Recreation reduces tick density through fine-scale risk effects on deer space-use

Altered interactions between pathogens, their hosts and vectors have potential consequences for human disease risk. Notably, tick-borne pathogens, many of which are associated with growing deer abundance, show global increasing prevalence and pose increasing challenges for disease prevention. Human activities can largely affect the patterns of deer space-use and can therefore be potential management tools to alleviate human-wildlife conflicts. Here, we tested how deer space-use patterns are influenced by human recreational activities, and how this in turn affects the spatial distribution of the sheep tick (Ixodes ricinus), a relevant disease vector of zoonoses such as Lyme borrelioses. We compared deer dropping and questing tick density on transects near (20 m) and further away from (100 m) forest trails that were either frequently used (open for recreation) or infrequently used (closed for recreation, but used by park managers). In contrast to infrequently used trails, deer dropping density was 31% lower near (20 m) than further away from (100 m) frequently used trails. Similarly, ticks were 62% less abundant near (20 m) frequently used trails compared to further away from (100 m) these trails, while this decline in tick numbers was only 14% near infrequently used trails. The avoidance by deer of areas close to human-used trails was thus associated with a similar reduction in questing tick density near these trails. As tick abundance generally correlates to pathogen prevalence, the use of trails for recreation may reduce tick-borne disease risk for humans on and near these trails. Our study reveals an unexplored effect of human activities on ecosystems and how this knowledge could be potentially used to mitigate zoonotic disease risk

Using by‐catch data from wildlife surveys to quantify climatic parameters and the timing of phenology for plants and animals using camera traps

Gaining a better understanding of global environmental change is an important challenge for conserving biodiversity. Shifts in phenology are an important consequence of environmental change. Measuring phenology of different taxa simultaneously at the same spatial and temporal scale is necessary to study the effects of changes in phenology on ecosystems. Camera traps that take both time‐lapse as well as motion‐triggered images are increasingly used to study wildlife populations. The by‐catch data of these networks of camera traps provide a potential alternative for measuring several climatic and phenological variables. Here, we tested this ability of camera traps, and quantified climatic variables as well as the timing of changes in plant and animal phenology. We obtained data from 193 camera‐unit deployments during a year of camera trapping on a peninsula in northern Sweden aimed at studying wildlife. We estimated daily temperature at noon and snow cover using recordings provided by cameras. Estimates of snow cover were accurate, but temperature estimates were higher compared with a local weather station. Furthermore, we were able to identify the timing of leaf emergence and senescence for birches (Betula sp.) and the presence of bilberry berries (Vaccinium myrtillus ), as important food sources for herbivores. These were linked to the timing of the growth of antlers and the presence of new‐born young for three ungulate species as well as the presence of migratory Eurasian cranes (Grus grus ). We also identified the timing of spring and autumn moulting of mountain hares (Lepus timidus ) in relation to snow cover. In this novel study, we show the potential of (by‐catch) data from camera traps to study phenology across a broad range of taxa, suggesting that a global network of camera traps has great potential to simultaneously track wildlife populations and the phenology of interactions between animals and plants

Environmental controls on African herbivore responses to landscapes of fear

Herbivores balance forage acquisition with the need to avoid predation, often leading to tradeoffs between forgoing resources to avoid areas of high predation risk, or tolerating increased risk in exchange for improved forage. The outcome of these decisions is likely to change with varying resource levels, with herbivores altering their response to predation risk across heterogeneous landscapes. Such contrasting responses will alter the strength of non-consumptive predation effects, but are poorly understood in multiple-predator/multiple-prey systems. We combined fine-scaled spatial information on two predator and 11 herbivore species with remotely-sensed measurements of forage quantity and vegetation structure to assess variation in herbivore response to predation risk with changing environmental context, herbivore body size, herbivore foraging strategy (browsers versus grazers), predator type (ambush versus coursing hunters) and group size across a South African savanna landscape. Medium-sized herbivore species were more likely to adjust their response to risk with a changing resource landscape: warthog, nyala and wildebeest tolerated increased long-term predator encounter risk in exchange for abundant (warthog and nyala) or preferred (wildebeest) forage, and nyala selected areas with higher visibility only in landscapes where food was abundant. Impala were more likely to be observed in areas of high visibility where wild dog risk was high. In addition, although buffalo did not avoid areas of high lion encounter risk, large buffalo groups were more frequently observed in open areas where lion encounter risk was high, whereas small groups did not alter their space use across varying levels of risk. Our findings suggest that risk effects are not uniform across landscapes for medium-sized herbivores and large buffalo groups, instead varying with environmental context and leading to a dynamic landscape of fear. However, responses among these and other prey species were variable and not consistent, highlighting the complexities inherent to multi-predator/multi-prey systems.Data availability statement: Data available from the Dryad Digital Repository: (Davies et al. 2020).http://www.oikosjournal.orghj2022Mammal Research InstituteZoology and Entomolog

Airborne laser scanning reveals uniform responses of forest structure to moose (Alces alces) across the boreal forest biome

1. The moose Alces alces is the largest herbivore in the boreal forest biome, where it can have dramatic impacts on ecosystem structure and dynamics. Despite the importance of the boreal forest biome in global carbon cycling, the impacts of moose have only been studied in disparate regional exclosure experiments, leading to calls for common analyses across a biome-wide network of moose exclosures. 2. In this study, we use airborne laser scanning (ALS) to analyse forest canopy re-sponses to moose across 100 paired exclosure-control experimental plots dis-tributed across the boreal biome, including sites in the United States (Isle Royale), Canada (Quebec, Newfoundland), Norway, Sweden and Finland. 3. We test the hypotheses that canopy height, vertical complexity and above- ground biomass (AGB) are all reduced by moose and that the impacts vary with moose density, productivity, temperature and pulse disturbances such as logging and insect outbreaks. 4. We find a surprising convergence in forest canopy response to moose. Moose had negative impacts on canopy height, complexity and AGB as expected. The responses of canopy complexity and AGB were consistent across regions and did not vary along environmental gradients. The difference in canopy height be-tween exclosures and open plots was on average 6 cm per year since the start of exclosure treatment (±2.1 SD). This rate increased with temperature, but only when moose density was high. 5. The difference in AGB between moose exclosures and open plots was 0.306 Mg ha−1 year−1 (±0.079). In browsed plots, stand AGB was 32% of that in the exclosures, a difference of 2.09 Mg ha−1. The uniform response allows scaling of the estimate to a biome-wide impact of moose of the loss of 448 (±115) Tg per year, or 224 Tg of carbon. 6. Synthesis: Analysis of ALS data from distributed exclosure experiments identified a largely uniform response of forest canopies to moose across regions, facilitat-ing scaling of moose impacts across the whole biome. This is an important step towards incorporating the effect of the largest boreal herbivore on the carbon cycling of one of the world's largest terrestrial biomes.publishedVersio

Structural diversity and tree density drives variation in the biodiversity-ecosystem function relationship of woodlands and savannas

Positive biodiversity-ecosystem function relationships (BEFRs) have been widely documented, but it is unclear if BEFRs should be expected in disturbance-driven systems. Disturbance may limit competition and niche differentiation, which are frequently posited to underlie BEFRs. We provide the first exploration of the relationship between tree species diversity and biomass, one measure of ecosystem function, across southern African woodlands and savannas, an ecological system rife with disturbance from fire, herbivores and humans. We used >1000 vegetation plots distributed across 10 southern African countries, and structural equation modelling, to determine the relationship between tree species diversity and aboveground woody biomass, accounting for interacting effects of resource availability, disturbance by fire, tree stem density and vegetation type. We found positive effects of tree species diversity on aboveground biomass, operating via increased structural diversity. The observed BEFR was highly dependent on organismal density, with a minimum threshold of c. 180 mature stems ha-1. We found that water availability mainly affects biomass indirectly, via increasing species diversity. The study underlines the close association between tree diversity, ecosystem structure, environment and function in highly disturbed savannas and woodlands. We suggest that tree diversity is an under-appreciated determinant of wooded ecosystem structure and function

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Camtrap DP: an open standard for the FAIR exchange and archiving of camera trap data

Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap-derived Big Data are becoming increasingly solvable with the help of scalable cyber-infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, “Camera Trap Metadata Standard” (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media-based and event-based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in-depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standard. Biodiversity data, camera traps, data exchange, data sharing, information standardspublishedVersio

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives