Showing results for: [ Conservation and Biodiversity ]
Bio-physical, ecological and social information have been used to parameterise two computer models able to simulate (ALCES and Ecopath with Ecosim [EwE]) land, coastal and marine processes. A careful ... moreexamination of a large volume of publications from the academic, private and public sector has also allowed us to identify a number of climate and social economic development scenarios the Kimberly region may experience in the decades to comeless
WAMSI-Kim 2.2.8 MSE Modelling Knowledge - MSE modelling and ecosystem modelling - Published 22 Nov 2019
Vegetation Fractional Cover represents the exposed proportion of Photosynthetic Vegetation (PV), Non-Photosynthetic Vegetation (NPV) and Bare Soil (BS) within each pixel. The sum of the three fraction... mores is 100% (+/- 3%) and shown in Red/Green/Blue colors. In forested canopies the photosynthetic or non-photosynthetic portions of trees may obscure those of the grass layer and/or bare soil. This product is derived from the MODIS Nadir BRDF-Adjusted Reflectance product (MCD43A4) collection 6 and has 500 meters spatial resolution.
A suite of derivative products are also produced including monthly fractional cover, total vegetation cover (PV+NPV), and anomaly of total cover against the time series.
Monthly: The monthly product is aggregated from the 8-day composites using the medoid method.
Anomaly: represents the difference between total vegetation cover (PV+NPV) in a given month and the mean total vegetation cover for that month in all years available, expressed in units of cover. For example, if the mean vegetation cover in January (2001-current year) was 40% and the vegetation cover for the pixel in January 2018 was 30%, the anomaly for the pixel in Jan 2018 would be -10%.
Decile: represents the ranking (in ten value intervals) for the total vegetation cover in a given month in relation to the vegetation cover in that month for all years in the time-series.
MODIS fractional cover has been validated for Australia. less
DoAWR - Improving the RaPP Map monitoring tool for Australia - - Published 11 Nov 2019
Reproduction and recruitment underlie the maintenance of biological communities. For most marine organisms the ocean environment provides the potential for widespread dispersal of organisms during var... moreious life cycle stages via currents, tides and wind.
Within the Kimberley region, key biological communities have a range of reproductive modes. Understanding patterns of larval connectivity is critical to managing the exposure of biological communities to disturbances in space and time.
KSN Project 1.1.3 employed genomic tools (microsatellite DNA markers and single nucleotide polymorphisms) and microchemistry to provide the first comprehensive measurements of the distances moved by marine organisms between Kimberley reefs, and how frequently organisms move between the Kimberley and other regions (e.g. offshore shoals, the Pilbara). The research also identified potential barriers to movement. Seven organisms (two
hard corals, two seagrasses, a mollusc, two fishes) were chosen as models for exploring connectivity in the Kimberley at both fine and broad scales.
This metadata record applies to three of the seven species investigated as part of project WAMSI 2 KSN 1.1.3. The data held is Raw SNP genotype. Metadata records associated with other species and lodged by AIMS, WA Museum, Curtin University, Department of Fisheries (WA) and Edith Cowan University can be accessed via Pawsey.
WAMSI-Kim 1.1.3 Ecological connectivity - Survey - Published 25 Oct 2019
Datasets of standing dead tree and down woody debris attributes from the multi-century Eucalyptus salubris (gimlet) time since fire chronosequence in the Great Western Woodlands, south-western Austral... moreia. These data include measures of piece sizes, densities, volumes and biomass, and have been used in the publication:
Gosper, C.R., Yates C.J., Fox, E. and Prober, S.M. (in press) Time since fire and prior fire interval shape coarse woody debris dynamics in obligate-seeder woodlands. Ecosphereless
TERN: Great Western Woodlands - Eucalyptus salubris chronosequence - Published 20 Sep 2019
This collection comprises two components. These are spatial projections of the estimated patterns in species richness for two subterranean faunal groups, across the Pilbara region of Australia: (1) st... moreygofauna; (2) troglofauna. These spatial layers were created as part of a collaborative research project between CSIRO and BHP to improve our understanding of diversity patterns of subterranean fauna in he Pilbara region.
Pilbara Community Level Modelling - - Published 04 Sep 2019
Dataset of bird survey results at the multi-century Eucalyptus salubris (gimlet) chronosequence in the Great Western Woodlands, south-western Australia. This data has been used to describe responses o... moref bird species, functional groups and community composition to time since fire (Gosper et al. 2019 Biol Cons 230, 82-90; Gosper et al. in press Ecol Appl). less
TERN: Great Western Woodlands - - Published 02 Aug 2019
Online survey data from Australian residents, distributed nationally, in October 2017. Rating scores of aesthetic beauty are provided for 181 coral reef images that featured a set of specific attribut... morees that were tested as correlates of aesthetic beauty ratings.less
NESP TWQ - 5.6 - Design of an aesthetics long term monitoring program - - Published 29 May 2019
These images of terrestrial biodiversity habitats across Australia relate to a project that aimed to construct and test a method for habitat condition data capture across Australia using expert elicit... moreation. The images in this collection were assembled from various sources to represent habitats from a wide variety of vegetation types and climates in a variety of different condition states (from ‘good’ to ‘poor’). These images represent a continent-wide library suitable for various purposes, including training and validation of model-based approaches to habitat condition assessment.less
Habitat condition data capture using expert elicitation - National Reference Library of Expert Site Condition Assessments - Published 23 May 2019
Land that is owned or managed by Australia’s Indigenous communities, or over which Indigenous people have use and rights, was compiled from information supplied by Australian, state and territory gove... morernments and other statutory authorities with Indigenous land and sea management interests. Indigenous land and sea interests was comprised of:
a) Indigenous tenure for Australia (Aboriginal Reserve, Aboriginal Deed of Grant, Aboriginal Freehold Land (inalienable and alienable), Aboriginal Local Government Lease, Aboriginal held lease (other than pastoral), Aboriginal held pastoral lease, Multi feature Aboriginal freehold – National Parks) (1,105,992 km2);
b) Indigenous Protected Areas IPAs including sea country (684,124 km2);
c) Native title outcomes for areas within determinations
a. exclusive possession (851,117 km2), and
b. non-exclusive possession (1,500,776 km2) ;
d) Collaborative Australian Protected Areas Database 2014 – (Aboriginal Areas, and National Park Aboriginal) – (16,790 km2).
Note 1: overlaps have been removed between tenure types (a-d).
Note 2: Registered native title claims (yet to be determined) and Indigenous Land Use Agreements (ILUAs) are excluded
DoE: RFQ 1415-0422 Lead authors for biod - Spatial analysis of Indigenous land interests - Published 03 Apr 2019
These data relate to a project that aimed to construct and test a method for habitat condition data capture across Australia using expert elicitation. The data derived from experts are in two forms: (... more1) habitat condition scores for specified areas at a specified date range, and; (2) habitat condition scores based on images (photographs) of ecosystems. The image based habitat condition data were collected to enable cross-calibration of contributed site assessment data. These data represent the start of a continent-wide library of ecological condition data suitable for training and validation of model-based approaches to habitat condition assessment.less
Habitat condition data capture using expert elicitation - National Reference Library of Expert Site Condition Assessments - Published 05 Mar 2019
SELTMP is assisting Reef managers and other decision-makers within the Great Barrier Reef region to incorporate the human dimension into their planning and management. Analogous to the Australian Cens... moreus, SELTMP gathers long-term data specific to Reef users, communities and industries, enabling new insights into relationships, vulnerabilities and dependencies between people and the natural resources.less
SELTMP II Social and economic long term monitoring program for the GBR - - Published 26 Feb 2019
The Secretariat to the Australian Landcare Council provided a table summarising government and non-government investment programs in ILM. We used this table to guide our searching of web sites and oth... moreer documents to compile an Excel spreadsheet which now includes 2,229 records of separate projects. We were not able to source complete data on a number of the identified sources of investment, including those from State governments, investments by private corporations and not-for-profit organisations. Nevertheless, the data set is the most comprehensive that has ever been assembled on ILM in Australia. While substantial literature exists on Indigenous land management, the relevant documents are widely scattered across internet sites, in diverse State and Territory jurisdictions, in regional and local government and non-government organisations, and across sectoral boundaries (e.g. water management reports, biodiversity management reports). We anticipate that the opportunities and barriers faced by Indigenous land managers may vary across locations, sectors and local/regional/national scales. A simple national maps was produced demonstrating the locations of specific studies contained within reviewed literature. less
CLSD 1173.3 DAFF Indigenous land manag - Spatial analysis of the investment of funding for Indigenous land and sea managment - Published 11 Feb 2019
This dataset contains anonymised, expert elicited data about the management effectiveness of 19 Key Threatening Processes listed under the NSW Biodiversity Conservation Act 2016. Two key pieces of inf... moreormation are generated using the data and the associated R and Matlab code: (1) the expected effectiveness of management under current uncertainty, and (2) the expected value of removing uncertainty about management. Full details of the analysis are contained in the report: Nicol S, Brazill-Boast J, Gorrod E, McSorley A, Peyrard N, Chadès I (2018). Prioritising research and management of key threatening processes and listed species using value of information. CSIRO, Brisbane.less
A value of information analysis to determine the species that would benefit the most from an adaptive management program - - Published 24 Dec 2018
Raw photographs and georectified orthopotographs of three wetland sites on the Kakadu Flood Plain, East Alligator section. Flights captured areas that are under intensive weed management regimes (aer... moreial spraying and ground spraying) to control Para grass (Urochloa mutica).less
Nthn NESP 5.5 Kakadu bushtucker monitoring - UAS photographs - Published 12 Dec 2018
These data provide rasterised layers of edaphic (physical and chemical conditions of the soil) and land surface physiography (landform and geomorphology) attributes hypothesised to explain spatial pat... moreterns in biological diversity at continental scales for immediate use with statistical modelling tools. These data are intended to be used along with a similarly compiled and spatially standardised set of climatic layers (See " 0.01 degree stack of climate layers for continental analysis of biodiversity pattern: version 1.0 " in related materials).NOTE: Full details of the data, with a list of data sources and bibliography, are provided in a PDF file included as part of the data collection.less
Closed DEWHA Harness Cntnnt-wide Bdvrsty - Spatial Environmental Data Preparation - Published 11 Dec 2018
This data collection is the source data for the manuscript "Shifting the conservation paradigm - a synthesis of options for renovating nature under climate change" by Suzanne M. Prober, Veronica A. J.... more Doerr, Linda M. Broadhurst, Kristen J. Williams, Fiona Dickson and published in the peer-reviewed journal "Ecological Monographs" in 2018. The data are provided as an excel spreadsheet with three sheets. The results are provided in "SourceData_Prober_etal_EcolMono" including the cited references (peer-reviewed journal articles). The full citation of each reference is given in Appendix S1 of the manuscript (and on tab 3). less
Decision Pathways - Ecosystem Engineers - A synthesis component to review established and emerging ecological engineering options - Published 31 Aug 2018
Land-use change due to agriculture has a major influence on arthropod biodiversity, and may influence species differently depending on their traits. It is unclear how species traits vary across differ... moreent land uses and their edges, with most studies focussing on single habitat types and overlooking edge effects. We examined variation in morphological traits of carabid beetles (Coleoptera:Carabidae) on both sides of edges between woodlands and four adjoining, but contrasting farmland uses in an agricultural landscape. less
Legacy data - - Published 24 Jun 2018
Seasonal differences in beetle assemblages and the vegetation community in woodland remnants compared with four adjoining farmland uses. Study area was a highly modified agricultural landscape in elev... moreen sites in the Lachlan River Catchment, New South Wales, Australia.
Seasonal differences in beetle assemblages and the vegetation community in woodland remnants compared with four adjoining farmland uses. Study area was a highly modified agricultural landscape in eleven sites in the Lachlan River Catchment, New South Wales, Australia. Our survey design consisted of four 400 m transects running from inside each patch out into the adjoining farmland. We sampled beetles and vegetation at three locations along each transect: 200 m inside the patch, 200 m inside the farmland, and 0 m at the patch-farmland boundary.
We sampled from the same trap location during two distinct periods in terms of plant phenology and agronomic practices in farmland: spring when crops and spring-active species were at peak growth, and summer when crops have been harvested (stubble retained; fine woody debris treatment applied) and summer-active species at peak growth. Each sampling location comprised a pair of pitfall traps, consisting of plastic jars (6.5 cm diameter, 250 ml) dug into the ground with the rim level with the soil surface, filled with 100 ml of preservative (1:3 glycol – water mixture, and a drop of detergent to reduce surface tension). Individual traps from each pair were placed on either side of a drift fence (60 cm long x 10 cm high) to help direct arthropods into the trap. We opened a total of 132 pairs of traps (11 replicate sites x 4 transects x 3 trap pairs) for 14 days during spring (October–November 2014) and summer (January–February 2015).
During beetle sampling in spring and summer, the same observer (KN) recorded: (1) six vegetation structural variables (vegetation height and cover of litter, native forb, native grass, exotic perennial grasses, exotic annual forbs and grasses) within a 20 × 10 m plot centred around the sampling location (Table 1); and (2) the composition of all plant species from five 1 × 1 m quadrats placed randomly within each 20 × 10 m plot. Plant species composition data were pooled from these quadrats for each sampling location.
Our survey design consisted of four 400 m transects running from inside each patch out into the adjoining farmland. We sampled beetles and vegetation at three locations along each transect: 200 m inside the patch, 200 m inside the farmland, and 0 m at the patch-farmland boundary. Individual traps from each pair were placed on either side of a drift fence (60 cm long x 10 cm high) to help direct arthropods into the trap. Traps were plastic jars (6.5 cm diameter, 250 ml) dug into the ground with the rim level with the soil surface, filled with 100 ml of preservative (1:3 glycol – water mixture, and a drop of detergent to reduce surface tension). We sampled from the same pitfall trap locations during two distinct periods of the cropping cycle: spring when crops were at peak flowering, and summer after crop harvest (stubble retained). less
Legacy data - - Published 13 Mar 2018
Seasonal differences in beetle assemblages in woodland remnants compared with four adjoining farmland uses in a highly modified agricultural landscape in eleven sites in the Lachlan River Catchment, N... moreew South Wales, Australia. We used a split-plot sampling design where each remnant patch was matched with the four different farmland matrix types. We sampled beetles along a 400 m transect from 200 m in each patch out into 200 m in each of the four adjoining farmland matrix types. We then sampled beetles with a pair of pitfall traps located at each end of the transect: 200 m inside the remnant patch and 200 m in the adjoining farmland matrix. Individual traps from each pair were placed on either side of a drift fence (60 cm long x 10 cm high) to help direct arthropods into the trap. Traps were plastic jars (6.5 cm diameter, 250 ml) dug into the ground with the rim level with the soil surface, filled with 100 ml of preservative (1:3 glycol – water mixture, and a drop of detergent to reduce surface tension). We sampled from the same pitfall trap locations during two distinct periods of the cropping cycle: spring when crops were at peak flowering, and summer after crop harvest (stubble retained). A total of 88 pairs of traps (11 replicate sites x 4 transects x 2 trap pairs) were opened for 14 days during spring (October–November 2014) and summer (January–February 2015).
Acquired - - Published 07 Nov 2017
Temporal patterns of species richness, abundance, and movement across edges between remnant woodlands and four farmland uses (plantings, fallow, annual crops, woody debris applied over crops post
harv... moreest) in southeastern Australia. Directional pitfall traps allow inference of movement (by looking at relative abundance in traps on either side of drift fences). Beetles were sampled at edges, and 20 m and 200 m on both sides of edges, during spring and summer in eleven sites within the Lachlan River Catchment, New South Wales, Australia.less
Legacy data - - Published 30 Oct 2017
This collection contains 3-arcsecond gridded datasets (ESRI binary float format in WGS84) showing the baseline (1990-centred) predicted potential distribution of 102 (class numbers range between 1 and... more 125) "Keith" Vegetation Classes for New South Wales based on their correlation with baseline ecological environments (c.1990 climates, substrate and landform). The vegetation patterns and classification derive from a map for NSW compiled by David Keith. A kernel regression was used with a geographically even sample of 9,951 locations of training classes for the 102 classes attributed with 21 GDM-scaled environmental predictors for Vascular Plants representing baseline ecological environments. The training class data input to the kernel regression is provided with this package. The GDM-scaled environmental predictors, source biological data and model fit parameters are also provided with the data package. Using the 1990 baseline training class data, and without constraining the prediction to pre-existing map boundaries, the kernel regression predicted the potential distribution of the 102 Vegetation Classes using 1990-centred (30 year average) baseline climates derived from ANUCLIM v6.1 (Xu and Hutchinson 2011) and soil/geology/landform attributes. The kernel regression generates unconstrained probabilities varying in the range from 0 and up to 1 for each of the 102 classes. The data are provided as 3-arcsecond (approximately 90m), ESRI binary float grid format in WGS84. Each class is denoted “UNCON###”, where the number refers to the code originally assigned to that class in the vegetation map. A lookup table linking the vegetation classes to the output codes and descriptive title is provided. The methods are described in "Doerr, VAJ, Williams, KJ, Drielsma, M, Doerr, ED, Davies, MJ, Love, J, Langston, A, Low Choy, S, Manion, G, Cawsey, EM, McGinness, HM, Jovanovic, T, Crawford, D, Austin, M & Ferrier, S 2013, Designing landscapes for biodiversity under climate change: Final report, National Climate Change Adaptation Research Facility, Gold Coast, 260 pp.". A plain English description of the method used (but applied Nationally) can be found in the AdaptNRM Guide “Helping biodiversity adapt to climate change: a community-level modelling approach”, available online at: www.adaptnrm.org. Source of vegetation class data: KEITH, D. A. (2002) A compilation map of native vegetation for New South Wales. NSW Biodiversity Strategy, New South Wales Government. KEITH, D. A. (2004) Ocean shores to desert dunes, Hurstville, Department of Environment and Conservation (NSW).
1157.1 TB NARP Best Practice Landscape - Macroecological modelling of vegetation patterns using GDM and kernel regression - Published 01 Aug 2017
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 turno... morever.
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.
Assessing present and future representation of terrestrial biodiversity within Australia's National Reserve System - GDM-based assessment of National Reserve System Representativeness - Published 14 Jun 2017
In April 2014 and March 2015 surveys of coral populations were undertaken at Enderby and West Lewis Islands in the Dampier Archipelago, Western Australia. The corals investigated in this study were Ac... moreropora millepora, Turbinaria mesenterina and massive Porites spp. (mainly P. lobata and P. lutea). For each species, population size-frequency distributions were obtained by recording the size of all colonies within a one metre distance on either side of permanent transects (60 m2). Using the permanent transect as a reference point, the locations of all colonies were recorded, and all colonies were tagged, measured and photographed. Tagged colonies were re-located and re-measured approximately one year later. A total of 737 corals were examined; 473 corals from Enderby Island and 264 from West Lewis Islands. Similar numbers of massive Porites (279), T. mesenterina (229) and A. millepora (272) colonies were tagged. Of the colonies tagged 733 corals were re-located a year later and assessed for survival, growth, partial mortality and fission.less
WAMSI-Dredg T4 Coral response - Demographic processes in corals of Dampier Archipelago - Published 16 May 2017
This collection contains AdaptNRM biodiversity change datasets and maps contextualised for Tasmania and surrounding Islands, and specifically: novel ecological environments, disappearing ecological en... morevironments, and composite ecological change datasets and maps for amphibians, reptiles, mammals, and vascular plants. The Tasmania extent of the equivalent ‘Potential degree of ecological change’ datasets are also included for completeness, although identical to the national datasets. Ecological change is derived from change in long term (30 year average) climates between the present (1990 centred) and projected future (2050 centred) under the MIROC5 and CanESM2 global climate models (RCP 8.5), scaled using Generalised Dissimilarity Modelling (GDM) of compositional turnover for four biological groups (GDMs: AMP_r2_PTS1, MAM_r2, REP_r3_v2, and VAS_v5_r11). The source GDM models are listed in related materials below (AMP_V2_R2 is the same as the model also denoted ‘AMP_r2_PTS1’; REP_V2_R3 is the same as REP_r3_v2; MAM_V1_R2 is the same as MAM_r2). The equivalent national datasets for novel and disappearing ecological environments, composite ecological change and Potential degree of ecological change are also listed in related materials below.
NOVEL ECOLOGICAL ENVIRONMENTS: this metric describes the nature of the projected 2050-centred future environmental conditions for each 9s grid cell. Using each cell of a GDM projection surface, the metric looks out to all other cells in the specified region, and records the ecological similarity of the future state of the cell to the most similar cell in the present (1990-centred). A novel ecological environment is a possible new ecological environment scaled by ecological similarity that may arise in the future but which doesn’t exist anywhere at present.
DISAPPEARING ECOLOGICAL ENVIRONMENTS: this metric describes the extent to which the long term average environmental conditions for each 9s grid cell in the present (1990-centred) will be present in a projected 2050 centred future. For each cell of a GDM, the metric looks out to all other cells in a specified region, and records the ecological similarity of the present state of the cell to the most similar cell in the future. A disappearing ecological environment is a present-day ecological environment scaled by ecological similarity that may become absent in the future.
COMPOSITE ECOLOGICAL CHANGE: this metric is a composite measure that integrates the Potential degree of ecological change with the degree to which ecological environments are becoming novel or disappearing, showing where different combinations of change may occur and how extreme that change may be.
A technical report for the project provides details about the rationale, methods and data. Further details are 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). 2. GeoTIFF files (*.tif). After extracting from the zip archive, these files can be imported into most GIS software packages. Component measures are provided in both ESRI float and GeoTiff formats, while composite rasters are provided in GeoTiff format.
Datasets in this series use a consistent naming convention: see the file readme_filenames.txt for a full explanation.
Readme and xml files for how to reproduce the 3-band colours in the composite measure are also provided.
Higher resolution images used in the technical report are also provided. less
Customised AdaptNRM biodiversity impact datasets for Tasmania - Ecological Change Modelling - Published 26 Apr 2017
Compositional turnover patterns in mammal species across continental Australia were derived using Generalised Dissimilarity Modelling (GDM). These models use best-available biological data extracted f... morerom the Atlas of Living Australia current to 26th February 2014 and spatial environmental predictor data compiled at 9 second resolution (with novel climate seasonality predictors, undersampling covariates and >3 species aggregated per 9-second grid cell). The models were developed to underpin continental assessments of biodiversity significance and identify gaps in biological surveys. GDM is a statistical technique that models the dissimilarity in composition of species between pairs of surveyed locations, as a function of environmental differences between these locations. The compositional dissimilarity between a given pair of locations can be thought of as the proportion of species occurring at one location that do not occur at the other location (averaged across the two locations) - ranging from ‘0’ if the two locations have exactly the same species through to ‘1’ if they have no species in common. GDM effectively weights and transforms the environmental variables such that distances between locations in this transformed multidimensional environmental space now correlate, as closely as possible, with the observed biological compositional dissimilarities between these same locations. Once a GDM model has been fitted to the biological data from the sampled locations using environmental predictor data, it can be used to predict compositional dissimilarity values for sites lacking biological data, based purely on their mapped environmental attributes. For this purpose, a set of GDM-scaled environmental grids are produced for use in subsequent spatial assessments of biodiversity significance. This collection includes the source biological and environmental data, the GDM-fitted model, the GDM-scaled environmental predictors for the fitted-model which comprises substrate (constant) and 1990-centred climates, and a derived classification. Projections using past and future climates are not included here (available upon request). This model was used in the AdaptNRM series of reports by Williams et al. (2013) and Prober et al. (2014). less
1173.3 Strat: WPC Global Prot Area Ass - Macroecological Modelling - Published 09 Jan 2017