Liv Guri Velle

Increased climate variability is expected to intensify short-term drought events. Plants have evolved stress tolerance strategies involving trade-offs in resource conservation, mycorrhizal collaboration and plant size, yet how these strategies promote drought resistance across different herbaceous plant groups remains unknown. Leveraging 63 globally distributed grassland and shrubland sites from the International Drought Experiment, we identified plant traits linked to drought resistance in 661 populations of 421 species after 1 year of extreme drought. We assessed how traits, site precipitation and drought severity affected cover change across growth forms and lifespans, and how trait–environment interactions influenced drought resistance. Across all species, leaf N (an acquisitive trait) was associated with drought resistance, whereas in forbs, drought resistance was also associated with a conservative root trait and plant size. In addition, interactions among traits mediated drought resistance; root traits predicted performance only in concert with other traits. Environmental variables influenced trait effects on drought resistance, notably for annuals in wetter sites, suggesting that drought-escape strategies in annuals may be advantageous only under mild stress. Our study highlights variability in traits that predict drought resistance across herbaceous plant groups, emphasizing the importance of species context, environmental stress and the selection of traits in research and management.

A number of modelling frameworks exist to estimate resilience from ecological datasets. A subset of these frameworks seeks to estimate the whole ‘stability landscape', which can be used to calculate resilience and identify stable states and tipping points. These methods provide opportunities for insights into possible causes and consequences of variation in ecosystem resilience and dynamics. However, because such models can be complex to implement, there has so far been a substantial barrier to their application in ecological research. Here, we present the ‘mixglm' package for R software, which parametrizes stability landscapes using a mixture model approach. It provides tools for the calculation of resilience, identification of stable states and tipping points, as well as visualization functions. Flexible model specification allows the mean, precision, and probability of each mixture component to be linked to multiple predictors, such as environmental covariates. ‘mixglm' is based on Bayesian inference via NIMBLE and supports normal, beta, gamma, and negative binomial distributed response variables. We illustrate the use of ‘mixglm' with a published case of tree cover in South America, which reports a stability landscape with distinct stable states. Using ‘mixglm', we replicated the identification of these states. Moreover, we quantified the uncertainty of our estimates, and computed resilience estimates of South America's forests. We also conducted a power analysis to provide guidance regarding required sample sizes. ‘mixglm' can be readily used to describe stability landscapes and identify stable states in most spatial datasets, and it is accompanied by tools for the calculation of resilience estimates.

Aims A number of modelling frameworks exist to aid in the identification and exploration of stable states and the assessment of resilience from ecological datasets. However, because such models are complex to implement there is a substantial barrier for the application in ecological research. Here we develop a flexible model of ecological resilience based on Bayesian approximation of the “stability landscape”. We illustrate its usage on a tropical area where variation in tree cover has been previously interpreted as alternative stable states. Methods The stability landscape, from which stable states and resilience parameters are computed, is modelled using a mixture of multiple distributions, each representing a regression between the system state variable and the environmental covariates. Our “mixglm” model allows the mean, precision, and probability parameters of these distributions in the landscape to be dependent on multiple external covariates. “Mixglm” is implemented as a function in R package with the same name, internally using Bayesian inference via NIMBLE. We also conducted a power analysis to provide guidance regarding required sample size. Results We illustrate the use of the “mixglm” on a published case of tree cover in South America which reports a stability landscape with three distinct stable states. Using “mixglm”, we were able to replicate the identification of these states. Moreover, we quantified uncertainty of our estimates, and computed resilience of South America’s forests. Conclusions “Mixglm” can be readily used for description of stability landscapes and identification of stable states in most spatial datasets of system state variables, and it is accompanied by tools for calculation of resilience metrics. It can also be further expanded using regression framework to account for more complex data structures such as spatio-temporal data.

Climate change is increasing the frequency and severity of short-term (~1 y) drought events—the most common duration of drought—globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function—aboveground net primary production (ANPP)—was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.

Questions: During the winter of 2014, an intense drought combined with sub‐zero temperatures resulted in a massive Calluna dieback in Norwegian heathlands. We studied the initial vegetation recovery under two management approaches: natural recovery and prescribed burning. We hypothesized that natural recovery will be slower in more drought‐affected sites, whereas burning will facilitate post‐fire recovery in all sites by effectively removing dead and damaged heath. Both natural recovery and post‐fire succession will be slower in the north.Location: Calluna heath in seven sites spanning an approx. 600‐km latitudinal gradient along the coast of Norway (60.22–65.69° N).Methods: After a natural drought, 10 permanent plots per site were either burnt or left for natural recovery. Vegetation data were recorded annually in 2016 (pre‐fire) and 2017–2019 (post‐fire) reflecting a factorial repeated‐measures design (n = 280). The data were analyzed using mixed‐effects models.Results: Two years after the drought, we observed high but variable Calluna damage and mortality. Over the four years of study, damaged Calluna recovered, whereas dead Calluna showed little recovery. Both the extent of the damage and mortality, as well as the rate of natural recovery, are only weakly related to site climate or environmental factors. Fire efficiently removed dead and damaged Calluna and facilitated post‐fire successional dynamics and recovery in a majority of sites.Conclusions: Extreme winter drought resulted in substantial and often persistent damage and dieback on Calluna along the latitudinal gradient. In sites with high mortality, prescribed burning removed the dead biomass and, in some cases, facilitated vegetation recovery. Traditional heathland management, which uses burning to facilitate all‐year grazing by Old Norse sheep in Atlantic coastal heathlands, can be an efficient tool to mitigate dieback events and more generally to increase resistance to and resilience after extreme drought events in the future.

The coastal heathlands of Northwest Europe are highly valued cultural landscapes, that are critically endangered due to land use and climatic changes, such as increased frequency and severity of drought events. Our study is the first to assess how the germination and early seedling growth of Calluna vulgaris respond to drought. In a factorial design field experiment, we exposed maternal plants to three in‐situ drought treatments (control, 60%, 90% roof coverage), across three successional stages after fire (pioneer, building, mature), and two regions (60°N, 65°N). Seeds from 540 plants within the experiment were, weighed, and exposed to five water potentials, ranging from −0.25 to −1.7 MPa, in a growth chamber experiment. We recorded germination (percentage, rate), seedling growth (above‐ vs. belowground allocation), and seedling functional traits (specific leaf area [SLA], specific root length [SRL]). Overall variation in germination between regions, successional stages, and maternal drought treatments was largely mediated by variation in seed mass. Plants from the northernmost region had higher seed mass and germination percentages. This is indicative of higher investment in seeds, likely linked to the populations' absence of vegetative root sprouting. Seeds from the mature successional stage germinated to lower final percentages than those from earlier successional stages, especially when the maternal plants had been exposed to drought (60% and 90% roof coverage). Exposure to reduced water availability decreased germination percentage and increased the time to 50% germination. Seedlings fully developed in the range −0.25 to −0.7 MPa, with increased root:shoot and lower SRL during reduced water availability, suggesting a resource‐conservative response to drought during the early stages of development. Our results thus suggest a sensitivity to drought during the germination and seedling life‐history stages that may reduce Calluna's ability to re‐establish from seeds as the incidence and severity of droughts are projected to increase under future climates.

We conducted a national survey on a high-quality internet panel to study landscape preferences in Norway, using photos as stimuli. We examined preference heterogeneity with respect to socio-demographic characteristics and latent topics brought up by the respondents, using ordinal logistic regression and structural topic modelling (STM), a machine learning-based analysis. We found that pasture landscapes are the most favoured (55%), while densely planted spruce forests are the least favoured (8%). The contrast was particularly strong between eastern and western Norway, between men and women, and between young and old. STM revealed that the choices were mainly driven by the preference for landscape openness, especially by women. Other important drivers were concerns regarding reforestation of former farmlands, aesthetic properties, forest management, biodiversity issues, and cultural values. Our results suggest that landscape policies may clash with socio-cultural preferences, and failure to account for these may undermine the success of a policy.

In recent years, severe and deadly wildland-urban interface (WUI) fires have resulted in an increased focus on this particular risk to humans and property, especially in Canada, USA, Australia, and countries in the Mediterranean area. Also, in areas not previously accustomed to wildfires, such as boreal areas in Sweden, Norway, and in the Arctic, WUI fires have recently resulted in increasing concern. January 2014, the most severe wooden town fire in Norway since 1923 raged through Lærdalsøyri. Ten days later, a wildfire raged through the scattered populated community of Flatanger and destroyed even more structures. These fires came as a surprise to the fire brigades and the public. We describe and analyze a proposed way forward for exploring if and how this increasing fire incidence can be linked to concomitant changes in climate, land-use, and habitat management; and then aim at developing new dynamic adaptive fire risk assessment and management tools. We use coastal Norway as an example and focus on temporal changes in fire risk in wooden structure settlements and in the Norwegian Calluna vulgaris L. dominated WUI. In this interface, the fire risk is now increasing due to a combination of land-use changes, resulting in large areas of early successional vegetation with an accumulation of biomass, and the interactive effects of climatic changes resulting in increased drought risk. We propose a novel bow-tie framework to explore fire risk and preventive measures at various timescales (years, months, weeks, hours) as a conceptual model for exploring risk contributing factors and possibilities for risk management. Ignition is the top event of the bow-tie which has the potential development towards a fire disaster as a worst case outcome. The bow-tie framework includes factors such as changes in the built environment and natural habitat fuel moisture content due to the weather conditions, WUI fuel accumulation, possibly improved ecosystem management, contribution by civic prescribed burner groups, relevant fire risk modeling, and risk communication to the fire brigades and the public. We propose an interdisciplinary research agenda for developing this framework and improving the current risk understanding, risk communication, and risk management. This research agenda will represent important contributions in paving the road for fire disaster prevention in Norway, and may provide a model for other systems and regions.