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Inland waters are among the most threatened biodiversity hotspots. Ponds located in alpine areas are experiencing more rapid and dramatic water temperature increases than any other biome. Despite their prevalence, alpine ponds and their biodiversity responses to climate change have been poorly explored, reflecting their small size and difficult access. To understand the effects of climate change on alpine pond biodiversity, we performed a comprehensive literature review for papers published since 1955. Through analysis of their geographic distribution, environmental features, and biodiversity values, we identified which environmental factors related to climate change would have direct or indirect effects on alpine pond biodiversity. We then synthesized this information to produce a conceptual model of the effects of climate change on alpine pond biodiversity. Increased water temperature, reduced hydroperiod, and loss of connectivity between alpine ponds were the main drivers of biodiversity geographic distribution, leading to predictable changes in spatial patterns of biodiversity. We identified three major research gaps that, if addressed, can guide conservation and restoration strategies for alpine ponds biodiversity in an uncertain future. [ABSTRACT FROM AUTHOR]

Citizen science can facilitate in‐depth learning for pupils and students, contribute to scientific research, and permit civic participation. Here, we describe the development of the transnational school‐based citizen science project Phenology of the North Calotte. Its primary goal is to introduce pupils (age 12–15; grades 7–10) in northern Norway, Russia, and Finland to the local and global challenges of climate change resulting in life cycle changes at different trophic and ecosystem levels in their backyards. Partnerships between regional scientists and staff from NIBIO Svanhovd, State nature reserves, national parks, and teachers and pupils from regional schools aim to engage pupils in project‐based learning. The project uses standardized protocols, translated into the different languages of participating schools. The phenological observations are centered around documenting clearly defined life cycle phases (e.g., first appearance of species, flowering, ripening, leaf yellowing, snow fall, and melt). The observations are collected either on paper and are subsequently submitted manually to an open‐source online database or submitted directly via a newly developed mobile app. In the long term, the database is anticipated to contribute to research studying changes in phenology at different trophic levels. In principle, guided school‐based citizen science projects have the potential to contribute to increased environmental awareness and education and thereby to transformative learning at the societal level while contributing to scientific progress of understudied biomes, like the northern taiga and (sub)arctic tundra. However, differences in school systems and funding insecurity for some schools have been major prohibiting factors for long‐term retention of pupils/schools in the program. Project‐based and multidisciplinary learning, although pedagogically desired, has been partially difficult to implement in participating schools, pointing to the need of structural changes in national school curricula and funding schemes as well as continuous offers for training and networking for teachers. [ABSTRACT FROM AUTHOR]

The ecological and genetic changes that underlie the evolution of host–microbe interactions remain elusive, primarily due to challenges in disentangling the variables that alter microbiome composition. To understand the impact of host habitat, host genetics, and evolutionary history on microbial community structure, we examined gut microbiomes of river‐ and three cave‐adapted morphotypes of the Mexican tetra, Astyanax mexicanus, in their natural environments and under controlled laboratory conditions. Field‐collected samples were dominated by very few taxa and showed considerable interindividual variation. We found that lab‐reared fish exhibited increased microbiome richness and distinct composition compared to their wild counterparts, underscoring the significant influence of habitat. Most notably, however, we found that morphotypes reared on the same diet throughout life developed distinct microbiomes suggesting that genetic loci resulting from cavefish evolution shape microbiome composition. We observed stable differences in Fusobacteriota abundance between morphotypes and demonstrated that this could be used as a trait for quantitative trait loci mapping to uncover the genetic basis of microbial community structure. [ABSTRACT FROM AUTHOR]

The anthropogenic impacts on the environment, including deforestation and the escalating emissions of greenhouse gases, have significantly contributed to global climate change that can lead to alterations in ecosystems. In this context, protected areas (PAs) are pillars for biodiversity conservation by being able, for example, to maintain the viability of populations of endangered species. On the other hand, the species range shifts do not follow the limits of PAs, jeopardizing the conservation of these species. Furthermore, the effectiveness of PAs is consistently undermined by impacts stemming from land use, hunting activities, and illegal exploitation, both within the designated areas and in their adjacent zones. The objectives of this study are to quantify the impacts of climate change on the distribution of threatened and endemic birds of the Amazon biome, evaluate the effectiveness of PAs in protecting the richness of threatened birds, and analyze the representativeness of species within PAs. We found with our results that climate suitability loss is above 80 for 65% of taxa in the optimistic scenario and above 93% in the pessimistic scenario. The results show that PAs are not effective in protecting the richness of Amazonian birds, just as they are ineffective in protecting most of the taxa studied when analyzed individually Although some taxa are presented as "Protected," in future scenarios these taxa may suffer major shrinkages in their distributions and consequently present population unviability. The loss of climatically suitable areas and the effectiveness of PAs can directly influence the loss of ecosystem services, fundamental to maintaining the balance of biodiversity. Therefore, our study paves the way for conservation actions aimed at these taxa so that they can mitigate current and future extinctions due to climate change. [ABSTRACT FROM AUTHOR]

Occupancy modeling is an essential tool for understanding species‐habitat associations, thereby helping to plan the conservation of rare and threatened wildlife species. The conservation status and ecology of several avian species, particularly ground‐dwelling birds, are poorly known in Ethiopia. We used camera trap‐based occupancy modeling to investigate habitat covariate influence on occupancy (Ψ) and detection probability (ρ) estimates of Moorland Francolins Scleroptila psilolaema from spatially replicated surveys across both relatively pristine and disturbed landscapes in the Afroalpine biome of Ethiopia. Model‐averaged estimate of ψ̂$$ \hat{\uppsi} $$ across all sites was 0.76 (SD = 0.28) and ρ̂$$ \hat{\uprho} $$ was 0.77 (SD = 0.13) in the pristine landscape. The ψ̂$$ \hat{\uppsi} $$ of the species in the disturbed landscape was 0.56 (SD = 0.19) and ρ̂$$ \hat{\uprho} $$ was 0.48 (SD = 0.06). As hypothesized, based on our model‐averaged beta coefficient estimates (βmean ± SE), predators significantly negatively influenced the occupancy of Moorland Francolins in pristine habitat. We also found a significant positive association of occupancy with herb species richness. Contrary to our prediction, distance to road significantly negatively influence the occupancy of the species, suggesting that occupancy probability was highest in proximity to roadsides and trails in the pristine habitat. There was no significant influence of habitat covariates on the occupancy of the species in the disturbed habitat. The most important covariates that significantly influence the detectability of the species in pristine habitat included sampling occasion and precipitation. The greater occupancy and detectability of this endemic species in the pristine habitat could be linked with the particular conservation status and management of this biodiversity hotspot in the central highlands of Ethiopia. Our results suggest that strict legal enforcement is required to sustainably preserve Moorland Francolins and the ecological integrity of the entire Afroalpine biome. We recommend using camera traps in order to develop realistic and effective conservation and management strategies for rare, sensitive, cryptic, and ground‐dwelling animals in the region. [ABSTRACT FROM AUTHOR]

Scientists are increasingly using volunteer efforts of citizen scientists to classify images captured by motion‐activated trail cameras. The rising popularity of citizen science reflects its potential to engage the public in conservation science and accelerate processing of the large volume of images generated by trail cameras. While image classification accuracy by citizen scientists can vary across species, the influence of other factors on accuracy is poorly understood. Inaccuracy diminishes the value of citizen science derived data and prompts the need for specific best‐practice protocols to decrease error. We compare the accuracy between three programs that use crowdsourced citizen scientists to process images online: Snapshot Serengeti, Wildwatch Kenya, and AmazonCam Tambopata. We hypothesized that habitat type and camera settings would influence accuracy. To evaluate these factors, each photograph was circulated to multiple volunteers. All volunteer classifications were aggregated to a single best answer for each photograph using a plurality algorithm. Subsequently, a subset of these images underwent expert review and were compared to the citizen scientist results. Classification errors were categorized by the nature of the error (e.g., false species or false empty), and reason for the false classification (e.g., misidentification). Our results show that Snapshot Serengeti had the highest accuracy (97.9%), followed by AmazonCam Tambopata (93.5%), then Wildwatch Kenya (83.4%). Error type was influenced by habitat, with false empty images more prevalent in open‐grassy habitat (27%) compared to woodlands (10%). For medium to large animal surveys across all habitat types, our results suggest that to significantly improve accuracy in crowdsourced projects, researchers should use a trail camera set up protocol with a burst of three consecutive photographs, a short field of view, and determine camera sensitivity settings based on in situ testing. Accuracy level comparisons such as this study can improve reliability of future citizen science projects, and subsequently encourage the increased use of such data. [ABSTRACT FROM AUTHOR]

Transects that traverse substantial climate gradients are important tools for climate change research and allow questions on the extent to which phenotypic variation associates with climate, the link between climate and species distributions, and variation in sensitivity to climate change among biomes to be addressed. However, the potential limitations of individual transect studies have recently been highlighted. Here, we argue that replicating and networking transects, along with the introduction of experimental treatments, addresses these concerns. Transect networks provide cost-effective and robust insights into ecological and evolutionary adaptation and improve forecasting of ecosystem change. We draw on the experience and research facilitated by the Australian Transect Network to demonstrate our case, with examples, to clarify how population- and community-level studies can be integrated with observations from multiple transects, manipulative experiments, genomics, and ecological modeling to gain novel insights into how species and systems respond to climate change. This integration can provide a spatiotemporal understanding of past and future climate-induced changes, which will inform effective management actions for promoting biodiversity resilience. [ABSTRACT FROM AUTHOR]

There have been numerous attempts to synthesize the results of local-scale biodiversity change studies, yet several geographic data gaps exist. These data gaps have hindered ecologist's ability to make strong conclusions about how local-scale species richness is changing around the globe. Research on four of the major drivers of global change is unevenly distributed across the Earth's biomes. Here, we use a dataset of 638 anthropogenically driven species richness change studies to identify where data gaps exist across the Earth's terrestrial biomes based on land area, future change in drivers, and the impact of drivers on biodiversity, and make recommendations for where future studies should focus their efforts. Across all drivers of change, the temperate broadleaf and mixed forests and the tropical moist broadleaf forests are the best studied. The biome-driver combinations we have identified as most critical in terms of where local-scale species richness change studies are lacking include the following: land-use change studies in tropical and temperate coniferous forests, species invasion and nutrient addition studies in the boreal forest, and warming studies in the boreal forest and tropics. Gaining more information on the local-scale effects of the specific human drivers of change in these biomes will allow for better predictions of how human activity impacts species richness around the globe. [ABSTRACT FROM AUTHOR]

Climate change will likely affect flooding regimes, which have a large influence on the functioning of freshwater riparian wetlands. Low water levels predicted for several fluvial systems make wetlands especially vulnerable to the spread of invaders, such as the common reed ( Phragmites australis), one of the most invasive species in North America. We developed a model to map the distribution of potential germination grounds of the common reed in freshwater wetlands of the St. Lawrence River ( Québec, Canada) under current climate conditions and used this model to predict their future distribution under two climate change scenarios simulated for 2050. We gathered historical and recent (remote sensing) data on the distribution of common reed stands for model calibration and validation purposes, then determined the parameters controlling the species establishment by seed. A two-dimensional model and the identified parameters were used to simulate the current (2010) and future (2050) distribution of germination grounds. Common reed stands are not widespread along the St. Lawrence River (212 ha), but our model suggests that current climate conditions are already conducive to considerable further expansion (>16,000 ha). Climate change may also exacerbate the expansion, particularly if river water levels drop, which will expose large bare areas propitious to seed germination. This phenomenon may be particularly important in one sector of the river, where existing common reed stands could increase their areas by a factor of 100, potentially creating the most extensive reedbed complex in North America. After colonizing salt and brackishwater marshes, the common reed could considerably expand into the freshwater marshes of North America which cover several million hectares. The effects of common reed expansion on biodiversity are difficult to predict, but likely to be highly deleterious given the competitiveness of the invader and the biological richness of freshwater wetlands. [ABSTRACT FROM AUTHOR]