The coastal heathlands of North-west Europe are valuable cultural landscapes, created and maintained over millennia by a land-use regime involving burning and grazing. These heathlands are now critically threatened throughout their range by land-use change and, increasingly, climatic changes. The climatic change impacts are complex, as the coastal heathland regions are experiencing increased temperature and precipitation, but also increased frequency and severity of extreme events, such as drought. Previous studies reveal that established heathland vegetation, including Calluna, are vulnerable to drought, but also that these vulnerabilities vary throughout the range, and with successional stage after fire. Recruitment from seed is an important regeneration strategy for Calluna heathland vegetation after burning, and our study is the first to assess how the seed germination and early seedling growth of Calluna respond to drought. We will do this in a lab germination experiment, where we will expose Calluna seeds to five different drought treatments, from -0.25 MPa to -1.7 MPa, and measure germination, and record germination percentage, germination rates, and seedling growth, below-ground allocation, and functional traits (Specific Leaf Area, Specific Root Length). To allow assessment of variation in drought responses due to geographic origin, successional stage, and the maternal plants’ drought exposure, we will conduct this experiment on seeds from 540 Calluna plants sampled from across three drought treatments (control, 50%, and 90% coverage), in three successional stages after fire (pioneer, building, mature), in two regions (60N, 65N), using a factorial design.

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series even more exciting results especially about range shifts can be expected. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented.

Estimating the distribution of phenotypes in populations and communities is central to many questions in ecology and evolutionary biology. These distributions can be characterized by their moments: the mean, variance, skewness, and kurtosis. Typically, these moments are calculated using a community-weighted approach (e.g. community-weighted mean) which ignores intraspecific variation. As an alternative, bootstrapping approaches can incorporate intraspecific variation to improve estimates, and also quantify uncertainty in the estimate. Here, we compare the performance of different approaches for estimating the moments of trait distributions across a variety of sampling scenarios, taxa, and datasets. We introduce the traitstrap R package to facilitate inferences of trait distributions via bootstrapping. Our results suggest that randomly sampling ~9 individuals per sampling unit and species, focusing on covering all species in the community, and analysing the data using nonparametric bootstrapping generally enables reliable inference on trait distributions, including the central moments, of communities.

The COVID-19 crisis has forced researchers in Ecology to change the way we work almost overnight. Nonetheless, the pandemic has provided us with several novel components for a new way of conducting international Science. In this perspective piece, we summarize eight central insights that are helping us, as early career researchers, navigate the uncertainties, fears and challenges of advancing Science during the COVID-19 pandemic. We highlight how innovative, collaborative and often Open Science-driven developments that have arisen from this crisis can form a blueprint for a community reinvention in academia. Our insights include personal approaches to managing our new reality, maintaining capacity to focus and resilience in our projects, and a variety of tools that facilitate remote collaboration. We also highlight how, at a community level, we can take advantage of online communication platforms for gaining accessibility to conferences and meetings, and for maintaining research networks and community engagement while promoting a more diverse and inclusive community. Overall, we are confident that these practices can support a more inclusive and kinder scientific culture for the longer term.