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Phenology changes are increasingly recognized as a common response of species to ongoing global change. Phenology can be influenced by environmental cues that impact the initiation or duration of life history events as well as intrinsic organismal traits that may affect how different species respond to such environmental cues. Despite the importance of phenology for biodiversity conservation as demonstrated by terrestrial and marine research, freshwater phenology is understudied. Therefore, we conducted a literature review on freshwater phenology research to summarize the spatial, taxonomic and temporal biases of studies; as well as relationships between phenology metrics, environmental cues and intrinsic species traits studied in these systems. We find that phenology research in freshwaters may be limited by a lack of long‐term time‐series data, especially in lotic habitats. Phenology metrics studied differed between lotic and lentic habitats, with limnological research focused on planktonic population growth whereas macroinvertebrate emergence and fish spawning seasons are the most frequently studied aspects of phenology in streams and rivers. Across habitats, temperature is the most investigated environmental cue, with additional research attention to resources and hydrology in influencing phenology events in lentic and lotic environments, respectively. Knowledge gaps in contemporary freshwater phenology research include relationships between phenology and environmental cues in tropical systems, understanding of non‐salmonid fish phenology and testing hypotheses related to intrinsic traits. We recommend that future research broaden the biological, spatial and temporal scales of phenology studies in these systems, and make use of novel data sources, methods and technologies to address contemporary research gaps.

As climate change unfolds, changes in population dynamics and species distribution ranges are expected to fundamentally reshuffle communities worldwide. Yet, a comprehensive understanding of the mechanisms and extent of community reorganization remains elusive. This is particularly true in riverine systems, which are simultaneously exposed to changing temperature and streamflow, and where land-use change continues to be a major driver of biodiversity loss. Here, we use the most comprehensive compilation of fish abundance time series to date to provide a global synthesis of climate- and LU-induced effects on riverine biota with respect to changes in species thermal and streamflow affinities. We demonstrate that fish communities are increasingly dominated by thermophilic (warm-water) and limnophilic (slow-water) species. Despite being consistent with trends in water temperature and streamflow observed over recent decades, these community changes appear largely decoupled from each other and show wide spatial variation. We further reveal a synergy among climate- and land use-related drivers, such that community thermophilization is heightened in more human-modified systems. Importantly, communities in which species experience thermal and flow regimes that approach or exceed their tolerance thresholds (high community sensitivity), as well as species-poor communities (low community resilience), also display faster rates of compositional change. This research illustrates that quantifying vulnerability of riverine systems to climate change requires a broadening from a narrower thermal focus to more integrative approaches that account for the spatially varying and multifaceted sensitivity of riverine organisms to the interactive effects of water temperature, hydrology, and other anthropogenic changes.

Aim: The elucidation of patterns and drivers of community assembly remains a fundamental issue in ecology. Past studies have focused on a limited number of communities at local or regional scales, thus precluding a comprehensive examination of assembly rules. We addressed this challenge by examining stream fish community assembly within numerous independent watersheds spanning a broad environmental gradient. We aimed to answer the following questions: (1) are fish communities structured non-randomly, and (2) what is the relative importance of environmental filtering, predator–prey interactions and interspecific competition in driving species associations? Location: The conterminous USA. Methods: We used null models to analyse species associations in streams. Non-random communities were defined as those where the summed number of segregated and aggregated species pairs exceeded the number expected by chance. We used species traits to characterize species dissimilarity in environmental requirements (ENV), identify potential predator-prey interactions (PRED) and estimate likely degree of competition based on species similarity in body size, feeding strategies and phylogeny (COMP). To evaluate the effect of environmental filtering, predation and competition on species associations, we related ENV, PRED and COMP to the degree of species segregation. Results: The majority (75-85%) of watersheds had non-random fish communities. Species segregation increased with species dissimilarity in environmental requirements (ENV). An increase in competition strength (COMP) did not appear to increase segregation. Species pairs engaging in predator–prey interactions (PRED) were more segregated than non-predator–prey pairs. ENV was more predictive of the degree of species segregation than PRED. Main conclusions: We provide compelling evidence for widespread nonrandom structure in US stream fish communities. Community assembly is governed largely by environmental filtering, followed by predator–prey interactions, whereas the influence of interspecific competition appears minimal. Applying a traits-based approach to continent-wide datasets provides a powerful approach for examining the existence of assembly rules in nature.

Identifying how close species live to their physiological thermal maxima is essential to understand historical warm‐edge elevational limits of montane faunas and forecast upslope shifts caused by future climate change. We used laboratory experiments to quantify the thermal tolerance and acclimation potential of four fishes (Notropis leuciodus, N. rubricroceus, Etheostoma rufilineatum, E. chlorobranchium) that are endemic to the southern Appalachian Mountains (USA), exhibit different historical elevational limits, and represent the two most species‐rich families in the region. All‐subsets selection of linear regression models using AICc indicated that species, acclimation temperature, collection location and month, and the interaction between species and acclimation temperature were important predictors of thermal maxima (Tmax), which ranged from 28.5 to 37.2°C. Next, we implemented water temperature models and stochastic weather generation to characterize the magnitude and frequency of extreme heat events (Textreme) under historical and future climate scenarios across 25 379 stream reaches in the upper Tennessee River system. Lastly, we used environmental niche models to compare warming tolerances (acclimation‐corrected Tmax minus Textreme) between historically occupied versus unoccupied reaches. Historical warming tolerances, ranging from +2.2 to +10.9°C, increased from low to high elevation and were positive for all species, suggesting that Tmax does not drive warm‐edge (low elevation) range limits. Future warming tolerances were lower (−1.2 to +9.3°C) but remained positive for all species under the direst warming scenario except for a small proportion of reaches historically occupied by E. rufilineatum, indicating that Tmax and acclimation potentials of southern Appalachian minnows and darters are adequate to survive future heat waves. We caution concluding that these species are invulnerable to 21st century warming because sublethal thermal physiology remains poorly understood. Integrating physiological sensitivity and warming exposure demonstrates a general and fine‐grained approach to assess climate change vulnerability for freshwater organisms across physiographically diverse riverscapes.

In an era of global change, the process of biotic homogenisation by which regional biotas become more similar through time has attracted considerable attention from ecologists. Here, a retrospective look at the literature is taken and the question asked how comprehensive is the understanding of this global phenomenon? The goal is to identify potential areas for additional and future enquiries to advance this research frontier and best ensure the long-term preservation of biological diversity across the world. Six propositions are presented here to; (1) broaden our geographic and taxonomic understanding, (2) diversify the spatial and temporal scales of inquiry, (3) reconcile past and embrace new approaches to quantification, (4) improve our knowledge of the underlying drivers, (5) reveal the conservation implications and (6) forecast future homogenisation. It is argued that significant progress in the understanding of the causes, consequences and conservation implication of biotic homogenisation will come by integrating concepts and approaches from ecology, evolution and conservation across a hierarchy of spatial and temporal scales.

Monitoring the expansion of commodity crops in the tropics is crucial to safeguard forests for biodiversity and ecosystem services. Oil palm (Elaeis guineensis) is one such crop that is a major driver of deforestation in Southeast Asia. We evaluated the use of a semi-automated approach with random forest as a classifier and combined optical and radar datasets to classify oil palm land-cover in 2015 in Sumatra, Indonesia, using Google Earth Engine. We compared our map with two existing remotely-sensed oil palm land-cover products that utilized visual and semi-automated approaches for the same year. We evaluated the accuracy of oil palm land-cover classification from optical (Landsat), radar (synthetic aperture radar (SAR)), and combined optical and radar satellite imagery (Combined). Combining Landsat and SAR data resulted in the highest overall classification accuracy (84%) and highest producer’s and user’s accuracy for oil palm classification (84% and 90%, respectively). The amount of oil palm land-cover in our Combined map was closer to official government statistics than the two existing land-cover products that used visual interpretation techniques. Our analysis of the extents of disagreement in oil palm land-cover indicated that our map had comparable accuracy to one of them and higher accuracy than the other. Our results demonstrate that a combination of optical and radar data outperforms the use of optical-only or radar-only datasets for oil palm classification and that our technique of preprocessing and classifying combined optical and radar data in the Google Earth Engine can be applied to accurately monitor oil-palm land-cover in Southeast Asia.

The structural heterogeneity of vegetation is a key factor for explaining animal diversity patterns at a local scale. Improvements in airborne light detection and ranging (lidar) technologies have enabled researchers to study forest 3D structure with increasing accuracy. Most structure–animal diversity work has focused on structural metrics derived from lidar returns from canopy and terrain features. Here, we built new lidar structural metrics based on the Leaf Area Density (LAD) at each vegetation height layer, and used these metrics to study how different aspects of forest structural heterogeneity explain variation in bird species richness. Our goals were to test: (1) whether LAD-based metrics better explained bird species richness compared to metrics based on the top of the canopy; and (2) if different aspects of structural heterogeneity had diverse effects on bird richness. We used discrete lidar data together with 61 breeding landbird points provided by the National Ecological Observatory Network at five forest sites of the eastern US. We used the lidar metrics as predictors of bird species richness and analyzed the shape of the response curves against each predictor. Metrics based on LAD measurements had better explanatory power (43% of variance explained) than those based on the variation of canopy heights (32% of variance explained). Dividing the forest plots into smaller grids allowed us to study the within-plot horizontal variation of the vertical heterogeneity, as well as to analyze how the vegetation density is horizontally distributed at each height layer. Bird species richness increased with horizontal heterogeneity, while vertical heterogeneity had negative effects, contrary to previous research. The increasing capabilities of lidar will allow researchers to characterize forest structure with higher detail. Our findings highlight the need for structure–animal diversity studies to incorporate metrics that are able to capture different aspects of forest 3D heterogeneity.

Species can be rare or common in three different dimensions: geographic range size, habitat breadth, and local abundance. Understanding drivers of rarity are not only fundamentally interesting; it is also pertinent for their conservation. We addressed this challenge by analyzing the rarity of 291 native freshwater fishes occurring in ca 3500 independent stream reaches that span a broad environmental gradient across continental USA. Using phylogenetic regression and path analysis, we examined the concordance among the three rarity dimensions, and identified possible mechanisms by which species life-history, habitat affinities, and biogeography drive variation in rarity. Weak double extinction jeopardies were driven by weakly positive correlations between habitat breadth and local abundance, and between habitat breadth and geographic range size. However, a triple extinction jeopardy was averted as local abundance and range size were not positively linked in our study. This is because large-river and lacustrine habitat use mediated a trade-off between local abundance and range size. Large rivers and lacustrine habitats represent important dispersal pathways and refugia that enabled fishes to acquire wide ranges; however, species using these habitats are less abundant overall because they are less adapted to small lotic channels, which comprise the majority of stream habitats in the US. Life-history traits were key in governing the relationship between abundance and range size as large-river and lacustrine habitat use were driven by body size, egg size, and parental care. Our analysis contributes novel insights into mechanisms that underlie multiple dimensions of rarity in freshwater fish and informs the prioritization of multiply rare species for conservation.

Mechanisms that mitigate greenhouse-gas emissions via forest conservation have been portrayed as a cost-effective approach that can also protect biodiversity and vital ecosystem services. However, the costs of conservation -– including opportunity costs -– are spatially heterogeneous across the globe. The lowland rainforests of Southeast Asia represent a unique nexus of large carbon stores, imperiled biodiversity, large stores of timber, and high potential for conversion to oil-palm plantations, making this region one where understanding the costs of conservation is critical. Previous studies have underestimated the gap between conservation costs and conversion benefits in Southeast Asia. Using detailed logging records, cost data, and species-specific timber auction prices from Borneo, we show that the profitability of logging, in combination with potential profits from subsequent conversion to palm-oil production, greatly exceeds foreseeable revenues from a global carbon market and other ecosystem-service payment mechanisms. Thus, the conservation community faces a massive funding shortfall to protect the remaining lowland primary forests in Southeast Asia.