Spatially explicit null models in biogeography: Toward a multi-scale understanding of the niche.

In general, most ecologists envision the niche as a central organizing tenet, and that particular parameters of the niche help structure biogeographic patterns of diversity, distribution and abundance. The major emergent alternative to the niche concept requires the inference of background stochasticity, and its application through null models. For example, rather than competitive interactions of species shaping the coexistence of species, historical accidents of dispersal have been suggested. In this thesis I explore, in some detail, the concept of niche using of null models. In this thesis, two detailed and quite different null models are presented. The first, based on the Mid-Domain Effect (MDE), explores the influence of continental geometry on patterns in species richness and range size frequency distributions. I compared the MDE predictions first to observations on tree species richness in continental North America (n = 417 species), and then to amphibian, bird and mammal species richness across North and South America (n = 2216, 3771 and 1605 species, respectively) contrasting the relative contributions of null model results and environmental correlates. I have developed a novel null methodology to predict the niche of a species, or a group of species; I applied this at local and regional scales to examine null spatial distribution predictions for a single, endangered species at the local scale ( Opuntia humifusa at Point Pelee National Park), and for groups of rare species at a regional scale (based on reported occurrences across south-western Ontario). Results can be regarded as representing intermediate states between the extremes of continua of which niche and neutral models form the ends. With respect to the relative strengths of stochastic and deterministic processes, this thesis has characterized the attributes of groups of species. For example, large-ranged NA tree species are influenced by the MDE more than small-ranged species; moreover, regional, null species distribution models performed best for birds, insects, reptiles, sedges, as well as for aquatic and terrestrial plants. It seems most likely that real species distributions are the product of variation in relative strength of stochastic and deterministic processes.Dept. of Biological Sciences. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .V36. Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3559. Thesis (Ph.D.)--University of Windsor (Canada), 2006

Climate change refugia for terrestrial biodiversity

AbstractWe are currently facing the likelihood of severe climate change before the close of the century. In the face of such a global driver of species loss, we urgently need to identify refugia that will shelter species from the worst impacts of climate change. This  will be  a critical component of successful conservation and management of our biodiversity. Despite this, little is known about how best to identify refugia in the landscape, and the practical strategies needed to identify, protect and expand refugia are just beginning to be developed. Identifying refugia that will protect most species, or large numbers of species, remains a complex and daunting endeavour due to the large variations in climatic and biotic requirements of species. A first step to identifying refugia for biodiversity across Australia is to locate the areas which show the least change into the future (i.e. the most environmentally stable), particularly along axes of temperature and precipitation. The second and crucial step is to identify the areas that will retain most of their biodiversity and provide opportunities for additional species to relocate to into the future. Using these approaches in this project, we take the first steps to identify refugial areas across the Australian continent under contemporary climate change scenarios. We find that the southern and eastern parts of the continent contain refugia that many species will retreat to over the next 75 years, but that the current reserve system may be inadequate to allow species to shift to and persist in these areas. Disturbingly, we also find that there is a large portion of the Australian vertebrate community for which adequate natural refugia do not appear to exist. Fine-scaled regional analyses will be required to clarify these broad findings, and we examine a number of case studies demonstrating how these regional analyses might best proceed. Lessons learnt across the multiple techniques employed in this study include:1. High elevation areas are important refugia.2. Tasmania and the east coast of mainland Australia contain most of the key areas for refugia into the future.3. Results are dependent on which objectives, techniques, taxonomic groups and climate scenarios are used.Please cite this report as:Reside, AE, VanDerWal, J, Phillips, B, Shoo, LP, Rosauer, DF, Anderson, BA, Welbergen, J, Moritz, C, Ferrier, S, Harwood, TD, Williams, KJ, Mackey, B, Hugh, S, Williams, SE 2013 Climate change refugia for terrestrial biodiversity: Defining areas that promote species persistence and ecosystem resilience in the face of global climate change, National Climate Change Adaptation Research Facility, Gold Coast, pp. 216We are currently facing the likelihood of severe climate change before the close of the century. In the face of such a global driver of species loss, we urgently need to identify refugia that will shelter species from the worst impacts of climate change. This  will be  a critical component of successful conservation and management of our biodiversity. Despite this, little is known about how best to identify refugia in the landscape, and the practical strategies needed to identify, protect and expand refugia are just beginning to be developed. Identifying refugia that will protect most species, or large numbers of species, remains a complex and daunting endeavour due to the large variations in climatic and biotic requirements of species. A first step to identifying refugia for biodiversity across Australia is to locate the areas which show the least change into the future (i.e. the most environmentally stable), particularly along axes of temperature and precipitation. The second and crucial step is to identify the areas that will retain most of their biodiversity and provide opportunities for additional species to relocate to into the future. Using these approaches in this project, we take the first steps to identify refugial areas across the Australian continent under contemporary climate change scenarios. We find that the southern and eastern parts of the continent contain refugia that many species will retreat to over the next 75 years, but that the current reserve system may be inadequate to allow species to shift to and persist in these areas. Disturbingly, we also find that there is a large portion of the Australian vertebrate community for which adequate natural refugia do not appear to exist. Fine-scaled regional analyses will be required to clarify these broad findings, and we examine a number of case studies demonstrating how these regional analyses might best proceed. Lessons learnt across the multiple techniques employed in this study include:High elevation areas are important refugia.Tasmania and the east coast of mainland Australia contain most of the key areas for refugia into the future.Results are dependent on which objectives, techniques, taxonomic groups and climate scenarios are used

Incorporating altered fire frequency scenarios in species distribution models improves climate change predictions for tropical savanna birds

Biodiversity conservation in the face of changing climate requires reliable predictions of species distributions. Distribution models need to include variables that strongly influence species persistence. Species will be affected by climate change directly by altering the amount and location of suitable climatic space, and indirectly by climate driven modification of habitat. While climate is a good predictor of species distributions, biotic and abiotic landscape factors also influence distribution. Very few studies of climate change effects on biodiversity have included key landscape factors in distribution modelling, despite recognition that landscape alteration through processes such as fire and land clearing changes fauna patterning. For birds in Australian tropical savannas, change in fire regimes is a critical conservation issue, linked to species decline. While species may show gradual shifts in distribution due to changes in temperature and rainfall, species are likely to show a more immediate response to changes in fire as a result of climatic changes. This study examines species' responses to changes in fire by projecting species distribution modelling algorithms built using Maxent onto scenarios with increased fire frequency. We accounted for important static landscape elements by including remnant vegetation and soil spatial layers. This study identified that increased fire frequency alters the predictions for birds by changing the amount of suitable habitat. Climate change combined with increased fire frequency will reduce available habitat; more than simply using climate predictions alone. Our results demonstrate the importance of including landscape factors into distribution modelling when generating species predictions. Understanding the impacts of landscape factors on bird distributions, in particular fire, is a critical step in conservation planning and adaptation of land management for combating biodiversity loss due to climate change

Examining current or future trade-offs for biodiversity conservation in north-eastern Australia

With the high rate of ecosystem change already occurring and predicted to occur in the coming decades, long-term conservation has to account not only for current biodiversity but also for the biodiversity patterns anticipated for the future. The trade-offs between prioritising future biodiversity at the expense of current priorities must be understood to guide current conservation planning, but have been largely unexplored. To fill this gap, we compared the performance of four conservation planning solutions involving 662 vertebrate species in the Wet Tropics Natural Resource Management Cluster Region in north-eastern Australia. Input species data for the four planning solutions were: 1) current distributions; 2) projected distributions for 2055; 3) projected distributions for 2085; and 4) current, 2055 and 2085 projected distributions, and the connectivity between each of the three time periods for each species. The four planning solutions were remarkably similar (up to 85% overlap), suggesting that modelling for either current or future scenarios is sufficient for conversation planning for this region, with little obvious trade-off. Our analyses also revealed that overall, species with small ranges occurring across steep elevation gradients and at higher elevations were more likely to be better represented in all solutions. Given that species with these characteristics are of high conservation significance, our results provide confidence that conservation planning focused on either current, near-or distant-future biodiversity will account for these species.Peer reviewe

Weather, Not Climate, Defines Distributions of Vagile Bird Species

Background\ud \ud Accurate predictions of species distributions are essential for climate change impact assessments. However the standard practice of using long-term climate averages to train species distribution models might mute important temporal patterns of species distribution. The benefit of using temporally explicit weather and distribution data has not been assessed. 1We hypothesized that short-term weather associated with the time a species was recorded should be superior to long-term climate measures for predicting distributions of mobile species.\ud \ud Methodology\ud \ud We tested our hypothesis by generating distribution models for 157 bird species found in Australian tropical savannas (ATS) using modelling algorithm Maxent. The variable weather of the ATS supports a bird assemblage with variable movement patterns and a high incidence of nomadism. We developed “weather” models by relating climatic variables (mean temperature, rainfall, rainfall seasonality and temperature seasonality) from the three month, six month and one year period preceding each bird record over a 58 year period (1950–2008). These weather models were compared against models built using long-term (30 year) averages of the same climatic variables.\ud \ud Conclusions\ud \ud Weather models consistently achieved higher model scores than climate models, particularly for wide-ranging, nomadic and desert species. Climate models predicted larger range areas for species, whereas weather models quantified fluctuations in habitat suitability across months, seasons and years. Models based on long-term climate averages over-estimate availability of suitable habitat and species' climatic tolerances, masking species potential vulnerability to climate change. Our results demonstrate that dynamic approaches to distribution modelling, such as incorporating organism-appropriate temporal scales, improves understanding of species distributions

Regional seasonality of fire size and fire weather conditions across Australia's northern savanna

Australia's northern savannas have among the highest fire frequencies in the world. The climate is monsoonal, with a long, dry season of up to 9 months, during which most fires occur. The Australian Government's Emissions Reduction Fund allows land managers to generate carbon credits by abating the direct emissions of CO2 equivalent gases via prescribed burning that shifts the fire regime from predominantly large, high-intensity late dry season fires to a more benign, early dry season fire regime. However, the Australian savannas are vast and there is significant variation in weather conditions and seasonality, which is likely to result in spatial and temporal variations in the commencement and length of late dry season conditions. Here, we assess the temporal and spatial consistency of the commencement of late dry season conditions, defined as those months that maximise fire size and where the most extreme fire weather conditions exist. The results demonstrate that significant yearly, seasonal and spatial variations in fire size and fire weather conditions exist, both within and between bioregions. The effective start of late dry season conditions, as defined by those months that maximise fire size and where the most extreme fire weather variables exist, is variable across the savannas

The Biodiversity and Climate Change Virtual Laboratory: Where ecology meets big data

Advances in computing power and infrastructure, increases in the number and size of ecological and environmental datasets, and the number and type of data collection methods, are revolutionizing the field of Ecology. To integrate these advances, virtual laboratories offer a unique tool to facilitate, expedite, and accelerate research into the impacts of climate change on biodiversity. We introduce the uniquely cloud-based Biodiversity and Climate Change Virtual Laboratory (BCCVL), which provides access to numerous species distribution modelling tools; a large and growing collection of biological, climate, and other environmental datasets; and a variety of experiment types to conduct research into the impact of climate change on biodiversity. Users can upload and share datasets, potentially increasing collaboration, cross-fertilisation of ideas, and innovation among the user community. Feedback confirms that the BCCVL's goals of lowering the technical requirements for species distribution modelling, and reducing time spent on such research, are being met

The Biodiversity and Climate Change Virtual Laboratory: How Ecology and Big Data can be utilised in the fight against vector-borne diseases

Advances in computing power and infrastructure, increases in the number and size of ecological and environmental datasets, and the number and type of data collection methods, are revolutionizing the field of Ecology. To integrate these advances, virtual laboratories offer a unique tool to facilitate, expedite, and accelerate research into the impacts of climate change on biodiversity. We introduce the uniquely cloud-based Biodiversity and Climate Change Virtual Laboratory (BCCVL), which provides access to numerous species distribution modelling tools; a large and growing collection of biological, climate, and other environmental datasets, as well as a variety of experiment types to conduct research into the impact of climate change on biodiversity. Users can upload and share datasets, potentially increasing collaboration and cross-fertilisation of ideas and innovation among the user community. Feedback confirms that the BCCVL's goals of lowering the technical requirements for species distribution modelling, and reducing time spent on such research, are being met. We present a case study that illustrates the utility of the BCCVL as a research tool that can be applied to the problem of vector borne diseases and the likelihood of climate change altering their future distribution across Australia. This case study presents the preliminary results of an ensemble modelling experiment which employs multiple (15) different species distribution modelling algorithms to model the distribution of one of the main mosquito vectors of the most common vector borne disease in Australia: Ross River Virus (RRV). We use the BCCVL to do future projection of these models with future climates based on two extreme emissions scenarios, for multiple years. Our results show a large range in both the modelled current distribution, and projected future distribution, of the mosquito species studied. Most models (that were built using different algorithms) show somewhat similar current distributions of the species however there are three models that are obvious outliers. The projected models show a similar range in the distribution of the species, with some models indicating a fewer areas (and also areas with a lower probability of occurrence in specific areas) where the species is likely to be found under a climate change scenario. However, a majority of models show an expanded distribution, with some areas that have a greater probability of the occurrence of this species; this will provide a more robust indication of future distribution for policy makers and planners, than if just one or a few models had been employed. The economic and human health impact of vector borne diseases underline the importance of scientifically sound projections of the future spread of common disease vectors such as mosquitos under various climate change scenarios. This is because such information is essential for policy–makers to identify vulnerable communities and to better manage outbreaks and potential epidemics of such diseases. The BCCVL has provided the means to effectively and robustly bracket multiple sources of uncertainty in the future spread of RRV: this study focuses on two of these - the future distribution of a primary mosquito vector of the disease under two extreme scenarios of climate change. Research is underway to expand our analysis to take into account more sources of uncertainty: more vector and amplifying host species, emissions scenarios, and future climate projections from a range of different global climate model

Modelling the distribution and compositional variation of plant communities at the continental scale

P. 978-990Aim: To investigate whether (1) environmental predictors allow to delineate the distri- bution of discrete community types at the continental scale and (2) how data complete- ness influences model generalization in relation to the compositional variation of the modelled entities.S