Vegetation structure from LiDAR explains the local richness of birds across Denmark.

Classic ecological research into the determinants of biodiversity patterns emphasised the important role of three-dimensional (3D) vegetation heterogeneity. Yet, measuring vegetation structure across large areas has historically been difficult. A growing focus on large-scale research questions has caused local vegetation heterogeneity to be overlooked compared with more readily accessible habitat metrics from, for example, land cover maps. Using newly available 3D vegetation data, we investigated the relative importance of habitat and vegetation heterogeneity for explaining patterns of bird species richness and composition across Denmark (42,394 km2 ). We used standardised, repeated point counts of birds conducted by volunteers across Denmark alongside metrics of habitat availability from land-cover maps and vegetation structure from rasterised LiDAR data (10 m resolution). We used random forest models to relate species richness to environmental features and considered trait-specific responses by grouping species by nesting behaviour, habitat preference and primary lifestyle. Finally, we evaluated the role of habitat and vegetation heterogeneity metrics in explaining local bird assemblage composition. Overall, vegetation structure was equally as important as habitat availability for explaining bird richness patterns. However, we did not find a consistent positive relationship between species richness and habitat or vegetation heterogeneity; instead, functional groups displayed individual responses to habitat features. Meanwhile, habitat availability had the strongest correlation with the patterns of bird assemblage composition. Our results show how LiDAR and land cover data complement one another to provide insights into different facets of biodiversity patterns and demonstrate the potential of combining remote sensing and structured citizen science programmes for biodiversity research. With the growing coverage of LiDAR surveys, we are witnessing a revolution of highly detailed 3D data that will allow us to integrate vegetation heterogeneity into studies at large spatial extents and advance our understanding of species' physical niches.

Cross-scale regulation of seasonal microclimate by vegetation and snow in the Arctic tundra.

Climate warming is inducing widespread vegetation changes in Arctic tundra ecosystems, with the potential to alter carbon and nutrient dynamics between vegetation and soils. Yet, we lack a detailed understanding of how variation in vegetation and topography influences fine-scale temperatures ("microclimate") that mediate these dynamics, and at what resolution vegetation needs to be sampled to capture these effects. We monitored microclimate at 90 plots across a tundra landscape in western Greenland. Our stratified random study design covered gradients of topography and vegetation, while nested plots (0.8-100 m2 ) enabled comparison across different sampling resolutions. We used Bayesian mixed-effect models to quantify the direct influence of plot-level topography, moisture and vegetation on soil, near-surface and canopy-level temperatures (-6, 2, and 15 cm). During the growing season, colder soils were predicted by shrub cover (-0.24°C per 10% increase), bryophyte cover (-0.35°C per 10% increase), and vegetation height (-0.17°C per 1 cm increase). The same three factors also predicted the magnitude of differences between soil and above-ground temperatures, indicating warmer soils at low cover/height, but colder soils under closed/taller canopies. These findings were consistent across plot sizes, suggesting that spatial predictions of microclimate may be possible at the operational scales of satellite products. During winter, snow cover (+0.75°C per 10 snow-covered days) was the key predictor of soil microclimate. Topography and moisture explained little variation in the measured temperatures. Our results not only underline the close connection of vegetation and snow with microclimate in the Arctic tundra but also point to the need for more studies disentangling their complex interplay across tundra environments and seasons. Future shifts in vegetation cover and height will likely mediate the impact of atmospheric warming on the tundra soil environment, with potential implications for below-ground organisms and ecosystem functioning.

Improving ecological insights from dendroecological studies of Arctic shrub dynamics: Research gaps and potential solutions.

Rapid climate change has been driving changes in Arctic vegetation in recent decades, with increased shrub dominance in many tundra ecosystems. Dendroecological observations of tundra shrubs can provide insight into current and past growth and recruitment patterns, both key components for understanding and predicting ongoing and future Arctic shrub dynamics. However, generalizing these dynamics is challenging as they are highly scale-dependent and vary among sites, species, and individuals. Here, we provide a perspective on how some of these challenges can be overcome. Based on a targeted literature search of dendrochronological studies from 2005 to 2022, we highlight five research gaps that currently limit dendro-based studies from revealing cross-scale ecological insight into shrub dynamics across the Arctic biome. We further discuss the related research priorities, suggesting that future studies could consider: 1) increasing focus on intra- and interspecific variation, 2) including demographic responses other than radial growth, 3) incorporating drivers, in addition to warming, at different spatial and temporal scales, 4) implementing systematic and unbiased sampling approaches, and 5) investigating the cellular mechanisms behind the observed responses. Focusing on these aspects in dendroecological studies could improve the value of the field for addressing cross-scale and plant community-framed ecological questions. We outline how this could be facilitated through the integration of community-based dendroecology and dendroanatomy with remote sensing approaches. Integrating new technologies and a more multidisciplinary approach in dendroecological research could provide key opportunities to close important knowledge gaps in our understanding of scale-dependencies, as well as intra- and inter-specific variation, in vegetation community dynamics across the Arctic tundra.

Experimental warming differentially affects vegetative and reproductive phenology of tundra plants.

Rapid climate warming is altering Arctic and alpine tundra ecosystem structure and function, including shifts in plant phenology. While the advancement of green up and flowering are well-documented, it remains unclear whether all phenophases, particularly those later in the season, will shift in unison or respond divergently to warming. Here, we present the largest synthesis to our knowledge of experimental warming effects on tundra plant phenology from the International Tundra Experiment. We examine the effect of warming on a suite of season-wide plant phenophases. Results challenge the expectation that all phenophases will advance in unison to warming. Instead, we find that experimental warming caused: (1) larger phenological shifts in reproductive versus vegetative phenophases and (2) advanced reproductive phenophases and green up but delayed leaf senescence which translated to a lengthening of the growing season by approximately 3%. Patterns were consistent across sites, plant species and over time. The advancement of reproductive seasons and lengthening of growing seasons may have significant consequences for trophic interactions and ecosystem function across the tundra.

Strengthening the evidence base for temperature-mediated phenological asynchrony and its impacts.

Climate warming has caused the seasonal timing of many components of ecological food chains to advance. In the context of trophic interactions, the match-mismatch hypothesis postulates that differential shifts can lead to phenological asynchrony with negative impacts for consumers. However, at present there has been no consistent analysis of the links between temperature change, phenological asynchrony and individual-to-population-level impacts across taxa, trophic levels and biomes at a global scale. Here, we propose five criteria that all need to be met to demonstrate that temperature-mediated trophic asynchrony poses a growing risk to consumers. We conduct a literature review of 109 papers studying 129 taxa, and find that all five criteria are assessed for only two taxa, with the majority of taxa only having one or two criteria assessed. Crucially, nearly every study was conducted in Europe or North America, and most studies were on terrestrial secondary consumers. We thus lack a robust evidence base from which to draw general conclusions about the risk that climate-mediated trophic asynchrony may pose to populations worldwide.

Local snow melt and temperature-but not regional sea ice-explain variation in spring phenology in coastal Arctic tundra.

The Arctic is undergoing dramatic environmental change with rapidly rising surface temperatures, accelerating sea ice decline and changing snow regimes, all of which influence tundra plant phenology. Despite these changes, no globally consistent direction of trends in spring phenology has been reported across the Arctic. While spring has advanced at some sites, spring has delayed or not changed at other sites, highlighting substantial unexplained variation. Here, we test the relative importance of local temperatures, local snow melt date and regional spring drop in sea ice extent as controls of variation in spring phenology across different sites and species. Trends in long-term time series of spring leaf-out and flowering (average span: 18 years) were highly variable for the 14 tundra species monitored at our four study sites on the Arctic coasts of Alaska, Canada and Greenland, ranging from advances of 10.06 days per decade to delays of 1.67 days per decade. Spring temperatures and the day of spring drop in sea ice extent advanced at all sites (average 1°C per decade and 21 days per decade, respectively), but only those sites with advances in snow melt (average 5 days advance per decade) also had advancing phenology. Variation in spring plant phenology was best explained by snow melt date (mean effect: 0.45 days advance in phenology per day advance snow melt) and, to a lesser extent, by mean spring temperature (mean effect: 2.39 days advance in phenology per °C). In contrast to previous studies examining sea ice and phenology at different spatial scales, regional spring drop in sea ice extent did not predict spring phenology for any species or site in our analysis. Our findings highlight that tundra vegetation responses to global change are more complex than a direct response to warming and emphasize the importance of snow melt as a local driver of tundra spring phenology.