Urban environments represent a theatre for life history evolution. Species able to survive in cities can adapt to the local and often divergent environmental conditions compared to rural or natural environments. Dispersal determines establishment, gene flow, and thus the potential for local adaptation. Since habitats in urban environments are highly fragmented, and showing substantial turnover, contrasting adaptive effects on dispersal are expected. Fragmentation selects against dispersal while patch turn-over is expected to promote the evolution of dispersal. We here show both processes to act in concert when different scales are considered. Dispersal behaviour of juvenile, lab-reared garden spiders from two mid-sized European cities were tested under standardized conditions. While long-distance dispersal showed to be overall rare, short-distance dispersal strategies increased with urbanization at small scales, but declined when urbanization was quantified at large scales. We discuss the putative drivers behind these differences in natal dispersal and highlight its importance for urban evolution and ecology.

Weed species are ecological models that recently received considerable attention due to their particular strategies linked to their ruderal-competitive traits. They are known to have the potential to provide additional floral resources for insects in flower-poor agroecosystems. However, their floral traits are much more scarcely studied than those of plants found in other habitats, such as grasslands. The aim of this study was to describe the floral phenotype of weeds and to determine to what extent their floral traits match their ecological strategies as described on the basis of leaf traits. We therefore cultivated 19 forb weeds from perennial agroecosystems, previously identified in Mediterranean fields, in a greenhouse for seven months and collected data on 12 floral and 5 leaf traits. We tested whether these traits covaried and whether they exhibited an ecological strategy at the phenotype scale. We found that in matters of flower production, weed species face a trade-off: either numerous small, low-stature flowers with small quantities of pollen and nectar, or few, large, higher-held flowers with more pollen and nectar. The floral traits were found to reflect Grime’s CSR strategies: the weed species producing fewer but costlier flowers belonged to C-strategy species, whereas those producing more but less costly flowers belonged to species dominated by an R strategy These findings indicate that the potential of weeds as floral resources for insects is related to their ecological strategies, which are known to be affected by agricultural practices that filter species composition. This implies that, as for the provision of other ecosystem services, weed communities can be managed so as to select species with interesting floral traits for pollinators.

Color polymorphism is an adaptive strategy in which a species exhibits multiple color phenotypes in a population. Often times, phenotypes are variably suited to different environmental conditions which may buffer the population against variable conditions. Modern climate change is creating novel selective pressures for many species, especially in winter habitats. Few studies have quantified the benefits of polymorphism for allowing species to cope with climate-induced environmental change. We investigated how color polymorphism mediates selective pressures in ruffed grouse Bonasa umbellus, a widespread and winter-adapted bird species of North American forests. Ruffed grouse display phenotypic variation in plumage color, ranging from red to gray. Over five winter seasons (2015-2022), we monitored weather conditions, habitat use, and weekly survival for 94 ruffed grouse to test whether individuals had lower survival when grouse were phenotypically mismatched with snow cover (e.g., a gray bird on a snowless landscape or a red bird in snow). Grouse phenotypically mismatched with snow cover had lower survival, but only when winter survival rates were lowest. During winters of lower overall survival, red grouse exhibited higher survival during snow-free periods, whereas gray grouse had higher survival when snow was present. We also found that open habitat negatively impacted survival, regardless of color. While the effect of phenotypic mismatch was variable among years, it was a stronger predictor of winter survival than land cover features, suggesting that snow is an important habitat feature mediating overwinter survival. Our work offers an advancement in understanding how environmental variability affects geographic variation in and maintenance of multiple color phenotypes in seasonally-snow covered environments. Our finding that interactions between color morph and snow cover are important for conferring winter survival provides further evidence that color polymorphism may serve as a buffer against rapidly changing conditions and a pathway for persistence of polymorphic species.

Ecosystem management aims at providing many ecosystem services simultaneously. Such ecosystem multifunctionality can be limited by trade-offs and increased by synergies among the underlying ecosystem functions (EF), which need to be understood to develop targeted management. Previous studies found differences in the correlation between EFs. We hypothesised that correlations between EFs are variable even under the controlled conditions of a field experiment and that seasonal and annual variation, plant species richness, and plot identity (identity effects of plant communities such as the presence and absence of functional groups and species) are drivers of these correlations. We used data on 31 EFs related to plants, consumers, and physical soil properties that were measured over 5 to 19 years, up to three times per year, in a temperate grassland experiment with 80 different plots, constituting six sown plant species richness levels (1, 2, 4, 8, 16, 60 species). We found that correlations between pairs of EFs were variable, and correlations between two particular EFs could range from weak to strong correlations or from negative to positive correlations among the repeated measurements. To determine the drivers of pairwise EF correlations, the covariance between EFs was partitioned into contributions from plant species richness, plot identity, and time (including years and seasons). We found that most of the covariance for synergies was explained by species richness (26.5%), whereas for trade-offs, most covariance was explained by plot identity (29.5%). Additionally, some EF pairs were more affected by differences among years and seasons and therefore showed a higher temporal variation. Therefore, correlations between two EFs from single measurements are insufficient to draw conclusions on trade-offs and synergies. Consequently, pairs of EFs need to be measured repeatedly under different conditions to describe their relationships with more certainty and be able to derive recommendations for the management of grasslands.

Plant lifespan has important evolutionary, physiological, and ecological implications related to population persistence, community stability, and resilience to ongoing environmental change impacts. Although biologists have long puzzled over the extraordinary variation in plant lifespan and its causes, our understanding of interspecific variability in plant lifespan and the key internal and external factors influencing longevity remains limited. Here, we demonstrate the concurrent impacts of environmental, morphological, physiological, and anatomical constraints on interspecific variation in longevity among >300 vascular dicot plant species naturally occurring at an elevation gradient (2800-6150 m) in the western Himalayas. First, we show that plant longevity is largely related to species’ habitat preferences. Ecologically stressful habitats such as alpine and subnival host long-lived species, while productive ruderal and wetland habitats contain a higher proportion of short-lived species. Second, longevity is influenced by growth form. Small-statured cushion plants with compact canopies and deep roots, most found on cold and infertile alpine and subnival soils, had a higher chance of achieving longevity. Third, plant traits reflecting plant adaptations to stress and disturbance modulate interspecific differences in plant longevity. Importantly, we show that longevity and growth are negatively correlated. Slow-growing plants are those that have a higher chance of reaching a maximum age. Finally, changes in plant carbon, nitrogen, and phosphorus content in root and leaf tissue were significantly associated with variations in longevity. We discuss the link between the longevity and productivity and stability of studied Himalayan ecosystems and the intrinsic growth dynamics and physiological constraints under increasing environmental pressure.

Explaining the mechanisms underlying spatial and temporal variation in community composition is a major challenge. Nevertheless, the processes controlling temporal variation at a site (i.e., temporal β-diversity, including its turnover and nestedness components) are less understood than those affecting variation among sites (i.e., spatial β-diversity). Short-term temporal turnover (e.g., throughout an annual cycle) is expected to correlate positively with seasonal environmental variability and landscape connectivity, but also species pool size (γ-diversity). We use the megadiverse Amazonian freshwater ichthyofauna as a model to ask whether seasonality and landscape connectivity drive variation in temporal species turnover among geomorphological habitat types, while taking into account between-habitat variation in γ-diversity. 11,397 fish representing 260 species were collected during a year-long sampling program in an area containing the lowland Amazon’s four major geomorphological habitat types: rivers, floodplains, terra firme streams, and shield streams. River-floodplain systems exhibit strong but predictable seasonality (via a high-amplitude annual flood pulse), high connectivity, and high species richness with many rare species. Terra firme and shield streams exhibit low seasonality, low connectivity, and low species richness with proportionally fewer rare species. Based on these parameters we predicted that river-floodplain systems should have higher temporal turnover than stream systems. Using a null model approach combined with β-deviation calculations, we confirmed that rivers and floodplains do exhibit higher turnover (but not nestedness) than terra firme and shield streams, even when controlling for the potentially confounding effect of higher species richness in river-floodplain systems. All habitats exhibit low temporal nestedness, indicating that short-term changes in community composition result primarily from temporal species turnover. Our results provide a timely reminder that efforts to conserve the Amazon’s threatened aquatic biodiversity should account for the distinct temporal dynamics of habitat types and variation in hydrological seasonality.

Like many top consumers, parasites can regulate feeding of their prey via trait-mediated means. If parasites modify the feeding behavior of ecologically important grazers, they may have cascading effects on the structure and functioning of whole plant communities. The extent to which parasites can influence plant communities in this way is largely dependent on the strength of their behavioral alteration, their prevalence in host grazers, and the density of those hosts. Recent experiments and comparative surveys in southeastern USA salt marshes revealed that common larval trematode parasites suppress the per capita grazing impacts of the marsh periwinkle (Littoraria irrorata), generating a trophic cascade that protects foundational marsh plants from drought-associated overgrazing. Here, we conducted a field manipulation wherein we modified grazer host density while holding infection prevalence constant at an ecologically relevant level (20%) to determine whether the indirect, facilitative effects of parasites on marsh plants varied with the density of grazers. We found that parasites had significant positive impacts on marsh net primary productivity at moderate densities of snails (≥50 snails/ 0.5 m2), but that the positive effects of parasites were negligible at lower densities. Our results confirm the findings of previous studies that parasites can protect marsh plants from overgrazing at sufficiently high prevalence, but show that their ability to do so depends on host density.

Snowpack dynamics have a major influence on wildlife movement ecology and predator-prey interactions. Specific snow properties such as density, hardness, and depth determine how much an animal sinks into the snowpack, which in turn drives both the energetic cost of locomotion and predation risk. Here, we quantified the relationships between 15 field-measured snow variables and snow track sink depths for widely distributed predators (bobcats [Lynx rufus], coyotes [Canis latrans], wolves [C. lupus]) and sympatric ungulate prey (caribou [Rangifer tarandus], white-tailed deer [Odocoileus virginianus], mule deer [O. hemionus], and moose [Alces alces]) in interior Alaska and northern Washington, USA. We first used generalized additive models to identify which snow metrics best predicted sink depths for each species and across all species. For species occurring in both sites, we then tested whether the snow metric-sink depth relationship differed across regions. Finally, we used breakpoint regression to identify thresholds for the best-performing predictor of sink depth for each species (i.e., values wherein tracks do not appreciably sink into the snow). Near-surface (0-10cm) snow density was the strongest predictor of sink depth across species. This relationship varied slightly by region for wolves and moose but did not differ for coyotes. Thresholds of support occurred at snow densities of 230 kg/m3 for coyotes, 280 kg/m3 for bobcats, 290 kg/m3 for wolves, 340 kg/m3 for deer, 440 kg/m3 for caribou, and 550 kg/m3 for moose. Together, these critical thresholds define the bounds of “danger zones,” the range of snow density in which carnivores have a comparative movement advantage over ungulates. These results can be used to link predator-prey relationships with spatially explicit snow modeling outputs and projected future changes in snow density. As climate change rapidly reshapes snowpack dynamics, these danger zones provide a useful framework to anticipate likely winners and losers of future winter conditions.

Root traits and functioning: from individual plants to ecosystemsFine roots, the most distal portions of the root system, are responsible for the uptake of water and nutrients by plants, represent the main type of plant tissue contributing to soil organic matter accrual, and are key drivers of mineral weathering and soil microbial dynamics (Bardgett et al. 2014). Despite the overwhelming importance of fine root traits for plant and plant community functioning and biogeochemical cycles, basic information about their ecology is lacking, particularly compared to the wealth of information developed for leaves and stems. Testing hypotheses on how root traits underlie these ecosystem processes has been particularly hampered due to (1) a paucity of systematically collected data and (2) the complexity of the relationships between root traits and root, plant and ecosystem functioning. Nonetheless, the development of the field of root ecology in the last two decades has been outstanding, in particular in the compilation of belowground trait datasets (Iversen et al. 2017), methodological root ecological handbooks (Freschet et al. 2021b), novel conceptual frameworks to describe root trait diversity (Bergmann et al. 2020), its connection with belowground plant and community function (Bardgett et al. 2014, Freschet et al. 2021a), species’ distributions (Laughlin et al. 2021), and scaling up traits from the individual root to the ecosystem level (McCormack et al. 2017). The papers that feature in this Special Issue on Root traits and functioning: from individual plants to ecosystems cover different climate regions, taxonomic and spatial scales, and a diversity of traits (Table 1) and form perfect examples of this upward moment of the belowground component in plant ecology.

Predictive modelling is fundamental to ecology and essential for objective biodiversity assessment. However, while predictive biodiversity models are generally well-developed, models for predicting patterns within and among ecosystems have not been adequately operationalized. We contend the scarcity of such models marks a concerning gap in the scientific community’s ability to make ecosystem predictions across landscapes, and more broadly for supporting the conservation of biodiversity and ecosystem functions. We propose ecosystem spatial pattern models (ESPM) to fill this gap in modelling capacity. Under our approach to ESPM, spatial patterns of ecosystem properties are the basis for resolving ecosystem organization at local and landscape extents. Our integrative modelling framework differs from others in that it accords biotic and abiotic constituents equally, based on with their joint mechanistic influence on ecosystem dynamics. Development of ESPM is especially timely for ecosystem assessment is undergoing a contemporary groundswell, as scientists and conservation groups propose ambitious targets for ecosystem conservation and restoration.