Kristen Williams - Academia.edu (original) (raw)

Papers by Kristen Williams

These data provide rasterised layers of climatic variables hypothesised to explain spatial patter... more These data provide rasterised layers of climatic variables hypothesised to explain spatial patterns in biological diversity at continental scales for use with statistical modelling tools. Specifically, these data were derived for modelling the compositional pattern of multiple species with environmental factors such as climate, soil and topography using the statistical technique Generalised Dissimilarity Modelling applied to continental Australia. Climate variables are monthly mean values for minimum temperature, maximum temperature, relative humidity, vapour pressure, precipitation, aridity, solar radiation, evaporation, wind and others. Some of these monthly variables were used to generate growth indices (using the GROCLIM module of ANUCLIM). These data for Generalised Dissimilarity Modelling (GDM) analysis were masked to consistently define data/nodata values and supplied in DIVA-GIS floating-grid format in the WGS84 geographic reference system. NOTE: Full details of the data, wi...

Composite ecological change as a function of three metrics (the potential degree of ecological ch... more Composite ecological change as a function of three metrics (the potential degree of ecological change and of disappearing and novel ecological environments) shows where change might be greatest and different types of vulnerability using 30-year climate averages between the present (1990:1976- 2005) and projected future (2050:2036-2065) under the CanESM2 global climate model (RCP 8.5), based on a Generalised Dissimilarity Modelling (GDM) of compositional turnover for reptiles (REP_R3_V2). Wherever the Potential degree of ecological change is scored low, ecological environments can neither be novel nor disappearing and minimal change is expected. But when the Potential degree of ecological change is scored high, a variety of possible types of change can occur depending on whether scores for Novel and/or Disappearing ecological environments are also high. To create a composite view, we assigned each of the three component measures to a colour band in a composite-band raster: local simi...

Remote Sensing

The growth of citizen science presents a valuable potential source of calibration and validation ... more The growth of citizen science presents a valuable potential source of calibration and validation data for environmental remote sensing at greater spatial and temporal scales, and with greater cost efficiency than is achievable by professional in situ reference-data collection alone. However, the frequent mismatch between in situ data-quality requirements for remote-sensing-product development and current data quality assurance in citizen science presents a significant challenge if widespread use of these complementary data sources is to be achieved. To evaluate the scope of this challenge, we conducted a targeted literature review into the nature of data-quality issues faced by citizen-science projects for routine incorporation into terrestrial environmental-monitoring systems. From the literature, we identify the challenges and trade-offs to inform best-practice implementation of data quality assurance in citizen-science projects. To assist practitioners in implementing our finding...

Representation within the National Reserve System 2015 for Vascular Plants as a function of curre... more Representation within the National Reserve System 2015 for Vascular Plants as a function of current climate and climate change based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric represents a measure of the support provided for the ecological environments of each grid cell by the NRS. A full description of the project can be found in the report "Assessing the ecological representativeness of Australia's terrestrial National Reserve System: A community-level modelling approach" by KJ Williams, TD Harwood & S Ferrier (2016) at https://publications.csiro.au/rpr/pub?pid=csiro:EP163634 Four subfolders are provided: 1. P maps: 9s resolution mapping of cellwise P metric for representation of the environment of each cell within the NRS based on a GDM model of Vascular Plants. 2. IBRA maps: 9s resolution mapping of summary statistics (17: proportion 17% represented and Geometric Mean: P metric summarised by region) with single value applied to all cells within each IBRA bioregion. 3. IBRASUB maps: 9s resolution mapping of summary statistics (17: proportion 17% represented and Geometric Mean: P metric summarised by region) with single value applied to all cells within each IBRA subregion. Format ESRI float grids 4. Summary statistics: Regional statistics and histograms of distribution of values within IBRA bioregions and IBRA subregions. Format: Microsoft Excel spreadsheets. Files contain a row for each numbered region. Statistics files show the Geometric and Arithmetic Mean, the proportion of each region achieving target representation and the Maximum and Minimum cellwise representation within each region.

Novel ecological environments for Vascular Plants as a function of change in long term (30 year a... more Novel ecological environments for Vascular Plants as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the CanESM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the nature of the projected 2050 centred future environmental conditions for each 9s grid square. Using a Generalised Dissimilarity Model of compositional turnover (the effects of changing environment on changing species), each future location is compared with the continent in the present. For each cell, the metric looks out to all other cells in the continent, and records the ecological similarity of the future state of the cell to the most similar cell in the present. A value of 1 indicates that the future environment is similar to a current location in the present, and perfect analogue can found somewhere in Australia. A value of 0 indicates that the most similar environment to be found in the present is ecologically so different that we would expect no species in common, i.e. there are no current analogues for this environment; it is novel. Intermediate values show how ecologically similar the most similar cell is. However, no weight is given to the proximity of the most similar cell. The environment may be similar, but the cells thousands of kilometres apart. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide "Implications of Climate Change for Biodiversity: a community-level modelling approach", available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extracting from the zip archive, these files can be imported into most GIS s [...]

Potential degree of ecological change in Vascular Plants as a function of change in long term (30... more Potential degree of ecological change in Vascular Plants as a function of change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the CanESM2 model (RCP 8.5) based on Generalised Dissimilarity Modelling (GDM) of compositional turnover. This metric describes the change in long term average environmental conditions at a single location (9s grid square) from the present (1990 centred) to a 2050 centred future, scaled in terms of its expected effects on the turnover of species. Compositional turnover patterns in amphibian species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extracted from the Atlas of Living Australia (ALA) in 2013, and spatial environmental predictor data compiled at 9 second resolution. GDM-scaled environmental grids were used as the basis for pairwise cell comparisons across space and time using the highly parallel CSIRO Muru software to derive the potential degree of ecological change. Each location is compared with its future state. The difference in environment is presented as an expected ecological similarity, ranging from 1 (completely similar) to 0, for which we would expect no species in common. If this environmental difference was observed in a different spatial location within the present, we would expect to observe such a difference if we visited both sites. This metric was developed along with others for use in an assessment of the efficacy of the protected area system for biodiversity under climate change at continental and global scales, presented at the IUCN World Parks Congress 2014. It is described in the AdaptNRM Guide "Implications of Climate Change for Biodiversity: a community-level modelling approach", available online at: www.adaptnrm.org. Data are provided in two forms: 1. Zipped ESRI float grids: Binary float grids (*.flt) with associated ESRI header files (*.hdr) and projection files (*.prj). After extractin [...]

International Journal of Geographical Information Science, Aug 26, 2015

The Atlas of Living Australia (ALA: http://www.ala.org.au) provides the largest free and open rep... more The Atlas of Living Australia (ALA: http://www.ala.org.au) provides the largest free and open repository of integrated biological and environmental information in a consistent format for the Australian region. As of June 2015, the ALA contained over 55 million records (10% of Global Biodiversity Information Facility’s (GBIF’s) total), consisting of 150,000+ native and alien species, nearly 500 layers of gridded and polygonal bio-environmental data, 39+ million pages of biological literature, and 45,000+ images of species and other integrated biological data. The development of the research interface to the ALA (http://spatial.ala.org.au) was the trigger to develop an architecture designed to tightly integrate environmental data for online use with biological data. Environmental layers are classed as environmental (gridded with continuous values) or contextual (polygonal with discrete class values). A suite of analysis and visualization tools have been developed to demonstrate the value of integrating the ALA’s biological and environmental data. This paper outlines the purpose and process of establishing the ALA and discusses the integration of environmental data relevant to biodiversity research in the Australian region and the vision for continually improved services for research, area management, education, and citizen science. The ALA’s environmental infrastructure addresses current needs but increased data types, volumes, and resolution suggests new directions are needed to provide quality services into the future. The experience of building the ALA has relevance for other agencies setting up similar infrastructure which supports integrated access to and use of their national biological and environmental information.

Global biodiversity is in decline and businesses are being asked to urgently create new operating... more Global biodiversity is in decline and businesses are being asked to urgently create new operating models to ameliorate the crisis. Amongst the strategies proposed to do this, the development of an economy that is 'nature-positive' has captured worldwide attention. Publicised as biodiversity's catch-all equivalent for a carbon net-zero future, organisations from the Taskforce on Nature-related Financial Disclosures to the World Economic Forum are calling for a transition to nature-positive, but little guidance exists as to what this means and how to do it. In this article, we outline financial opportunities, ecological concepts, and risks underpinning aspirations for a nature-positive economy, including seven financial instruments, and four ecological concepts that form the foundation of nature-positive (health, abundance, diversity, and resilience). We then outline six classes and 30 drivers of risk that could arise through poor design or implementation of the nature-positive economy, and touch on mitigation measures to prevent these.

Methods in Ecology and Evolution, May 18, 2016

Summary Consistent and repeatable estimation of habitat condition for biodiversity assessment acr... more Summary Consistent and repeatable estimation of habitat condition for biodiversity assessment across large areas (i.e. regional to global) with limited field observations presents a major challenge for remote sensing (RS). RS can describe what a site looks like and how it behaves (using time series), but is unable to distinguish anthropogenic impacts from natural dynamics. Consequently, it is possible to mistake a heavily degraded habitat for a natural habitat, for example a logged forest may appear identical to an intact open woodland. This problem is compounded by the existence of multiple natural states in any given environment, and spatial variation in the natural composition and structure of vegetation as a function of variation in environment. Uncertainty in assessing habitat condition from RS is often further exacerbated by sparseness in the spatial coverage of training data. We describe a novel generic, RS‐based algorithm called Habitat Condition Assessment System, designed to address the above sources of uncertainty and to be highly flexible in its application. It allows for variability in the definition of condition and in the type and quantity of input data employed. Here, we demonstrate the mechanics of the new algorithm in a simple worked example and its practical application in a case study using inferred ‘natural‐only’ reference data, reflective remotely sensed data, and associated environmental data, to map condition for Australia at a 0·01° resolution. We assess the behaviour and shortcomings of the method, and compare the national case study with estimates from two existing national data sets, and field measured condition data observed at 16 967 sites across the State of Victoria. The modelled predictions outperform both of the existing national data sets, explaining 52% of the variability in field observations for well‐sampled cells (relative to 8% and 12% for the existing products). The methodology can potentially address some of the key pitfalls of condition modelling and could be applied in other regions with sufficient coverage of reference data. The approach also has good potential to be extended to work with reference data for which condition is measured on a continuous scale, for example from field‐based condition assessment initiatives.

Environmental Research Letters, Feb 1, 2019

Essential biodiversity variables (EBV) are information products for assessing biodiversity change... more Essential biodiversity variables (EBV) are information products for assessing biodiversity change. Species populations EBVs are one class of EBVs that can be used to monitor the spread of invasive species. However, systematic, reliable, repeatable procedures to process primary data into EBVs do not yet exist, and environmental research infrastructures still must improve their capabilities to deliver EBV data products. Here, we tested the ability of two mature biodiversity data infrastructures, the Global Biodiversity Information Facility and the Atlas of Living Australia, to cooperatively produce EBV data products for three alien invasive species. We detailed workflow steps to discover, filter, retrieve and prepare the primary data before evaluating species' distributional changes. The two data infrastructures were able to execute several workflow steps, but external tools, third-party sources and expert judgement were required, and a repeatable workflow was difficult to establish. Nevertheless, the resulting data products revealed strong range expansions for the invasive species, demonstrating the policy-relevant information about global environmental change that can be provided by EBV data products. Our results show that more coordination between infrastructure providers is needed to efficiently produce EBV-ready data products for invasion monitoring in a repeatable fashion. Addressing these issues will allow improved tracking of invasive species range dynamics and hence monitoring of ongoing global biodiversity change.

CSIRO advises that the information contained in this publication comprises general statements bas... more CSIRO advises that the information contained in this publication comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CSIRO (including its employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it.

Global Change Biology, 2021

Globally, collapse of ecosystems—potentially irreversible change to ecosystem structure, composit... more Globally, collapse of ecosystems—potentially irreversible change to ecosystem structure, composition and function—imperils biodiversity, human health and well‐being. We examine the current state and recent trajectories of 19 ecosystems, spanning 58° of latitude across 7.7 M km2, from Australia's coral reefs to terrestrial Antarctica. Pressures from global climate change and regional human impacts, occurring as chronic ‘presses’ and/or acute ‘pulses’, drive ecosystem collapse. Ecosystem responses to 5–17 pressures were categorised as four collapse profiles—abrupt, smooth, stepped and fluctuating. The manifestation of widespread ecosystem collapse is a stark warning of the necessity to take action. We present a three‐step assessment and management framework (3As Pathway Awareness, Anticipation and Action) to aid strategic and effective mitigation to alleviate further degradation to help secure our future.

Remote Sensing

International Journal of Geographical Information Science, Aug 26, 2015

Methods in Ecology and Evolution, May 18, 2016

Environmental Research Letters, Feb 1, 2019

Global Change Biology, 2021