Basic and Applied Ecology最新文献

In the challenging environmental conditions of high elevation ecosystems, cushion plants create micro-climatic and fertile shelters which host a vast diversity of organisms. Yet, the taxonomic diversity of these hosts remains poorly described, and to what extent cushion plants structure these communities remains unclear. We sampled soils beneath six different species of cushion plants, along with bare-ground controls, across two different elevation gradients in the French Alps. We used environmental DNA metabarcoding to investigate the effect of different species of cushion plants on the $\alpha$ and $\beta$ diversity of fungi, bacteria, eukaryotes, and for the first time in these ecosystems, unicellular eukaryotes and soil worms. Cushion plants hosted a surprisingly large diversity of organisms, from bacteria to mites and collembolans, forming rich and complex ecosystems. $\alpha$-diversity between cushion plant and bare soil samples differed only for fungi, with communities partly structured by the cushion plant species’ identity. The effect of cushion plant species on composition and $\beta$-diversity of eukaryotic and fungal communities surpassed the environmental effect, while it equaled the site effect for bacterial communities. These results highlight the key role of biotic interactions in shaping the composition of high elevation communities, and clarify the role of cushion plants as engineer and foundation species in these harsh environments. By sheltering highly diverse communities at such high elevation, cushion plants may play a prominent role in the ecological assembly of these diverse, yet poorly known, ecosystems.

Cliff ecology has been studied for decades, providing information about its high biodiversity values and their vulnerability to climate change. Also, insular ecosystems present biodiversity hotspots with high endemicity, but they are also severely affected by anthropogenic effects. Together, insular cliff communities combine both biodiversity uniqueness and high vulnerability to global change, but few studies have evaluated these particular ecosystems. Our aim was to provide information on the spatial distribution of insular cliff-specific vegetation assessing which environmental and climatic variables contribute to the definition of cliff habitat conditions. Ecological niche modelling for cliff populations in Balearic Islands has been calculated with presences of 20 plant species and climatic and geographical variables using a Random Forest model. The most important climatic variables for the model generation were mean temperature of the driest quarter and precipitation of the coldest quarter. The map obtained showed that mountain ranges from all islands provide highly suitable conditions for rupicolous species. Both the pessimistic and optimistic models showed that the habitat suitability of cliff vegetation in the mountain ranges would decrease, while they are close to zero in lowlands for the period 2021–2040. This study emphasizes the vulnerability of cliff habitats to climate change due to their limited dispersal capacity and distribution and the strict requirements for habitat suitability. From this work, future studies can focus on single-species analysis to evaluate if any cliff specialist species can be at risk of extinction due to climate change.

Cliffs harbor unique and specialized biodiversity that warrants attention and conservation. At the same time, cliffs are under increased threat from anthropogenic disturbance and climate change. Since cliffs are highly heterogeneous, spatially isolated, and often inaccessible compared to nearby habitats, land managers require up-to-date and site-specific information to protect them. Cliffs are often overlooked due to the technical and logistical challenges posed by surveying these environments, but field inventorying and monitoring can fill this gap. We present three case studies of cliff monitoring in action: mapping populations of an endemic rare plant in the Southern Appalachian Mountains (US), photo-sampling of cliff specialist plants in Spain, and surveying peregrine falcons in Western North Carolina (US). These case studies highlight the application of various monitoring techniques, the possibilities for collaboration among stakeholders, and some ways that data from monitoring can inform cliff conservation and stewardship. To facilitate the development of easy-to-implement monitoring, we outline three approaches and associated best practices for monitoring cliff plants. Methods range from simple photo point monitoring to more in-depth species inventories and could be implemented by community scientists alongside a broader audience interested in providing up-to-date data on cliff environments. We call for action, urging the expansion and advancement of cliff biodiversity monitoring.

Long-term research in grassland biodiversity experiments has provided empirical evidence that ecological and evolutionary processes are intertwined in determining both biodiversity–ecosystem functioning (BEF) and biodiversity–stability relationships. Focusing on plant diversity, we hypothesize that multifunctional stability is highest in high-diversity plant communities and that biodiversity–stability relationships increase over time due to a variety of forms of ecological complementarity including the interaction with other biota above and below ground. We introduce the multiple-mechanisms hypothesis of biodiversity–stability relationships suggesting that it is not an individual mechanism that drives long-term biodiversity effects on ecosystem functioning and stability but that several intertwined processes produce increasingly positive ecosystem effects. The following six mechanisms are important. Low-diversity plant communities accumulate more plant antagonists over time (1), and use resources less efficiently and have more open, leaky nutrient cycles (2). Conversely, high-diversity plant communities support a greater diversity and activity of beneficial interaction partners across trophic levels (3); diversify in their traits over time and space, within and across species, to optimize temporal (intra- and interannual) and spatial complementarity (4), create a more stable microclimate (5), and foster higher top-down control of aboveground and belowground herbivores by predators (6). In line with the observation that different species play unique roles in ecosystems that are dynamic and multifaceted, the particular mechanism contributing most to the higher performance and stability of diverse plant communities might differ across ecosystem functions, years, locations, and environmental change scenarios. This indicates “between-context insurance” or “across-context complementarity” of different mechanisms. We introduce examples of experiments that will be conducted to test our hypotheses and which might inspire additional work.

Floodplains are unique environments that provide a dynamic link between terrestrial and aquatic systems. Intensification of human activity – particularly agriculture and urbanisation – has resulted in the degradation of floodplains worldwide. Restoration and sustainable management of floodplains requires holistic assessment and compromise between stakeholders to successfully balance environmental, economic, and social benefits. Yet, understanding these complex systems sufficiently to provide evidence-based recommendations is a challenge. We present the lessons learned from establishing an interdisciplinary research-based framework on the agricultural floodplain of Lake Saint Pierre, Québec, Canada, whose mandate was to a) understand and define key environmental, agricultural, and socioeconomic attributes of the landscape, b) quantify the trade-offs and synergies between these attributes across different agricultural practices, regions, and land uses, and c) explore novel agri-environmental management practices to assess their role in sustainable floodplain management. Within this manuscript, we explore the benefits that such an approach offers in evaluating sustainable floodplain land use. We found that an interdisciplinary research-based approach demonstrated important benefits such as knowledge transfer, more efficient use of resources (e.g., personnel, funding), and a flexible yet robust research framework. A framework of individual research projects connected to broader interdisciplinary themes allowed a more holistic synthesis of the floodplain systems and assessment of agri-environmental practices. By implicitly considering spatial and social scales, we conceptualised not just how redistribution of the land use types can meet sustainable management objectives, but also explored how compromises within existing uses can optimise socio-economic, agricultural and environmental dimensions and move towards a sustainable multifunctional landscape.

The broad negative effects of land-use conversion for agriculture on wildlife species are well known, but few studies have evaluated how different land-use types impact spatiotemporal patterns and trophic strategy of large carnivores. We conducted sign surveys for the Asiatic black bear, a critically endangered subspecies in southeastern Iran. We applied Bayesian occupancy modelling and quantified spatiotemporal determinants of black bear occurrence as a function of date palms, distance to agriculture, elevation, precipitation, and protected area (PA) size. We also investigated its diet composition based on scat (n = 150) analyses. Date palm area size (β = 2.07; 95 % Credible Interval = 0.67 to 3.89) and distance to croplands had a strong and significant (β = −1.06, 95 % CrI = −2.10 to −0.20) influence on the occupancy. Elevation, precipitation, village density, and PA size did not substantially influence occupancy. Black bear detection probability became 100 % only above 14 km survey effort, indicating its overall rarity, and bears were much more easily detected during and after rainfall. Bears mainly relied on date palms (41 %) followed by herbaceous plants (24.6 %), insects (15 %), wild mammals (6.4 %), wild fruits (5.6 %), livestock (4.9 %) and other vertebrates (2.5 %, e.g., birds). Most of the predicted bear occupancy was outside PAs and thus suggests a high likelihood of human-bear conflicts. Presumably, resource density is insufficient to support bears inside PAs, but information concerning resource density is currently lacking. Our results showed that the agricultural landscape provided an important feeding (46 %) area for bears. Consequently, effective conservation programs such as the protection of abandoned date palm groves as a conflict-free food source are necessary. Practical training such as protective measures against crop-raiding behavior of bears would be essential to foster the tolerance of people toward bears and thus can help facilitate coexistence.

Understanding patterns of species-genetic diversity correlations (SGDC) is important for conservation purposes because it allows us to infer whether conservation of species diversity (SD) influences conservation of genetic diversity (GD) and the other way around. Here, we studied SGDCs using aquatic macrofauna in a set of 31 urban ponds in the metropolitan area of Stockholm, Sweden. We also estimated how land use and pond environmental factors affect SD and GD. SD was estimated as species richness. GD was estimated in four focal species that differed in their dispersal abilities: Asellus aquaticus (Isopoda), Haliplus ruficollis (Coleoptera), Planorbis planorbis (Gastropoda), Rana temporaria (Amphibia), using double digest restriction associated DNA (ddRAD) sequencing data. There were no significant SGDCs for any of the species. Similarly, GD was not related to land use or pond environment. However, SD had a significant positive correlation with total invertebrate abundance and pond area. Given the absence of significant SGDCs in our study, and the mixed positive and negative patterns found in previous studies reporting SGDCs, we suggest that simultaneously preserving species and genetic diversity in urban areas will prove challenging.

In livestock management systems, the rapid removal of cattle dung by dung beetles plays an essential role in returning areas of pasture to grazing which normally would be lost because of dung contamination. Thus, dung removal is an ecosystem process with established links to services with potentially valuable outcomes. We focused on dung removal under two dung beetle abundance scenarios. We then calculated the economic value of dung beetle action on dung degradation in US sub-tropical pasturelands under each scenario by measuring the costs associated with restriction of new forage growth by dung pat smothering, and the amount of forage gained because of dung beetle mediated dung decomposition. We found if dung is left unmanipulated by dung beetles, it would naturally decompose at an average rate of 3.75 g per day, and dung in pastures with a high abundance of dung beetles would decay at 10.73 g per day. We show the economic benefit of dung decomposition under each scenario is directly related to both the presence and abundance levels of dung beetles in cattle pastures, for instance, resulting in additional grass area to become available to raise 1,131 cows and 1,676 cows under low dung beetle abundances and under high dung beetle abundances, respectively. This amounts to an additional income of USD 918,688 per year in Florida sub-tropical livestock systems containing low abundances of dung beetles and an income of USD 1,360,770 per year for pastures sustaining a higher abundances of dung beetles. Despite their importance in livestock systems dung beetle populations are imperiled by the widespread use of agrochemicals. Reducing agrochemical usage and introducing biodiversity-friendly practices in livestock systems will be important for conserving dung beetles and the ecological functions that dung beetles provide in working landscapes.

Modern approaches with advanced technology can automate and expand the extent and resolution of biodiversity monitoring. We present the development of an innovative system for automated wildlife monitoring in a coastal Natura 2000 nature reserve of the Netherlands with 65 wireless 4G wildlife cameras which are deployed autonomously in the field with 12 V/2A solar panels, i.e. without the need to replace batteries or manually retrieve SD cards. The cameras transmit images automatically (through a mobile network) to a sensor portal, which contains a PostgreSQL database and functionalities for automated task scheduling and data management, allowing scientists and site managers via a web interface to view images and remotely monitor sensor performance (e.g. number of uploaded files, battery status and SD card storage of cameras). The camera trap sampling design combines a grid-based sampling stratified by major habitats with the camera placement along a traditional monitoring route, and with an experimental set-up inside and outside large herbivore exclosures. This provides opportunities for studying the distribution, habitat use, activity, phenology, population structure and community composition of wildlife species and allows comparison of traditional with novel monitoring approaches. Images are transferred via application programming interfaces to external services for automated species identification and long-term data storage. A deep learning model for species identification was tested and showed promising results for identifying focal species. Furthermore, a detailed cost analysis revealed that establishment costs of the automated system are higher but the annual operating costs much lower than those for traditional camera trapping, resulting in the automated system being >40 % more cost-efficient. The developed end-to-end data pipeline demonstrates that continuous monitoring with automated wildlife camera networks is feasible and cost-efficient, with multiple benefits for extending the current monitoring methods. The system can be applied in open habitats of other nature reserves with mobile network coverage.