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1. The term “applied ecology of fear” was recently introduced to describe the growing research field that applies the theory of the ecology of fear to manage wildlife behaviour. The management goal is to drive targeted species spatially and temporally away from areas of human interest by inducing cues from real or simulated predators to reduce human-wildlife conflict.

2. We aimed to quantify, through a meta-analysis, if prey anti-predator response would vary among field trials versus pen-based studies, predator cue types, predator hunting style and prey feeding type, and be stronger in response to larger predators relative to the prey's size. We also explored what studies found in terms of wildlife habituation to cues.

3. We used species belonging to the Cervidae family as a case study since deer are among the group of species with the highest degree of human-wildlife conflict. We retrieved 114 studies from online databases and collected information from 39 of those studies that fitted our research scope.

4. We found that acoustic cues more frequently led to an anti-predator response in deer than olfactory or visual cues. Neither predator hunting strategy nor deer feeding strategy or type of study (free-ranging or pen-based animals) influenced the extent to which deer responded to cues. Deer more frequently responded to cues that belonged to a larger predator relative to their size. Habituation was reported in less than one-third of the studies, with a study period ranging from 1 to 90 days, and occurred as soon as 7 days after the start of the study on average.

5. Our meta-analysis suggested that acoustic cues hold most potential as a tool to manage deer behaviour. These findings support the development of applied ecology of fear tools that introduce predator cues to reduce human-wildlife conflicts. Major knowledge gaps remain that limit the effective use of such tools in wildlife management and future research should focus on improving our understanding of habituation to cues, on comparing the effectiveness of different types of cues, on simultaneously using a combination of cue types, and on testing cues at spatial–temporal scales of actual land-uses.

Human-mediated dispersal of non-native earthworms can cause substantial changes to the functioning and composition of ecosystems previously earthworm-free. Some of these earthworm species have the potential to “geoengineer” soils and increase plant nitrogen (N) uptake. Yet the possible consequences of increased plant N concentrations on rodent grazing remains poorly understood. In this study, we present findings from a common garden experiment with two tundra communities, meadow (forb dominated) and heath (shrub dominated), half of them subjected to 4 years of earthworm presence (Lumbricus spp. and Aporrectodea spp.). Within four summers, our earthworm treatment changed plant community composition by increasing graminoid density by, on average, 94% in the heath vegetation and by 49% in the meadow. Rodent winter grazing was more intense on plants growing in soils with earthworms, an effect that coincided with higher N concentrations in plants, indicating a higher palatability. Even though earthworms reduced soil moisture, plant community productivity, as indicated by vegetation greenness (normalized difference vegetation index), was not negatively impacted. We conclude that earthworm-induced changes in plant composition and trophic interactions may fundamentally alter the functioning of tundra ecosystems.

Arctic and alpine tundra ecosystems are large reservoirs of organic carbon^1,2. Climate warming may stimulate ecosystem respiration and release carbon into the atmosphere^3,4. The magnitude and persistency of this stimulation and the environmental mechanisms that drive its variation remain uncertain^5–7. This hampers the accuracy of global land carbon–climate feedback projections^7,8. Here we synthesize 136 datasets from 56 open-top chamber in situ warming experiments located at 28 arctic and alpine tundra sites which have been running for less than 1 year up to 25 years. We show that a mean rise of 1.4 °C [confidence interval (CI) 0.9–2.0 °C] in air and 0.4 °C [CI 0.2–0.7 °C] in soil temperature results in an increase in growing season ecosystem respiration by 30% [CI 22–38%] (n = 136). Our findings indicate that the stimulation of ecosystem respiration was due to increases in both plant-related and microbial respiration (n = 9) and continued for at least 25 years (n = 136). The magnitude of the warming effects on respiration was driven by variation in warming-induced changes in local soil conditions, that is, changes in total nitrogen concentration and pH and by context-dependent spatial variation in these conditions, in particular total nitrogen concentration and the carbon:nitrogen ratio. Tundra sites with stronger nitrogen limitations and sites in which warming had stimulated plant and microbial nutrient turnover seemed particularly sensitive in their respiration response to warming. The results highlight the importance of local soil conditions and warming-induced changes therein for future climatic impacts on respiration.

The on-going climate warming is promoting shrub abundance in high latitudes, but the effect of this phenomenon on ecosystem functioning is expected to depend on whether deciduous or evergreen species increase in response to warming. To explore effects of long-term warming on shrubs and further on ecosystem functioning, we analysed vegetation and ecosystem CO₂ exchange after 20 years of warming in the forest–tundra ecotone in subarctic Sweden. A previous study conducted 9 years earlier had found increased evergreen Empetrum nigrum ssp. hermaphroditum in the forest and increased deciduous Betula nana in the tundra. Following current understanding, we expected continued increase in shrub abundance that would be stronger in tundra than in forest. We expected warming to increase ecosystem respiration (R_e) and gross primary productivity (GPP), with a greater increase in R_e in tundra due to increased deciduous shrub abundance, leading to a less negative net ecosystem exchange and reduced ecosystem C sink strength. As predicted, vascular plant abundances were higher in the warmed plots with a stronger response in tundra than in forest. However, whereas B. nana had increased in abundance since the last survey, E. hermaphroditum abundance had declined due to several moth and rodent outbreaks during the past decade. In contrast to predictions, R_e was significantly lower in the warmed plots irrespective of habitat, and GPP increased marginally only in the forest. The lower R_e and a higher GPP under warming in the forest together led to increased net C sink. R_e was negatively associated with the total vascular plant abundance. Our results highlight the importance of disturbance regimes for vegetation responses to warming. Climate warming may promote species with both a high capacity to grow under warmer conditions and a resilience towards herbivore outbreaks. Negative correlation between R_e and total vascular plant abundance further indicate that the indirect impacts of increased plants on soil microclimate may become increasingly important for ecosystem CO₂ exchange in the long run, which adds to the different mechanisms that link warming and CO₂ fluxes in northern ecosystems. Read the free Plain Language Summary for this article on the Journal blog.

• Seasonal dynamics of root growth play an important role in large-scale ecosystem processes; they are largely governed by growth regulatory compounds and influenced by environmental conditions. Yet, our knowledge about physiological drivers of root growth is mostly limited to laboratory-based studies on model plant species.
• We sampled root tips of Eriophorum vaginatum and analyzed their auxin concentrations and meristem lengths biweekly over a growing season in situ in a subarctic peatland, both in surface soil and at the permafrost thawfront.
• Auxin concentrations were almost five times higher in surface than in thawfront soils and increased over the season, especially at the thawfront. Surprisingly, meristem length showed an opposite pattern and was almost double in thawfront compared with surface soils. Meristem length increased from peak to late season in the surface soils but decreased at the thawfront.
• Our study of in situ seasonal dynamics in root physiological parameters illustrates the potential for physiological methods to be applied in ecological studies and emphasizes the importance of in situ measurements. The strong effect of root location and the unexpected opposite patterns of meristem length and auxin concentrations likely show that auxin actively governs root growth to ensure a high potential for nutrient uptake at the thawfront.

Herbivores drive shifts in plant species composition by interacting with vegetation through defoliation, trampling and nutrient addition: urine and faeces. As herbivore effects on vegetation accumulate over time, they might spillover to other trophic levels, but how and when this happens is poorly understood. Since it is methodologically demanding to measure biodiversity across spatial gradients, an alternative approach is to assess it through biodiversity indices of vascular plants. We employed the Index of biodiversity relevance developed for Swedish flora which provides an estimated number of organisms associated with a plant species, allowing the quantification of trophic community size. Values from this index were coupled with vegetation data from a network of 96 fenced and paired grazed plots across Fennoscandia. We analysed the role herbivory has on plant richness and diversity, and on the number of organisms that interact with the vegetation according to the index values. We also explored how herbivores influence the competitive effects of tall shrubs on other plants since the dominance of a vegetation type links directly to biodiversity. Plant diversity had no clear response to grazing. Overall vegetation and the vegetation subgroups herbs and non-fruit shrubs had higher biodiversity index values in fenced plots, indicating a higher number of plant–host interactions. Herb cover was negatively related to shrubs in both treatments but with a faster decline in the absence of herbivores. This study highlights the importance of maintaining herbivore populations in the Arctic to conserve the vegetation structure and biodiversity of the tundra. This method of coupling biodiversity indexes with vegetation data provides complementary information to the plant diversity, especially when methodological or time constraints prevent complete field inventories.

Terrestrial animals are key elements in the cycling of elements in the Arctic where nutrient availability is low. Waste production by herbivores, in particular urine deposition, has a crucial role for nitrogen (N) recycling, still, it remains largely unexplored. Also, experimental evidence is biased toward short-term studies and Arctic regions under high herbivore pressure. In this study, we aimed to examine the fate of N derived from urine in a nutrient poor tundra heath in West Greenland, with historical low level of herbivory. We performed a pulse labelling with ¹⁵N-urea over the plant canopy and explored ecosystem N partition and retention in the short-term (2 weeks and 1 year) and longer-term (5 years). We found that all vascular plants, irrespective of their traits, could rapidly take up N-urea, but mosses and lichens were even more efficient. Total ¹⁵N enrichment was severely reduced for all plants 5 years after tracer addition, with the exception of cryptogams, indicating that non-vascular plants constituted a long-term sink of ¹⁵N-urea. The ¹⁵N recovery was also high in the litter suggesting high N immobilization in this layer, potentially delaying the nutrients from urine entering the soil compartment. Long-term ¹⁵N recovery in soil microbial biomass was minimal, but as much as 30% of added ¹⁵N remained in the non-microbial fraction after 5 years. Our results demonstrate that tundra plants that have evolved under low herbivory pressure are well adapted to quickly take advantage of labile urea, with urine having only a transient effect on soil nutrient availability.

Reports of fading vole and lemming population cycles and persisting low populations in some parts of the Arctic have raised concerns about the spread of these fundamental changes to tundra food web dynamics. By compiling 24 unique time series of lemming population fluctuations across the circumpolar region, we show that virtually all populations displayed alternating periods of cyclic/non-cyclic fluctuations over the past four decades. Cyclic patterns were detected 55% of the time (n = 649 years pooled across sites) with a median periodicity of 3.7 years, and non-cyclic periods were not more frequent in recent years. Overall, there was an indication for a negative effect of warm spells occurring during the snow onset period of the preceding year on lemming abundance. However, winter duration or early winter climatic conditions did not differ on average between cyclic and non-cyclic periods. Analysis of the time series shows that there is presently no Arctic-wide collapse of lemming cycles, even though cycles have been sporadic at most sites during the last decades. Although non-stationary dynamics appears a common feature of lemming populations also in the past, continued warming in early winter may decrease the frequency of periodic irruptions with negative consequences for tundra ecosystems.

Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we present The Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m−2) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic.

High-resolution unoccupied aerial vehicle (UAVs) data have alleviated the mismatch between the scale of ecological processes and the scale of remotely sensed data, while machine learning and deep learning methods allow new avenues for quantification in ecology. Ant nests play key roles in ecosystem functioning, yet their distribution and effects on entire landscapes remain poorly understood, in part because they and their mounds are too small for satellite remote sensing. This research maps the distribution and impact of ant mounds in a 20 ha treeline ecotone. We evaluate the detectability from UAV imagery using a deep learning model for object detection and different combinations of RGB, thermal and multispectral sensor data. We were able to detect ant mounds in all imagery using manual detection and deep learning. However, the highest precision rates were achieved by deep learning using RGB data which has the highest spatial resolution (1.9 cm) at comparable UAV flight height. While multispectral data were outperformed for detection, it allows for novel insights into the ecology of ants and their spatial impact on vegetation productivity using the normalized difference vegetation index. Scaling up, this suggests that ant mounds quantifiably impact vegetation productivity for up to 4% of our study area and up to 8% of the Betula nana vegetation communities, the vegetation type with the highest abundance of ant mounds. Therefore, they could have an overlooked role in nutrient-limited tundra vegetation, and on the shrubification of this habitat. Further, we show the powerful combination UAV multi-sensor data and deep learning for efficient ecological tracking and monitoring of mound-building ants and their spatial impact.