Kristen J. Williams

Geographical limits to species-range shifts are suggested by climate velocity

The reorganization of patterns of species diversity driven by anthropogenic climate change, and the consequences for humans, are not yet fully understood or appreciated. Nevertheless, changes in climate conditions are useful for predicting shifts in species distributions at global and local scales. Here we use the velocity of climate change to derive spatial trajectories for climatic niches from 1960 to 2009 (ref. 7) and from 2006 to 2100, and use the properties of these trajectories to infer changes in species distributions. Coastlines act as barriers and locally cooler areas act as attractors for trajectories, creating source and sink areas for local climatic conditions. Climate source areas indicate where locally novel conditions are not connected to areas where similar climates previously occurred, and are thereby inaccessible to climate migrants tracking isotherms: 16% of global surface area for 1960 to 2009, and 34% of ocean for the ‘business as usual’ climate scenario (representative concentration pathway (RCP) 8.5) representing continued use of fossil fuels without mitigation. Climate sink areas are where climate conditions locally disappear, potentially blocking the movement of climate migrants. Sink areas comprise 1.0% of ocean area and 3.6% of land and are prevalent on coasts and high ground. Using this approach to infer shifts in species distributions gives global and regional maps of the expected direction and rate of shifts of climate migrants, and suggests areas of potential loss of species richness.

Which environmental variables should I use in my biodiversity model

Appropriate selection of environmental variables is critical to the performance of biodiversity models, but has received less attention than the choice of modelling method. Online aggregators of biological and environmental data, such as the Global Biodiversity Information Facility and the Atlas of Living Australia, necessitate a rational approach to variable selection. We outline a set of general principles for systematically identifying, compiling, evaluating and selecting environmental variables for a biodiversity model. Our approach aims to maximise the information obtained from the analysis of biological records linked to a potentially large suite of spatial environmental variables. We demonstrate the utility of this structured framework through case studies with Australian vascular plants: regional modelling of a species distribution, continent-wide modelling of species compositional turnover and environmental classification. The approach is informed by three components of a biodiversity model: (1) an ecological framework or conceptual model, (2) a data model concerning availability, resolution and variable selection and (3) a method for analysing data. We expand the data model in structuring the problem of choosing environmental variables. The case studies demonstrate a structured approach for the: (1) cost-effective compilation of variables in the context of an explicit ecological framework for the study, attribute accuracy and resolution; (2) evaluation of non-linear relationships between variables using knowledge of their derivation, scatter plots and dissimilarity matrices; (3) selection and grouping of variables based on hypotheses of relative ecological importance and perceived predictor effectiveness; (4) systematic testing of variables as predictors through the process of model building and refinement and (5) model critique, inference and synthesis using direct gradient analysis to evaluate the shape of response curves in the context of ecological theory by presenting predictions in both geographic and environmental space.

Conservation planning with irreplaceability: does the method matter?

A number of systematic conservation planning tools are available to aid in making land use decisions. Given the increasing worldwide use and application of reserve design tools, including measures of site irreplaceability, it is essential that methodological differences and their potential effect on conservation planning outcomes are understood. We compared the irreplaceability of sites for protecting ecosystems within the Brigalow Belt Bioregion, Queensland, Australia, using two alternative reserve system design tools, Marxan and C-Plan. We set Marxan to generate multiple reserve systems that met targets with minimal area; the first scenario ignored spatial objectives, while the second selected compact groups of areas. Marxan calculates the irreplaceability of each site as the proportion of solutions in which it occurs for each of these set scenarios. In contrast, C-Plan uses a statistical estimate of irreplaceability as the likelihood that each site is needed in all combinations of sites that satisfy the targets. We found that sites containing rare ecosystems are almost always irreplaceable regardless of the method. Importantly, Marxan and C-Plan gave similar outcomes when spatial objectives were ignored. Marxan with a compactness objective defined twice as much area as irreplaceable, including many sites with relatively common ecosystems. However, targets for all ecosystems were met using a similar amount of area in C-Plan and Marxan, even with compactness. The importance of differences in the outcomes of using the two methods will depend on the question being addressed; in general, the use of two or more complementary tools is beneficial.

Ecosystem greenspots: identifying potential drought, fire, and climate‐change micro‐refuges

In response to climate change and other threatening processes there is renewed interest in the role of refugia and refuges. In bioregions that experience drought and fire, micro-refuges can play a vital role in ensuring the persistence of species. We develop and apply an approach to identifying potential micro-refuges based on a time series of remotely sensed vegetation greenness (fraction of photosynthetically active radiation intercepted by the sunlit canopy; fPAR). The primary data for this analysis were NASA MODIS 16-day L3 Global 250 m (MOD13Q1) satellite imagery. This method draws upon relevant ecological theory (source sink habitats, habitat templet) to calculate a micro-refuge index, which is analyzed for each of the major vegetation ecosystems in the case-study region (the Great Eastern Ranges of New South Wales, Australia). Potential ecosystem greenspots were identified, at a range of thresholds, based on an index derived from: the mean and coefficient of variance (COV) of fPAR over the 10-year time series; the minimum mean annual fPAR; and the COV of the 12 values of mean monthly fPAR. These greenspots were mapped and compared with (1) an index of vascular plant species composition, (2) environmental variables, and (3) protected areas. Potential micro-refuges were found within all vegetation ecosystem types. The total area of ecosystem greenspots within the upper 25% threshold was 48 406 ha; around 0.2% of the total area of native vegetation (23.9 x 10(6) ha) in the study region. The total area affected by fire was 3.4 x 10(6) ha. The results of the environmental diagnostic analysis suggest deterministic controls on the geographical distribution of potential micro-refuges that may continue to function under climate change. The approach is relevant to other regions of the world where the role of micro-refuges in the persistence of species is recognized, including across the worlds arid zones and, in particular, for the Australian, southern African, and South American continents. Micro-refuge networks may play an important role in maintaining beta-diversity at the bio-region scale and contribute to the stability, resilience, and adaptive capacity of ecosystems in the face of ever-growing pressures from human-forced climate change, land use, and other threatening processes.

Optimisation and the selection of conservation contracts

This paper explores alternative techniques for the selection of conservation contracts under competitive tendering programs. Under these programs, purchasing decisions are often based on the benefits score and cost for proposed projects. The optimisation problem is to maximise the aggregate benefits without exceeding the budget. Because the budget rarely permits all projects to be funded, there is a binary choice problem, known in the operations research published work as a knapsack problem. The decision-maker must choose which projects are funded and which are not. Under some circumstances, the knapsack problem can be unsolvable because computational complexity increases exponentially with the number of projects. This paper explores the use of several decision rules for solving the optimisation problem including the use of advanced meta-heuristics. It is shown that commonly applied techniques for project selection may not be providing the optimal solution. Improved algorithms can increase the environmental programs benefits and staying within budget. The comparison of algorithms is based on real data from the Western Australian Conservation Auction.

Landscapes Toolkit: an integrated modelling framework to assist stakeholders in exploring options for sustainable landscape development

At present, stakeholders wishing to develop land use and management change scenarios at the landscape scale and to assess their corresponding impacts on water quality, biodiversity and economic performance, must examine the output of a suite of separate models. The process is not simple and presents a considerable deterrent to making such comparisons and impedes the development of more sustainable, multifunctional landscapes. To remedy this problem, we developed the Landscapes Toolkit, an integrated modelling framework that assists natural resource managers, policy-makers, planners and local communities explore options for sustainable landscape development. The Landscapes Toolkit links spatially-explicit disciplinary models, to enable integrated assessment of the water quality, biodiversity and economic outcomes of stakeholder-defined land use and management change scenarios. We use the Tully–Murray catchment in the Great Barrier Reef region of Australia as a case study to illustrate the development and application of the Landscapes Toolkit. Results show that the Landscapes Toolkit strikes a satisfactory balance between the inclusion of component models that sufficiently capture the richness of some key aspects of social-ecological system processes and the need for stakeholders to understand and compare the results of the different models. The latter is a prerequisite to making more informed decisions about sustainable landscape development. The flexibility of being able to add additional models and to update existing models is a particular strength of the Landscapes Toolkit design. Hence, the Landscapes Toolkit offers a promising modelling framework for supporting social learning and adaptive management through participatory scenario development and evaluation as well as being a tool to guide planning and policy discussions at the landscape scale.

Forests of East Australia: The 35th Biodiversity Hotspot

The newly identified “Forests of East Australia” Global High Biodiversity Hotspot corresponds with two World Wildlife Fund (WWF) Ecoregions: the Eastern Australian Temperate Forests and Queensland’s Tropical Rain forests. The region contains more than 1,500 endemic vascular plants, meeting the criterion for global biodiversity significance, and more than 70% of natural areas have been cleared or degraded, meeting the criterion for a hotspot. The hotspot, although covering a large latitudinal range (15.5°–35.6° South), has a predominantly summer rainfall pattern with increasing rainfall seasonality northwards into tropical areas of north Queensland. It covers large tracts of elevated tablelands and drier inland slopes, particularly in New South Wales, where it extends inland beyond the New England Tablelands and the Great Dividing Range. Varied soils result in a mosaic pattern of vegetation. Sclerophyllous communities dominated by Australia’s iconic plant, the gum-tree (Eucalyptus species), are the most prevalent vegetation type. Significant areas of rain forest exist throughout the region, much of which has persisted continuously since Gondwanan times, providing a rich living record of evolution over more than 100 million years. The human population of the hotspot as of 2006 was over nine million, with a population density of 36 people per square kilometer, mainly concentrated along the coast. About 18% of the land area is under some form of formal protection for its natural values. Gaps in the protected area network include some centers of plant endemism and some areas of critical habitat for threatened species. Whole of landscape conservation initiatives are enhancing connectivity throughout the Great Dividing Range through voluntary protection and restoration programs.

Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database

BackgroundMicrobial inhabitants of soils are important to ecosystem and planetary functions, yet there are large gaps in our knowledge of their diversity and ecology. The ‘Biomes of Australian Soil Environments’ (BASE) project has generated a database of microbial diversity with associated metadata across extensive environmental gradients at continental scale. As the characterisation of microbes rapidly expands, the BASE database provides an evolving platform for interrogating and integrating microbial diversity and function.FindingsBASE currently provides amplicon sequences and associated contextual data for over 900 sites encompassing all Australian states and territories, a wide variety of bioregions, vegetation and land-use types. Amplicons target bacteria, archaea and general and fungal-specific eukaryotes. The growing database will soon include metagenomics data. Data are provided in both raw sequence (FASTQ) and analysed OTU table formats and are accessed via the project’s data portal, which provides a user-friendly search tool to quickly identify samples of interest. Processed data can be visually interrogated and intersected with other Australian diversity and environmental data using tools developed by the ‘Atlas of Living Australia’.ConclusionsDeveloped within an open data framework, the BASE project is the first Australian soil microbial diversity database. The database will grow and link to other global efforts to explore microbial, plant, animal, and marine biodiversity. Its design and open access nature ensures that BASE will evolve as a valuable tool for documenting an often overlooked component of biodiversity and the many microbe-driven processes that are essential to sustain soil function and ecosystem services.

Efficiency and Concordance of Alternative Methods for Minimizing Opportunity Costs in Conservation Planning

Scarce resources and competing land-use goals necessitate efficient biodiversity conservation. Combining multicriteria analysis with conservation decision-support tools improves efficiency of conservation planning by maximizing outcomes for biodiversity while minimizing opportunity costs to society. An opportunity cost is the benefit that could have been received by taking an alternative course of action (i.e., costs to society of protecting an area for biodiversity rather than developing it for some other use). Although different ways of integrating multiple opportunity costs into conservation planning have been suggested, there have been no tests as to which method is most efficient. We compared the relative efficiency of 3 such procedures(Faith & Walker [1996], Sarkar et al. [2004], and a procedure of our own design) in a systematic conservation-planning framework for the Milne Bay Province of Papua New Guinea. We devised 14 opportunity costs and assigned these to 3 scenarios representing different conservation planning concerns: food security, macro-economic development, and biodiversity persistence. For each scenario, we compared the efficiency of the 3 methods in terms of amount of biodiversity protected relative to total expenditure for each opportunity cost. All 3 methods captured similar amounts of biodiversity, but differed in total cost. Our method had the least overall cost and was therefore most efficient. Nevertheless, there was a high correlation and geographical concordance among all 3 methods, indicating a high degree of spatial overlap. This suggests that choosing an appropriate approach may often depend on contextual factors related to the design of the planning question, rather than efficiency alone.

An Immunoglobulin G1 Monoclonal Antibody Highly Specific to the Wall of Cryptosporidium Oocysts

ABSTRACT The detection of Cryptosporidium oocysts in drinking water is critically dependent on the quality of immunofluorescent reagents. Experiments were performed to develop a method for producing highly specific antibodies to Cryptosporidium oocysts that can be used for water testing. BALB/c mice were immunized with six different antigen preparations and monitored for immunoglobulin G (IgG) and IgM responses to the surface of Cryptosporidiumoocysts. One group of mice received purified oocyst walls, a second group received a soluble protein preparation extracted from the outside of the oocyst wall, and the third group received whole inactivated oocysts. Three additional groups were immunized with sequentially prepared oocyst extracts to provide for a comparison of the immune response. Mice injected with the soluble protein extract demonstrated an IgG response to oocysts surface that was not seen in the whole-oocyst group. Mice injected with whole oocysts showed an IgM response only, while mice injected with purified oocyst walls showed little increase in IgM or IgG levels. Of the additional reported preparations only one, BME (2-mercaptoethanol treated), produced a weak IgM response to the oocyst wall. A mouse from the soluble oocyst extract group yielding a high IgG response was utilized to produce a highly specific IgG1 monoclonal antibody (Cry104) specific to the oocyst surface. Comparative flow cytometric analysis indicated that Cry104 has a higher avidity and specificity to oocysts in water concentrates than other commercially available antibodies.