No effect of snow on shrub xylem traits: Insights from a snow-manipulation experiment on Disko Island, Greenland.

Widespread shrubification across the Arctic has been generally attributed to increasing air temperatures, but responses vary across species and sites. Wood structures related to the plant hydraulic architecture may respond to local environmental conditions and potentially impact shrub growth, but these relationships remain understudied. Using methods of dendroanatomy, we analysed shrub ring width (RW) and xylem anatomical traits of 80 individuals of Salix glauca L. and Betula nana L. at a snow manipulation experiment in Western Greenland. We assessed how their responses differed between treatments (increased versus ambient snow depth) and soil moisture regimes (wet and dry). Despite an increase in snow depth due to snow fences (28-39 %), neither RW nor anatomical traits in either species showed significant responses to this increase. In contrast, irrespective of the snow treatment, the xylem specific hydraulic conductivity (Ks) and earlywood vessel size (LA95) for the study period were larger in S. glauca (p < 0.1, p < 0.01) and B. nana (p < 0.01, p < 0.001) at the wet than the dry site, while both species had larger vessel groups at the dry than the wet site (p < 0.01). RW of B. nana was higher at the wet site (p < 0.01), but no differences were observed for S. glauca. Additionally, B. nana Ks and LA95 showed different trends over the study period, with decreases observed at the dry site (p < 0.001), while for other responses no difference was observed. Our results indicate that, taking into account ontogenetic and allometric trends, hydraulic related xylem traits of both species, along with B. nana growth, were influenced by soil moisture. These findings suggest that soil moisture regime, but not snow cover, may determine xylem responses to future climate change and thus add to the heterogeneity of Arctic shrub dynamics, though more long-term species- and site- specific studies are needed.

Improved description of terrestrial habitat types by including microbial communities as indicators.

Soils host diverse communities of microorganisms essential for ecosystem functions and soil health. Despite their importance, microorganisms are not covered by legislation protecting biodiversity or habitats, such as the Habitats Directive. Advances in molecular methods have caused breakthroughs in microbial community analysis, and recent studies have shown that parts of the communities are habitat-specific. If distinct microbial communities are present in the habitat types defined in the Habitats Directive, the Directive may be improved by including these communities. Thus, monitoring and reporting of biodiversity and conservation status of habitat types could be based not only on plant communities but also on microbial communities. In the present study, bacterial and plant communities were examined in six habitat types defined in the Habitats Directive by conducting botanical surveys and collecting soil samples for amplicon sequencing across 19 sites in Denmark. Furthermore, selected physico-chemical properties expected to differ between habitat types and explain variations in community composition of bacteria and vegetation were analysed (pH, electrical conductivity (EC), soil texture, soil water repellency, soil organic carbon content (OC), inorganic nitrogen, and in-situ water content (SWC)). Despite some variations within the same habitat type and overlaps between habitat types, habitat-specific communities were observed for both bacterial and plant communities, but no correlation was observed between the alpha diversity of vegetation and bacteria. PERMANOVA analysis was used to evaluate the variables best able to explain variation in the community composition of vegetation and bacteria. Habitat type alone could explain 46% and 47% of the variation in bacterial and plant communities, respectively. Excluding habitat type as a variable, the best model (pH, SWC, OC, fine silt, and Shannon's diversity index for vegetation) could explain 37% of the variation for bacteria. For vegetation, the best model (pH, EC, ammonium content and Shannon's diversity index for bacteria) could explain 25% of the variation. Based on these results, bacterial communities could be included in the Habitats Directive to improve the monitoring, as microorganisms are more sensitive to changes in the environment compared to vegetation, which the current monitoring is based on.

Alteration of coastal productivity and artisanal fisheries interact to affect a marine food web.

Top-down and bottom-up forces determine ecosystem function and dynamics. Fisheries as a top-down force can shorten and destabilize food webs, while effects driven by climate change can alter the bottom-up forces of primary productivity. We assessed the response of a highly-resolved intertidal food web to these two global change drivers, using network analysis and bioenergetic modelling. We quantified the relative importance of artisanal fisheries as another predator species, and evaluated the independent and combined effects of fisheries and changes in plankton productivity on food web dynamics. The food web was robust to the loss of all harvested species but sensitive to the decline in plankton productivity. Interestingly, fisheries dampened the negative impacts of decreasing plankton productivity on non-harvested species by reducing the predation pressure of harvested consumers on non-harvested resources, and reducing the interspecific competition between harvested and non-harvested basal species. In contrast, the decline in plankton productivity increased the sensitivity of harvested species to fishing by reducing the total productivity of the food web. Our results show that strategies for new scenarios caused by climate change are needed to protect marine ecosystems and the wellbeing of local communities dependent on their resources.

Reconstructing ecological networks with noisy dynamics.

Ecosystems functioning is based on an intricate web of interactions among living entities. Most of these interactions are difficult to observe, especially when the diversity of interacting entities is large and they are of small size and abundance. To sidestep this limitation, it has become common to infer the network structure of ecosystems from time series of species abundance, but it is not clear how well can networks be reconstructed, especially in the presence of stochasticity that propagates through ecological networks. We evaluate the effects of intrinsic noise and network topology on the performance of different methods of inferring network structure from time-series data. Analysis of seven different four-species motifs using a stochastic model demonstrates that star-shaped motifs are differentially detected by these methods while rings are differentially constructed. The ability to reconstruct the network is unaffected by the magnitude of stochasticity in the population dynamics. Instead, interaction between the stochastic and deterministic parts of the system determines the path that the whole system takes to equilibrium and shapes the species covariance. We highlight the effects of long transients on the path to equilibrium and suggest a path forward for developing more ecologically sound statistical techniques.

Bats in a changing landscape: Linking occupancy and traits of a diverse montane bat community to fire regime.

Wildfires are increasing in incidence and severity across coniferous forests of the western United States, leading to changes in forest structure and wildlife habitats. Knowledge of how species respond to fire-driven habitat changes in these landscapes is limited and generally disconnected from our understanding of adaptations that underpin responses to fire.We aimed to investigate drivers of occupancy of a diverse bat community in a fire-altered landscape, while identifying functional traits that underpinned these relationships.We recorded bats acoustically at 83 sites (n = 249 recording nights) across the Plumas National Forest in the northern Sierra Nevada over 3 summers (2015-2017). We investigated relationships between fire regime, physiographic variables, forest structure and probability of bat occupancy for nine frequently detected species. We used fourth-corner regression and RLQ analysis to identify ecomorphological traits driving species-environment relationships across 17 bat species. Traits included body mass; call frequency, bandwidth, and duration; and foraging strategy based on vegetation structure (open, edge, or clutter).Relationships between bat traits and fire regime were underpinned by adaptations to diverse forest structure. Bats with traits adapting them to foraging in open habitats, including emitting longer duration and narrow bandwidth calls, were associated with higher severity and more frequent fires, whereas bats with traits consistent with clutter tolerance were negatively associated with fire frequency and burn severity. Relationships between edge-adapted bat species and fire were variable and may be influenced by prey preference or habitat configuration at a landscape scale.Predicted increases in fire frequency and severity in western US coniferous forests are likely to shift dominance in the bat community to open-adapted species and those able to exploit postfire resource pulses (aquatic insects, beetles, and snags). Managing for pyrodiversity within the western United States is likely important for maintaining bat community diversity, as well as diversity of other biotic communities.