otherwise discarded fishing gear (ALDFG). These findings highlight the urgent need for additional research to improve the knowledge base on the biodiversity of this unique spot in the Ionian Sea which would in turn ensure the development and implementation of more effective conservation and management measures.

Constituents of Coliform Species Contained in the Permeate of Microfiltration Membranes in Wastewater Treatment

MBRs (Membrane bioreactors) have been increasingly employed for municipal and industrial wastewater treatment in the last decades for their small footprint and excellent effluent quality. However, microorganisms are often detected in the permeates of microfiltration (MF) membranes even with small pore sizes. Coliform bacteria are known for indicating the potential presence of pathogenic bacteria that cause infectious disease such as bacteremia, respiratory tract infections, and urinary tract infections. Thus, the retention of coliform bacteria by membrane processes is important when the membrane process is utilized in water reclamation. In this study, a microbial community of coliform bacteria in the permeates of MF membranes with different pore sizes (0.2, 0.4, and 0.8 µm) was identified. The results showed that the dominant coliform bacteria changed from Enterobacter spp. and Citrobacter spp. in the activated sludge to Enterobacter spp. and Klebsiella spp. in the permeate of MF membranes, while some pieces of membranes showed complete retention. The bacterial regrowth on the surface of the piping system on the permeate side could be a significant factor contributing to the frequent and exclusive detection of Enterobacter spp. and Klebsiella spp. in the case of membranes with small pore size (0.2 and 0.4 µm) after a long continuous filtration time. To indicate the public health-related risk of treated wastewater by MF, Escherichia coli may not be a suitable indicator species because E. coli is relatively retentive in MF compared to other coliforms.

Ecological amplitude and indication potential of mining bees (Andrena spp.): a case study from the post-agricultural area of the Kampinos National Park (Poland)

The mining bee (Andrena spp.) play a key role in ensuring plant and animal diversity. The present study examines their diversity in a post-agricultural landscape exemplified by the Kampinos National Park (KNP), a UNESCO Biosphere Reserve in Poland. The following hypotheses were addressed: (H1) the mining bees demonstrate a narrow ecological amplitude, (H2) there are no indicator species for particular habitats, and (H3) the studied mining bees have the same ecological preferences to those presented in the literature. A total of 40 catch per unit effort samples (CPUE) were collected across various habitats with different soil humidity. Forty-six species were recorded, representing 46% of mining bees and approximately 10% of the known Polish bee fauna. Nineteen of the recorded species (41%) were assigned to CR-NT threat categories, indicating that the national park plays a significant role in preserving mining bee species diversity and their conservation. None of the hypotheses (H1, H2, H3) were confirmed. The mining bees were found to demonstrate a wide ecological amplitude. Surprisingly, habitats located in dry and wet soils were both characterised by high abundance and species richness. Seventeen indicators were distinguished among the dominant and rarer species. Our findings suggest that Andrena nigroaenea and A. ventralis (lower humidity), as well as A. alfkenella and A. minutuloides (higher humidity), have different significant relationships with habitat soil humidity to those reported in the literature.

Long-term cover crop monocultures and mixtures improve soil multifunctionality and shift microbial communities and functions

Long-term cover crops are an emerging approach for achieving sustainable agriculture by reducing fertilizer use and enhancing soil quality. However, soil microbial communities, multifunctionality (i.e., the ability of soil ecosystems to simultaneously provide and maintain multiple ecological functions), and their relationships in cover crops remain poorly understood, especially in cover crop mixtures. To address these issues, here, we conducted a 15-year field experiment under different cover crop deployments (one legume and one brassica grown in monoculture or in mixture) in Carya cathayensis plantations. We found that cover crops significantly increased soil microbial diversity and multifunctionality, especially in mixtures. The bacterial and fungal compositions was significantly affected by cover crops. Interestingly, some taxa may serve as potential indicator species for nutrient status (i.e., bacterial Subgroup_2, Subgroup_6 and Subgroup_17). Cover crops significantly increased beneficial microbial functions (e.g., nitrogen fixation) but decreased pathogen-related functions (e.g., pathotroph). Bacterial and fungal community assemblages under cover crops were dominated by stochastic processes. Cover crops, especially mixtures, had a higher habitat niche breadth (Bcom). In addition, cover crops have more complex and stable bacterial and fungal networks. Partial least squares path modeling further confirmed that the variations in soil multifunctionality were largely related to nutrient resources. Importantly, the relative abundance of rare microbial taxa was also highly correlated with soil multifunctionality. Overall, our study illustrates that the use of cover crops in the long term can foster soil microbial specific taxa and contribute to improved soil multifunctionality. Our study provides support for the benefits of a legume-brassica mixture over monocultures of either and a theoretical basis for exploring cover crops as an ecological management model.

Advancing Environmental Flows Science: Hindcasting and Forecasting Flow–Ecology Relationships

To advance current environmental flow standards in Texas, we developed field, laboratory, and analytical methods to model recruitment dynamics of indicator species selected to cover a range of population responses to flow variation. Preliminary investigations were conducted in three central Texas river basins to evaluate the feasibility of these methods for formulating and evaluating the state's environmental flow standards. Age analysis allowed back‐calculation of dates of fish hatching, mussel recruitment, and tree germination for estimation of temporal variation in recruitment. Recruitment data were then analyzed in relation to flow regime components. Statistical models were derived for flow–recruitment relationships of Shoal Chub Macrhybopsis hyostoma, Smallmouth Buffalo Ictiobus bubalus, threeridge mussel Amblema plicata, and boxelder Acer negundo. The Shoal Chub model was used to hindcast recruitment dynamics in the Brazos River, revealing a decline in recruitment after dam construction. The Smallmouth Buffalo model revealed that strong year‐classes were positively associated with springtime pulses of long duration but negatively associated with frequent short‐duration pulses. Results for the threeridge mussel were not as easily interpreted, but for all three river basins generally showed weaker recruitment during periods with extreme low and high flows. The boxelder model revealed positive associations between recruitment and high flow components and was used to forecast the probability of germination under five simulated flow regime scenarios, thereby providing an additional means for evaluating the suitability of environmental flow standards. Assessment of how hydrology influences recruitment provides an evidence‐based method to hindcast responses to past flow regimes and forecast responses to future flow scenarios, thereby providing a basis for evaluating environmental flow standards and water management options.

Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species

Modern forestry systems rely on typologies of forest types (FTs). In Argentina, several proposals have been developed, but they lack unified criteria. The objective was to compare different approaches, specifically focusing on (i) phenoclusters (functional forests based on vegetation phenology variations and climate variables) and (ii) forest canopy cover composition by tree species. We conducted comparative uni-variate analyses using data from national forest inventories, forest models (biodiversity, carbon, structure), and regional climate. We assessed the performance of phenoclusters in differentiating the variability of native forests (proxy: forest structure), biodiversity (proxy: indicator species), and environmental factors (proxies: soil carbon stock, elevation, climate). Additionally, we proposed a simple FT classification methodology based on species composition, considering the basal area of tree species. Finally, we compared the performance of both proposals. Our findings showed that classifications based on forest canopy cover composition are feasible to implement in regions dominated by mono-specific forests. However, phenoclusters allowed for the increased complexity of categories at the landscape level. Conversely, in regions where multi-specific stands prevailed, classifications based on forest canopy cover composition proved ineffective; however, phenoclusters facilitated a reduction in complexity at the landscape level. These results offer a pathway to harmonize national FT classifications by employing criteria and indicators to achieve sustainable forest management and conservation initiatives.

Breeding waterbird species as ecological indicators of shifts from turbid to clear water conditions in northwest European shallow eutrophic lakes

AbstractWe used biological and physical responses at 71 shallow waterbodies with contrasting nutrient levels undergoing recovery from eutrophication to predict potential changes in waterbird species abundance, an important component of lake ecosystems. These general predictions were tested using 28 years of breeding waterbird data from three Danish shallow eutrophic lakes, comparing species-specific responses to improved nutrient and water transparency in two lakes with a third where conditions remained constantly suitable for breeding waterbirds. We predicted positive responses to improved water quality from pursuit diving predators (three grebe species), a specialist zooplankton feeder (northern shoveler Anas clypeata) and waterbirds feeding on (common pochard Aythya ferina) or within (tufted duck A. fuligula) submerged macrophyte underwater canopies. These species were characterised by positive waterbird community composition changes (using Principal Components Analysis) associated with decreasing nutrient loading and increasing water transparency at two lakes, with no change in breeding waterbird community at the third. Secchi depth explained 73–95% of variance in both PC axes at both restored lakes, but not at the third, suggesting water transparency was the major factor driving waterbird community composition. These examples show predicting waterbird species-specific responses to management can usefully direct the use of breeding waterbirds as indicator species.

Efficient Electrochemical Microsensor for the Simultaneous Measurement of Hydrogen Peroxide and Ascorbic Acid in Living Brains.

Hydrogen peroxide (H2O2) and ascorbic acid (AA), acting as two significant indicative species, correlate with the oxidative stress status in living brains, which have historically been considered to be involved mainly in neurodegenerative disorders such as Alzheimer's disease, Huntington's disease, and Parkinson's disease (PD). The development of efficient biosensors for the simultaneous measurement of their levels in living brains is vital to understand their roles played in the brain and their interactive relationship in the progress of these diseases. Herein, a robust ratiometric electrochemical microsensor was rationally designed to realize the determination of H2O2 and AA simultaneously. Therefore, a specific probe was designed and synthesized with both recognition units responsible for reacting with H2O2 to produce a detectable signal on the microsensor and linkage units helping the probe modify onto the carbon substrate. A topping ingredient, single-walled carbon nanotubes (SWCNTs) was added on the surface of the electrode, with the purpose of not only facilitating the oxidation of AA but also absorbing methylene blue (MB), prompting to read out the inner reference signal. This proposed electrochemical microsensor exhibited a robust ability to real-time track H2O2 and AA in linear ranges of 0.5-900 and 10-1000 μM with high selectivity and accuracy, respectively. Eventually, the efficient electrochemical microsensor was successfully applied to the simultaneous measurement of H2O2 and AA in the rat brain, followed by microinjection, and in the PD mouse brain.

Artemisia Frigida Distribution Mapping in Grassland with Unmanned Aerial Vehicle Imagery and Deep Learning

Artemisia frigida, as an important indicator species of grassland degradation, holds significant guidance significance for understanding grassland degradation status and conducting grassland restoration. Therefore, conducting rapid surveys and monitoring it is crucial. In this study, to address the issue of insufficient identification accuracy due to the large density and small size of Artemisia frigida in UAV images, we improved the YOLOv7 object detection algorithm to enhance the performance of the YOLOv7 model in Artemisia frigida detection. We applied the improved model to the detection of Artemisia frigida across the entire experimental area, achieving spatial mapping of Artemisia frigida distribution. The results indicate: In comparison across different models, the improved YOLOv7 + Biformer + wise-iou model exhibited the most notable enhancement in precision metrics compared to the original YOLOv7, showing a 6% increase. The mean average precision at intersection over union (IoU) threshold of 0.5 (mAP@.5) also increased by 3%. In terms of inference speed, it ranked second among the four models, only trailing behind YOLOv7 + biformer. The YOLOv7 + biformer + wise-iou model achieved an overall detection precision of 96% and a recall of 94% across 10 plots. The model demonstrated superior overall detection performance. The enhanced YOLOv7 exhibited superior performance in Artemisia frigida detection, meeting the need for rapid mapping of Artemisia frigida distribution based on UAV images. This improvement is expected to contribute to enhancing the efficiency of UAV-based surveys and monitoring of grassland degradation. These findings emphasize the effectiveness of the improved YOLOv7 + Biformer + wise-iou model in enhancing precision metrics, overall detection performance, and its applicability to efficiently map the distribution of Artemisia frigida in UAV imagery for grassland degradation surveys and monitoring.

Variations in antimicrobial resistance genes present in the rectal faeces of seals in Scottish and Liverpool Bay coastal waters

Antibiotic resistance genes originating from human activity are considered important environmental pollutants. Wildlife species can act as sentinels for coastal environmental contamination and in this study we used qPCR array technology to investigate the variety and abundance of antimicrobial resistance genes (ARGs), mobile genetic elements (MGEs) and integrons circulating within seal populations both near to and far from large human populations located around the Scottish and northwest English coast. Rectal swabs were taken from 50 live grey seals and nine live harbour seals. Nucleic acids were stabilised upon collection, enabling extraction of sufficient quality and quantity DNA for downstream analysis. 78 ARG targets, including genes of clinical significance, four MGE targets and three integron targets were used to monitor genes within 22 sample pools. 30 ARGs were detected, as well as the integrons intl1 and intl2 and tnpA transposase. Four β-lactam, nine tetracycline, two phenicol, one trimethoprim, three aminoglycoside and ten multidrug resistance genes were detected as well as mcr-1 which confers resistance to colistin, an important drug of last resort. No sulphonamide, vancomycin, macrolide, lincosamide or streptogramin B (MLSB) resistance genes were detected. Resistance genes were detected in all sites but the highest number of ARGs (n = 29) was detected in samples derived from grey seals on the Isle of May, Scotland during the breeding season, and these genes also had the highest average abundance in relation to the 16S rRNA gene. This pilot study demonstrates the effectiveness of a culture-independent workflow for global analysis of ARGs within the microbiota of live, free-ranging, wild animals from habitats close to and remote from human habitation, and highlights seals as a valuable indicator species for monitoring the presence, abundance and land-sea transference of resistance genes within and between ecosystems.

Ectomycorrhizal fungi are influenced by ecoregion boundaries across Europe

AbstractAimEcoregions and the distance decay in community similarity are fundamental concepts in biogeography and conservation biology that are well supported across plants and animals, but not fungi. Here we test the relevance of these concepts for ectomycorrhizal (ECM) fungi in temperate and boreal regions.LocationEurope.Time Period2008–2015.Major Taxa StudiedEctomycorrhizal fungi.MethodsWe used a large dataset of ~24,000 ectomycorrhizas, assigned to 1350 operational taxonomic units, collected from 129 forest plots via a standardized protocol. We investigated the relevance of ecoregion delimitations for ECM fungi through complementary methodological approaches based on distance decay models, multivariate analyses and indicator species analyses. We then evaluated the effects of host tree and climate on the observed biogeographical distributions.ResultsEcoregions predict large‐scale ECM fungal biodiversity patterns. This is partly explained by climate differences between ecoregions but independent from host tree distribution. Basidiomycetes in the orders Russulales and Atheliales and producing epigeous fruiting bodies, with potentially short‐distance dispersal, show the best agreement with ecoregion boundaries. Host tree distribution and fungal abundance (as opposed to presence/absence only) are important to uncover biogeographical patterns in mycorrhizas.Main ConclusionsEcoregions are useful units to investigate eco‐evolutionary processes in mycorrhizal fungal communities and for conservation decision‐making that includes fungi.

Deep learning-based detection of indicator species for monitoring biodiversity in semi-natural grasslands

Deep learning (DL) has huge potential to provide valuable insights into biodiversity changes in species-rich agricultural ecosystems such as semi-natural grasslands, helping to prioritize and plan conservation efforts. However, DL has been underexplored in grassland conservation efforts, hindered by data scarcity, intricate ecosystem interactions, and limited economic incentives. Here, we developed a DL-based object-detection model to identify indicator species, a group of vascular plant species that serve as surrogates for biodiversity assessment in High Nature Value (HNV) grasslands. We selected indicator species Armeria maritima, Campanula patula, Cirsium oleraceum, and Daucus carota. To overcome the hurdle of limited data, we grew indicator plants under controlled greenhouse conditions, generating a sufficient dataset for DL model training. The model was initially trained on this greenhouse dataset. Then, smaller datasets derived from an experimental grassland plot and natural grasslands were added to the training to facilitate the transition from greenhouse to field conditions. Our optimized model achieved remarkable average precision (AP) on test datasets, with 98.6 AP50 on greenhouse data, 98.2 AP50 on experimental grassland data, and 96.5 AP50 on semi-natural grassland data. Our findings highlight the innovative application of greenhouse-grown specimens for the in-situ identification of plants, bolstering biodiversity monitoring in grassland ecosystems. Furthermore, the study illuminates the promising role of DL techniques in conservation programs, particularly as a monitoring tool to support result-based agri-environment schemes.

Promoting plant diversity and habitat heterogeneity through vineyard terracing

AbstractQuestionsViticulture on steep slopes has shaped the landscape and biodiversity in many regions, but insufficient profitability has led to management cessation and shrub encroachment. A solution to maintain economically viable cultivation could be vineyard terracing. We aimed to identify the potential of terracing to enhance plant diversity and habitat heterogeneity in vineyards, analyze effects of management intensity on vineyard vegetation, and assess how plant communities change after vineyard abandonment.LocationWine‐growing region of the Upper Middle Rhine Valley in Hesse (50.042342° N, 7.814533° E) and Rhineland‐Palatinate (50.119139° N, 7.719275° E), Germany.MethodsWe recorded vascular plant species and local vineyard parameters in vertically oriented vineyards with vegetated and tilled open inter‐rows, in terraced vineyards with tilled terrace inter‐rows and extensively managed embankments, and in vineyard fallows in a total of 45 study sites. We used plant species richness, Ellenberg indicator values and Grime's strategy types to describe how traits and ecological requirements respond to distinct vineyard management.ResultsPlant species richness and composition were determined by management‐derived disturbance intensities. Extensively managed embankments had a distinct plant community, the highest plant species richness, more perennial and indicator species, and lower nitrogen indicator values compared with inter‐rows. By contrast, highly disturbed open and terrace inter‐rows revealed plant communities associated with annuals and ruderals, but species richness did not differ between terrace inter‐rows and embankments. The plant communities of fallows were completely different with lower plant diversity.ConclusionsOur results highlight the potential of terraced vineyards for plant diversity with nutrient poor, extensively managed embankments providing conditions that have become rare in modern agricultural systems. A long environmental gradient from terrace inter‐rows to embankments created habitat heterogeneity within a narrow space. By contrast, intensive inter‐row management in vertically oriented vineyards hampers high plant diversity and abandonment fosters the spread of woody species at the expanse of plant diversity.

Revolutionizing aquatic eco-environmental monitoring: Utilizing the RPA-Cas-FQ detection platform for zooplankton

The integration of recombinase polymerase amplification (RPA) with CRISPR/Cas technology has revolutionized molecular diagnostics and pathogen detection due to its unparalleled sensitivity and trans-cleavage ability. However, its potential in the ecological and environmental monitoring scenarios for aquatic ecosystems remains largely unexplored, particularly in accurate qualitative/quantitative detection, and its actual performance in handling complex real environmental samples. Using zooplankton as a model, we have successfully optimized the RPA-CRISPR/Cas12a fluorescence detection platform (RPA-Cas-FQ), providing several crucial “technical tips”. Our findings indicate the sensitivity of CRISPR/Cas12a alone is 5 × 109 copies/reaction, which can be dramatically increased to 5 copies/reaction when combined with RPA. The optimized RPA-Cas-FQ enables reliable qualitative and semi-quantitative detection within 50 min, and exhibits a good linear relationship between fluorescence intensity and DNA concentration (R2 = 0.956–0.974***). Additionally, we developed a rapid and straightforward identification procedure for single zooplankton by incorporating heat-lysis and DNA-barcode techniques. We evaluated the platform's effectiveness using real environmental DNA (eDNA) samples from the Three Gorges Reservoir, confirming its practicality. The eDNA-RPA-Cas-FQ demonstrated strong consistency (Kappa = 0.43***) with eDNA-Metabarcoding in detecting species presence/absence in the reservoir. Furthermore, the two semi-quantitative eDNA quantification technologies showed a strong positive correlation (R2 = 0.58–0.87***). This platform also has the potential to monitor environmental pollutants by selecting appropriate indicator species. The novel insights and methodologies presented in this study represent a significant advancement in meeting the complex needs of aquatic ecosystem protection and monitoring.