13 research outputs found
The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling.
Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere
Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects
Automated sensors have potential to standardize and expand the monitoring of insects across the globe. As one of the most scalable and fastest developing sensor technologies, we describe a framework for automated, image-based monitoring of nocturnal insects—from sensor development and field deployment to workflows for data processing and publishing. Sensors comprise a light to attract insects, a camera for collecting images and a computer for scheduling, data storage and processing. Metadata is important to describe sampling schedules that balance the capture of relevant ecological information against power and data storage limitations. Large data volumes of images from automated systems necessitate scalable and effective data processing. We describe computer vision approaches for the detection, tracking and classification of insects, including models built from existing aggregations of labelled insect images. Data from automated camera systems necessitate approaches that account for inherent biases. We advocate models that explicitly correct for bias in species occurrence or abundance estimates resulting from the imperfect detection of species or individuals present during sampling occasions. We propose ten priorities towards a step-change in automated monitoring of nocturnal insects, a vital task in the face of rapid biodiversity loss from global threats
Global maps of soil temperature.
Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications
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Reading tea leaves worldwide: decoupled drivers of initial litter decomposition mass-loss rate and stabilisation
The breakdown of plant material fuels soil functioning and biodiversity. Currently, process understanding of global decomposition patterns and the drivers of such patterns are hampered by the lack of coherent large-scale datasets. We buried 36,000 individual litterbags (tea bags) worldwide and found an overall negative correlation between initial mass-loss rates and stabilization factors of plant-derived carbon, using the Tea Bag Index (TBI). The stabilization factor quantifies the degree to which easy-to-degrade components accumulate during early-stage decomposition (e.g. by environmental limitations). However, agriculture and an interaction between moisture and temperature led to a decoupling between initial mass-loss rates and stabilization, notably in colder locations. Using TBI improved mass-loss estimates of natural litter compared to models that ignored stabilization. Ignoring the transformation of dead plant material to more recalcitrant substances during early-stage decomposition, and the environmental control of this transformation, could overestimate carbon losses during early decomposition in carbon cycle models
Evaluating and communicating simulated wildlife responses to land-use scenarios
Reliable assessments of how human activities affect wildlife populations are essential for effective natural resource management. Agent-based models provide a powerful tool for integration of multiple drivers of ecological systems, but communication of model results is at the same time constrained by the complexity of the model responses. Here, we systematically modify a digital version of a real landscape to produce a set of model landscapes differing in the degree of heterogeneity and test how different landscapes affect abundance and occupancy of six model animal species in four different management scenarios using an agent-based model framework (ALMaSS). ALMaSS is capable of highly detailed modelling of individuals but the outputs can be complex and voluminous. We develop a statistic (the AOR-index) based on the abundance occupancy relationship to simplify presentation of model simulations and facilitate scenario comparisons. Scenario results demonstrate that species respond very differently to a particular land-use scenario and in some cases in opposite directions. The bird and mammal species generally showed larger responses than the invertebrates and changes in occupancy were often smaller than changes in abundance. The species-specific responses are caused by differences in habitat requirements and dispersal abilities, but the importance of such life history traits are affected by landscape dynamics and structure. Hence predictions of species-specific responses to land-use changes in terms of abundance and occupancy are greatly improved by incorporation in a model framework taking spatial and temporal dynamics into account. The use of the AOR-index simplifies the presentation of scenario comparison and provides and objective way to combine impacts across species. Its use, however, still requires management goals in order to evaluate scenario responses
Ecological specialization matters: long-term trends in butterfly species richness and assemblage composition depend on multiple functional traits
Phenology of high-arctic butterflies and their floral resources: species-specific responses to climate change
Current global warming is particularly pronounced in the Arctic and arthropods are expected to respond rapidly to these changes. Long-term studies of individual arthropod species from the Arctic are, however, virtually absent. We examined butterfly specimens collected from yellow pitfall traps over 14 years (1996-2009) at Zackenberg in high-arctic, north-east Greenland. Specimens were previously sorted to the family level. We identified them to the species level and examined long-term species-specific phenological responses to recent summer warming. Two species were rare in the samples (Polaris fritillary Boloria polaris and Arctic blue Plebejus glandon) and statistical analyses of phenological responses were therefore restricted to the two most abundant species (Arctic fritillary, B. chariclea and Northern clouded yellow Colias hecla). Our analyses demonstrated a trend towards earlier flight seasons in B. chariclea, but not in C. hecla. The timing of onset, peak and end of the flight season in B. chariclea were closely related to snowmelt, July temperature and their interaction, whereas onset, peak and end of the flight season in C. hecla was only related to timing of snowmelt. The duration of the butterfly flight season was significantly positively related to the temporal overlap with floral resources in both butterfly species. We further demonstrate that yellow pitfall traps are a useful alternative to transect walks for butterfly recording in tundra habitats. More phenological studies of Arctic arthropods should be carried out at the species level and ideally be analysed in context with interacting species to assess how ongoing climate change will affect Arctic biodiversity in the near futur
Phenology of high-arctic butterflies and their floral resources: species-specific responses to climate change
Long‐term trends mask variation in the direction and magnitude of short‐term phenological shifts
Plant co-existence patterns and High-Arctic vegetation composition in three common plant communities in north-east Greenland
Arctic regions are expected to experience substantial changes in climate in the coming decades. In order to predict potential changes of Arctic vegetation, it is important to understand the distinct role of life forms of plants and of individual species in relation to plant co-existence patterns. Our aim is to investigate if three common Arctic plant patch types dominated by contrasting life forms (by the dwarf shrubs Salix arctica or Dryas octopetala×intermedia or by mosses) are related (a) to the co-existence of vascular plants and species richness at patch scale and (b) to the floristic composition in three distinct plant communities (Salix snowbed, Dryas heath and fell-field) associated with contrasting abiotic regimes. The study was conducted at Zackenberg, in north-east Greenland. Dryas patches showed a clear negative effect on small-scale plant richness and co-existence in the fell-field. Salix and moss patches showed a similar pattern in all the plant communities, although the number of individuals growing in Salix patches was lower than in moss patches. Salix and mosses in the fell-fields hosted a high number of species in spite of the much less vegetated aspect of this harsh, upper zone. The floristic composition varied between plant communities, but it did not change substantially between patch types within each community. This study provides novel background knowledge of plant co-existence patterns at patch scale and of the structure of contrasting Arctic plant communities, which will help to better assess the potential effects of varying abiotic stress regimes on Arctic vegetation