Aim: Species distribution modelling is commonly used to guide future conservation policies in the light of potential climate change. However, arbitrary decisions during the model-building process can ...affect predictions and contribute to uncertainty about where suitable climate space will exist. For many species, the key climatic factors limiting distributions are unknown. This paper assesses the uncertainty generated by using different climate predictor variable sets for modelling the impacts of climate change. Location: Europe, 10°W to 50° E and 30° N to 60 ° N. Methods: Using 1453 presence pixels at 30 arcsec resolution for the great bustard (Otis tarda), predictions of future distribution were made based on two emissions scenarios, three general climate models and 26 sets of predictor variables. Twentysix current models were created, and 156 for both 2050 and 2080. Map comparison techniques were used to compare predictions in terms of the quantity and the location of presences (map comparison kappa, MCK) and using a range change index (RCI). Generalized linear models (GLMs) were used to partition explained deviance in MCK and RCI among sources of uncertainty. Results: The 26 different variable sets achieved high values of AUC (area under the receiver operating characteristic curve) and yet introduced substantial variation into maps of current distribution. Differences between maps were even greater when distributions were projected into the future. Some 64-78% of the variation between future maps was attributable to choice of predictor variable set alone. Choice of general climate model and emissions scenario contributed a maximum of 15% variation and their order of importance differed for MCK and RCI. Main conclusions: Generalized variable sets produce an unmanageable level of uncertainty in species distribution models which cannot be ignored. The use of sound ecological theory and statistical methods to check predictor variables can reduce this uncertainty, but our knowledge of species may be too limited to make more than arbitrary choices. When all sources of modelling uncertainty are considered together, it is doubtful whether ensemble methods offer an adequate solution.Future studies should explicitly acknowledge uncertainty due to arbitrary choices in the model-building process and develop ways to convey the results to decision-makers.
Abstract
Time is running out to limit further devastating losses of biodiversity and nature's contributions to humans. Addressing this crisis requires accurate predictions about which species and ...ecosystems are most at risk to ensure efficient use of limited conservation and management resources. We review existing biodiversity projection models and discover problematic gaps. Current models usually cannot easily be reconfigured for other species or systems, omit key biological processes, and cannot accommodate feedbacks with Earth system dynamics. To fill these gaps, we envision an adaptable, accessible, and universal biodiversity modeling platform that can project essential biodiversity variables, explore the implications of divergent socioeconomic scenarios, and compare conservation and management strategies. We design a roadmap for implementing this vision and demonstrate that building this biodiversity forecasting platform is possible and practical.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Understanding the dynamics of socio‐ecological systems is crucial to the development of environmentally sustainable practices. Models of social or ecological sub‐systems have greatly enhanced such ...understanding, but at the risk of obscuring important feedbacks and emergent effects. Integrated modelling approaches have the potential to address this shortcoming by explicitly representing linked socio‐ecological dynamics. We developed a socio‐ecological system model by coupling an existing agent‐based model of land‐use dynamics and an individual‐based model of demography and dispersal. A hypothetical case‐study was established to simulate the interaction of crops and their pollinators in a changing agricultural landscape, initialised from a spatially random distribution of natural assets. The bi‐directional coupled model predicted larger changes in crop yield and pollinator populations than a unidirectional uncoupled version. The spatial properties of the system also differed, the coupled version revealing the emergence of spatial land‐use clusters that neither supported nor required pollinators. These findings suggest that important dynamics may be missed by uncoupled modelling approaches, but that these can be captured through the combination of currently‐available, compatible model frameworks. Such model integrations are required to further fundamental understanding of socio‐ecological dynamics and thus improve management of socio‐ecological systems.
The interacting impacts of habitat fragmentation and climate change present a substantial threat for biodiversity, constituting a ‘deadly anthropogenic cocktail’. A range of conservation actions has ...been proposed to allow biodiversity to respond to those environmental changes. However, determining the relative effectiveness of these actions has been hampered by incomplete evidence. Empirical studies have provided important insights to inform conservation, but the challenge of considering multiple actions at large spatial and temporal scales is considerable. We adopt an individual-based modelling approach to qualitatively assess the effectiveness of alternative conservation actions in facilitating range expansion and patch occupancy for eight virtual species. We test actions to: (i) improve the quality of existing habitat patches, (ii) increase the permeability of the surrounding matrix, (iii) restore degraded habitat, (iv) create new habitat patches to form stepping-stones or (v) create new habitat to enlarge existing habitat patches. These actions are systematically applied to six real landscapes of the UK, which differ in their degree of habitat fragmentation and availability. Creating new habitat close to existing patches typically provides the strongest benefits for both range expansion and patch occupancy across species and landscapes. However, some landscapes may be so degraded that even under unrealistically high levels of management action, species' performances cannot be rescued. We identify that it is possible to develop a triage of conservation actions at the landscape, species and investment level, thereby providing timely evidence to inform action on the ground to lessen the hangover from the deadly anthropogenic cocktail.
•Conservation actions allow biodiversity to respond to climate change or habitat fragmentation.•Their actual effectiveness is hardly measurable in the field.•Individuals-based models incorporating demography and dispersal help develop a triage of conservation actions.
•Maximum tree height is associated with climatic variables across an elevation gradient.•Variables such as topography and soil are also important in a water limited system.•Associations between tree ...height and environmental variables are scale dependent.•At fine spatial scales, topography and soil variables increase in importance.•The results have implications on how forests are managed in the Western US.
Tall trees and vertical forest structure are associated with increased productivity, biomass and wildlife habitat quality. While climate has been widely hypothesized to control forest structure at broad scales, other variables could be key at fine scales, and are associated with forest management. In this study we identify the environmental conditions (climate, topography, soils) associated with increased tree height across spatial scales using airborne Light Detection and Ranging (LiDAR) data to measure canopy height. The study was conducted over a large elevational gradient from 200 to 3000 m in the Sierra Nevada Mountains (CA, USA) spanning sparse oak woodlands to closed canopy conifer forests. We developed Generalized Boosted Models (GBMs) of forest height, ranking predictor variable importance against Maximum Canopy Height (CHMax) at six spatial scales (25, 50, 100, 250, 500, 1000 m). In our study area, climate variables such as the climatic water deficit and mean annual precipitation were more strongly correlated with CHmax (18–52% relative importance) than soil and topographic variables, and models at intermediate (50–500 m) scales explained the most variance in CHMax (R2 0.77–0.83). Certain soil variables such as soil bulk density and pH, as well as topographic variables such as the topographic wetness index, slope curvature and potential solar radiation, showed consistent, strong associations with canopy structure across the gradient, but these relationships were scale dependent. Topography played a greater role in predicting forest structure at fine spatial scales, while climate variables dominated our models, particularly at coarse scales. Our results indicate that multiple abiotic factors are associated with increased maximum tree height; climatic water balance is most strongly associated with this component of forest structure but varies across all spatial scales examined (6.9–54.8% relative importance), while variables related to topography also explain variance in tree height across the elevational gradient, particularly at finer spatial scales (37.15%, 20.26% relative importance at 25, 50 m scales respectively).
Landscape ecological modelling provides a vital means for understanding the interactions between geographical, climatic, and socio-economic drivers of land-use and the dynamics of ecological systems. ...This growing field is playing an increasing role in informing landscape spatial planning and management. Here, we review the key modelling approaches that are used in landscape modelling and in ecological modelling. We identify an emerging theme of increasingly detailed representation of process in both landscape and ecological modelling, with complementary suites of modelling approaches ranging from correlative, through aggregated process based approaches to models with much greater structural realism that often represent behaviours at the level of agents or individuals. We provide examples of the considerable progress that has been made at the intersection of landscape modelling and ecological modelling, while also highlighting that the majority of this work has to date exploited a relatively small number of the possible combinations of model types from each discipline. We use this review to identify key gaps in existing landscape ecological modelling effort and highlight emerging opportunities, in particular for future work to progress in novel directions by combining classes of landscape models and ecological models that have rarely been used together.
An individual-based model of animal dispersal and population dynamics was used to test the effects of different climate change adaptation strategies on species range shifting ability, namely the ...improvement of existing habitat, restoration of low quality habitat and creation of new habitat. These strategies were implemented on a landscape typical of fragmentation in the United Kingdom using spatial rules to differentiate between the allocation of strategies adjacent to or away from existing habitat patches. The total area being managed in the landscape was set at realistic levels based on recent habitat management trends. Eight species were parameterised to broadly represent different stage structure, population densities and modes of dispersal. Simulations were initialised with the species occupying 20% of the landscape and run for 100years. As would be expected for a range of real taxa, range shifting abilities were dramatically different. This translated into large differences in their responses to the adaptation strategies. With conservative (0.5%) estimates of the area prescribed for climate change adaptation, few species display noticeable improvements in their range shifting, demonstrating the need for greater investment in future adaptation. With a larger (1%) prescribed area, greater range shifting improvements were found, although results were still species-specific. It was found that increasing the size of small existing habitat patches was the best way to promote range shifting, and that the creation of new stepping stone features, whilst beneficial to some species, did not have such broad effect across different species.
•We study species range shifting under climate change adaptation strategies.•An individual-based model of dispersal and population dynamics was used.•Strategies are based on habitat improvement, restoration and creation.•Broadest benefits came from habitat creation adjacent to small habitat patches.•At conservative levels of habitat management, range shifting benefits are minimal.
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