80 research outputs found
Incorporating movement in species distribution models: how do simulations of dispersal affect the accuracy and uncertainty of projections?
Species distribution models (SDMs) are one of the most important GIScience research areas in biogeography and are the primary means by which the potential effects of climate change on species' distributions and ranges are investigated. Dispersal is an important ecological process for species responding to changing climates, however, SDMs and their subsequent spatial products rarely reflect accessibility to any future suitable environment. Dispersal-related movement can be confounded by factors that vary across landscapes and climates, as well as within and among species, and it has therefore remained difficult to parametrise in SDMs. Here we compared 20 models that have previously been used (or have the potential to be used) to represent dispersal processes in SDM to predict future range shifts in response to climate change. We assessed the different dispersal models in terms of their accuracy at predicting future distributions, as well as the uncertainty associated with their predictions. Atlas data for 50 bird species from 1988 to 1991 in Great Britain were treated as base distributions (t1), with the species' environment relationships extrapolated (using three commonly used statistical methods) to 2008â 2011 (t2). Dispersal (in the form of the 20 different models) was simulated from the base distribution (t1) to 2008-2011 (t2). The results were then combined and used to identify locations that were both abiotically suitable (obtained from the statistical methods) and accessible (obtained from the dispersal models). The accuracy of these coupled projections was assessed with the 2008-2011 atlas data (the observed t2 distribution). There was substantial variation in the accuracy of the different dispersal models, and in general, the more restrictive dispersal models (e.g. fixed rate dispersal) resulted in lower accuracy for the metrics which reward correct prediction of presences. Ensemble models of the dispersal methods (generated by combining multiple projection outcomes) were created for each species, and a new Ensemble Agreement Index (EAI), which ranges from 0 (no agreement among models) to 1 (full agreement among models) was developed to quantify uncertainty among the projections. EAI values ranged from 0.634 (some areas of disagreement and therefore medium uncertainty among dispersal models) to 0.999 (large areas of agreement and low uncertainty among dispersal models). The results of this research highlight the importance of incorporating dispersal and also illustrate that the method with which dispersal is simulated greatly impacts the projected future distribution. This has important implications for studies aimed at predicting the effects of changing environmental conditions on species' distributions
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Developing a biodiversity-based indicator for large-scale environmental assessment: a case study of proposed shale gas extraction sites in Britain
1. Environmental impact assessments are important tools for predicting the consequences of development and changes in land use. These assessments generally use a small subset of total biodiversity – typically rare and threatened species and habitats – as indicators of ecological status. However, these indicators do not necessarily reflect changes in the many more widespread (but increasingly threatened) species, which are important for ecosystem functions. In addition, assessment of threatened species through field surveys is time-consuming and expensive and, therefore, only possible at small spatial scales. In contrast, planning changes in land use over large spatial scales (e.g. national infrastructure projects) require assessment and prioritization of biodiversity over large spatial extents.
2. Here, we provide a method for the assessment of biodiversity, which takes account of species diversity across larger spatial scales, based on occurrence records from 5553 species across 11 taxonomic groups. We compare the efficacy of the biodiversity-based indicator we developed against one based on threatened species only and then use it to consider spatial and temporal patterns in ecological status across Great Britain. Finally, we develop a case study to investigate biodiversity status in regions proposed for shale gas extraction in Great Britain.
3. Our results show a strong relationship between the ecological status of areas defined by all biodiversity versus only threatened species, although they also demonstrate that significant exceptions do exist where threatened species do not always accurately indicate the ecological status of wider biodiversity.
4. Spatial and temporal analyses show large variation in ecological status across Great Britain both within the area made available for shale gas licensing and within individual environmental zones. In total, however, 63% of hectads across Britain have suffered a net reduction in our biodiversity-based indicator since 1970.
5. Synthesis and applications. We provide a method and develop a biodiversity-based indicator for the assessment and prioritization of biodiversity at large spatial scales. We highlight the potential applications of this approach for the prioritization of areas that would benefit from conservation and restoration. We also emphasize the danger of insufficient consideration of more widespread species and not just rare and threatened species and habitats as indicators of ecological status when prioritizing large-scale national infrastructure projects. Our method should be a useful tool to complement existing environmental impact assessment methods
Temporal validation plots: quantifying how well correlative species distribution models predict species' range changes over time
1. The use of data documenting how species’ distributions have changed over time is crucial for testing how well
correlative species distribution models (SDMs) predict species’ range changes. So far, however, little attention
has been given to developing a reliable methodological framework for using such data.
2. We develop a new tool – the temporal validation (TV) plot – specifically aimed at making use of species’ distribution records at two times for a comprehensive assessment of the prediction accuracy of SDMs over time.
3. We extend existing presence–absence calibration plots to make use of distribution records from two time periods. TV plots visualize the agreement between change in modelled probabilities of presence and the probability
of observing sites gained or lost between time periods. We then present three measures of prediction accuracy
that can be easily calculated from TV plots.
4. We present our methodological framework using a virtual species in a simplified landscape and then provide a
real-world case study using distribution records for two species of breeding birds from two time periods of intensive recording effort across Great Britain.
5. Together with existing approaches, TV plots and their associated measures offer a simple tool for testing how
well SDMs model species’ observed range changes – perhaps the best way available to assess their ability to
predict likely future changes
Developing a national indicator of functional connectivity
Habitat loss is a significant driver of biodiversity loss, causing fragmentation into small, isolated patches of suitable land cover. This reduces the permeability of landscapes to the movement of individuals and reduces the likelihood of metapopulation persistence. Quantifying functional connectivity, the ability of a focal species to move between resource patches, is therefore essential for conservation management. There is substantial evidence supporting a technique based on ‘population synchrony’- the degree of correlation in time-series of annual population growth rates between different long-term monitoring sites, to provide a measure of functional connectivity. However, synchronised population dynamics are not only driven by the movement of individuals between sites, but also shared environmental conditions which must be accounted for. Here, we use species survey data from over four decades to investigate average levels and temporal trends in population synchrony for 58 British bird and butterfly species. We first show that population synchrony is significantly associated with synchrony in some seasonal climatic variables. Once we accounted for spatiotemporal climatic patterns, we found that synchrony in butterflies declined over time by 71% between 1985 and 2000 but increased by 64% in recent years. Synchrony in birds showed some decline between 1999 and 2005, after which there appears to being recovery, however most species (74%) show no significant overall change in synchrony. Our proposed indicator provides a ‘species-eye-view’ of functional connectivity using widely available abundance data. Developing such indicators of functional connectivity, which can be updated annually, is crucial to improve the effectiveness of land management strategies for conservation under increasing environmental change
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Developing a national indicator of functional connectivity
Habitat loss is a significant driver of biodiversity loss, causing fragmentation into small, isolated patches of suitable land cover. This reduces the permeability of landscapes to the movement of individuals and reduces the likelihood of metapopulation persistence. Quantifying functional connectivity, the ability of a focal species to move between resource patches, is therefore essential for conservation management. There is substantial evidence supporting a technique based on ‘population synchrony’- the degree of correlation in time-series of annual population growth rates between different long-term monitoring sites, to provide a measure of functional connectivity. However, synchronised population dynamics are not only driven by the movement of individuals between sites, but also shared environmental conditions which must be accounted for. Here, we use species survey data from over four decades to investigate average levels and temporal trends in population synchrony for 58 British bird and butterfly species. We first show that population synchrony is significantly associated with synchrony in some seasonal climatic variables. Once we accounted for spatiotemporal climatic patterns, we found that synchrony in butterflies declined over time by 71% between 1985 and 2000 but increased by 64% in recent years. Synchrony in birds showed some decline between 1999 and 2005, after which there appears to being recovery, however most species (74%) show no significant overall change in synchrony. Our proposed indicator provides a ‘species-eye-view’ of functional connectivity using widely available abundance data. Developing such indicators of functional connectivity, which can be updated annually, is crucial to improve the effectiveness of land management strategies for conservation under increasing environmental change
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Geographical range margins of many taxonomic groups continue to shift polewards
Many species are extending their leading-edge (cool) range margins polewards in response to recent climate change. In the present study, we investigated range margin changes at the northern (cool) range margins of 1573 southerly-distributed species from 21 animal groups in Great Britain over the past four decades of climate change, updating previous work. Depending on data availability, range margin changes were examined over two time intervals during the past four decades. For four groups (birds, butterflies, macromoths, and dragonflies and damselflies), there were sufficient data available to examine range margin changes over both time intervals. We found that most taxa shifted their northern range margins polewards and this finding was not greatly influenced by changes in recorder effort. The mean northwards range margin change in the first time interval was 23 km per decade (N = 13 taxonomic groups) and, in the second interval, was 18 km per decade (N = 16 taxonomic groups) during periods when the British climate warmed by 0.21 and 0.28 °C per decade, respectively. For the four taxa examined over both intervals, there was evidence for higher rate of range margin change in the more recent time interval in the two Lepidoptera groups. Our analyses confirm a continued range margin shift polewards in a wide range of taxonomic groups
Overcoming the challenges of public data archiving for citizen science biodiversity recording and monitoring schemes
1. Public data archiving (PDA) is widely advocated as a means of achieving open data standards, leading to improved data preservation, increased scientific reproducibility, and transparency, as well as additional data use.
2. Public data archiving was primarily conceived to archive data from short‐term, single‐purpose scientific studies. It is now more widely applied, including to large‐scale citizen science biodiversity recording and monitoring schemes which combine the efforts of volunteers with professional scientists.
3. This may affect the financial security of such schemes by reducing income from data and analytical services. Communication between scheme organizers and researchers may be disrupted, reducing scientific quality and impeding scheme development. It may also have an impact on the participation of some volunteers.
4. Synthesis and applications. In response to the challenges of public data archiving for citizen science biodiversity recording and monitoring schemes, the archive function of scheme organizations should be better recognized by those promoting open data principles. Increased financial support from the public sector or from commercial or academic data users may offset financial risk. Those in favour of public data archiving should do more to facilitate communication between nonscheme users and the originating schemes, while a more flexible approach to data archiving may be required to address potential impacts on volunteer participation
Relevance of Norepinephrine–Dopamine Interactions in the Treatment of Major Depressive Disorder
Central dopaminergic and noradrenergic systems play essential roles in controlling several forebrain functions. Consequently, perturbations of these neurotransmissions may contribute to the pathophysiology of neuropsychiatric disorders. For many years, there was a focus on the serotonin (5-HT) system because of the efficacy of selective serotonin reuptake inhibitors (SSRIs), the most prescribed antidepressants in the treatment of major depressive disorder (MDD). Given the interconnectivity within the monoaminergic network, any action on one system may reverberate in the other systems. Analysis of this network and its dysfunctions suggests that drugs with selective or multiple modes of action on dopamine (DA) and norepinephrine (NE) may have robust therapeutic effects. This review focuses on NE-DA interactions as demonstrated in electrophysiological and neurochemical studies, as well as on the mechanisms of action of agents with either selective or dual actions on DA and NE. Understanding the mode of action of drugs targeting these catecholaminergic neurotransmitters can improve their utilization in monotherapy and in combination with other compounds particularly the SSRIs. The elucidation of such relationships can help design new treatment strategies for MDD, especially treatment-resistant depression
Diurnal and nocturnal ecology of Golden Plovers Pluvialis apricaria and Lapwings Vanellus vanellus wintering on arable farmland
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Modelled relative abundance of bird species in Britain and Ireland 2007-2011
<p>This data package describes the modelled relative (not absolute) abundance of Carrion Crow (Corvus corone) and Magpie (Pica pica) in Britain and Ireland.</p>
<p>This was used to produce Bird Atlas 2007-2011 <a href="https://app.bto.org/mapstore/StoreServlet">maps</a> of relative abundance at a tetrad (2x2km) resolution. </p>
<p>Acknowledgement: These data originate from the Bird Atlas 2007–11 project which was run by the BTO in partnership with BirdWatch Ireland and the Scottish Ornithologists’ Club. We are grateful to the thousands of volunteers who undertook and organised the fieldwork for the atlas.</p>
<p>Please refer to the metadata for a more detailed description, and for information on dataset usage.</p>
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