Modelling human influences on biodiversity at a global scale–A human ecology perspective

Biodiversity conservation in the context of climate change: Facing challenges and management strategies

Biodiversity conservation amidst the uncertainty of climate change presents unique challenges that necessitate precise management strategies. The study reported here was aimed at refining understanding of these challenges and to propose specific, actionable management strategies. Employing a quantitative literature analysis, we meticulously examined 1268 research articles from the Web of Science database between 2005 and 2023. Through Cite Spaces and VOS viewer software, we conducted a bibliometric analysis and thematic synthesis to pinpoint emerging trends, key themes, and the geographical distribution of research efforts. Our methodology involved identifying patterns within the data, such as frequency of keywords, co-authorship networks, and citation analysis, to discern the primary focus areas within the field. This approach allowed us to distinguish between research concentration areas, specifically highlighting a predominant interest in Environmental Sciences Ecology (67.59 %) and Biodiversity Conservation (22.63 %). The identification of adaptive management practices and ecosystem services maintenance are central themes in the research from 2005 to 2023. Moreover, challenges such as understanding phenological shifts, invasive species dynamics, and anthropogenic pressures critically impact biodiversity conservation efforts. Our findings underscore the urgent need for precise, data-driven decision-making processes in the face of these challenges. Addressing the gaps identified, our study proposes targeted solutions, including the establishment of germplasm banks for at-risk species, the development of advanced genomic and microclimate models, and scenario analysis to predict and mitigate future conservation challenges. These strategies are aimed at enhancing the resilience of biodiversity against the backdrop of climate change through integrated, evidence-based approaches. By leveraging the compiled and analyzed data, this study offers a foundational framework for future research and practical action in biodiversity conservation strategies, demonstrating a path forward through detailed analysis and specified solutions.

Management of non-indigenous species in Macaronesia: Misconceptions and alerts to decision-makers

Human-induced pressures have led to substantial changes in marine ecosystems worldwide, with the introduction of non-indigenous species (NIS) emerging as a significant threat to ecological, economic, and social aspects. The Macaronesian islands, comprising the Azores, Madeira, Canary Islands, and Cabo Verde archipelagos, are regions where the regional economy is dependent on marine resources (e.g., marine traffic, ecotourism and fisheries). Despite their importance, concerted efforts to manage marine biological invasions in Macaronesia have been scarce. In this context, the current study aims to contribute to the much-needed debate on biosecurity measures in this unique insular ecosystem to prevent and mitigate the impact of NIS. By adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria, this work validated and analyzed 260 documents providing insights into the management of NIS in Macaronesia until 2022. These documents revealed the presence of 29 Invasive Alien Species (IAS), most of which are misconceptions regarding this terminology. Most studies focused on the stages of early detection, rapid response, and eradication across the archipelagos. Cabo Verde had comparatively fewer studies. The most common techniques include monitoring/sampling, literature reviews, and taxonomic reviews. NIS introduction pathways were mainly attributed to transport (stowaway) and unaided migration, with ship fouling, ballast water, rafting, ocean currents, and tropicalization being also identified as significant contributors. This systematic review highlights the current efforts to establish robust biosecurity protocols in Macaronesia and emphasizes the urgent need to safeguard the region's ecological, economic, and social well-being.

Opportunities and challenges for monitoring a recolonizing large herbivore using citizen science

Monitoring is a prerequisite for evidence-based wildlife management and conservation planning, yet conventional monitoring approaches are often ineffective for species occurring at low densities. However, some species such as large mammals are often observed by lay people and this information can be leveraged through citizen science monitoring schemes. To ensure that such wildlife monitoring efforts provide robust inferences, assessing the quantity, quality, and potential biases of citizen science data is crucial. For Eurasian moose (Alces alces), a species currently recolonizing north-eastern Germany and occurring in very low numbers, we applied three citizen science tools: a mail/email report system, a smartphone application, and a webpage. Among these monitoring tools, the mail/email report system yielded the greatest number of moose reports in absolute and in standardized (corrected for time effort) terms. The reported moose were predominantly identified as single, adult, male individuals, and reports occurred mostly during late summer. Overlaying citizen science data with independently generated habitat suitability and connectivity maps showed that members of the public detected moose in suitable habitats but not necessarily in movement corridors. Also, moose detections were often recorded near roads, suggestive of spatial bias in the sampling effort. Our results suggest that citizen science-based data collection can be facilitated by brief, intuitive digital reporting systems. However, inference from the resulting data can be limited due to unquantified and possibly biased sampling effort. To overcome these challenges, we offer specific recommendations such as more structured monitoring efforts involving the public in areas likely to be roamed by moose for improving quantity, quality, and analysis of citizen science-based data for making robust inferences.

Testing differences of marine non-indigenous species diversity across Macaronesia using a standardised approach

The introduction of non-indigenous species (NIS) induces severe impacts on marine biodiversity and ecosystems. Macaronesia is an ecologically relevant region where several NIS were detected recently. For the first time, a standard experimental approach was designed to examine biofouling assemblages and investigate NIS across the region. In this context, sessile biofouling assemblages were examined in four recreational marinas in all the Macaronesian archipelagos from 2018 to 2020: the Azores, Madeira, Canary Islands, and Cabo Verde. We hypothesised that NIS numbers, abundance, and recruitment differed in each location due to abiotic and biotic features. From the Azores (higher latitudes) to Cabo Verde (lower latitudes), NIS recruitment and percentage cover decreased following a partial latitude gradient. The present study unveiled 25 NIS, with new records for the Azores (two cryptogenic species), Canary Islands (one NIS and two cryptogenic species), and Cabo Verde (three NIS and three cryptogenic species). The present research represents a pioneer and relevant step in advancing our current understanding of marine biological invasions in Macaronesia, employing a standard and low-cost approach.

The Elusive Turkestan Lynx at the Northwestern Edge of Geographic Range: Current Suitable Habitats and Distribution Forecast in the Climate Change

The Turkestan lynx (Lynx lynx isabellina Blyth, 1847) is a rare and understudied subspecies of the Eurasian lynx occupying the mountains of Central and South Asia. This elusive felid’s northwestern range includes the Tien Shan and Zhetisu Alatau mountains in the border region of Kazakhstan, China, Kyrgyzstan, and Uzbekistan. As the first step to conserve this vulnerable carnivore, we have conducted the first full-scale research from 2013 until 2022 on its distribution in this region. Using 132 environmental predictors of 359 lynx sightings, we have created species habitat distribution models across the lynx’s northwestern range using machine learning approaches (Maximum Entropy—MaxEnt). Additionally, we created species distribution forecasts based on seven bio-climatic environmental predictors with each three different future global climate model scenarios. To validate these forecasts, we have calculated the changes in the lynx distribution range for the year 2100, making the first species distribution forecast for the Turkestan lynx in the area. Additionally, it provides insight into the possible effects of global climate change on this lynx population. Based on these distribution models, the lynx population in the Northern and Western Tien Shan and Zhetisu Alatau plays a significant role in maintaining the stability of the whole subspecies in its northwestern and global range, while the distribution forecast shows that most lynx distribution ranges will reduce in all future climate scenarios, and we might face the Turkestan lynx’s significant distribution range decline under the ongoing and advancing climate change conditions. For a future (year 2100) warming scenario of 3 deg. C (GCM IPSL), we observe a decrease of 35% in Kazakhstan, 40% in Kyrgyzstan, and 30% in China as the three countries with the highest current predicted distribution range. For a milder temperature increase of 1.5–2 deg. C. (GCM MRI), we observe an increase of 17% Kazakhstan, decrease of 10% in Kyrgyzstan, and 57% in China. For a cooling scenario of approx. 1–1.5 deg. C (GCM MIROC), we observe a decrease of 14% Kazakhstan, increase of 11% in Kyrgyzstan, and a decrease of 13% in China. These modeled declines indicate the necessity to create new and expand the existing protected areas and establish ecological corridors between the countries in Central and South Asia.

Anthropogenic pressure leads to more introductions: Marine traffic and artificial structures in offshore islands increases non-indigenous species

Anthropogenic pressures such as the introduction of non-indigenous species (NIS) have impacted global biodiversity and ecosystems. Most marine species spreading outside their natural biogeographical limits are promoted and facilitated by maritime traffic through ballast water and hull biofouling. Propagule pressure plays a primary role in invasion success mixed with environmental conditions of the arrival port. Moreover, with the current ocean sprawl, new substrates are offered for potential NIS recruits. Here, differences in the fouling assemblages thriving inside three different ports/marinas facilities in Madeira Island were assessed for comparison. The locations showed significant differences concerning assemblage structure. Most NIS were detected in plastic floating pontoons. Funchal harbour receives most of the marine traffic in Madeira, acting as the main hub for primary NIS introductions, being recreational boating involved in NIS secondary transfers. Our results highlight the need for future management actions in island ecosystems, particularly monitoring and sampling of recreational boating.

Robust Algorithms for Drone-Assisted Monitoring of Big Animals in Harsh Conditions of Siberian Winter Forests: Recovery of European elk (Alces alces) in Salair Mountains

Simple Summary

Forest animals can be used as a sensitive indicator of the real state of biodiversity. The research objective was to study the potential of drone planes equipped with thermal infrared imaging cameras for large animal monitoring in the conditions of Siberian winter forests with snow background at temperatures of −5 °C to −30 °C. The surveyed territory included the Salair State Nature Reserve in the Kemerovo Region, Russia. Drone planes were effective in covering large areas, while thermal infrared cameras provided accurate information in the harsh winter conditions of Siberia. The research featured the population of the European elk (Alces alces), which is gradually deteriorating due to poaching and deforestation. The designed technical methods and analytic algorithms are cost-efficient and they can be applied for monitoring large areas of Siberian, Canadian and Alaskan winter forests.

Abstract

There are two main reasons for monitoring the population of forest animals. First, regular surveys reveal the real state of biodiversity. Second, they guarantee a prompt response to any negative environmental factor that affects the animal population and make it possible to eliminate the threat before any permanent damage is done. The research objective was to study the potential of drone planes equipped with thermal infrared imaging cameras for large animal monitoring in the conditions of Siberian winter forests with snow background at temperatures −5 °C to −30 °C. The surveyed territory included the Salair State Nature Reserve in the Kemerovo Region, Russia. Drone planes were effective in covering large areas, while thermal infrared cameras provided accurate statistics in the harsh winter conditions of Siberia. The research featured the population of the European elk (Alces alces), which is gradually deteriorating due to poaching and deforestation. The authors developed an effective methodology for processing the data obtained from drone-mounted thermal infrared cameras. The research provided reliable results concerning the changes in the elk population on the territory in question. The use of drone planes proved an effective means of ungulate animal surveying in snow-covered winter forests. The designed technical methods and analytic algorithms are cost-efficient and they can be applied for monitoring large areas of Siberian and Canadian winter forests.

Multidrug-resistant epi-endophytic bacterial community in Posidonia oceanica of Mahdia coast as biomonitoring factor for antibiotic contamination

Faced with the significant disturbances, mainly of anthropogenic origin, which affect the Mediterranean coastal ecosystem, Posidonia oceanica (L.) Delile has often been used to assess the state of health of this environment. The present study aims to determine the multidrug resistance patterns among isolated and identified epi-endophytic bacterial strains in P. oceanica seagrass collected from Mahdia coastal seawater (Tunisia). To investigate the bacterial community structure and diversity from coastal seawater samples from Mahdia, total DNA extraction and 16S rRNA gene amplification were performed and analyzed by denaturing gradient gel electrophoresis (DGGE). The DGGE profiles showed that some bands were specific to a given site, while other bands were found to be common to more than one sample. In the other hand, bacterial strains were isolated from 1 mL of leaves and epiphytes suspension of P. oceanica seagrass in marine agar. Forty-three isolates were obtained, seven of them were selected and identified on the basis of 16S rRNA gene sequence analysis. These isolates belonged to the genus Bacillus, exhibiting 98-100% of identity with known sequences. Susceptibility patterns of these strains were studied toward commonly used antibiotics in Tunisia. All identified isolates were resistant to Aztreonam (72.1%), Ceftazidime (60.5%), Amoxicillin (56%) and Rifampicin (51.2%). S5-L13 strain had presented the highest multidrug resistance with a MAR index of 0.67.