TECHNICAL REPORT 3 • JULY 2015 Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
TECHNICAL REPORT 3 • JULY 2015
EXCERPT FROM A REPORT ON BIODIVERSITY PRIORITISATION ANALYSIS: Modelling Species and Threatened Ecological Plant Communities in the Hunter, Central & Lower North Coast Region of New South Wales
A This report was prepared for the Hunter and Central Coast Regional Environmental Management Strategy
This report has been funded through the Australian Government’s Biodiversity Fund
Authors: Dr Amy Whitehead, Dr Heini Kujala, Dr Brendan Wintle, University of Melbourne, NERP Environmental Decision Hub
The NERP Environmental Decisions Hub is supported through funding from the Australian Government’s National Environmental Research Program www.environment.gov.au/nerp and involves researchers from the University of Western Australia, The University of Melbourne, RMIT University, The Australian National Univeristy, The University of Queensland and CSIRO.
Enquiries to: Hunter & Central Coast Regional Environmental Management Strategy c/o- Environment Division Hunter Councils Inc. PO Box 3137 THORNTON NSW 2322 Phone: (02) 4978 4020 Email: [email protected] © University of Melbourne (2015)
Suggested bibliographic citation: Whitehead A, Kujala H & Wintle B (2015) Modelling Species and Threatened Ecological Plant Communities in the Hunter, Central & Lower North Coast Region of New South Wales, University of Melbourne VIC Disclaimer: This document has been compiled in good faith, exercising all due care and attention. Hunter Councils Inc and the author do not accept responsibility for inaccurate or incomplete information. Readers should seek professional advice when applying information to their specific circumstances Copyright: This work is copyright. It may be produced in whole or in part for study or training purposes subject to the inclusion of an acknowledgement of the source. It is not intended for commercial sale or use. Reproduction for purposes other than those listed above requires written permission from the authors. TECHNICAL REPORT 3 • JULY 2015 Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
Contents
Glossary of terms ...... 3 Frequently used abbreviations ...... 3
1. Introduction ...... 4 1.1. Flora and fauna species ...... 4 1.1.1. Species data: point occurrences and modelled distributions ...... 4 1.2. Ecological communities ...... 4 1.2.1. State-listed Endangered Ecological Communities (EECs) ...... 4
2. Modelling species potential distribution patterns ...... 6 2.1. Modelling the distribution of threatened species ...... 6 2.2. Environmental variables for species distribution modelling ...... 6 2.2.1. Sampling bias layers ...... 6 2.2.2. Environmental variables ...... 7 2.3. Species distribution modelling ...... 9 2.3.1. Modelling species distributions using MaxEnt ...... 9 2.3.2 Modelling EEC distributions using boosted regression trees ...... 9 2.3.3. Model selection ...... 10 2.4. Results ...... 10 2.4.1. Model performance ...... 10 2.4.2. Regional distribution patterns and uncertainty ...... 13 2.5. Discussion ...... 13 2.5.1. Overview ...... 13 2.5.2. Limitations and sources of uncertainty ...... 14
3. References ...... 16
4. Appendix: Individual results for species distributions modelled using Maxent ...... 17
LIST OF FIGURES Figure 1. Schematic diagram representing the two-step modelling process used to generate the conservation prioritisation. A) Occurrence data for species and endangered ecological communities (EECs) were obtained from online databases and combined with environmental data to produce species distribution models using MaxEnt (species) or boosted regression trees (EECs). B) These models were clipped to LHSA region and combined with additional biological features in the spatial conservation prioritisation software, Zonation, to identify high priority areas for conservation. We identified the high priority conservation areas (the best 30% the landscape) based on the spatial prioritisation...... 7 Figure 2. Boxplot of AUC values for 642 feature distributions modelled using MaxEnt (species) or boosted regression trees (EECs) summarised across the six broad taxonomic groups. AUC values greater than 0.7 are considered to be informative (Swets, 1988a)...... 11 Figure 3. Spatial distribution patterns for species and EECs within the Greater Hunter region. A) Relative richness of species and EECs included in the analysis, calculated by summing the
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outputs of the 674 distribution models retained for inclusion in the spatial prioritisation. B) Mean predictive uncertainty across 653 modelled species distributions. These data were calculated by quantifying the coefficient of variation for each species’ MaxEnt predictions based on five-fold cross validation and then averaging across all species (see section 2.3.1)...... 13
LIST OF TABLES Table 1. Abbreviated names and definitions of mapped environmental data used as candidate predictor variables for inclusion in species distribution models. All environmental data were available in raster format with a resolution of 100 m...... 8 Table 2. AUC values and the relative importance of each environmental variable for 674 species distribution models summarised across taxonomic groups (mean ± standard error), along with the number of species per group. Variables with no data for a given taxa were not included in the model for that group. Variable descriptions are given in Table 1. Results are based on MaxEnt models for species, while EECs were modelled using boosted regression trees...... 11 Table 3. List of poorly modelled species with mean AUC values less than 0.7. These species were either excluded from subsequent analyses or included as point data if they had less than 100 records. Number of records refers to observations within the Greater Hunter region...... 12 Table 4. Mean results from MaxEnt models for amphibians within the Greater Hunter region. Results show the number of records used to construct each model and the mean (± standard deviation) test AUC value across five-fold cross-validated models. The data shown for the environmental variables represent the permutation importance for each variable used to construct the full model...... 16 Table 5. Mean results from MaxEnt models for birds within the Greater Hunter region. Results show the number of records used to construct each model and the mean (± standard deviation) test AUC value across five-fold cross-validated models. The data shown for the environmental variables represent the permutation importance for each variable used to construct the full model...... 18 Table 6. Mean results from MaxEnt models for mammals within the Greater Hunter region. Results show the number of records used to construct each model and the mean (± standard deviation) test AUC value across five-fold cross-validated models. The data shown for the environmental variables represent the permutation importance for each variable used to construct the full model...... 30 Table 7. Mean results from MaxEnt models for plants within the Greater Hunter region. Results show the number of records used to construct each model and the mean (± standard deviation) test AUC value across five-fold cross-validated models. The data shown for the environmental variables represent the permutation importance for each variable used to construct the full model...... 33 Table 8. Mean results from MaxEnt models for reptiles within the Greater Hunter region. Results show the number of records used to construct each model and the mean (± standard deviation) test AUC value across five-fold cross-validated models. The data shown for the environmental variables represent the permutation importance for each variable used to construct the full model...... 40 Table 9. Mean results from Boosted Regression Tree models for EECs within the Greater Hunter region. Results show the number of training samples used to construct each model and the mean (± standard deviation) test AUC value across ten-fold cross-validated models. The data shown for the environmental variables represent the percent contribution of each variable used to construct full model...... 43
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Glossary of terms
Biodiversity Species, threatened ecological communities and other key elements features selected for inclusion in spatial conservation planning. Ecological Naturally occurring biological assemblage that occurs in a particular community type of habitat. Endangered Ecological communities listed under the NSW Threatened Species ecological Conservation Act 1995 (TSC Act) as critically endangered, endangered communities or vulnerable, depending on their risk of extinction, distribution pattern and other biodiversity value metrics. Only some of these communities align with the listed federally Threatened Ecological Communities under the Commonwealth Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act). Grid cell One rectangular cell within a raster grid data layer. Raster (data) layer Rasters are uniform grids of rectangular shape and commonly used in GIS based analyses. They typically describe characters of an area or distribution of features, each grid cell having one value within one raster layer. Threatened Species listed under the NSW Threatened Species Conservation Act species (flora and 1995 (TSC Act) as critically endangered, endangered or vulnerable fauna) depending on their risk of extinction, distribution pattern and other biodiversity value metrics. Only some of these species are listed federally under the Commonwealth Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act).
Frequently used abbreviations
ALA Atlas of Living Australia EEC Endangered Ecological Community EPBC Act Environment Protection and Biodiversity Conservation Act 1999 GIS Geographic Information System HCCREMS Hunter & Central Coast Regional Environmental Management Strategy IBRA Interim Biogeographic Regionalisation of Australia MNES Matters of National Environmental Significance OEH NSW Office of Environmental and Heritage TSC Act NSW Threatened Species Conservation Act 1995
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1. Introduction
he National Environmental Research Program (NERP) Environmental Decisions Hub, based at the TUniversity of Melbourne, undertook an analysis of biodiversity priorities within the Hunter, Central & Lower North Coast region of NSW for the HCCREMS program in 2014–2015. Over 600 spatial layers representing biodiversity features were created to be included in this analysis. This document is an excerpt from the main report (Whitehead A, Kujala H, & Wintle B (2015) Modelling Species and Threatened Ecological Plant Communities in the Hunter, Central & Lower North Coast Region of NSW, University of Melbourne, VIC) and provides information relevant to the HCCREMS Regional Biodiversity Program. This excerpt describes the sources of these data, how they were processed, and how they were used to model the feature’s distributions.
1.1. Flora and fauna species
1.1.1. SPECIES DATA: POINT OCCURRENCES AND MODELLED DISTRIBUTIONS Point occurrence data for all listed species within the Greater Hunter (Hunter, Central and Lower North Coast region of NSW) were downloaded from the ALA and BioNet. All species listed under Commonwealth (EPBC Act 1999) or NSW legislation (Threatened Species Conservation Act 1995, National Parks and Wildlife Service Act 1974) were identified as potential biodiversity features to include in the analyses. Additional point data for 101 species were provided by OEH and participants of the flora workshop, a technical expert review workshop.
To reduce biases due to potentially outdated and/or inaccurate spatial data, we undertook a process of filtering point occurrence records whereby species records were excluded if they were observed prior to 1 January 1990 to reduce uncertainties associated with spatial accuracy and subsequent changes in environmental data, particularly vegetation cover. We also excluded those records that had a spatial accuracy of greater than 100 m. The remaining data points for each species were then compared to a raster grid of the Greater Hunter with a 100 m grid resolution and all duplicate records within a given grid cell removed. Thus, the final data for each species represents the distribution of occurrence records across the Greater Hunter region since 1 January 1990 where duplicate records have been removed.
For 653 species with more than 20 occurrence points within the Greater Hunter we produced continuous distribution maps showing the likelihood of observing the species in any of the 100 m grid cells (see section 2).
1.2. Ecological communities
1.2.1. STATE-LISTED ENDANGERED ECOLOGICAL COMMUNITIES (EECs) Occurrence points for state-listed EECs within the Greater Hunter were extracted from the survey records and used as input data for constructing the GHVMv4 (Sivertsen et al., 2011) based on the Map Unit codes. Because EECs are mutually exclusive (i.e. two EECs cannot, by definition, occur in the same place), we treated these occurrences records as presence-absence data where the presence of one EEC indicated that all other EECs were absent.
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In addition, because these records were undertaken as part of a systematic survey, we considered them to be spatially accurate and no data filtering was undertaken.
For 21 EECs with more than 20 occurrence points within the Greater Hunter we produced continuous distribution maps showing the likelihood of observing the species in any of the 100 m grid cells (section 2.). For five EECs with less than 20 occurrences we used the occurrence records to indicate their known locations within the LHSA region. The full list of state-listed EECs included in the analyses can be found in Table 9 in the Appendix.
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2. Modelling species potential distribution patterns
2.1. Modelling the distribution of threatened species To identify areas important for conservation, it is necessary to understand how threatened species and other important biodiversity features are distributed across the landscape. Distribution data is typically available as occurrence records, where an observer has noted the location of an organism at a given point in time. However, incomplete sampling and difficulties in detecting species mean that these records often do not represent the entire habitat for a species. Therefore, prioritising sites for conservation based solely on known occurrence data is likely to bias areas towards those sites that are well sampled or where common and easy to survey species are located, with the very real risk of missing important habitats (Rondinini et al., 2006).
Species distribution modelling provides a tool that can predict the likely distribution of a species based on known occurrence data and environmental conditions at these localities (Figure 1). The technique is well established within the ecological literature and provides a robust and transparent method for predicting the distribution of species from available data. Here we predict the distribution of 653 species and 21 EECs using two species distribution modelling tools, MaxEnt (Phillips et al., 2006) and Boosted Regression Trees (BRTs; Elith et al., 2006). The outputs from this modelling are then used as input data for a spatial conservation prioritisation to identify high priority conservation areas for the region).
2.2. Environmental variables for species distribution modelling We used publically available species occurrence data in a species distribution modelling framework to characterise spatial patterns of threatened biodiversity within the Greater Hunter region. The collection and pre-processing of these data are described fully in section 1.
2.2.1. SAMPLING BIAS LAYERS Species distribution modelling techniques based on presence-only data assume that the landscape has been systematically or randomly sampled (Phillips et al., 2009) and failure to correct for geographic biases in the data can produce outputs that reflect the sampling effort rather than the true species distribution (Reddy and Dávalos, 2003). One option for reducing biases is to manipulate the background data used in the modelling process by introducing a sampling bias layer that mimics the biases in the occurrence data (Kramer-Schadt et al., 2013; Phillips et al., 2009).
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Figure 1. Schematic diagram representing the two-step modelling process used to generate the conservation prioritisation. A) Occurrence data for species and endangered ecological communities (EECs) were obtained from online databases and combined with environmental data to produce species distribution models using MaxEnt (species) or boosted regression trees (EECs). B) These models were clipped to LHSA region and combined with additional biological features in the spatial conservation prioritisation software, Zonation, to identify high priority areas for conservation. We identified the high priority conservation areas (the best 30% the landscape) based on the spatial prioritisation.
The spatial distribution of species observations within the Greater Hunter region is highly biased towards populated areas. Therefore, to reduce the influence of these observed biases in the species occurrence data, we generated sampling bias grids for five broad taxonomic groups (amphibians, birds, mammals, plants, reptiles). These bias grids were based on point data downloaded from the ALA and BioNet for all species observed within the Greater Hunter region. For each taxonomic group, we calculated a normalised kernel density layer from the available point data using a 10 km radius. We chose to use all species within a taxonomic group rather than just the listed species as it is likely that an observational technique that locates common species of a given taxa would also locate threatened species if they were present.
Because the sampling for EECs was conducted as part of a systematic survey, no bias layer was used in these models.
2.2.2. ENVIRONMENTAL VARIABLES A set of 18 ecologically-relevant environmental variables were selected as potential predictors of the distribution of threatened species and EECs within the Greater Hunter region (Table 1). These included variables describing the climate, vegetation, topography and soils that were available across the entire modelling region at 100 m resolution.
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Several vegetation spatial datasets were available across the Greater Hunter region, with varying levels of accuracy. We took the best available datasets and merged these to provide a single layer that represented the best available data at the level of Keith Formations (Keith, 2004) across the entire region. At the scale of the Lower Hunter region, we used Keith Formation data from an updated version of the Lower Hunter vegetation mapping produced by Parsons Brinkerhoff (Cockerill et al., 2013; updated by Mark Cameron, OEH, June 2014), while vegetation data outside the Lower Hunter region was obtained from the Greater Hunter Vegetation Mapping spatial database (v4.0; Sivertsen et al., 2011). In addition to the categorical Keith Formation layer (final_vegetation), we also generated a layer for three Keith Formations (dry sclerophyll forest, wet sclerophyll forest, rainforest) that represented the percentage cover of that vegetation community within a 2 km radius of each pixel in the landscape (Table 1). The percentage cover estimates were restricted to these three Keith Formations as they have been assessed as having a high degree of accuracy (John Hunter, pers. comm.)
Table 1. Abbreviated names and definitions of mapped environmental data used as candidate predictor variables for inclusion in species distribution models. All environmental data were available in raster format with a resolution of 100 m.
CANDIDATE VARIABLE DEFINITION UNITS
mean_temp Mean annual temperature derived from ANUCLIM degrees C
cold_temp Mean temperature of the coldest period derived from ANUCLIM degrees C
hot_temp Mean temperature of the hottest period derived from ANUCLIM degrees C
mean_rain Mean annual rainfall derived from ANUCLIM mm
seasonal_rain Mean seasonal rainfall derived from ANUCLIM mm
mean_solar Mean annual solar radiation derived from ANUCLIM W/m2/day
altitude The altitude of a cell (in metres) above sea level metres
slope The slope of a cell (in degrees) degrees
eastness The degree to which the aspect of a cell is east (east = 1, west = -1) index
northness The degree to which the aspect of a cell is north (north = 1, south = -1) index
rugg1000 Topographic ruggedness (standard deviation in elevation) in a 1000 m metres radius
terr1000 Relative terrain position in a 1000 m radius dimensionless
wetness Compound topographic index dimensionless
final_vegetation Keith formation vegetation categories derived from the Parsons categorical Brinkerhoff and Greater Hunter vegetation mapping (Cockerill et al., 2013; Sivertsen et al., 2011)
Dry_sclerophyll_forests The percentage of cells within a 2000 m radius dominated by dry % sclerophyll forest
rainforests The percentage of cells within a 2000 m radius containing rainforest %
Wet_sclerophyll_forests The percentage of cells within a 2000 m radius dominated by wet % sclerophyll forest
soils Digital Atlas of Australian Soils (CSIRO, 2014) categorical
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2.3. Species distribution modelling
2.3.1. MODELLING SPECIES DISTRIBUTIONS USING MAXENT All species distribution models were constructed using MaxEnt (Phillips et al., 2006, version 3.3.3k), a freely available software. MaxEnt uses presence-only occurrence data to predict the likelihood of observing a species in each pixel of the landscape, given the environmental conditions that exist there relative to the environmental conditions in pixels where the species is known to occur (Phillips and Dudík, 2008).
Models were built for 621 species including 151 threatened species, and a further 21 EECs with a minimum of 20 records within the Greater Hunter region using taxa-specific sampling bias grids to account for potential biases in the point data (Kramer-Schadt et al., 2013). All modelling was undertaken at the scale of the Greater Hunter region, using raster grids with a grid cell resolution of 100 m.
Prior to building the final model, we undertook a process of variable selection by including all 18 environmental variables in preliminary MaxEnt models for each species and then examining the outputs to identify the most important variables across broad taxonomic groups (amphibians, birds, mammals, plants, reptiles). Where variables were known to be spatially correlated (collinearity > 0.8), we retained the variable that had the highest mean training gain (a measure of how well a variable describes the presence data) for all species within a taxonomic group. We then reran the models and iteratively removed those variables that contributed little information based on their permutation importance (less than 1% on average across all species within a taxonomic group based on jack- knife tests) (Williams et al., 2012).
Once the parameter set was finalised, we ran the models using a five-fold cross-validation procedure (Hastie et al., 2001). With this process, the dataset was randomly divided into five exclusive subsets and model performance calculated by successively removing each subset, refitting the model with the remaining data and predicting the omitted data. We assessed the mean Area Under the receiver operator Curve (AUC) value of each modelled species to determine the model fit, that is, how well the models are able to predict species known occurrences. We retained those species for which the AUC value was greater than 0.7, which is generally considered to be a threshold of an informative model (Swets, 1988a). For these species, we then reran the models using the full dataset and predicted the likelihood of occurrence of each species across the Greater Hunter at a spatial resolution of 100 m.
To explore the spatial uncertainties in our species’ SDMs, we used the individual predictions from the models generated using five-fold cross-validation for each species to calculate the coefficient of variation (CV) within each grid cell: that is, for each species we calculated the mean and standard deviation of the predicted value in each grid cell across the five individual predictions, and divided the standard deviation by the mean in each cell (producing the CV for each cell). When estimated for a single species, a CV value greater than one represents a cell where the standard deviation across the five predictions is greater than the mean of those predictions, indicating notable variation and therefore potentially high uncertainty in the predicted value in the particular grid cell. To summarise the spatial patterns in SDM uncertainty, the CV values in each cell were then averaged across all species to identify how the variation in predictive ability of the SDMs changes across the landscape.
2.3.2 MODELLING EEC DISTRIBUTIONS USING BOOSTED REGRESSION TREES We used Boosted Regression Trees (BRT) to model the potential distributions of 21 EECs within the Greater Hunter region. This allowed us to utilise the absence points associated with the GHVM survey data, where the presence of a given EEC at a location necessarily indicates the absence of all other EECs. BRT models are an advanced regression technique based on machine learning (Friedman, 2002) and are being used
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increasingly to model the distributions of species (Elith et al., 2006). BRT models are capable of dealing with non-linear relationships between variables and can assess high-order interactions, making them particularly suited for ecological data (Elith et al., 2008b). BRT models are also robust to the effects of outliers and irrelevant predictors (Leathwick et al., 2006).
We used BRT to analyse the relationship between the occurrence of each EEC and the environment. All analyses were carried out in R (version 3.1.1) using the ‘dismo’ library (Hijmans et al., 2013). The models were allowed to fit interactions, using a tree complexity of three and a learning rate of 0.003. We used ten-fold cross validation to determine the optimal number of trees for each model, giving the maximum predictive performance. BRT models have a tendency to over-fit the training data, so the performance of the model was assessed by making predictions at sites that were not used during model development. The probability of occurrence of each EEC was predicted across the Greater Hunter region at a spatial resolution of 100 m. Because EECs have legal definitions that restrict them to specific bioregions, we clipped all EEC model outputs to their listed bioregions.
2.3.3. MODEL SELECTION The predictive power of each model was evaluated using the area under the receiver operator characteristic curve (Hanley and McNeil, 1982), where models with an AUC value of 0.7 or greater were considered to be informative (Swets, 1988b). Models for species or EECs with an AUC less than 0.7 were either excluded from subsequent analyses or replaced with their original point data if they were represented by less than 100 records.
2.4. Results
2.4.1. MODEL PERFORMANCE In general, model performance for each of the 642 modelled features was high, with mean AUC values greater than 0.83 for all taxonomic groups (Figure 2; Table 2). Seasonal rainfall, slope and local vegetation type were important drivers for all taxonomic groups. In addition, the percentage cover of dry and wet sclerophyll forest and rainforest within a 2km radius were important for all taxonomic groups. Using the iterative variable selection led to small changes in AUC values for all species, with no consistent trend.
26 species were identified as being poorly modelled by MaxEnt based on a mean AUC value of less than 0.7 (Table 3). The majority were common bird species, such as the Australian magpie (Cracticus tibicen) and laughing kookaburra (Dacelo novaeguineae), with a high number of records across the Greater Hunter region. These species typically occupy a broad range of habitat types and are, therefore, difficult to model accurately. Those poorly modelled species with greater than 100 records (20 out of 26) were excluded from subsequent analyses. For the remaining six species with less than 100 records (Table 3), we reverted to using the original point data in the spatial prioritisation.
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Figure 2. Boxplot of AUC values for 642 feature distributions modelled using MaxEnt (species) or boosted regression trees (EECs) summarised across the six broad taxonomic groups. AUC values greater than 0.7 are considered to be informative (Swets, 1988a).
Table 2. AUC values and the relative importance of each environmental variable for 674 species distribution models summarised across taxonomic groups (mean ± standard error), along with the number of species per group. Variables with no data for a given taxa were not included in the model for that group. Variable descriptions are given in Table 1. Results are based on MaxEnt models for species, while EECs were modelled using boosted regression trees.
AMPHIBIANS BIRDS MAMMALS PLANTS REPTILES EECs
N 39 305 65 177 67 21 AUC 0.89 (0.01) 0.84 (0.01) 0.83 (0.01) 0.91 (0.01) 0.85 (0.01) 0.95 (0.01) cold_temp 26.18 (3.46) 30.75 (1.34) 16.88 (1.94) 10.14 (1.07) 16.87 (2.13) – hot_temp 6.9 (1.28) 6.75 (0.54) 9.82 (1.72) 7.33 (0.98) 5.74 (0.93) – mean_rain 11.38 (2.17) 11.83 (0.91) 16.21 (2.41) – – 19.6 (2.9) seasonal_rain 14.95 (1.67) 10.2 (0.57) 13.54 (1.38) 10.24 (1) 10.31 (1.14) 14.16 (3.46) mean_solar – – – 23.37 (1.7) 17.38 (2.15) – slope 13.21 (1.76) 10.02 (0.56) 12.09 (0.99) 3.94 (0.47) 10.18 (1.06) 5.64 (1.02) rugg1000 3.5 (1.11) – – – – 5.74 (1.02) terr1000 – 3.29 (0.26) 2.97 (0.54) – 2.89 (0.31) – wetness – – – – – 3.32 (0.73) final_vegetation 4.55 (0.63) 3.96 (0.26) 8.02 (0.87) 6.62 (0.58) 10.52 (1.28) 7.02 (1.85) Dry_sclerophyll_forests 4.97 (1.14) 9.01 (0.57) 6.11 (0.76) 6.64 (0.75) 9.25 (1.2) 8.44 (1.67) rainforests 3.96 (0.84) 3.77 (0.36) 3.57 (0.75) 3.56 (0.45) 5.49 (1.59) 5.34 (1.72) Wet_sclerophyll_forests 8.45 (2.07) 10.41 (0.62) 8.3 (1.62) 6.16 (0.69) 8.74 (1.41) 4.04 (1.24) soil – – – 18.88 (1.19) – 9.48 (1.41)
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Table 3. List of poorly modelled species with mean AUC values less than 0.7. These species were either excluded from subsequent analyses or included as point data if they had less than 100 records. Number of records refers to observations within the Greater Hunter region.
NUMBER OF MEAN AUC SPECIES COMMON NAME STATUS RECORDS (± SE) DECISION
Birds
Acanthiza pusilla Brown Thornbill 4626 0.68 (0.01) exclude
Alisterus scapularis Australian King-Parrot 2244 0.68 (0.02) exclude
Aquila audax Wedge-tailed Eagle 1206 0.65 (0.02) exclude
Artamus personatus Masked Woodswallow 34 0.66 (0.09) points
Cacatua galerita Sulphur-crested Cockatoo 2256 0.69 (0.01) exclude
Colluricincla harmonica Grey Shrike-thrush 4255 0.67 (0.01) exclude
Cormobates leucophaea White-throated Treecreeper 4116 0.69 (0.01) exclude
Corvus coronoides Australian Raven 4501 0.7 (0.01) exclude
Cracticus tibicen Australian Magpie 5273 0.67 (0.01) exclude
Dacelo novaeguineae Laughing Kookaburra 5132 0.67 (0.01) exclude
Eopsaltria australis Eastern Yellow Robin 4385 0.69 (0.01) exclude
Lichenostomus chrysops Yellow-faced Honeyeater 5185 0.66 (0.01) exclude
Malurus cyaneus Superb Fairy-wren 4508 0.69 (0.01) exclude
Ninox connivens Barking Owl V,3 22 0.64 (0.12) points
Pachycephala pectoralis Golden Whistler 4186 0.7 (0.01) exclude
Pachycephala rufiventris Rufous Whistler 2672 0.69 (0.01) exclude
Pardalotus punctatus Spotted Pardalote 4030 0.68 (0.01) exclude
Philemon corniculatus Noisy Friarbird 3678 0.67 (0.01) exclude
Rhipidura albiscapa Grey Fantail 6063 0.66 (0.01) exclude
Strepera graculina Pied Currawong 4849 0.64 (0.01) exclude
Zosterops lateralis Silvereye 3191 0.69 (0.01) exclude
Mammals
Tachyglossus aculeatus Short-beaked Echidna P 2350 0.69 (0.01) exclude
Plants
Diuris sulphurea Tiger Orchid P 40 0.69 (0.10) points
Pterostylis obtusa Blue-tongue Greenhood P 29 0.55 (0.12) points
Reptiles
Lialis burtonis Burton’s Snake-lizard P 63 0.66 (0.08) points
Vermicella annulata Bandy-bandy P 62 0.65 (0.06) points
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2.4.2. REGIONAL DISTRIBUTION PATTERNS AND UNCERTAINTY We summed the predicted relative likelihood values in each grid cell across all species to give an estimate of the overall regional biodiversity patterns based on the species included in this analysis (Figure 3a). In general, species were distributed unevenly across the region, with more species predicted to be present closer to the coast. Maps of the predicted distributions for each of the modelled species are available upon request.
The mean predictive uncertainty in the model predictions across the Greater Hunter region ranged from 0.15–0.54 (median: 0.26), with the highest values occurring along the north-western boundary of the modelling region and around Barrington Tops National Park (Figure 3b).
Figure 3. Spatial distribution patterns for species and EECs within the Greater Hunter region. A) Relative richness of species and EECs included in the analysis, calculated by summing the outputs of the 674 distribution models retained for inclusion in the spatial prioritisation. B) Mean predictive uncertainty across 653 modelled species distributions. These data were calculated by quantifying the coefficient of variation for each species’ MaxEnt predictions based on five-fold cross validation and then averaging across all species (see section 2.3.1).
2.5. Discussion
2.5.1. OVERVIEW The modelling framework described in this report to predict the distribution of threatened species within the Greater Hunter region is well established amongst the conservation literature (e.g. Guisan and Zimmermann, 2000; Phillips and Dudík, 2008; Phillips et al., 2006; Williams et al., 2012). It provides a robust, transparent and repeatable method for identifying the relatively likelihood of species’ occurrences across the landscape.
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2.5.2. LIMITATIONS AND SOURCES OF UNCERTAINTY When using SDMs to inform decisions, it is necessary to consider the potential limitations and sources of uncertainty associated with the predictions (Guillera-Arroita et al., 2015). Uncertainty in species distribution modelling can arise from two major sources: poor quality input data or inappropriate model structures (Barry and Elith, 2006). For example, inaccurate occurrence data may result from spatial biases in sampling, imperfect detection and/or misidentification of species, while appropriate environmental variables may not be available or mapped at a sufficiently-high resolution to be ecologically relevant. Both issues can lead to models that may not reflect the true distribution of the species, with potential ramifications for the decision-making process. Also, the choice of modelling technique may influence model predictions. Here we chose to use two well- established methods (MaxEnt, BRT) to fully utilise the presence-only and presence-absence data available for species and EECs, respectively, and reduce any potential biases from model structure.
The occurrence data used in this analysis were obtained from two online databases that combine data from a range of sources, including systematic surveys, museum records, and observations by the general public. While the records were cleaned for spatial accuracy to the best of our ability, we were unable to compensate for inaccuracies due to species misidentifications or taxonomic changes. Therefore, it is possible that some inaccurate records were included in the model construction.
Initial analyses identified a strong spatial bias in the occurrence data, with records concentrated close to the coast. For this reason, we included a bias layer in the modelling approach to try and reduce the impact of this sampling bias when making predictions. Using a bias grid technique has previously been shown to help address issues related to sampling bias (Kramer-Schadt et al., 2013).
Species distribution models are reliant on the appropriate use of ecologically-relevant environmental data to make sensible predictions across the landscape and the availability of accurate data at an appropriate resolution can be problematic. We were able to include a range of environmental data describing characteristics of the climate, topography, soils and vegetation across the Greater Hunter region. Our modelling framework used a process whereby all species within a given taxonomic group were modelled using the same suite of environmental variables. While it would have ideally been better to have fine-tuned the models for each species individually, this was not possible due to time constraints and the large suite of species modelled. The high AUC values (Figure 2; Table 2) of most of our models indicate that, despite the somewhat generic variable selection process across taxonomic groups instead of individual species, our approach was successful in building distribution models that captured the known occurrences of species and notably increase our understanding of their distribution patterns within unsurveyed areas.
It is important to understand that there may be some mismatches between species’ observed distribution and their predicted distribution when a species is absent from a site identified as suitable habitat. This common observation of environmentally suitable but unoccupied sites often results from competitive exclusion by other species, a low dispersal ability that may prevent colonisation of otherwise suitable site or historic factors that may have excluded species from a previously occupied site (Guisan and Zimmermann, 2000). While these areas may not currently be occupied, they represent potentially suitable habitat for the species concerned and may still be important for conservation purposes.
Our analysis of spatial uncertainty in the predictions indicated some areas of higher uncertainty within the Greater Hunter modelling region, located predominantly in the north-western areas of the region (Figure 3). However, these uncertainty values are relatively low. Ideally, the predictions from SDMs should be validated to ensure that they accurately reflect the true distribution. There
14 TECHNICAL REPORT 3 • JULY 2015 Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
is a tradeoff between using unvalidated SDM models and the time required to generate potentially hundreds of highly accurate SDMs. While it is important to recognise the potential uncertainties associated with the model predictions, SDMs contain more information than the original point data (Rondinini et al., 2006). The models retained for use in the spatial prioritisation all had a high predictive value and low spatial uncertainty in the predictions. Therefore, we feel confident that they represent the best available distribution data for inclusion in the spatial conservation prioritisation (Hermoso et al., 2015). However, we recommend that sites highlighted by subsequent analyses as high priority for conservation or at risk from development be surveyed as part of the decision- making process.
15 TECHNICAL REPORT 3 • JULY 2015 Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
3. References
Details of all References included in this excerpt can be found in the main Report Kujala H, Whitehead AL & Wintle BA (2015) Identifying conservation priorities and assessing impacts and trade-offs of potential future development in the Lower Hunter Valley in New South Wales. The University of Melbourne, Melbourne, VIC.
16 TECHNICAL REPORT 3 • JULY 2015 Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
4. Appendix: Individual results for species
distributions modelled using Maxent
FORESTS SCLEROPHYLL_
2.41 7.39 2.33 8.45 2.71 0.38 0.86 6.75 4.50 4.88 1.87 0.15 1.28 1.41 0.48 3.91 3.72 0.00
WET_ 21.10 11.15 62.72 33.69 RAINFORESTS
3.91 6.93 1.46 0.66 0.71 4.01 1.23 0.77 1.25 6.59 4.81 0.11 1.28 0.75 0.89 0.32 0.33 0.21
18.83 12.71 16.18 12.88
FORESTS SCLEROPHYLL_
1.06 5.77 7.69 0.00 6.13 0.59 0.32 9.43 6.77 1.37 1.43 0.00 0.00 0.54 2.53 2.91 0.52 7.51 6.47 6.51
DRY_ 39.34 18.36
VEGETATION
FINAL_ 7.11 1.58 0.23 7.10 5.11 0.70 2.76 1.69 0.23 5.66 3.17 1.26 2.14 0.85 6.47 5.51 1.50 2.43 6.64 8.96 2.63
11.26 RUGG1000
0.04 0.97 1.08 0.09 2.23 0.94 2.10 0.22 0.51 0.62 0.05 2.67 1.94 2.53 2.68 0.46 0.17 1.37 0.00 0.75 3.78
15.16 SLOPE
1.12 5.09 0.17 1.22 9.70 1.98 2.89 3.09 6.24
16.29 26.41 17.82 14.84 10.51 10.25 15.34 13.17 38.36 32.69 15.57 27.77 11.17
RAIN
SEASONAL_ 5.28 1.65 7.12 2.66 0.30 2.22
12.37 11.04 29.64 21.97 30.06 13.95 23.19 23.62 12.00 30.98 14.81 18.79 12.90 39.96 25.05 16.31 MEAN_RAIN
1.71 1.66 0.15 1.83 2.57 5.46 8.83 7.04 0.01 0.00 1.82 4.11 8.46 5.02 1.94
34.72 10.72 19.38 37.05 35.96 43.90 30.58 HOT_TEMP
0.04 0.00 6.79 9.84 5.33 2.33 1.91 0.00 0.00 0.00 9.99 1.19 1.53 0.00 4.96
10.20 10.01 14.59 11.93 10.42 31.50 20.23 COLD_TEMP
7.02 8.96 3.22 0.14 3.33 5.69
15.32 21.94 17.75 20.81 37.59 59.59 46.08 41.14 39.30 47.98 57.12 12.11 32.08 11.54 66.41 25.72 TEST AUC TEST
0.744 (0.01) 0.93 (0.019) 0.82 (0.024) 0.813 (0.01) 0.82 (0.017)
0.913 (0.012) 0.964 (0.004) 0.973 (0.011) 0.838 (0.023) 0.843 (0.027) 0.851 (0.009) 0.839 (0.019) 0.951 (0.012) 0.931 (0.027) 0.742 (0.032) 0.915 (0.017) 0.938 (0.039) 0.985 (0.006) 0.922 (0.019) 0.954 (0.015) 0.929 (0.023) 0.858 (0.016) N.RECORDS 64 30 67 39 57 452 365 158 179 299 162 386 224 264 228 330 112 499 630 2249 1256 1310 AMPHIBIANS Adelotus brevis Adelotus Crinia signifera Crinia tinnula Heleioporus australiacus Lechriodus fletcheri Lechriodus Limnodynastes dumerilii Limnodynastes Limnodynastes ornatus Limnodynastes Limnodynastes peronii Limnodynastes Limnodynastes Limnodynastes tasmaniensis Litoria aurea Litoria Litoria brevipalmata Litoria Litoria caerulea Litoria Litoria chlorisLitoria Litoria citropa Litoria Litoria daviesae Litoria Litoria dentata Litoria Litoria fallax Litoria Litoria freycineti Litoria Litoria gracilenta Litoria Litoria jervisiensisLitoria Litoria latopalmata Litoria Litoria lesueuriLitoria Table 4. Mean results from MaxEnt models for amphibians within the Greater Hunter region. Results show the number of records used to construct used to each the number of records Results show region. Hunter amphibians within the Greater MaxEnt models for from 4. Mean results Table represent variables for the environmental shown The data models. five-fold cross-validated across value AUC test deviation) model and the mean (± standard details. more construct importancethe permutation used to each variable the full model. for
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Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS
SCLEROPHYLL_
WET_ 0.22 2.41 4.43 3.83 5.06 1.28 1.76 1.53 0.00 0.05 0.75 7.28
31.21 20.23 15.32 34.56 17.68 RAINFORESTS
5.17 0.85 1.15 4.72 1.17 0.86 0.63 5.76 2.68 1.00 0.00 0.31 1.50 0.39 1.23
13.47 16.72
FORESTS
SCLEROPHYLL_
DRY_ 2.87 1.77 0.93 0.89 3.94 0.23 1.64 0.24 2.01 3.44 0.14 9.95 5.27 5.35 3.53
13.45 13.04
VEGETATION FINAL_
0.04 7.10 0.05 1.82 1.76 0.00 4.88 2.57 5.43 0.54 7.77 4.88 5.44
11.60 13.86 10.25 14.52 RUGG1000
2.33 1.45 0.00 0.79 0.71 0.55 0.55 0.13 0.05 2.46 0.56 0.57 1.16
21.64 23.99 10.26 28.98 SLOPE
0.98 7.72 2.07 3.61 7.83 9.73 0.72 2.43
35.68 10.57 21.66 34.47 11.86 12.03 15.24 30.75 26.13
RAIN SEASONAL_
4.63 0.00 3.40 8.52 0.47 6.83 7.79
10.94 22.91 15.64 17.96 11.23 12.84 29.60 32.79 14.37 27.27 MEAN_RAIN
1.56 4.90 5.85 4.26 2.21 4.69 6.60 5.02 6.36 2.69 8.30
12.33 11.03 16.87 54.79 10.47 23.14 HOT_TEMP
0.00 2.58 1.18 6.45 0.00 8.88 0.00 7.50 0.45 5.02 5.18 0.35 2.75
17.06 16.11 31.27 11.69 COLD_TEMP 1.94 5.27 5.81 0.10 7.74
74.90 16.41 23.65 65.74 49.80 30.61 18.75 66.50 16.36 14.71 27.63 14.12 TEST AUC TEST 0.938 0.896 0.985 0.866 0.944 0.985 0.845 0.891 0.865 0.829 (0.027) (0.014) (0.009) (0.016) (0.015) (0.006) (0.026) (0.011) (0.021) (0.019)
0.91 (0.03)
0.97 (0.007) 0.77 (0.015) 0.819 (0.02) 0.73 (0.109) 0.945 (0.01) 0.95 (0.012) N.RECORDS 46 66 50 23 71 91 176 981 579 366 381 425 261 187 828 231 395 TABLE 4 CONTINUED 4 TABLE AMPHIBIANS Litoria nasuta Litoria Litoria pearsoniana Litoria Litoria peronii Litoria Litoria phyllochroa Litoria Litoria revelata Litoria Litoria subglandulosa Litoria Litoria tyleriLitoria Litoria verreauxii Litoria Litoria wilcoxii Litoria Mixophyes fasciolatus Mixophyes Paracrinia haswelli Paracrinia Philoria sphagnicolus Philoria Pseudophryne australis Pseudophryne bibronii Pseudophryne coriacea Uperoleia fusca Uperoleia Uperoleia laevigata Uperoleia
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FORESTS SCLEROPHYLL_
2.55 1.39 7.18 6.80 3.35 6.49 7.48 6.19 0.00 4.58 3.25 7.11 2.80 7.90 0.89 6.97 4.59
WET_ 19.96 15.08 15.72 24.93 38.22 23.03 22.36 RAINFORESTS
0.49 0.81 0.66 6.00 3.69 1.94 2.56 0.73 2.52 3.54 4.51 0.44 0.82 0.98 0.99 0.00 3.09 0.39 1.06 0.00 2.42 0.37
12.81 13.91
FORESTS SCLEROPHYLL_
0.00 0.61 7.51 4.76 1.90 7.16 1.47 2.95 2.23 8.89 4.69 2.93 0.71 3.55 2.43
DRY_ 14.06 17.28 11.61 23.33 15.94 38.54 11.84 14.54 10.77
VEGETATION FINAL_
0.03 1.29 0.82 3.29 0.14 2.12 0.71 0.45 9.57 0.50 1.99 9.55 3.70 1.44 0.69 2.70 2.03 1.91 5.31 4.37 6.19 7.00 0.00
17.45 TERR1000
0.11 0.00 0.00 1.69 2.50 0.65 4.81 1.09 9.16 8.58 3.38 0.64 6.98 4.89 4.07 4.42 0.61 2.39 0.35 2.10 7.26 1.34
10.56 33.98 SLOPE
0.51 1.20 3.76 4.72 1.09 3.63 9.04 1.60 9.75 8.31 5.04
17.25 15.85 22.42 21.51 12.73 19.63 30.04 16.35 25.41 15.72 23.54 19.40 23.25
RAIN SEASONAL_
8.72 5.55 0.82 6.64 2.82 8.46 9.99 4.48 6.36 8.06 2.41 8.35 0.46 4.32 0.00 7.50 1.09
30.33 52.74 18.39 20.27 15.27 10.36 17.82 MEAN_RAIN
2.49 4.48 1.22 0.00 0.00 3.92 3.91 8.38 5.76 7.18 0.00 3.42 0.69 0.00 9.73 0.00 0.00 0.00 3.35
46.27 13.19 29.43 14.35 11.91 HOT_TEMP
0.08 5.27 0.25 1.85 8.72 0.00 6.04 8.50 1.60 2.98 8.79 9.88 6.77 1.60 4.03 4.38
17.75 24.37 13.40 16.49 15.85 14.13 19.74 12.07 COLD_TEMP
1.98 0.81 0.57 3.45
67.35 63.57 63.59 29.64 36.18 75.47 21.72 23.83 16.33 10.59 16.41 21.23 41.93 44.21 42.77 32.10 38.30 55.31 24.33 23.15 TEST AUC TEST 0.78 (0.01)
0.905 (0.01) 0.82 (0.013) 0.87 (0.011) 0.77 (0.029) 0.722 (0.01) 0.681 (0.01) 0.83 (0.071)
0.907 (0.007) 0.789 (0.013) 0.971 (0.019) 0.923 (0.019) 0.888 (0.007) 0.675 (0.015) 0.827 (0.016) 0.802 (0.013) 0.962 (0.019) 0.865 (0.015) 0.805 (0.022) 0.741 (0.022) 0.772 (0.021) 0.722 (0.011) 0.736 (0.013) 0.752 (0.018) N.RECORDS 86 59 53 701 231 995 812 731 473 466 634 334 766 1915 2037 2440 1335 2244 1442 3890 4626 2270 2258 1054 Anthochaera chrysoptera Anthochaera Anthochaera carunculata Anthochaera Anseranas semipalmata Anseranas Anhinga novaehollandiae Anhinga Anas superciliosa Anas Anas rhynchotis Anas Anas gracilis Anas Anas castanea Anas Alisterus scapularis Alisterus Alectura lathami Ailuroedus crassirostris Ailuroedus Aegotheles cristatus Aegotheles Actitis hypoleucos Acrocephalus australis Acrocephalus BIRDS Accipiter novaehollandiae Accipiter Accipiter fasciatus Accipiter Accipiter cirrocephalus Accipiter Acanthorhynchus tenuirostris Acanthorhynchus Acanthiza reguloides Acanthiza Acanthiza pusilla Acanthiza Acanthiza nana Acanthiza Acanthiza lineata Acanthiza Acanthiza chrysorrhoaAcanthiza Acanthagenys rufogularis Acanthagenys Table 5. Mean results from MaxEnt models for birds within the Greater Hunter region. Results show the number of records used to construct each model and the mean (± standard construct used to each model and the mean (± standard the number of records Results show region. Hunter within the Greater birds MaxEnt models for from 5. Mean results Table to the permutation importancevariable for each used represent variables for the environmental shown The data models. five-fold cross-validated across value AUC test deviation) construct the full model.
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FORESTS SCLEROPHYLL_
9.99 1.43 7.40 5.14 0.00 3.17 8.10 5.95 0.91 0.08 1.03 7.19 5.66 5.55 9.23 7.76 7.41 5.04
WET_ 13.26 17.53 22.57 18.08 45.16 13.48 27.84 12.28 RAINFORESTS
3.63 0.00 2.07 0.79 0.44 3.16 4.84 0.00 0.37 3.40 1.50 0.26 0.15 4.34 0.78 1.38 0.88 3.71 0.68 0.65 2.13 0.39 0.74 0.48
20.56 15.69
FORESTS SCLEROPHYLL_
3.14 9.26 7.58 5.14 4.30 0.11 5.72 1.30 0.06 0.00 1.57 4.77 2.38 4.95 3.68 4.50
DRY_ 11.66 16.94 16.58 15.60 20.64 14.95 13.22 16.40 10.78 21.27
VEGETATION FINAL_
1.20 9.31 3.93 3.66 0.36 0.00 4.23 2.29 1.25 2.59 1.25 1.31 0.00 7.66 8.24 1.01 2.32 0.85 1.34 3.92 1.52 4.89 0.00 3.40 5.28
10.76 TERR1000
0.22 4.59 5.12 0.18 0.76 4.61 0.36 3.32 0.93 0.88 0.08 3.68 0.59 3.78 0.13 6.25 1.64 0.67 1.08 2.57 3.30 0.74
10.24 11.52 11.92 10.36 SLOPE
0.98 3.54 8.10 0.84 0.78 3.47 3.37 0.12 9.98 1.14 0.32 9.26 0.37 1.25 6.65 1.05 8.02 0.05
15.33 15.28 19.61 13.50 11.33 17.62 13.28 27.60
RAIN SEASONAL_
8.98 4.35 1.04 3.69 4.86 0.00 4.94 4.26 5.21 7.03 2.85 8.64 3.03 2.41
48.91 18.06 20.81 10.85 10.73 23.81 29.05 13.12 24.68 18.29 15.80 22.25 MEAN_RAIN
2.32 5.04 4.00 1.82 1.84 8.26 3.38 0.35 8.32 0.92 0.00 4.86 8.15 0.00 4.69 4.63 3.39 3.45 6.75 8.18
39.13 58.68 37.97 14.58 23.95 13.52 HOT_TEMP
2.71 4.29 2.36 5.15 0.05 5.59 3.32 0.18 1.92 2.26 0.01 4.91 7.96 5.30 0.51 4.85 2.44 4.83 3.88 4.71 0.29 2.73
13.84 16.59 10.36 25.81 COLD_TEMP
9.82 8.58 0.39
26.90 27.04 27.91 22.81 56.34 16.34 28.16 10.43 62.17 48.53 56.16 60.49 11.14 15.77 70.03 36.75 30.89 70.58 68.70 61.97 60.04 42.38 31.35 TEST AUC TEST
0.95 (0.018) 0.928 (0.01) 0.866 (0.01)
0.967 (0.009) 0.723 (0.023) 0.798 (0.022) 0.716 (0.013) 0.938 (0.011) 0.882 (0.017) 0.693 (0.013) 0.966 (0.012) 0.928 (0.014) 0.843 (0.015) 0.825 (0.026) 0.993 (0.003) 0.738 (0.053) 0.664 (0.089) 0.928 (0.009) 0.791 (0.025) 0.967 (0.017) 0.826 (0.019) 0.885 (0.008) 0.654 (0.022) 0.877 (0.036) 0.797 (0.022) 0.718 (0.088) N.RECORDS 88 94 86 34 63 83 26 235 519 365 389 438 237 150 525 331 549 527 479 439 865 654 2439 2256 1043 1206 Calidris acuminata Calidris Cacomantis variolosus Cacomantis Cacomantis pallidus Cacomantis Cacomantis flabelliformis Cacomantis Cacatua tenuirostris Cacatua Cacatua sanguinea Cacatua Cacatua galerita Cacatua Butorides striatus Butorides Burhinus grallarius Biziura lobata Biziura Aythya australis Aythya Aviceda subcristata Aviceda Atrichornis rufescens Atrichornis Artamus superciliosus Artamus personatus Artamus leucorynchus TABLE 5 CONTINUED 5 TABLE BIRDS Artamus cyanopterus Arenaria interpres Arenaria Ardea pacifica Ardea Ardea modesta Ardea Ardea intermedia Ardea Ardea ibis Ardea Aquila audax Aquila Apus pacificus Apus Anthus novaeseelandiae Anthus Anthochaera phrygia Anthochaera
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FORESTS SCLEROPHYLL_
4.96 0.00 7.82 0.00 3.34 6.30 0.00 5.94 1.74 7.69 3.78 3.77 8.05
WET_ 16.73 10.36 57.94 15.24 17.38 26.66 34.93 12.08 53.39 20.93 13.73 33.87 RAINFORESTS
0.43 7.10 0.50 0.69 0.18 0.16 3.51 1.51 1.97 0.32 0.37 0.00 8.00 5.83 4.12 0.28 0.12 1.21 1.07 0.31 0.96 0.00 0.22 0.02
15.68
FORESTS SCLEROPHYLL_
3.80 4.44 4.94 1.03 4.50 4.97 5.04 3.47 3.54 1.08 8.43 0.54 0.39 6.01 6.95 6.46
DRY_ 35.34 15.79 10.95 26.29 13.52 31.29 16.61 10.93 14.98
VEGETATION FINAL_
3.22 2.01 4.35 8.45 0.45 4.41 2.52 5.01 0.00 0.11 0.85 2.85 4.48 7.66 5.28 1.78 0.94 4.81 0.67 1.27 1.99 2.43 0.38
12.21 35.94 TERR1000
4.26 7.28 0.28 0.25 1.61 1.47 5.15 0.40 0.40 0.11 3.76 0.51 4.37 3.82 0.36 1.59 0.74 0.28 0.01 1.76 0.19 0.38
35.15 15.76 18.40 SLOPE
6.03 3.34 0.29 0.56 1.11 0.73 2.85 0.14 3.74 6.40 0.00 0.09 1.40 5.05 4.58 0.06
11.50 10.02 18.91 22.63 12.16 15.00 24.46 51.30 24.00
RAIN SEASONAL_
2.65 2.25 9.23 0.43 8.25 0.55 6.66 5.58 2.18 0.00 9.23 3.93 0.74 0.87 7.80 0.90 1.10
15.06 12.75 22.12 18.98 17.77 12.49 17.74 12.10 MEAN_RAIN
0.00 1.66 1.90 4.80 0.44 0.00 0.08 0.66 7.42 0.88 0.59 3.92 0.89 0.00 2.42 1.21
11.80 18.33 35.01 33.28 47.84 32.34 38.54 22.98 56.25 HOT_TEMP
0.00 3.94 0.14 0.64 3.23 0.45 3.50 0.00 4.79 2.35 0.44 0.00 2.21 1.17 0.08 0.12 0.00 0.65 0.31
11.79 58.13 49.18 11.05 27.35 17.01 COLD_TEMP
2.27 8.43 1.78 0.00 5.01 9.97 9.72 3.33 4.67 1.19
22.23 71.39 14.14 42.01 58.17 56.50 21.95 17.23 19.21 72.19 42.49 33.90 55.86 52.06 49.92 TEST AUC TEST 0.82 (0.03)
0.838 (0.03) 0.94 (0.006) 0.873 (0.06)
0.817 (0.026) 0.894 (0.037) 0.891 (0.015) 0.982 (0.011) 0.945 (0.026) 0.785 (0.069) 0.738 (0.011) 0.974 (0.006) 0.982 (0.006) 0.977 (0.009) 0.736 (0.018) 0.782 (0.026) 0.805 (0.022) 0.841 (0.015) 0.958 (0.017) 0.762 (0.013) 0.991 (0.002) 0.978 (0.008) 0.925 (0.051) 0.982 (0.006) 0.974 (0.014) N.RECORDS 55 23 65 55 66 95 25 27 53 23 329 171 527 202 164 967 355 435 683 186 134 105 1403 2325 1784 Cinclosoma punctatumCinclosoma Cincloramphus mathewsi Cincloramphus Cincloramphus cruralis Cincloramphus Chthonicola sagittata Chthonicola Chroicocephalus Chroicocephalus novaehollandiae Chlidonias leucopterus Chlidonias hybrida Cheramoeca leucosterna Cheramoeca Chenonetta jubata Charadrius ruficapillus Charadrius Charadrius mongolus Charadrius Charadrius bicinctusCharadrius Chalcophaps indica Chalcophaps Chalcites osculans Chalcites Chalcites lucidus Chalcites TABLE 5 CONTINUED 5 TABLE BIRDS Chalcites basalis Chalcites Ceyx azureus Ceyx Centropus phasianinus Centropus Calyptorhynchus lathami Calyptorhynchus Calyptorhynchus funereus Calyptorhynchus Calidris tenuirostris Calidris Calidris ruficollis Calidris Calidris melanotos Calidris Calidris ferruginea Calidris Calidris canutus Calidris
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FORESTS SCLEROPHYLL_
8.22 2.61 0.00 3.86 0.20 4.74 3.09 0.58 0.00 0.30 3.91 1.03 0.58 3.35 0.20 1.37 0.76 0.24 1.94 9.82 2.50
WET_ 12.89 13.40 21.06 14.66 15.17 RAINFORESTS
9.10 2.71 0.05 0.00 2.11 0.69 0.00 1.14 8.22 5.80 2.02 4.48 1.10 4.90 1.84 4.63 2.40 0.00 4.59 3.26 0.00 5.41 2.71 1.48
10.11 22.25
FORESTS SCLEROPHYLL_
4.94 2.17 3.23 4.65 2.14 0.00 1.93 3.52 4.99 3.78 0.96 4.52 6.88 0.41 3.17 3.88 4.12 3.62
DRY_ 19.16 16.99 17.80 20.79 13.01 16.33 10.15 11.71
VEGETATION FINAL_
2.05 1.05 0.05 0.50 1.62 0.00 1.24 3.37 0.00 0.34 2.74 0.00 7.27 6.51 0.92 0.00 7.58 9.21 0.35 0.26 1.30
10.09 12.63 12.96 12.44 26.97 TERR1000
2.62 0.23 3.26 2.07 1.27 2.14 3.87 2.38 1.73 1.86 0.13 0.45 2.81 2.26 3.40 0.92 4.77 3.23 2.06 0.17 3.73 0.19 5.64 0.94 0.39 0.54 SLOPE
0.85 7.47 4.43 8.62 8.44 9.53 3.70 5.70 5.03 2.69
24.66 26.72 22.69 29.93 41.28 13.36 15.79 17.55 21.67 19.93 15.11 31.61 27.80 10.27 19.28 13.76
RAIN SEASONAL_
5.74 2.03 6.53 0.00 2.43 4.05 4.03 5.05 8.04 6.01 2.70 0.54 3.60 8.26 6.53 1.27 9.55
17.95 36.99 10.62 13.53 16.60 20.56 13.09 36.78 27.59 MEAN_RAIN
4.31 4.95 0.00 6.21 0.00 0.00 2.15 3.09 0.00 0.00 2.74 0.00 0.00 1.56 4.36 4.08
10.25 21.20 32.57 11.51 23.75 26.53 10.84 51.00 58.70 10.50 HOT_TEMP
0.38 4.23 7.28 7.69 8.48 6.05 0.48 0.00 0.00 3.01 7.58 0.57 3.91 3.55 0.07 3.81 4.12 5.55 5.38 1.68 0.48 6.54 0.00
11.17 12.14 38.06 COLD_TEMP
1.28
38.96 32.63 22.20 58.21 61.97 53.86 60.97 44.37 55.68 39.95 28.99 32.75 16.01 57.47 10.38 26.03 21.13 15.30 62.79 20.89 21.53 15.87 28.71 13.22 61.57 TEST AUC TEST 0.69 (0.01) 0.8 (0.017)
0.954 (0.02) 0.74 (0.019) 0.88 (0.007) 0.77 (0.049) 0.699 (0.01) 0.789 (0.03) 0.671 (0.01)
0.921 (0.026) 0.669 (0.009) 0.718 (0.011) 0.675 (0.009) 0.736 (0.012) 0.801 (0.026) 0.887 (0.025) 0.897 (0.014) 0.797 (0.048) 0.742 (0.017) 0.707 (0.011) 0.841 (0.013) 0.903 (0.028) 0.843 (0.026) 0.893 (0.013) 0.868 (0.031) 0.921 (0.015) N.RECORDS 54 89 89 94 823 462 181 771 110 906 790 300 701 217 299 486 438 5132 1117 3532 5273 2225 4501 4116 3753 4255 Dendrocygna eytoni Dendrocygna Dendrocygna arcuata Dendrocygna Daphoenositta chrysoptera Dacelo novaeguineae Dacelo Cygnus atratus Cygnus Cracticus torquatus Cracticus tibicen Cracticus nigrogularis Coturnix ypsilophora Coturnix Coturnix pectoralis Coturnix Corvus tasmanicus Corvus orru Corvus mellori Corvus coronoides Cormobates leucophaea Cormobates Corcorax melanorhamphos Corcorax TABLE 5 CONTINUED 5 TABLE BIRDS Coracina tenuirostris Coracina Coracina papuensis Coracina Coracina novaehollandiae Coracina Columba leucomela Columba Colluricincla harmonica Colluricincla Climacteris picumnus victoriae Climacteris erythrops Cisticola exilis Cisticola Circus assimilis Circus Circus approximans Circus
22 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLL_
2.51 5.15 4.03 9.98 7.09 5.57 5.09 0.76 2.54 4.52 0.00 8.71 4.69
WET_ 19.97 20.53 42.22 33.55 21.73 78.19 31.64 11.12 15.16 16.59 16.32 18.39 11.46 RAINFORESTS
2.71 4.25 6.34 2.60 1.67 5.18 2.13 3.32 1.35 2.34 1.31 8.18 0.14 1.74 3.94 4.40 1.37 8.05 1.27 0.79 0.00 0.29 0.71 0.41 0.29
30.24
FORESTS SCLEROPHYLL_
6.88 0.70 9.85 1.77 0.99 1.53 0.84 5.29 2.97 0.16 8.74 2.65 6.55 3.59 8.24 3.51 5.73 1.28 8.49
DRY_ 13.91 17.44 10.33 19.41 11.75 11.89 15.26
VEGETATION FINAL_
1.67 6.17 1.02 1.95 3.55 1.96 5.33 0.36 0.85 2.83 8.68 1.35 4.50 0.86 2.00 3.30 2.04 1.09 1.13 1.80 7.14 0.17 7.38
26.99 16.50 18.55 TERR1000
1.51 5.26 2.22 2.75 0.57 4.76 5.38 1.70 0.62 0.40 0.59 0.03 1.25 3.58 1.35 4.09 3.28 1.13 4.02 1.23 1.42 6.08 0.87 0.00 0.09 2.35 SLOPE
6.66 7.16 3.13 7.47 4.81 0.00 1.86 0.24 0.37 4.45 4.52 6.98 2.33 4.87 0.59 4.84 0.24
12.74 11.17 17.36 11.59 15.87 13.01 12.43 17.33 17.60
RAIN SEASONAL_
7.16 3.96 1.42 3.68 3.26 0.00 0.91 6.94 2.12 4.89 2.40 6.40 5.71 6.12 1.56 2.49 8.40 1.24 5.63 4.72 7.89
37.06 19.82 21.43 21.21 30.26 MEAN_RAIN
7.47 5.49 1.00 3.75 2.78 0.00 0.00 1.05 3.60 7.18 0.52 1.78 0.61 0.67 0.00 2.61 4.65 0.00 2.30 6.44 0.35 4.97
48.79 34.39 10.90 12.27 HOT_TEMP
3.31 7.91 8.90 1.38 1.74 0.44 0.20 3.21 0.29 0.46 0.00 7.52 1.10 1.37 7.85 0.00 7.53 5.10 1.76 1.97 0.00 4.97 2.73 2.39
13.65 38.72 COLD_TEMP
6.33 3.13 9.19 9.45 0.00
60.13 14.33 44.61 50.06 26.64 31.86 70.24 29.07 75.42 34.48 73.86 34.08 59.09 34.14 30.26 54.76 51.91 62.57 70.82 74.10 37.17 TEST AUC TEST
0.809 (0.02) 0.98 (0.007) 0.96 (0.018) 0.686 (0.01) 0.749 (0.01) 0.95 (0.028)
0.855 (0.017) 0.778 (0.027) 0.774 (0.071) 0.815 (0.026) 0.815 (0.021) 0.767 (0.017) 0.743 (0.023) 0.791 (0.015) 0.822 (0.013) 0.983 (0.012) 0.974 (0.011) 0.921 (0.009) 0.852 (0.018) 0.899 (0.016) 0.821 (0.017) 0.808 (0.011) 0.937 (0.009) 0.879 (0.061) 0.926 (0.013) 0.701 (0.015) N.RECORDS 32 52 28 81 44 591 344 382 403 981 537 501 100 147 447 340 322 787 568 545 1464 1142 4385 2575 2347 1818 Fulica atra Fulica Falcunculus frontatus frontatus frontatus Falcunculus Falco subniger Falco Falco peregrinus Falco Falco longipennis Falco Falco cenchroides Falco Falco berigora Falco Eurystomus orientalis Eurostopodus mystacalis Eurostopodus Eudyptula minor Eudyptula Eudynamys orientalis Eudynamys Esacus magnirostris Erythrogonys cinctusErythrogonys Epthianura albifrons Epthianura Ephippiorhynchus asiaticus Ephippiorhynchus Eopsaltria australis Eopsaltria TABLE 5 CONTINUED 5 TABLE BIRDS Eolophus roseicapillus Eolophus Entomyzon cyanotis Entomyzon Elseyornis melanops Elseyornis Elanus axillaris Egretta sacra Egretta Egretta novaehollandiae Egretta Egretta garzetta Egretta Dromaius novaehollandiae Dromaius Dicrurus bracteatus Dicaeum hirundinaceum
23 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLL_
0.33 8.13 0.89 4.90 4.41 8.34 3.14 5.27 1.81 3.17 9.08 2.52 5.78 8.56 7.92 3.14 4.29 6.73
WET_ 16.44 12.84 25.98 19.30 23.25 13.90 10.51 18.72 RAINFORESTS
0.42 0.00 0.00 1.73 1.05 0.29 1.55 0.35 0.57 0.05 1.61 1.69 0.15 0.29 0.01 1.51 0.00 1.23 5.55 0.56 0.24 3.29 4.02 1.41
14.45 14.02
FORESTS SCLEROPHYLL_
0.00 1.97 5.42 0.60 4.78 1.62 6.29 6.87 0.30 1.99 0.00 1.89 1.96 3.19 5.91 8.08 5.59 3.17
DRY_ 33.54 23.13 11.53 47.17 26.90 13.89 13.75 12.50
VEGETATION FINAL_
8.31 0.33 0.78 0.91 2.50 5.91 0.60 0.30 1.34 0.63 0.46 0.01 3.95 3.31 2.26 5.22 2.90 6.23 7.03 2.35 1.66 0.74 3.31 0.96 2.15
10.71 TERR1000
2.96 0.16 8.02 0.80 3.30 0.39 0.22 0.12 0.57 0.22 1.47 5.50 1.87 0.04 2.84 0.96 5.58 0.70 0.00 1.62 2.46 0.93 0.08 0.90 3.96 1.14 SLOPE
1.48 1.57 8.73 0.03 0.57 0.04 1.13 2.22 4.14 0.00 2.05 8.35 0.20 2.47 8.88 8.67
20.53 10.32 11.33 15.22 16.69 31.12 12.35 20.29 39.37 10.44
RAIN SEASONAL_
0.46 8.57 8.52 8.19 0.32 4.81 0.00 8.04 8.19 8.87 1.30 2.65 6.90 5.28 5.52 5.56
15.59 10.17 19.99 18.33 19.04 11.58 24.94 10.49 12.24 14.87 MEAN_RAIN
5.42 0.00 0.76 3.64 9.21 1.15 3.95 0.00 5.43 5.33 5.01 9.32 5.75 3.41 0.08 2.89 5.08
43.71 20.15 59.55 12.95 22.92 60.08 15.60 15.57 32.36 HOT_TEMP
9.64 0.00 7.52 5.98 4.08 1.59 2.19 0.41 1.59 2.69 0.00 1.65 2.46 6.22 6.36 0.45 7.24 0.29 4.79 1.75 4.74
10.32 10.34 12.18 22.07 11.60 COLD_TEMP
4.49 2.52 0.00 5.06
22.31 66.35 42.10 31.15 43.52 74.15 25.32 71.80 49.72 73.99 34.53 20.78 59.32 19.87 18.11 11.22 37.32 59.36 61.51 36.13 62.10 52.05 TEST AUC TEST 0.8 (0.022)
0.97 (0.009) 0.808 (0.02) 0.94 (0.008) 0.816 (0.02)
0.888 (0.029) 0.736 (0.011) 0.768 (0.033) 0.891 (0.009) 0.967 (0.011) 0.891 (0.008) 0.967 (0.006) 0.977 (0.008) 0.867 (0.061) 0.744 (0.009) 0.779 (0.018) 0.975 (0.012) 0.774 (0.012) 0.972 (0.008) 0.904 (0.037) 0.759 (0.015) 0.834 (0.014) 0.981 (0.007) 0.915 (0.018) 0.825 (0.014) 0.911 (0.018) N.RECORDS 33 48 96 105 354 709 463 238 225 452 167 936 549 167 509 115 231 264 3476 1271 1621 3473 2219 1155 1149 1042 Hylacola pyrrhopygia Hydroprogne caspia Hydroprogne Hirundo neoxena Hirundapus caudacutus Himantopus himantopus Hieraaetus morphnoides Haliastur sphenurus Haliastur indus Haliaeetus leucogaster Haematopus longirostris Haematopus Haematopus fuliginosus Haematopus Grantiella pictaGrantiella Grallina cyanoleucaGrallina Glossopsitta pusilla Glossopsitta concinna Gliciphila melanops TABLE 5 CONTINUED 5 TABLE BIRDS Gerygone mouki Gerygone levigaster Gerygone fusca Gerygone albogularis Geopelia striata Geopelia humeralis Gelochelidon nilotica Gallirallus philippensis Gallinula tenebrosa Gallinago hardwickii
24 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLL_
7.37 4.16 8.20 0.96 2.09 2.26 1.23 6.03 1.76 4.33 0.92 1.66 4.01 9.07 7.55 0.10 4.25
WET_ 15.30 25.97 26.64 19.93 17.03 14.85 19.02 20.24 19.71 RAINFORESTS
5.64 2.09 0.02 0.00 0.48 0.23 2.07 0.21 0.49 0.13 1.03 6.34 0.16 2.30 2.59 0.00 3.25 6.73 2.06 5.42 4.13 4.31
12.16 11.06 20.77 20.40
FORESTS SCLEROPHYLL_
7.69 0.00 2.35 9.41 0.27 0.17 0.00 8.11 8.58 7.39 3.32 8.45 0.63 0.62 3.41 8.63 3.22 2.73
DRY_ 10.94 23.76 10.54 61.40 54.67 19.88 20.72 12.28
VEGETATION FINAL_
1.28 2.11 0.00 2.56 2.43 1.80 2.77 2.90 0.13 0.48 0.63 0.55 1.16 5.78 3.06 7.93 5.92 6.62 4.61 7.99 2.25 9.46 1.39 0.64 4.13
11.57 TERR1000
1.05 7.89 1.80 4.06 0.43 8.77 1.62 4.27 5.53 2.76 1.89 1.83 0.51 0.10 4.14 0.76 3.75 1.66 4.30 0.00 6.41 5.65 0.41 0.46 5.66 0.33 SLOPE
2.44 5.46 1.95 9.27 2.02 8.45 2.68 1.17 2.52 1.95 3.82 8.61 9.58 0.19 6.86 2.14 4.24
13.64 24.84 11.26 12.65 14.91 22.11 15.56 12.31 25.35
RAIN SEASONAL_
4.22 1.40 4.48 0.69 6.20 2.53 7.60 7.08 5.40 7.49 6.72 1.30
25.30 58.95 52.94 14.79 13.62 27.91 11.68 23.18 10.42 13.94 22.66 47.28 15.38 25.81 MEAN_RAIN
7.40 7.88 0.00 6.40 1.81 0.00 1.36 1.59 3.13 2.36 5.35 0.00 3.29 3.73 3.87 0.05 2.57
18.36 21.45 38.61 18.39 46.44 17.83 16.42 24.78 54.86 HOT_TEMP
3.15 0.38 0.79 6.42 0.00 5.61 6.51 0.00 0.35 5.55 8.40 5.55 0.77 4.37 2.54 0.49 4.14 6.24 0.00 6.13
21.69 13.13 27.40 11.13 39.95 13.77 COLD_TEMP
7.63 7.42 3.02 2.33 5.62 3.93 0.79 4.29 8.27
32.16 30.00 72.50 64.79 61.06 13.71 22.27 35.60 19.01 38.70 33.74 34.54 25.52 20.73 13.77 60.44 16.75 TEST AUC TEST
0.94 (0.014) 0.725 (0.01) 0.92 (0.021) 0.931 (0.03) 0.97 (0.009) 0.96 (0.007) 0.923 (0.02) 0.82 (0.018) 0.665 (0.01)
0.748 (0.013) 0.784 (0.012) 0.687 (0.011) 0.808 (0.012) 0.821 (0.017) 0.914 (0.027) 0.984 (0.009) 0.843 (0.022) 0.895 (0.013) 0.845 (0.025) 0.888 (0.036) 0.756 (0.014) 0.939 (0.022) 0.782 (0.034) 0.873 (0.061) 0.898 (0.038) 0.933 (0.022) N.RECORDS 93 92 79 72 79 56 56 75 68 255 508 119 433 398 503 584 768 351 211 1701 3582 2041 4508 1304 5185 1418 Megalurus gramineus Manorina melanophrys Manorina melanocephala Malurus melanocephalus Malurus lamberti Malurus cyaneus Malacorhynchus membranaceus Malacorhynchus Macropygia amboinensis Macropygia Lopholaimus antarcticus Lopholaimus Lophoictinia isura Lophoictinia Lonchura castaneothorax Lonchura Limosa limosa Limosa lapponica Lichmera indistinctaLichmera Lichenostomus penicillatus Lichenostomus Lichenostomus melanops Lichenostomus TABLE 5 CONTINUED 5 TABLE BIRDS Lichenostomus leucotis Lichenostomus Lichenostomus fuscus Lichenostomus Lichenostomus chrysopsLichenostomus Lewinia pectoralis Lewinia Leucosarcia picata Leucosarcia Lathamus discolor Lathamus Lalage sueurii Lalage leucomela Ixobrychus flavicollis Irediparra gallinacea Irediparra
25 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLL_
4.63 5.46 2.37 1.69 5.43 3.59 0.00 6.38 3.17 9.09 0.45 0.02 3.21 7.57 2.32
WET_ 17.59 13.71 15.47 19.88 20.10 33.15 15.80 17.13 30.32 16.77 20.48 RAINFORESTS
2.75 2.57 1.32 0.15 0.00 0.67 8.19 0.00 0.00 1.54 4.57 3.27 0.87 1.48 0.75 1.20 2.88 2.32 9.67 0.00 0.25 0.19 1.54 0.85
14.70 13.58
FORESTS SCLEROPHYLL_
3.13 3.16 5.18 9.58 5.79 5.65 6.53 5.10 4.00 7.16 2.59 0.00 5.34 2.76 0.07 3.10
DRY_ 10.02 11.92 13.77 14.61 20.27 10.07 16.80 30.87 21.26 35.85
VEGETATION FINAL_
0.00 2.31 0.95 1.19 2.88 5.60 4.55 9.67 2.97 3.80 6.57 0.38 4.29 0.69 4.37 6.89 0.45 8.21 0.32 6.44 1.74
14.05 13.29 11.66 10.35 13.32 TERR1000
0.72 2.74 1.86 0.51 0.34 2.58 6.11 4.34 3.34 2.02 1.34 0.32 3.46 3.06 6.40 4.03 1.70 6.27 4.66 0.01 0.93 6.13 0.69 1.16
21.71 30.02 SLOPE
5.70 3.19 2.96 6.90 0.59 0.00 8.80 0.58 4.56 1.98 7.92 3.17 0.67 0.31 6.43
10.33 14.92 18.35 18.69 20.25 47.87 14.90 21.98 19.11 14.40 12.02
RAIN SEASONAL_
1.04 8.96 2.31 8.21 1.17 3.97 6.38 8.31 3.87 9.75 6.30 6.62 3.66 9.67 2.80 3.12 4.21 6.11 9.85 8.80
12.31 14.05 11.13 12.19 30.40 21.82 MEAN_RAIN
0.00 2.69 0.57 1.77 0.79 1.90 4.70 6.26 9.42 4.27 2.79 0.00 7.47 4.03 6.83
16.31 55.13 56.19 46.35 12.41 16.74 19.25 29.70 30.31 34.29 25.99 HOT_TEMP
0.00 1.43 3.65 1.71 5.38 0.00 3.93 1.87 3.70 8.50 2.66 2.69 0.00 3.33 0.95 7.31 4.24 0.88 5.86 1.66
31.57 62.11 26.35 16.59 10.97 48.56 COLD_TEMP
0.96 3.26 5.40 0.00 0.00 1.19 4.58 4.38 6.82 3.52 4.03
69.08 44.21 14.60 47.87 53.98 45.95 28.54 41.78 38.20 22.98 56.53 11.40 36.06 14.04 45.86 TEST AUC TEST
0.791 (0.01) 0.849 (0.02) 0.82 (0.009) 0.94 (0.025)
0.869 (0.024) 0.975 (0.005) 0.962 (0.006) 0.754 (0.014) 0.642 (0.119) 0.705 (0.011) 0.765 (0.107) 0.759 (0.012) 0.744 (0.018) 0.734 (0.037) 0.744 (0.047) 0.982 (0.004) 0.781 (0.013) 0.792 (0.066) 0.763 (0.017) 0.867 (0.012) 0.797 (0.021) 0.738 (0.015) 0.945 (0.021) 0.813 (0.019) 0.721 (0.009) 0.932 (0.017) N.RECORDS 22 22 36 60 257 222 404 291 950 283 122 224 567 152 638 262 2381 1667 3279 1787 1323 1027 1669 1892 1564 4630 Ocyphaps lophotes Nycticorax caledonicus Numenius phaeopus Numenius madagascariensis Ninox strenua Ninox Ninox novaeseelandiae Ninox Ninox connivens Ninox Neochmia temporalis Neochmia modesta Myzomela sanguinolenta Myiagra rubecula Myiagra Myiagra inquieta Myiagra Myiagra cyanoleucaMyiagra Morus serrator Monarcha melanopsis Monarcha Milvus migrans TABLE 5 CONTINUED 5 TABLE BIRDS Microeca fascinans Microcarbo melanoleucos Merops ornatus Merops Menura novaehollandiae Melithreptus lunatus Melithreptus Melithreptus gularis gularisMelithreptus Melithreptus brevirostris Melithreptus Meliphaga lewinii Melanodryas cucullata cucullata Megalurus timoriensis
26 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLL_
2.09 6.97 8.62 7.95 3.87 7.71 7.78 2.42 0.18 9.95 1.08 0.94
WET_ 14.05 11.92 12.13 10.36 15.54 10.43 11.77 15.89 13.55 10.47 14.43 13.74 11.54 17.81 RAINFORESTS
1.29 0.09 1.37 7.44 0.24 0.72 0.19 1.59 0.99 8.06 1.21 2.04 4.11 5.79 1.16 2.12 1.15 1.12 0.33 4.05 8.71 1.96 0.77 0.40
13.73 18.95
FORESTS SCLEROPHYLL_
1.16 2.23 7.77 2.24 2.00 2.15 1.95 5.75 3.68 5.63 1.61 0.53 0.97 6.47
DRY_ 19.13 22.89 11.54 10.31 14.03 17.36 33.01 32.67 21.02 10.60 14.84 42.78
VEGETATION FINAL_
2.18 0.29 7.58 0.18 0.75 1.73 0.26 2.52 4.72 9.58 2.95 0.94 6.50 0.13 1.87 1.01 1.50 7.58 3.61 6.45
16.32 10.93 12.71 11.70 10.54 10.53 TERR1000
0.18 0.00 3.35 1.20 0.32 3.75 1.27 1.98 1.39 8.12 1.44 4.62 3.97 0.74 6.65 3.74 0.28 2.35 4.35 2.84 0.00 4.29 2.50 3.77
10.56 11.73 SLOPE
3.74 3.46 5.40 4.61 9.60 0.23 5.76 0.50 9.32 0.35 0.92 0.92 0.00 5.39
23.97 17.37 11.36 19.80 33.88 39.23 37.99 18.36 28.97 14.78 10.64 21.09
RAIN SEASONAL_
5.24 4.59 3.94 5.66 3.87 3.71 8.47 0.00 9.49 3.84 2.79 8.70 9.88 8.19 8.92 7.40 0.08 3.68
12.91 11.88 31.84 17.59 15.40 12.74 19.03 20.64 MEAN_RAIN
1.20 0.00 9.91 0.86 1.89 5.09 2.65 7.12 8.44 2.21 7.29 0.00 1.01 8.86 0.00 0.62 2.85 3.62 3.84 9.04
10.98 38.00 23.24 14.01 45.48 21.74 HOT_TEMP
0.82 8.32 1.88 1.19 0.27 0.00 7.78 4.27 5.26 0.27 1.79 4.50 3.17 5.76 3.23 6.24 5.03 5.12
35.63 19.14 16.00 22.75 19.74 16.90 11.45 12.99 COLD_TEMP
4.42 0.80 2.25 0.00 3.56 0.45 9.13 0.60 5.49
17.88 59.61 31.57 11.65 54.54 74.91 56.04 69.82 20.77 11.54 69.59 48.29 21.67 29.57 34.49 44.30 51.93 TEST AUC TEST
0.884 (0.02) 0.902 (0.01) 0.92 (0.029) 0.72 (0.043) 0.75 (0.024) 0.828 (0.02) 0.956 (0.01) 0.697 (0.01)
0.671 (0.011) 0.758 (0.043) 0.823 (0.047) 0.794 (0.023) 0.933 (0.011) 0.879 (0.011) 0.911 (0.012) 0.751 (0.019) 0.876 (0.041) 0.904 (0.008) 0.726 (0.016) 0.679 (0.011) 0.695 (0.012) 0.952 (0.028) 0.875 (0.062) 0.901 (0.019) 0.724 (0.013) 0.893 (0.012) N.RECORDS 28 579 123 126 514 793 982 984 130 116 226 552 419 427 129 225 331 1365 3678 1383 1771 1549 4030 2672 4186 2020 Phylidonyris novaehollandiae Phylidonyris Phylidonyris niger Phylidonyris Philemon corniculatus Philemon Philemon citreogularis Philemon Phaps elegans Phaps Phaps chalcoptera Phaps Phalacrocorax varius Phalacrocorax Phalacrocorax sulcirostris Phalacrocorax Phalacrocorax carbo Phalacrocorax Petroica rosea Petroica Petroica phoenicea Petroica Petroica goodenovii Petroica Petroica boodang Petroica Petrochelidon nigricans Petrochelidon Petrochelidon ariel Petrochelidon Pelecanus conspicillatus Pelecanus TABLE 5 CONTINUED 5 TABLE BIRDS Pardalotus striatus Pardalotus Pardalotus punctatus Pardalotus Pandion cristatus Pandion Pachycephala rufiventris Pachycephala Pachycephala pectoralis Pachycephala Pachycephala olivacea Pachycephala Oxyura australis Orthonyx temminckii Oriolus sagittatus Origma solitariaOrigma
27 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLL_
7.71 0.60 1.81 3.82 0.38 2.24 4.43 1.95 5.35 2.02 4.29 6.60 5.76 8.15 1.69 9.85 0.95
WET_ 42.04 16.28 13.58 15.69 44.29 15.51 32.70 18.46 RAINFORESTS
3.23 3.74 0.00 2.22 0.59 0.09 1.15 0.00 2.71 0.13 0.22 1.62 4.67 0.96 0.00 0.58 2.02 1.21 3.71 1.88 5.16
38.52 10.57 16.99 26.77
FORESTS SCLEROPHYLL_
0.63 2.67 0.18 7.84 8.46 8.53 4.63 1.72 7.61 5.51 9.52 7.22 0.29 2.32 0.00 2.74 8.41 7.84 2.87
DRY_ 14.67 17.02 11.11 28.70 13.95 14.85
VEGETATION FINAL_
0.00 0.00 4.28 1.84 2.74 1.85 4.56 4.63 0.38 2.47 1.96 7.44 0.68 0.00 5.18 1.18 1.17 0.00 7.77 2.87 0.29 4.27 2.45
11.16 10.58 TERR1000
9.51 0.10 0.83 2.65 4.04 9.69 0.34 1.04 0.12 0.50 1.27 0.05 2.34 0.75 0.69 0.32 0.16 0.06 2.17 1.72 1.97 3.65 6.32 5.75
14.65 SLOPE
1.57 2.29 5.84 9.55 2.27 1.24 0.00 0.00 0.04 4.84 6.13 4.29 2.42 9.01 0.15
17.58 13.51 20.21 46.86 14.69 14.25 10.26 19.96 23.12 18.01
RAIN SEASONAL_
4.67 3.66 5.90 4.16 0.00 7.36 0.28 0.34 0.00 4.80 5.46 8.15
11.23 18.27 15.63 41.01 20.33 12.38 17.60 18.19 13.05 43.61 12.94 26.74 17.01 MEAN_RAIN
8.67 0.44 5.83 3.87 2.54 2.25 2.38 2.47 0.00 4.61 0.00 4.13 3.33 0.00
13.51 27.88 20.74 33.03 16.18 22.92 62.47 38.36 18.32 10.37 11.03 HOT_TEMP
8.48 7.88 1.26 3.71 0.00 0.83 1.36 7.71 4.11 0.00 0.00 2.29 1.43 0.35 2.13 5.69 1.09 5.10 3.37 2.32
14.02 20.22 13.48 13.17 52.60 COLD_TEMP
6.45 7.83 5.22 3.66 0.00 7.48 7.80 6.32 8.52 1.08
22.58 27.14 31.98 44.13 56.60 43.56 33.58 41.93 64.29 42.97 67.57 16.53 67.10 57.75 44.57 TEST AUC TEST
0.87 (0.012)
0.707 (0.013) 0.853 (0.072) 0.874 (0.064) 0.873 (0.028) 0.721 (0.009) 0.835 (0.015) 0.941 (0.023) 0.933 (0.033) 0.904 (0.044) 0.847 (0.012) 0.916 (0.008) 0.951 (0.024) 0.913 (0.018) 0.913 (0.033) 0.723 (0.013) 0.971 (0.014) 0.973 (0.013) 0.946 (0.024) 0.706 (0.009) 0.709 (0.014) 0.909 (0.008) 0.902 (0.015) 0.876 (0.024) 0.967 (0.019) N.RECORDS 27 37 42 46 30 46 81 29 84 76 164 556 813 137 174 756 782 233 198 2186 4323 1101 1423 3845 2230 Ptilonorhynchus violaceus Ptilonorhynchus Ptilinopus superbus Ptilinopus regina Ptilinopus magnificus Psophodes olivaceus Psophodes Psephotus haematonotus Psephotus Porzana tabuensis Porzana Porzana pusilla Porzana Porzana fluminea Porzana Porphyrio porphyrio Porphyrio Pomatostomus temporalis temporalis Pomatostomus temporalis Pomatostomus superciliosus Pomatostomus Poliocephalus poliocephalus Poliocephalus Podiceps cristatus Podiceps Podargus strigoides Podargus TABLE 5 CONTINUED 5 TABLE BIRDS Pluvialis squatarola Pluvialis Pluvialis fulva Pluvialis Plegadis falcinellus Plegadis Plectorhyncha lanceolata Plectorhyncha Platycercus eximius Platycercus Platycercus elegans Platycercus Platalea regia Platalea Platalea flavipes Platalea Pitta versicolor Pitta Phylidonyris pyrrhoptera Phylidonyris
28 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLL_
2.50 7.41 6.32 3.08 3.50 5.83 4.41 0.80 2.83 3.36 8.28 6.26 1.81 0.00 6.57 0.45 3.36
WET_ 20.06 16.49 39.43 27.89 36.70 26.42 11.79 12.20 19.55 RAINFORESTS
0.25 2.36 0.00 5.19 4.26 2.36 5.68 0.62 0.73 3.35 0.00 0.72 1.31 0.92 0.00 5.70 1.32 2.43 1.13 2.21 0.41 2.96
16.31 25.17 12.31 32.08
FORESTS SCLEROPHYLL_
0.78 5.22 3.98 4.01 0.92 6.21 7.55 4.58 8.63 0.00 5.32 1.65 3.63 0.00 0.00 9.07 0.80 1.57
DRY_ 62.58 34.05 12.13 13.36 12.67 10.76 14.92 38.31
VEGETATION FINAL_
4.56 2.41 4.57 2.17 6.68 3.88 3.78 2.75 3.18 0.78 0.74 1.48 6.57 0.30 6.49 0.48 6.92 4.24 2.65 0.24 2.14 3.35 2.36 2.33
11.22 12.83 TERR1000
7.88 3.82 2.99 1.56 5.42 5.38 0.27 5.91 0.12 0.96 0.09 5.44 0.04 2.57 0.98 5.80 3.31 3.92 8.34 2.78 0.22 3.22 0.74
24.38 10.18 10.31 SLOPE
3.89 9.07 9.88 9.59 4.01 1.90 0.60 1.04 0.33 9.84 1.32 6.12 5.28 6.90 7.45 0.98 1.57 4.42
23.82 19.89 19.85 12.65 17.79 17.65 25.55 23.66
RAIN SEASONAL_
9.44 6.56 3.49 2.54 0.00 5.79 6.18 6.56 5.18 0.20 1.88 7.56 7.20 9.27 3.75 6.72 3.74 0.00 5.11 1.64 2.75
23.57 11.55 17.39 21.27 17.41 MEAN_RAIN
0.00 6.64 1.22 0.00 0.57 0.24 5.09 1.13 3.70 0.04 0.00 0.00 6.62
53.88 30.42 21.00 66.89 14.77 39.08 34.11 21.84 49.63 41.73 21.07 12.24 37.67 HOT_TEMP
4.81 8.78 0.00 5.09 3.06 1.74 5.30 2.83 0.00 0.09 0.60 3.11 8.40 2.84 0.00 8.33 0.00 5.96 0.33 4.11
10.98 14.80 23.75 11.16 24.45 20.88 COLD_TEMP
8.60 2.72 4.33 9.97 3.77 2.65 6.59 0.59
12.01 23.97 10.16 45.93 25.60 28.74 22.28 11.30 77.51 23.14 21.91 35.69 71.95 20.14 58.17 36.87 66.09 10.98 TEST AUC TEST 0.9 (0.023)
0.64 (0.011) 0.829 (0.02) 0.661 (0.01)
0.887 (0.031) 0.836 (0.019) 0.892 (0.063) 0.802 (0.013) 0.856 (0.032) 0.708 (0.114) 0.916 (0.015) 0.907 (0.046) 0.975 (0.011) 0.967 (0.017) 0.981 (0.005) 0.913 (0.013) 0.874 (0.016) 0.824 (0.017) 0.707 (0.011) 0.834 (0.015) 0.765 (0.016) 0.775 (0.014) 0.723 (0.011) 0.971 (0.014) 0.976 (0.013) 0.951 (0.014) N.RECORDS 20 28 24 34 96 67 111 687 845 105 324 158 139 198 794 697 484 614 855 989 126 4849 3780 1346 3364 6063 Taeniopygia guttata Taeniopygia Taeniopygia bichenovii Taeniopygia Tadorna tadornoides Tadorna Tachybaptus novaehollandiae Tachybaptus Symposiachrus trivirgatus Symposiachrus Strepera versicolor Strepera Strepera graculina Strepera Stipiturus malachurus Stipiturus Stictonetta naevosa Sternula albifrons Sternula Sterna striata Sterna Sterna hirundo Sterna Stagonopleura guttata Stagonopleura Sphecotheres vieilloti Sphecotheres Smicrornis brevirostris Smicrornis Sericulus chrysocephalus TABLE 5 CONTINUED 5 TABLE BIRDS Sericornis magnirostra Sericornis frontalis Sericornis citreogularis Scythrops novaehollandiae Rhipidura rufifrons Rhipidura leucophrys Rhipidura albiscapa Recurvirostra novaehollandiae Pycnoptilus floccosus Pycnoptilus Ptiloris paradiseus
29 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLL_
2.79 0.77 5.71 4.21 3.21 2.92 2.63 0.51 2.13 2.44 0.72 2.14 9.75
WET_ 42.83 21.38 40.03 17.87 12.38 14.31 14.13 12.43 15.21 17.84 RAINFORESTS
3.93 0.01 0.56 5.44 0.19 1.22 1.01 5.06 1.43 0.15 0.08 0.60 0.10 2.79 0.83 0.11 0.32
12.23 42.47 14.67 18.81 28.21 28.06
FORESTS SCLEROPHYLL_
8.84 1.02 5.55 0.00 3.08 0.70 6.34 7.86 1.87 0.56 1.54 2.19 5.05 0.76 9.05 2.39 4.53
DRY_ 14.97 19.84 17.52 43.38 16.90 10.40
VEGETATION FINAL_
1.77 1.69 1.05 8.22 0.15 3.98 4.18 0.00 2.66 4.38 0.88 5.09 1.63 0.00 0.06 7.57 1.34 1.90 0.92 1.52 1.21 0.29
11.05 TERR1000
7.53 2.55 4.68 1.95 0.56 1.91 0.12 4.51 2.30 1.61 0.44 0.44 0.18 0.08 6.97 1.91 2.72 0.73 0.47 0.37 0.47
18.42 11.62 SLOPE
6.64 1.20 0.38 9.63 1.05 0.06 1.11 4.03 0.03 3.69 1.28 0.33 2.19 9.37 1.17 0.29
14.98 17.28 10.70 16.79 21.65 13.99 38.87
RAIN SEASONAL_
6.12 9.04 5.88 2.25 5.02 9.90 7.69 2.89 9.70 0.26 3.55 9.25 9.76 8.28 1.82 8.39
12.81 10.09 24.07 23.20 25.40 41.94 10.14 MEAN_RAIN
0.40 2.46 0.14 2.78 3.25 7.30 2.87 2.31 0.84 0.56 1.81 2.02 1.93
15.56 12.80 15.48 12.97 81.56 25.85 63.87 16.21 16.59 36.40 HOT_TEMP
0.00 6.66 1.97 2.11 1.38 3.61 4.39 0.00 1.45 0.64 0.11 1.10 8.66 5.17 6.19 3.46 0.00 0.74 1.15 1.11
24.08 10.58 15.69 COLD_TEMP
4.11 3.11 9.53 4.74 5.54 9.82 1.09 7.08 4.62
46.94 78.68 32.36 17.07 30.93 38.46 76.71 81.24 11.12 61.00 56.94 23.02 80.10 30.36 TEST AUC TEST 0.87 (0.04)
0.811 (0.08) 0.794 (0.01) 0.921 (0.03) 0.86 (0.007) 0.917 (0.01) 0.85 (0.081) 0.78 (0.013)
0.688 (0.012) 0.811 (0.027) 0.986 (0.004) 0.923 (0.011) 0.828 (0.023) 0.726 (0.038) 0.799 (0.034) 0.981 (0.009) 0.978 (0.004) 0.976 (0.007) 0.882 (0.029) 0.899 (0.027) 0.823 (0.013) 0.894 (0.009) 0.959 (0.007) N.RECORDS 71 63 44 36 26 93 329 357 256 203 190 101 220 132 998 144 775 3191 2769 2774 1724 1034 1325 Zosterops lateralis Zosterops Zoothera lunulata Zoothera Zoothera heinei Zoothera Xenus cinereus Xenus Vanellus tricolor Vanellus Vanellus miles Vanellus Tyto tenebricosa Tyto Tyto novaehollandiae Tyto Tyto longimembris Tyto Tyto javanica Tyto Turnix varius Turnix Tringa stagnatilis Tringa Tringa nebularia Tringa TABLE 5 CONTINUED 5 TABLE BIRDS Tringa brevipes Tringa Trichoglossus haematodus Trichoglossus Trichoglossus chlorolepidotus Trichoglossus Tribonyx ventralis Tribonyx Tregellasia capito Tregellasia Todiramphus sanctus Todiramphus Todiramphus macleayii Todiramphus Threskiornis spinicollis Threskiornis molucca Thalasseus bergii Thalasseus
30 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS
SCLEROPHYLL SCLEROPHYLL
WET WET 4.98 7.36 0.55 0.85 2.44 0.88 5.15 2.36 0.16 2.78 0.61 0.03 5.25 0.61 4.29 0.29 2.14 6.75
19.93 13.34 70.61 51.31 23.96 39.19 RAINFORESTS
5.58 1.67 0.11 0.36 0.66 0.71 1.77 2.07 0.00 2.79 4.60 1.45 1.49 0.20 2.88 2.13 1.86 1.50 1.54 0.97 1.15 4.95 0.58
28.52
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 3.85 1.38 1.74 0.40 1.76 2.24 1.51 3.91 1.71 0.95 4.57 6.64 0.00 7.04 8.80 1.63 0.74 0.36 5.44 2.59
16.06 24.39 10.62 23.36
VEGETATION FINAL FINAL
5.78 3.34 3.42 2.27 3.84 2.53 7.53 9.95 0.25 4.74 3.38 8.77 2.41 7.81 0.52 3.24 7.46 5.52
12.12 23.80 15.95 25.08 19.13 15.52 TERR1000
4.10 0.00 9.53 1.81 1.86 0.05 4.40 1.42 2.97 2.57 3.77 1.20 1.50 1.07 2.83 5.78 0.07 0.46 2.98 2.25 2.16 2.24 4.99
14.89 SLOPE
7.67 6.89 4.51 2.25 8.96 8.73 2.51 3.75 6.46 0.40 0.18 4.03 5.40
12.83 17.85 18.78 14.20 18.24 15.04 32.61 18.02 13.02 10.41 12.46
RAIN SEASONAL_
7.84 3.52 6.41 8.91 2.18 8.02 0.06 5.43 6.44
23.90 10.44 10.77 11.46 27.70 42.14 12.04 31.25 10.14 22.77 11.02 11.53 20.22 47.72 23.86 MEAN_RAIN
8.00 6.22 7.27 1.17 0.00 7.08 0.74 2.97 4.63 5.92 5.70 4.89 1.13 3.39
44.15 63.85 12.48 19.66 53.74 10.10 62.90 23.66 15.33 46.47 HOT_TEMP
3.46 0.00 9.20 1.19 3.07 6.16 2.18 2.85 2.36 0.05 8.88 9.88 1.48 0.00 0.00 0.00
17.22 12.71 53.35 17.18 12.69 13.92 16.60 81.64 COLD_TEMP
0.00 0.03 4.51 1.56 6.69 2.33 0.86 0.01 1.08 0.06 0.00 9.70
23.05 12.89 12.43 24.67 16.20 10.48 24.18 15.27 16.70 74.00 35.95 11.85 TEST AUC TEST
0.83 (0.011) 0.78 (0.015)
0.777 (0.028) 0.843 (0.094) 0.824 (0.036) 0.844 (0.037) 0.862 (0.057) 0.847 (0.027) 0.707 (0.022) 0.723 (0.014) 0.747 (0.042) 0.774 (0.057) 0.849 (0.017) 0.951 (0.011) 0.811 (0.015) 0.943 (0.014) 0.802 (0.027) 0.764 (0.017) 0.997 (0.001) 0.878 (0.035) 0.883 (0.009) 0.769 (0.017) 0.832 (0.018) 0.725 (0.062) N.RECORDS 29 60 70 40 53 85 268 197 129 188 838 197 396 188 227 264 730 857 519 1390 1077 1379 1106 1008 MAMMALS Acrobates pygmaeus Acrobates Aepyprymnus rufescens Antechinus flavipes Antechinus Antechinus stuartiiAntechinus Antechinus swainsonii Antechinus Cercartetus nanus Cercartetus Chalinolobus dwyeri Chalinolobus gouldii Chalinolobus morio Dasyurus maculatus Falsistrellus tasmaniensis Falsistrellus Hydromys chrysogaster Hydromys Isoodon macrourus Kerivoula papuensis Kerivoula Macropus giganteus Macropus Macropus parma Macropus Macropus robustus Macropus Macropus rufogriseus Macropus Mastacomys fuscus Mastacomys Melomys cervinipesMelomys Miniopterus australis Miniopterus schreibersii oceanensis Miniopterus schreibersii Mormopterus norfolkensis Mormopterus planiceps Table 6. Mean results from MaxEnt models for mammals within the Greater Hunter region. Results show the number of records used to construct used to each model and the mean (± the number of records Results show region. Hunter mammals within the Greater MaxEnt models for from 6. Mean results Table the permutation importancevariablefor each represent variables for the environmental shown The data models. five-fold cross-validated across value AUC test deviation) standard constructused to the full model.
31 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS
SCLEROPHYLL SCLEROPHYLL
WET WET 6.60 0.31 2.99 0.00 0.87 3.30 0.00 0.69 1.42 1.76 7.53 0.45 0.39 1.34 0.42 2.03 0.00 3.64 0.44
12.36 24.07 20.05 19.28 11.35 18.67 36.34 RAINFORESTS
4.13 0.21 2.65 4.56 1.67 3.29 1.91 1.17 2.46 4.14 2.23 0.00 1.27 2.62 0.50 3.95 0.23 1.52 0.00 0.96 0.00 0.00 4.49 0.00 1.08
23.48
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 7.06 6.16 4.84 7.01 4.19 1.91 1.76 9.76 0.00 0.00 1.13 0.00 8.21 0.15 0.80 2.91 3.94 0.14 4.67 8.24
15.10 10.49 11.35 10.25 11.11 11.89
VEGETATION FINAL FINAL
0.11 6.95 7.19 8.78 7.71 6.07 7.15 1.36 0.38 2.34 4.82 1.62 5.60 0.29 2.40 0.78 4.19 1.55 8.95 2.60
10.31 18.05 33.78 13.29 10.97 12.63 TERR1000
1.45 2.08 0.44 0.90 0.60 1.24 1.11 2.02 8.81 5.30 3.98 2.25 1.55 0.21 1.83 0.19 2.07 4.76 0.89 0.97 1.35 5.63 1.84 1.33 2.39
31.17 SLOPE
7.61 1.28 9.70 9.52 2.86 8.41 0.00 8.34 4.89 7.23 6.39 7.21
20.82 17.97 19.82 18.67 12.45 13.97 17.06 15.92 10.23 31.76 27.65 10.48 17.13 14.51
RAIN SEASONAL_
4.46 4.86 7.79 0.94 2.67 5.26 3.07 0.00 9.16 7.38 4.05 9.25 6.58 4.52
12.00 16.58 27.33 10.14 10.80 16.42 26.36 18.85 10.39 33.77 35.85 22.14 MEAN_RAIN
1.13 0.41 0.38 3.03 0.56 0.35 9.90 3.49 4.29 3.53 1.21 1.90
10.31 26.20 43.20 37.76 44.30 53.20 12.71 75.91 28.70 12.95 54.78 44.69 10.55 29.04 HOT_TEMP
0.44 1.32 8.77 0.45 3.11 1.21 6.11 8.60 3.42 2.36 0.00 4.88 4.38 9.73 6.53 8.03 0.00 0.16 8.19
12.29 47.51 18.82 13.68 31.36 24.66 10.07 COLD_TEMP
0.35 3.86 2.95 7.41 7.11 1.75 7.40 8.42 4.51
42.48 22.82 11.32 12.05 18.53 21.64 33.01 30.91 28.18 12.08 17.12 31.28 34.47 54.76 35.51 21.73 22.42 TEST AUC TEST 0.8 (0.01)
0.783 (0.02) 0.85 (0.012) 0.818 (0.02) 0.82 (0.023)
0.834 (0.019) 0.745 (0.027) 0.804 (0.022) 0.854 (0.013) 0.875 (0.007) 0.857 (0.009) 0.868 (0.014) 0.896 (0.023) 0.839 (0.023) 0.716 (0.006) 0.859 (0.037) 0.818 (0.014) 0.969 (0.012) 0.857 (0.034) 0.957 (0.037) 0.877 (0.042) 0.829 (0.013) 0.886 (0.014) 0.782 (0.058) 0.916 (0.034) 0.807 (0.025) N.RECORDS 63 45 25 68 75 68 345 357 687 655 785 826 180 271 164 928 474 536 379 410 2049 1626 2092 6867 1166 1115 TABLE 6 CONTINUED 6 TABLE MAMMALS Myotis macropus Myotis Nyctophilus geoffroyi Nyctophilus gouldi Ornithorhynchus anatinus Ornithorhynchus Perameles nasuta Perameles Petauroides volans Petauroides Petaurus australis Petaurus Petaurus breviceps Petaurus Petaurus norfolcensis Petaurus Petrogale penicillata Petrogale Phascogale tapoatafa Phascogale Phascolarctos cinereus Phascolarctos Potorous tridactylus Potorous Pseudocheirus peregrinus Pseudocheirus Pseudomys gracilicaudatus Pseudomys Pseudomys novaehollandiae Pseudomys Pseudomys oralis Pseudomys Pteropus poliocephalus Pteropus Pteropus scapulatus Pteropus Rattus fuscipes Rattus lutreolus Rhinolophus megaphyllus Saccolaimus flaviventris Saccolaimus Scoteanax rueppellii Scoteanax Scotorepens balstoni Scotorepens Scotorepens orion Scotorepens
32 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS
SCLEROPHYLL SCLEROPHYLL
WET WET 8.15 7.09 1.35 6.90 8.84 2.56 1.80 1.06 1.22 7.04 0.03 0.00 7.40
28.09 15.72 RAINFORESTS
1.09 7.31 3.28 0.00 9.72 5.27 3.69 0.00 5.62 4.88 1.90 0.38 1.25
29.03 20.28
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 8.21 0.47 3.36 3.61 0.01 9.15 2.31 2.70 4.47 6.40
12.17 19.56 10.92 14.18 24.59
VEGETATION FINAL FINAL
8.20 3.25 1.41 5.13 4.03 6.54 5.75 3.75 8.12
14.21 10.43 18.29 15.41 23.47 19.34 TERR1000
4.15 0.00 1.05 2.97 1.85 1.66 4.35 2.83 1.84 0.52 0.23 0.20 3.12 4.85 1.99 SLOPE
0.26 7.96 6.14 6.67 2.50
28.56 12.48 21.18 24.21 17.39 19.64 17.34 29.07 12.32 13.35
RAIN SEASONAL_
8.19 4.31 5.48 0.00 3.07 3.54 7.39 9.55
30.18 23.16 26.13 14.08 13.73 15.43 39.32 MEAN_RAIN
3.11 0.00 0.00 1.24 4.65 5.29 2.38 7.05 0.48 3.28
15.48 24.41 10.86 34.71 14.97 HOT_TEMP
2.00 3.45 2.84 0.54 3.16 6.44 0.43 1.24 6.04 9.80
11.45 34.60 17.43 11.38 15.62 COLD_TEMP
9.30 7.22 6.13 2.53
27.25 52.55 62.08 14.95 17.67 13.16 18.42 18.10 24.17 10.05 14.74 TEST AUC TEST
0.893 (0.02) 0.829 (0.04) 0.76 (0.012)
0.789 (0.053) 0.955 (0.032) 0.689 (0.011) 0.762 (0.016) 0.927 (0.034) 0.917 (0.012) 0.716 (0.012) 0.773 (0.035) 0.847 (0.013) 0.758 (0.037) 0.752 (0.015) 0.744 (0.012) N.RECORDS 22 42 150 966 365 304 387 798 247 126 2350 2018 1310 2009 1591 TABLE 6 CONTINUED 6 TABLE MAMMALS Sminthopsis murina Sminthopsis Syconycteris australis Syconycteris Tachyglossus aculeatus Tachyglossus Tadarida australis Tadarida Thylogale stigmatica Thylogale Thylogale thetis Thylogale Trichosurus caninus Trichosurus Trichosurus vulpecula Trichosurus Vespadelus darlingtoni Vespadelus Vespadelus pumilus Vespadelus Vespadelus regulus Vespadelus Vespadelus troughtoni Vespadelus Vespadelus vulturnus Vespadelus Vombatus ursinus Vombatus Wallabia bicolor Wallabia
33 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
7.31 3.37 4.87 2.02 9.11 6.68 7.76 4.99 1.20 4.93
26.81 20.76 29.19 14.57 64.19 57.45 53.25 25.12 14.89 30.44 44.15 20.83 17.81 23.04
FORESTS
SCLEROPHYLLS SCLEROPHYLLS
WET WET 4.56 4.94 0.00 1.95 0.02 1.08 1.89 0.33 2.01 0.57 0.99 4.31 1.07 1.38 1.94 0.56 4.73 3.15 1.66 1.52 4.71
10.30 12.42 18.63 RAINFORESTS
2.66 2.42 3.64 3.12 1.45 8.21 0.00 0.96 4.00 0.66 0.56 0.52 2.63 1.58 0.51 5.28 4.84 0.03 0.43 0.10 1.44 1.91 8.61
16.62
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 1.19 3.53 0.80 0.27 2.90 1.45 2.84 4.64 3.29 7.45 0.08 2.23 1.34 0.78 0.00 5.82 1.04 0.10 5.21 2.02 3.02 4.67
59.42 26.04
VEGETATION FINAL FINAL
3.42 7.32 9.23 5.31 7.05 1.24 0.00 0.53 7.15 9.76 9.11 6.03 1.98 8.73 1.14 0.16 0.57 1.91
22.33 17.46 13.82 25.94 26.43 19.03 SLOPE
0.83 0.00 0.78 5.19 7.26 2.23 0.94 6.29 1.07 3.43 0.01 0.69 7.23 4.28 5.55 7.37 0.47 0.31 0.90 1.87 0.06
14.92 10.11 23.35 MEAN_SOLAR
0.79 5.91 0.00 0.00 0.00 0.97 5.63 5.23 0.15
33.49 18.03 53.74 48.09 54.03 17.50 49.74 41.75 47.32 14.08 36.07 28.75 23.52 12.28 20.92 SEASONAL_RAIN
5.98 1.18 5.02 2.03 1.36 0.00 5.39 0.76 0.00 6.28 5.68 0.41 4.43
13.04 38.48 26.42 11.65 29.96 12.10 15.02 29.60 14.28 22.19 40.52 HOT_TEMP
8.01 2.21 8.32 4.60 0.38 0.80 0.00 1.78 0.00 0.00 1.14 0.54 2.10 0.00 2.23 9.85 3.60 2.38 1.88
11.37 25.12 18.16 25.41 46.17 COLD_TEMP
0.00 8.26 9.34 3.95 2.87 2.25 0.74 5.80 0.00 9.78 3.02 0.00 0.00 2.45 5.95 2.59 0.54 1.90
35.82 14.91 34.74 37.85 26.45 26.05 TEST AUC TEST
0.97 (0.011) 0.865 (0.02) 0.927 (0.02) 0.953 (0.03)
0.975 (0.013) 0.906 (0.048) 0.942 (0.022) 0.906 (0.008) 0.874 (0.049) 0.836 (0.058) 0.941 (0.009) 0.972 (0.003) 0.975 (0.022) 0.974 (0.018) 0.799 (0.018) 0.822 (0.018) 0.898 (0.066) 0.795 (0.109) 0.741 (0.015) 0.918 (0.013) 0.832 (0.031) 0.984 (0.004) 0.994 (0.003) 0.987 (0.003) N.RECORDS 25 31 68 68 52 28 47 64 26 21 20 35 745 348 316 308 131 567 488 283 195 132 126 1051 Boronia floribunda Boronia Boronia falcifolia Boronia Boronia anethifolia Boronia Blandfordia grandiflora Blandfordia Banksia spinulosa Asplenium australasicum Asplenium Asperula asthenes Asperula Arthrochilus prolixus Archontophoenix cunninghamiana Archontophoenix Angophora inopina Angophora Allocasuarina simulans Allocasuarina defungens Adiantum silvaticum Adiantum Adiantum hispidulum Adiantum Adiantum formosum Adiantum Adiantum diaphanum Adiantum Adiantum atroviride Adiantum Adiantum aethiopicum Adiantum Actinotus helianthi Acianthus fornicatus Acianthus PLANTS Acianthus collinus Acianthus Acacia pendula Acacia Acacia courtiiAcacia Acacia bynoeana Acacia Table 7. Mean results from MaxEnt models for plants within the Greater Hunter region. Results show the number of records used to construct each model and the mean (± standard construct used to each model and the mean (± standard the number of records Results show region. Hunter within the Greater plants MaxEnt models for from 7. Mean results Table to the permutation importancevariable for each used represent variables for the environmental shown The data models. five-fold cross-validated across value AUC test deviation) construct the full model.
34 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
2.68 7.28 5.77 9.76 8.70 3.81 2.71 3.65 8.67
36.07 21.97 29.26 38.46 41.29 38.12 22.53 12.91 33.31 16.66 14.77 17.68 15.59 19.50 19.35 70.16
FORESTS
SCLEROPHYLLS SCLEROPHYLLS
WET WET 4.46 6.48 7.51 0.23 3.01 2.25 3.78 6.87 0.51 8.41 0.10 5.18 2.06 5.94 4.24 0.00 5.91 5.49 0.00 0.00 2.96 0.24 0.10 6.89
14.41 RAINFORESTS
0.59 0.00 5.77 2.78 0.00 3.86 0.15 0.00 0.00 0.00 2.22 0.33 9.75 0.97 3.06 4.57 2.89 1.80 0.25 2.04 2.35 0.05 0.18
10.46 10.26
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 0.05 1.39 1.55 3.45 3.98 0.12 0.61 0.40 4.18 0.21 0.25 3.40 6.78 3.17 1.53 6.84 0.88 1.15 2.19
13.35 13.96 10.00 27.20 13.40 11.99
VEGETATION FINAL FINAL
5.53 0.53 0.00 5.70 6.30 4.93 5.26 0.00 2.46 9.72 0.80 5.90 0.51 5.88 3.67 6.92 1.75
13.30 21.39 10.14 16.35 10.45 26.51 30.26 10.04 SLOPE
5.19 0.00 4.46 0.00 0.00 1.38 2.94 0.99 0.95 0.18 4.60 5.96 0.58 1.03 2.50 2.95 2.80 0.01 6.39 3.19 1.37 0.48
33.56 44.38 33.83 MEAN_SOLAR
0.38 1.85 0.62 2.91 1.81 4.00 0.98 4.92 2.43
28.05 63.53 14.40 53.03 28.28 33.52 13.48 14.92 25.47 26.17 17.38 14.99 86.27 56.43 40.40 22.45 SEASONAL_RAIN
6.75 0.00 1.55 0.75 6.17 9.59 3.08 2.20 0.21 7.39 5.10 5.90 0.00 4.19 0.12 1.96 4.04 0.00 0.00 7.59 1.91 0.95
16.17 25.80 34.85 HOT_TEMP
0.00 5.04 3.40 1.76 9.82 0.00 3.62 5.31 1.02 0.00 2.27 1.89 6.15 7.91 0.00 0.85 3.82 2.00
89.02 21.87 10.77 23.10 17.77 13.08 11.90 COLD_TEMP
0.00 0.00 2.69 1.46 0.16 0.42 0.53 0.42 0.20 0.19 4.73 6.23 4.93
11.06 18.56 38.93 26.62 26.14 11.03 15.66 14.62 14.91 50.46 21.68 10.47 TEST AUC TEST
0.91 (0.023) 0.78 (0.082) 0.77 (0.055)
0.708 (0.084) 0.996 (0.002) 0.904 (0.046) 0.845 (0.065) 0.924 (0.018) 0.951 (0.022) 0.925 (0.037) 0.863 (0.025) 0.896 (0.042) 0.977 (0.003) 0.896 (0.034) 0.923 (0.034) 0.886 (0.031) 0.882 (0.045) 0.936 (0.027) 0.958 (0.007) 0.998 (0.001) 0.963 (0.018) 0.929 (0.018) 0.933 (0.018) 0.909 (0.041) 0.963 (0.011) N.RECORDS 20 24 26 27 78 57 34 39 34 53 78 43 51 33 45 46 162 153 308 290 156 284 106 154 153 . Chiloglottis sylvestris Chiloglottis pluricallata Chiloglottis diphylla Cestichis reflexa Cestichis Ceratopetalum gummiferum Ceratopetalum Caustis recurvata Caustis Caustis pentandra Caustis Caustis flexuosa Caustis cunninghamiana Casuarina cunninghamiana subsp Casuarina Calochilus robertsoniiCalochilus Calochilus paludosus Calochilus Callistemon linearifolius Callistemon Caleana major Caleana Calanthe triplicata Calanthe Caladenia catenata Caladenia Caladenia carnea Caladenia Bulbophyllum shepherdii Bulbophyllum Bulbophyllum exiguum Bulbophyllum Bothriochloa biloba Boronia serrulata Boronia Boronia rubiginosa Boronia TABLE 7 CONTINUED 7 TABLE PLANTS Boronia polygalifolia Boronia Boronia pinnata Boronia Boronia parvifloraBoronia Boronia ledifolia Boronia
35 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
8.11 5.16 1.85 4.72 9.64 4.12 2.45 2.27
40.73 36.01 40.28 27.54 47.37 11.17 61.76 30.17 10.66 16.17 27.84 13.46 18.22 19.10 13.01 44.32 21.95 29.81
FORESTS
SCLEROPHYLLS SCLEROPHYLLS
WET WET 0.00 0.00 1.55 0.18 0.53 1.78 0.46 9.31 0.00 1.92 9.59 1.19 0.10 1.51 3.87 0.19 0.01 1.03 3.08 2.77 8.09 3.80
21.31 22.98 19.99 10.76 RAINFORESTS
0.00 5.61 0.00 6.84 1.10 6.63 7.03 7.27 0.13 0.00 0.00 0.00 3.79 1.05 6.78 9.23 0.00 0.03
15.43 17.98 13.54 38.92 19.82 23.31 25.16 10.60
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 0.48 4.69 7.67 4.14 1.83 1.96 0.08 4.90 0.41 3.82 4.50 0.42 3.81 2.20 2.02 2.78 0.44 0.91 2.37 5.67 1.24 4.38 0.00 0.15 0.92 0.00
VEGETATION FINAL FINAL
1.32 3.15 1.09 6.04 7.35 6.56 4.53 2.11 3.61 0.00 5.80 5.05 4.94 3.09 0.34 2.51 0.84 0.00 7.02 0.63 0.00
11.88 15.05 16.40 22.19 11.37 SLOPE
1.74 8.74 0.91 1.29 0.00 0.32 4.88 2.20 1.56 2.91 3.14 0.00 0.65 1.81 1.37 0.53 3.19 3.16 4.19 2.10 5.11 0.00 8.03 0.37 0.00
13.14 MEAN_SOLAR
2.22 1.27 0.73 0.00 2.14 1.69 0.00 2.60 4.90
35.14 13.08 34.28 42.94 12.78 10.68 14.20 32.60 89.49 11.83 28.72 67.54 25.02 28.75 64.29 70.58 46.26 SEASONAL_RAIN
0.00 0.00 1.36 1.70 2.73 2.13 0.41 0.53 2.20 7.27 9.48 0.12 1.18 1.19 2.24 0.96 1.36 0.00 0.28 2.08 0.11
12.63 14.83 34.78 14.27 20.11 HOT_TEMP
0.11 7.98 0.00 0.00 2.46 1.89 1.25 2.16 2.57 2.04 0.44 0.08 1.24 5.06 8.40 4.26 3.49 0.00 0.00 0.48
19.67 19.70 15.66 46.58 11.71 24.69 COLD_TEMP
0.49 0.32 4.18 5.98 0.00 1.97 7.45 1.46 3.73 1.03 7.28 0.00 3.33 6.35 2.91
32.22 13.90 11.38 43.02 47.41 28.04 25.65 13.32 34.27 57.36 60.87 TEST AUC TEST
0.954 (0.02) 0.923 (0.01)
0.994 (0.002) 0.689 (0.102) 0.768 (0.053) 0.912 (0.034) 0.847 (0.058) 0.936 (0.027) 0.949 (0.018) 0.857 (0.102) 0.823 (0.063) 0.911 (0.033) 0.916 (0.044) 0.855 (0.043) 0.994 (0.001) 0.884 (0.046) 0.833 (0.018) 0.968 (0.016) 0.944 (0.016) 0.893 (0.019) 0.789 (0.099) 0.955 (0.011) 0.934 (0.016) 0.968 (0.026) 0.826 (0.067) 0.941 (0.045) N.RECORDS 57 40 67 26 50 54 20 51 86 34 63 93 56 26 20 24 41 118 126 127 287 162 256 152 108 308 Diuris tricolor Diuris sulphurea Dipodium punctatum Dicksonia antarctica Dendrobium tetragonum Dendrobium Dendrobium teretifolium Dendrobium Dendrobium schoeninum Dendrobium Dendrobium pugioniforme Dendrobium Dendrobium mortiiDendrobium Dendrobium linguiforme Dendrobium Dendrobium gracilicaule Dendrobium Dendrobium fairfaxiiDendrobium Dendrobium aemulum Dendrobium Darwinia glaucophylla Cynanchum elegans Cynanchum Cymbidium suave Cymbidium Cymbidium canaliculatum Cymbidium Cyathea leichhardtiana Cyathea Cyathea australis Cyathea Cyanicula caerulea Cyanicula Cryptostylis subulata Cryptostylis erecta TABLE 7 CONTINUED 7 TABLE PLANTS Crowea saligna Crowea Corybas fimbriatus Cordyline stricta Cordyline Chiloglottis trilabra
36 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
1.05 3.62 7.36 2.97 7.44 3.76 7.32 4.29 0.00 2.61 8.46 8.50 0.74 1.24 2.98 2.95 2.64
10.28 19.30 37.61 14.65 19.41 17.57 86.06
FORESTS
SCLEROPHYLLS SCLEROPHYLLS
WET WET 9.25 1.77 4.89 0.74 0.42 2.76 0.00 0.92 0.28 0.00 9.22 0.09 0.57 4.65 1.58 0.94 6.93 0.00 0.31
18.01 11.59 55.92 13.04 16.02 RAINFORESTS
0.00 0.27 0.09 0.66 0.11 9.55 5.79 1.53 3.31 0.00 0.42 0.00 3.68 1.86 0.51 1.02 0.01 0.76 0.93 0.00 5.22
20.34 15.69 10.57
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 2.21 8.81 5.60 0.74 2.31 2.07 0.00 1.24 1.81 2.52 1.33 1.47 3.34 1.91
11.14 28.05 44.04 15.29 47.34 22.80 11.10 11.95 34.03 11.95
VEGETATION FINAL FINAL
2.96 0.11 0.99 8.42 0.14 0.00 1.91 0.07 1.74 1.74 0.31 4.69 0.00 2.05 0.92 2.57 2.19 0.00 0.17 2.44 5.86 0.74 0.65
11.47 SLOPE
2.75 1.40 0.46 0.38 7.07 5.00 0.12 3.96 5.16 8.45 8.20 3.08 1.62 7.04 3.81 2.47 1.30 2.71 9.88 0.17 0.00 0.00 0.03
12.46 MEAN_SOLAR
0.68 4.92 4.76 1.16 0.14 0.00 8.38 1.27
68.94 57.98 11.30 67.51 47.37 80.59 17.80 54.40 13.91 40.98 24.73 19.56 10.23 38.65 23.03 56.38 SEASONAL_RAIN
0.02 4.92 9.70 0.00 0.00 2.47 0.64 1.34 0.42 0.00 2.03 1.31 1.04 0.00
21.39 22.55 19.21 33.96 12.90 29.11 20.74 57.41 27.11 24.40 HOT_TEMP
3.82 3.33 0.89 0.00 1.07 1.70 2.98 0.67 6.15 0.00 2.73 2.26 3.51 8.57 0.00
11.83 14.36 61.62 32.44 55.14 19.59 18.78 12.26 77.24 COLD_TEMP
0.51 0.34 0.00 0.00 1.99 0.47 9.68 3.00 0.54 2.74 2.94 0.91 0.00 0.00 0.00 7.68 0.00 0.00 4.16 0.00 7.76
19.64 31.24 25.95 TEST AUC TEST 0.8 (0.06)
0.97 (0.019) 0.98 (0.007)
0.985 (0.004) 0.969 (0.011) 0.971 (0.014) 0.985 (0.006) 0.939 (0.009) 0.983 (0.003) 0.994 (0.003) 0.968 (0.003) 0.902 (0.054) 0.915 (0.013) 0.981 (0.016) 0.978 (0.013) 0.981 (0.002) 0.988 (0.006) 0.938 (0.021) 0.968 (0.009) 0.998 (0.001) 0.984 (0.008) 0.974 (0.006) 0.998 (0.001) 0.963 (0.008) N.RECORDS 68 86 34 21 25 33 33 46 26 27 63 24 50 22 156 476 344 556 306 343 173 203 192 189 . . . parviflora Kunzea capitata Kunzea Kunzea ambigua Kunzea Isopogon dawsonii Isopogon anethifolius Isopogon anemonifolius Hibbertia procumbens Hakea archaeoides Grevillea parvifloraGrevillea subsp Glossodia minor Glossodia major Gahnia sieberiana Euphrasia ciliolata Euphrasia Eucalyptus seeana Eucalyptus Eucalyptus parramattensis subsp parramattensis Eucalyptus parramattensis Eucalyptus parramattensis subsp parramattensis Eucalyptus decadens Eucalyptus oblonga Eucalyptus Eucalyptus largeana Eucalyptus Eucalyptus glaucina Eucalyptus Eucalyptus fractaEucalyptus Eucalyptus camfieldii Eucalyptus TABLE 7 CONTINUED 7 TABLE PLANTS Eucalyptus camaldulensis Eucalyptus Eriostemon australasius Eriostemon Dracophyllum macranthum Dracophyllum Doryanthes excelsa
37 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
3.31 2.43 6.60 3.53 4.77 0.53 0.42
27.10 28.97 20.40 21.19 30.96 27.62 19.04 33.86 10.23 30.99 13.48 19.56 15.30 20.42 12.64 17.42 12.36 18.71 21.89
FORESTS
SCLEROPHYLLS SCLEROPHYLLS
WET WET 0.00 3.75 6.60 0.68 3.73 0.25 9.59 0.05 4.45 4.74 4.65 2.77 3.29 1.68 1.16 0.00 0.49 0.24 1.05
10.51 23.32 22.06 38.46 11.51 11.90 10.22 RAINFORESTS
7.14 0.00 2.80 0.27 0.00 1.43 0.00 0.00 0.19 1.11 0.84 0.59 0.22 0.18 0.65 4.74 0.00 0.01 0.43 0.00 0.00 4.39 0.73 0.00 3.90
16.74
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 0.60 0.30 0.97 4.26 2.79 0.67 0.95 4.70 9.73 6.24 0.59 3.90 3.62 3.98 0.51 1.05 0.09 6.71
24.08 44.00 31.45 15.72 22.79 20.41 32.07 11.87
VEGETATION FINAL FINAL
0.97 3.59 0.03 3.02 3.25 2.14 0.22 3.41 1.65 0.06 5.97 0.28 0.19 6.36 2.08 0.84 0.47 3.27 1.12
17.96 20.24 22.72 29.92 10.71 21.25 32.85 SLOPE
4.75 0.51 0.02 0.51 3.66 2.01 0.00 1.28 1.41 3.32 1.09 3.59 2.60 0.68 4.14 0.27 0.28 3.33 0.00 2.47 8.30 0.96 6.14 0.00
15.79 18.94 MEAN_SOLAR
9.30 0.00 4.51 2.36 0.00 1.37 9.76 9.00 0.96 4.60 3.04 0.00
24.74 72.68 42.54 20.79 64.69 16.80 20.64 10.07 29.11 21.01 16.04 23.78 54.54 16.02 SEASONAL_RAIN
0.00 0.00 2.39 5.80 7.56 0.00 1.82 0.44 0.04 7.87 1.18 9.96
79.04 13.41 20.05 43.52 45.17 19.62 26.37 18.23 15.41 23.91 25.24 12.95 29.60 24.86 HOT_TEMP
0.00 2.87 0.00 1.14 0.20 1.88 0.00 0.25 0.51 0.83 0.00 0.01 6.91 0.36 0.00 0.00 5.69 7.02 5.68 5.90 0.22
15.50 23.52 11.88 11.84 15.80 COLD_TEMP
0.26 4.18 0.00 1.65 0.00 9.28 0.57 9.83 0.00 0.00 2.89 3.15 0.00 0.00 2.23 4.74
11.21 66.94 12.02 21.87 40.10 10.34 19.57 27.27 44.81 12.64 TEST AUC TEST 0.9 (0.042)
0.737 (0.01) 0.93 (0.023) 0.85 (0.051) 0.908 (0.07) 0.93 (0.028)
0.953 (0.029) 0.998 (0.001) 0.983 (0.009) 0.962 (0.013) 0.908 (0.007) 0.929 (0.047) 0.965 (0.008) 0.984 (0.007) 0.868 (0.072) 0.862 (0.043) 0.939 (0.027) 0.972 (0.002) 0.959 (0.019) 0.926 (0.016) 0.969 (0.008) 0.918 (0.011) 0.913 (0.031) 0.883 (0.013) 0.937 (0.006) 0.977 (0.011) N.RECORDS 26 48 24 31 48 31 71 65 95 30 27 36 21 51 35 121 913 278 113 510 136 246 432 448 662 2145 Persoonia pinifolia Persoonia Persoonia pauciflora Persoonia Persoonia oleoides Persoonia Persoonia media Persoonia Persoonia linearis Persoonia Persoonia levis Persoonia Persoonia laurina Persoonia Persoonia lanceolata Persoonia Persoonia isophylla Persoonia Persoonia conjuncta Persoonia Papillilabium beckleri Papillilabium Microtis unifolia Microtis parviflora Melaleuca groveana Melaleuca biconvexa Maundia triglochinoides Macrozamia reducta Macrozamia Macrozamia flexuosa Macrozamia Macrozamia concinna Macrozamia Macrozamia communis Macrozamia Lyperanthus suaveolens Lyperanthus Lycopodium deuterodensum Lycopodium TABLE 7 CONTINUED 7 TABLE PLANTS Lomatia silaifolia Lomatia Livistona australis Livistona Linospadix monostachya Lepidozamia peroffskyana Lepidozamia
38 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
5.80 2.34 5.97
18.84 44.85 20.50 41.42 26.40 25.78 26.63 27.38 19.13 54.97 59.12 36.02 25.08 24.50 17.69 23.59 13.60 16.26 16.95 20.81 40.03 36.30 28.20
FORESTS
SCLEROPHYLLS SCLEROPHYLLS
WET WET 1.54 2.40 0.00 4.21 5.43 0.54 5.75 5.99 8.49 2.80 0.00 0.00 5.44 6.96 2.61 4.40 1.48 1.49 4.16 2.08
19.62 24.18 22.43 24.97 11.61 40.86 RAINFORESTS
0.71 0.20 1.82 0.26 0.10 2.87 0.00 0.00 0.00 0.00 0.00 0.19 0.00 0.00 0.00 0.04 0.43 4.16 0.00 0.00 0.32 0.90 0.19
13.57 26.90 11.01
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 5.31 4.95 0.00 4.45 0.36 2.24 4.32 0.00 0.11 3.52 5.00 2.04 2.14 4.46 5.27 0.89 0.23 8.67 3.18 0.21 6.18
18.52 11.09 13.13 47.14 13.83
VEGETATION FINAL FINAL
1.86 0.45 5.71 6.12 6.72 2.71 3.93 0.28 0.03 1.57 5.64 0.20 7.10 0.27
29.91 10.41 14.84 10.62 24.48 17.15 24.33 29.51 19.22 14.61 12.75 10.15 SLOPE
0.27 0.00 7.01 0.00 4.60 4.30 6.06 2.60 1.19 3.80 1.91 0.76 0.32 0.00 0.14 0.06 1.75 6.02 0.22 3.25 3.46 0.00 2.49 0.91 4.89 0.29 MEAN_SOLAR
2.40 0.57 1.00 9.92 2.81 3.74 0.37 1.70 5.75 0.07 6.55 8.92 0.00
18.02 37.54 16.96 39.53 63.06 23.80 17.92 54.85 23.41 53.25 19.00 54.74 56.11 SEASONAL_RAIN
5.04 6.87 5.02 0.42 0.02 0.00 0.00 0.00 0.00 0.05 8.85 0.72 6.27 3.19 0.00
51.63 12.58 32.09 10.49 10.26 13.69 19.71 14.13 25.36 11.97 42.85 HOT_TEMP
3.49 5.06 2.00 2.20 2.12 0.00 2.87 0.02 0.00 3.68 0.00 0.22 9.52 3.24 0.29 8.26 0.65 1.90 0.00 0.00 5.97 8.31 0.93
13.51 14.00 13.75 COLD_TEMP
1.10 0.67 0.00 1.53 5.00 2.23 6.25 2.91 0.13 3.07 0.00 0.16 0.00 0.00 0.00 1.49 0.97 1.29 0.37 4.02 0.21
12.05 30.89 35.41 13.04 40.83 TEST AUC TEST
0.758 (0.08) 0.82 (0.057)
0.974 (0.004) 0.775 (0.067) 0.555 (0.117) 0.774 (0.035) 0.821 (0.046) 0.713 (0.065) 0.899 (0.071) 0.899 (0.034) 0.867 (0.054) 0.994 (0.001) 0.993 (0.003) 0.843 (0.117) 0.875 (0.057) 0.987 (0.011) 0.887 (0.067) 0.821 (0.035) 0.908 (0.038) 0.827 (0.019) 0.915 (0.025) 0.859 (0.068) 0.991 (0.005) 0.887 (0.032) 0.958 (0.006) 0.988 (0.005) N.RECORDS 25 22 29 83 78 47 30 32 36 49 25 20 26 43 62 80 23 47 35 439 132 122 127 412 125 330 Rutidosis heterogama Pterostylis pedunculata Pterostylis Pterostylis parvifloraPterostylis Pterostylis obtusa Pterostylis Pterostylis nutans Pterostylis Pterostylis longifolia Pterostylis Pterostylis curtaPterostylis Pterostylis concinna Pterostylis Pterostylis coccina Pterostylis Pterostylis baptistii Pterostylis Pterostylis acuminata Pterostylis Prostanthera junonis Prostanthera Prostanthera askania Prostanthera Prasophyllum odoratum Prasophyllum Prasophyllum brevilabre Prasophyllum Pomaderris reperta Pomaderris Pomaderris queenslandica Pomaderris Plectorrhiza tridentata Platycerium superbum Platycerium Platycerium bifurcatum Platycerium Philotheca salsolifolia Philotheca Philotheca myoporoides Philotheca TABLE 7 CONTINUED 7 TABLE PLANTS Philotheca buxifolia Philotheca Phebalium squamulosum Phebalium Petrophile pulchella Petrophile Persoonia stradbrokensis Persoonia
39 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
8.08 4.31 6.08 1.20 5.15 9.49 5.21 5.49 3.87 6.32 5.50
10.61 21.80 38.21 12.94 20.06 66.60 14.86 15.51 34.54 18.02 35.83 19.47 15.63 19.28 19.39
FORESTS
SCLEROPHYLLS SCLEROPHYLLS
WET WET 2.56 8.50 5.41 0.68 0.23 0.19 5.61 4.16 0.61 4.53 5.82 0.29 1.96 2.18 3.83 4.42 4.15 4.72 6.75 1.51
16.96 23.07 54.46 46.19 11.72 16.25 RAINFORESTS
3.51 0.00 5.84 8.14 2.07 2.92 0.74 8.73 1.42 2.24 1.45 0.80 1.09 1.31 0.83 0.48 0.02 0.46 1.72 0.65 0.55 1.86 4.95 0.38 1.42
26.77
FORESTS
SCLEROPHYLL SCLEROPHYLL
DRY DRY 0.61 9.54 1.04 1.39 0.82 1.70 5.19 0.50 6.87 1.05 2.88 6.66 0.13 7.12 1.51 5.66 4.37 5.41 2.67 0.00 0.00
17.77 24.06 17.74 12.01 11.14
VEGETATION FINAL FINAL
0.38 0.21 3.52 1.92 0.56 1.07 2.47 9.95 8.26 0.61 3.56 1.60 0.02 2.12 0.06 2.89 3.15 2.04 3.60 0.61 0.00 3.08
11.18 12.98 22.73 13.19 SLOPE
6.11 3.31 3.68 1.45 1.15 1.08 1.36 2.41 0.68 8.87 0.10 0.34 0.09 4.91 1.04 3.71 0.27 3.12 0.76 2.27 0.03
10.45 14.83 28.26 14.73 16.37 MEAN_SOLAR
1.41 2.02 6.03 3.47 0.00 4.78 6.47 9.00
13.17 57.27 34.86 23.77 23.89 40.38 53.85 26.51 26.92 68.85 47.85 12.15 73.65 35.68 23.59 45.09 77.36 43.03 SEASONAL_RAIN
0.60 2.01 9.83 3.13 0.68 4.66 2.46 6.49 3.53 0.07 0.00 0.00 6.43 0.26 0.00 0.90 4.88 2.10
13.73 13.82 19.58 12.87 35.31 23.65 18.46 46.85 HOT_TEMP
0.00 0.00 6.14 0.49 0.48 0.43 3.34 6.11 9.89 0.37 7.76 2.30 1.42 3.15 0.61 9.90 0.60 0.56 1.74 0.00 0.11 0.00 1.28
47.05 12.28 19.44 COLD_TEMP
2.45 0.00 4.46 0.00 5.23 0.00 3.34 1.63 0.75 0.00 5.76 0.00 0.48 0.00 0.95 7.99
45.50 10.34 45.13 34.22 38.90 12.74 12.18 10.39 18.24 14.31 TEST AUC TEST
0.815 (0.03) 0.942 (0.02) 0.943 (0.02) 0.97 (0.012) 0.918 (0.04) 0.876 (0.06) 0.805 (0.07)
0.962 (0.026) 0.927 (0.015) 0.976 (0.007) 0.948 (0.015) 0.864 (0.051) 0.932 (0.013) 0.954 (0.007) 0.868 (0.047) 0.888 (0.036) 0.974 (0.014) 0.922 (0.031) 0.946 (0.003) 0.985 (0.008) 0.971 (0.016) 0.987 (0.004) 0.995 (0.002) 0.941 (0.029) 0.846 (0.061) 0.933 (0.017) N.RECORDS 23 35 82 54 75 38 26 67 52 33 36 30 29 200 168 102 163 179 334 130 136 119 133 127 161 1126 . flabellatus Zieria smithii Zannichellia palustris Xylomelum pyriforme Xylomelum Xanthorrhoea resinosa Xanthorrhoea Xanthorrhoea media Xanthorrhoea Xanthorrhoea malacophylla Xanthorrhoea Xanthorrhoea macronema Xanthorrhoea Xanthorrhoea latifolia Xanthorrhoea Xanthorrhoea johnsonii Xanthorrhoea Xanthorrhoea glauca Xanthorrhoea Xanthorrhoea fulva Xanthorrhoea Xanthorrhoea arborea Xanthorrhoea Todea barbara Todea Tetratheca juncea Tetratheca Tetratheca glandulosa Tetratheca Telopea speciosissima Telopea Tasmannia purpurascens Tasmannia Tasmannia glaucifolia Tasmannia Syzygium paniculatum Sticherus flabellatus var flabellatus Sticherus Sprengelia incarnata Sprengelia Spiranthes australis Spiranthes TABLE 7 CONTINUED 7 TABLE PLANTS Senna acclinis Sarcochilus olivaceus Sarcochilus Sarcochilus hillii Sarcochilus Sarcochilus falcatus Sarcochilus
40 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLLS SCLEROPHYLLS
0.76 3.84 1.75 5.68 WET WET 9.94 1.10 0.97 1.54 0.24 9.44 1.66 4.08 2.06 9.20 0.31 2.11
23.01 14.42 15.33 18.96 37.00 32.88 57.49 24.98 RAINFORESTS
2.35 0.20 4.62 2.94 0.00 3.66 0.00 4.12 0.00 0.00 0.00 6.26 0.14 0.86 0.89 0.00 4.13 2.11 0.00 0.00 1.08 2.14
20.78 11.06
FORESTS SCLEROPHYLL SCLEROPHYLL
4.50 2.76 0.83 3.15 DRY DRY 5.33 1.27 2.85 4.74 0.74 6.24 0.84 3.14 1.89 1.90 3.70 2.31
27.01 28.78 15.69 24.16 24.17 10.64 17.03 10.48
VEGETATION FINAL FINAL
8.09 4.73 2.05 5.48 0.43 1.47 5.78 4.16 8.36 1.39 9.43 0.00 9.34 5.45 5.41 7.34
30.06 23.16 12.26 14.45 21.56 39.13 19.21 15.37 TERR1000
5.18 0.55 3.82 5.64 7.70 1.05 0.81 1.23 4.87 1.30 1.20 1.87 5.49 0.73 2.60 2.57 4.68 0.34 5.01 1.59 1.13 1.90 1.91
11.89 SLOPE
2.22 2.90 3.67 0.77 5.09 9.66 6.50 5.52 1.71 4.81 8.49 3.90 0.68
10.77 29.70 17.35 15.02 30.68 11.57 16.58 10.26 17.12 27.11 12.86 MEAN_SOLAR
3.15 4.10 2.29 0.42 3.15 2.05 4.19 4.28 1.85 1.00 4.56 2.32 9.20 7.58 0.00
27.57 27.27 66.02 66.62 27.12 56.55 28.52 22.34 37.12 SEASONAL_RAIN
0.00 0.80 6.20 3.33 6.66 8.22 0.32 2.90 0.00 7.27 3.46 4.39
16.49 12.81 20.27 31.72 13.36 19.89 11.75 27.15 30.21 17.80 12.66 13.61 HOT_TEMP
2.58 3.17 0.00 6.29 0.00 1.57 1.20 4.05 7.12 0.01 2.25 1.68 1.04 0.43 1.71 2.93 7.85 4.16 0.00 1.85
22.33 10.35 26.01 15.02 COLD_TEMP
2.14 4.20 0.16 7.67 0.82 5.54 8.99 6.58 2.11 9.07
31.67 11.04 17.71 33.71 17.07 27.44 35.27 18.86 13.76 14.52 34.00 49.15 48.34 14.88 TEST AUC TEST 0.86 (0.05) 0.75 (0.05)
0.94 (0.029) 0.88 (0.024) 0.783 (0.03) 0.87 (0.027)
0.847 (0.077) 0.876 (0.037) 0.819 (0.021) 0.887 (0.087) 0.844 (0.043) 0.883 (0.019) 0.913 (0.031) 0.842 (0.041) 0.891 (0.027) 0.774 (0.038) 0.851 (0.034) 0.771 (0.033) 0.856 (0.016) 0.823 (0.064) 0.862 (0.031) 0.862 (0.036) 0.827 (0.049) 0.814 (0.055) N.RECORDS 34 95 24 28 71 52 99 23 42 59 31 421 188 104 138 231 160 141 314 441 129 102 106 193 REPTILES Acanthophis antarcticus Acanthophis Acritoscincus platynota Acritoscincus Amphibolurus muricatus Amphibolurus Amphibolurus nobbi Amphibolurus Anomalopus leuckartiiAnomalopus Anomalopus swansoni Anomalopus Bellatorias major Bellatorias Cacophis krefftiiCacophis Cacophis squamulosus Cacophis Calyptotis ruficauda Calyptotis Carlia tetradactylaCarlia Chelodina longicollis Cryptoblepharus virgatus Cryptophis nigrescens Ctenotus robustus Ctenotus Ctenotus taeniolatus Ctenotus Cyclodomorphus gerrardii Cyclodomorphus Cyclodomorphus michaeli Cyclodomorphus Demansia psammophis Dendrelaphis punctulatusDendrelaphis Diplodactylus vittatus Egernia cunninghami Egernia Egernia mcpheei Egernia Egernia striolata Egernia Table 8. Mean results from MaxEnt models for reptiles within the Greater Hunter region. Results show the number of records used to construct used to each model and the mean (± the number of records Results show region. Hunter within the Greater reptiles MaxEnt models for from 8. Mean results Table the permutation importancevariablefor each represent variables for the environmental shown The data models. five-fold cross-validated across value AUC test deviation) standard constructused to the full model.
41 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLLS SCLEROPHYLLS
3.95 0.22 0.00 6.64 1.52 WET WET 3.21 1.43 4.44 0.45 3.72 1.09 2.45 5.56 4.72 2.07 7.78 0.00 0.51 0.04 7.15
22.22 10.10 20.42 11.13 30.32 RAINFORESTS
0.23 3.45 8.72 2.19 0.00 2.42 0.56 2.48 2.19 0.07 2.72 0.47 2.81 2.32 2.69 2.25 7.32 0.82 0.00 0.14 0.31
57.19 24.34 11.51 12.85
FORESTS SCLEROPHYLL SCLEROPHYLL
5.84 5.82 0.29 5.38 DRY DRY 8.48 1.55 7.06 0.16 4.73 0.86 3.73 0.15
16.47 21.03 17.53 12.84 11.65 10.03 22.72 38.68 12.60 16.14 37.51 16.37 28.77
VEGETATION FINAL FINAL
7.95 6.39 1.99 2.62 2.56 5.93 0.44 5.75 4.68 6.91 9.07 7.11 6.64 0.30 0.51 5.65
25.20 10.73 12.51 37.75 16.66 20.97 29.24 10.68 19.04 TERR1000
3.69 2.03 0.00 1.32 4.72 2.22 4.42 1.96 2.33 2.80 3.12 4.18 0.08 3.20 0.96 6.45 4.31 0.36 1.53 7.25 0.00 2.87 1.58 3.26 1.15 SLOPE
7.75 4.77 7.71 0.88 1.85 3.96 0.87 1.14 0.61 0.48 2.96 3.64 5.67 8.69
22.33 16.15 21.05 14.28 14.03 19.65 22.42 18.41 14.23 15.66 14.59 MEAN_SOLAR
4.07 0.55 3.82 1.38 0.05 6.97 2.34 0.00 1.05 3.19
16.40 36.45 35.77 22.51 42.27 22.34 35.01 34.20 23.25 29.70 39.63 16.41 10.26 34.93 49.31 SEASONAL_RAIN
6.51 1.18 0.03 5.44 3.30 5.17 4.25 7.43 2.63 0.00 4.49 1.50 3.76 0.29
15.61 19.70 16.35 14.46 13.38 28.57 13.44 12.10 26.14 18.01 32.46 HOT_TEMP
3.53 0.42 2.02 2.06 2.88 2.79 0.78 0.87 5.92 0.38 0.01 5.96 0.21 1.03 0.33 3.93 5.29 0.30 1.62 2.85
10.24 25.67 12.70 25.01 39.29 COLD_TEMP
1.30 0.85 0.59 5.41 4.72 0.72 5.22 2.37 1.39 0.00 5.88 0.55 1.76
20.02 57.73 13.88 15.36 56.62 77.64 29.01 10.52 24.94 14.64 11.93 28.78 TEST AUC TEST 0.9 (0.02)
0.797 (0.04) 0.818 (0.07) 0.91 (0.014)
0.935 (0.029) 0.955 (0.035) 0.946 (0.014) 0.795 (0.021) 0.746 (0.064) 0.834 (0.033) 0.793 (0.077) 0.856 (0.048) 0.906 (0.024) 0.983 (0.006) 0.778 (0.014) 0.843 (0.019) 0.938 (0.021) 0.662 (0.078) 0.968 (0.016) 0.882 (0.027) 0.811 (0.028) 0.906 (0.029) 0.721 (0.077) 0.768 (0.105) 0.912 (0.014) N.RECORDS 29 59 40 80 87 21 38 45 63 45 59 63 26 235 101 104 526 130 133 454 182 226 259 260 1289 TABLE 8 CONTINUED 8 TABLE REPTILES Egernia whitii Egernia Eulamprus heatwolei Eulamprus Eulamprus kosciuskoi Eulamprus Eulamprus murrayi Eulamprus Eulamprus quoyii Eulamprus Eulamprus tenuis Eulamprus Furina diadema Furina Hemiaspis signata Hemiergis decresiensis Hemiergis Hoplocephalus stephensii Hoplocephalus Hypsilurus spinipes Lampropholis amicula Lampropholis Lampropholis caligula Lampropholis Lampropholis delicata Lampropholis Lampropholis guichenoti Lampropholis Lerista bougainvillii Lerista Lialis burtonis Liopholis modesta Lygisaurus foliorum Lygisaurus Morelia spilota Morelia Morethia boulengeri Morethia Notechis scutatus Notechis Oedura lesueuriiOedura Oedura robusta Oedura Phyllurus platurus Phyllurus
42 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast
FORESTS SCLEROPHYLLS SCLEROPHYLLS
6.37 6.27 1.82 5.37 WET WET 6.23 0.00 0.45 0.06 0.01 9.30 0.90 7.37 3.04
26.36 44.38 11.39 15.36 11.12 RAINFORESTS
0.05 0.16 0.19 4.32 0.00 9.98 0.00 0.84 0.96 0.96 0.18 0.17 0.99 7.53 0.00 0.08
73.19 51.00
FORESTS SCLEROPHYLL SCLEROPHYLL
2.66 0.94 0.99 9.34 1.25 DRY DRY 1.00 8.34 1.52 0.00 0.73 1.28 1.57 0.00 1.97
12.04 19.75 28.95 17.13
VEGETATION FINAL FINAL
6.86 8.18 2.01 6.20 1.98 0.82 9.95 1.01 2.18 2.50 4.61
13.02 56.41 11.71 15.38 16.86 13.12 20.92 TERR1000
3.29 4.16 1.83 0.08 7.26 0.72 0.25 0.12 2.59 2.17 1.75 2.05 1.41 1.52 1.44 3.25 7.75
11.15 SLOPE
4.68 6.07 0.00 9.08 0.38 2.90 2.61 1.40 1.84
13.94 42.28 17.30 11.98 12.34 10.06 14.87 18.44 12.85 MEAN_SOLAR
6.46 0.00 0.37 0.35 0.39 4.06 0.49 0.87
33.74 26.70 13.18 31.23 28.14 26.88 23.02 10.16 29.23 48.36 SEASONAL_RAIN
1.83 2.54 0.50 6.82 0.46 0.43 2.09 8.37 0.04 2.22 4.63
21.28 12.37 13.51 30.70 18.27 26.81 10.50 HOT_TEMP
4.30 1.31 2.01 5.73 6.04 4.51 7.25 0.01 0.00 7.30 0.00 0.63 4.68
11.75 11.78 12.11 14.30 11.48 COLD_TEMP
3.05 3.02 3.90 6.90 0.05 8.75 0.40 7.96
21.90 12.63 30.38 11.37 24.70 58.66 27.36 22.13 28.92 51.37 TEST AUC TEST 0.7 (0.045)
0.772 (0.03) 0.75 (0.021) 0.65 (0.056)
0.789 (0.022) 0.984 (0.008) 0.774 (0.067) 0.802 (0.052) 0.926 (0.022) 0.789 (0.034) 0.903 (0.039) 0.968 (0.013) 0.856 (0.035) 0.963 (0.016) 0.819 (0.031) 0.909 (0.017) 0.939 (0.041) 0.771 (0.015) N.RECORDS 34 49 80 65 37 29 34 62 495 254 569 155 146 247 142 264 123 984 TABLE 8 CONTINUED 8 TABLE REPTILES Physignathus lesueurii Physignathus Pogona barbata Pogona Pseudechis porphyriacus Pseudechis Pseudemoia pagenstecheri Pseudemoia Pseudonaja textilis Pseudonaja Pygopus lepidopodus Pygopus Ramphotyphlops nigrescens Rankinia diemensis Saiphos equalis Saltuarius swaini Saproscincus challengeri Saproscincus Saproscincus mustelinus Saproscincus Saproscincus rosei Saproscincus Tiliqua scincoides Tiliqua Underwoodisaurus milii Varanus rosenbergi Varanus Varanus varius Varanus Vermicella annulata Vermicella
43 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
2.36 2.34 4.34 8.50 0.85 4.18
20.86 18.54 14.39 14.90 21.33 12.66 14.05
FORESTS
SCLEROPHYLL SCLEROPHYLL
WET WET 2.16 4.75 8.09 0.76 0.47 3.54 0.80 0.00 2.94 2.05 0.31
11.10 25.19 RAINFORESTS
5.60 2.92 0.00 0.63 4.11 1.62 0.50 0.63 0.24 2.24
13.68 24.74 17.46
LFORESTS
SCLEROPHYL SCLEROPHYL
DRY DRY 2.01 1.72 5.63 0.55 0.86 5.39 3.39
16.58 11.05 24.69 12.83 25.20 13.27
VEGETATION FINAL FINAL
7.56 2.91 1.40 0.30 0.29 1.94 1.61 0.65 2.22
11.09 14.01 32.82 11.13 WETNESS
2.35 4.54 6.64 1.15 0.72 1.51 1.45 3.67 1.08 2.29 3.32 0.67
12.98 RUGG1000
3.71 8.02 6.96 2.27 0.85 3.19 5.35 2.53 0.81
14.54 13.25 14.35 12.96 SLOPE
6.63 5.90 2.22 0.31 5.48 1.37 9.35 3.96 2.58 3.64 3.66
15.91 17.45
RAIN SEASONAL_
6.09 3.78 0.89 5.55 3.59 1.19 2.02 5.99
10.55 26.96 27.79 13.19 19.20 MEAN_RAIN
7.20 7.96 8.77 1.69
23.00 24.05 12.03 12.60 17.66 45.62 20.64 28.95 46.06 TEST AUC TEST
0.99 (0.004) 0.89 (0.031)
0.977 (0.006) 0.942 (0.007) 0.921 (0.021) 0.948 (0.004) 0.992 (0.003) 0.992 (0.002) 0.944 (0.027) 0.891 (0.008) 0.995 (0.001) 0.953 (0.005) 0.915 (0.009) N.RECORDS 55 51 71 39 28 59 23 121 130 359 171 147 148 Lowland rainforest on floodplain in the NSW North rainforest Lowland bioregion Coast Lowland rainforest in NSW North Coast and Sydney in NSW North and Sydney Coast rainforest Lowland Basin bioregion EECS Lower Hunter valley dry rainforest in the Sydney Basin in the Sydney dry valley Hunter rainforest Lower and NSW North bioregion Coast Lower Hunter spotted gum ironbark forest in the Sydney in the Sydney forest gum ironbark spotted Hunter Lower Basin bioregion Littoral rainforest in the NSW North Coast Sydney Basin in the NSW North Sydney Coast rainforest Littoral bioregion and South East Corner Kurri sand swamp woodland in the Sydney Basin in the Sydney woodland Kurri sand swamp bioregion Kincumber scribbly gum forest in the Sydney Basin in the Sydney Kincumber scribbly gum forest bioregion Hunter valley footslopes slaty gum woodland in the slaty gum woodland footslopes valley Hunter Basin bioregion Sydney Hunter lowland redgum forest in the Sydney Basin and in the Sydney forest redgum lowland Hunter NSW North bioregion Coast Grassy white box woodlands box white Grassy Freshwater wetlands on coastal floodplains of the NSW on coastal wetlands Freshwater Basin and SouthNorth East Corner Sydney Coast bioregion Central Hunter ironbark spotted gum grey box forest in forest box gum grey spotted ironbark Hunter Central Basin bioregion the NSW North and Sydney Coast Central Hunter grey box ironbark woodland in the NSW woodland ironbark box grey Hunter Central Basin bioregion North and Sydney Coast Table 9. Mean results from Boosted Regression Tree models for EECs within the Greater Hunter region. Results show the number of training samples used to construct samples used to each model the number of training Results show region. Hunter EECs within the Greater models for Tree Regression Boosted from 9. Mean results Table of contribution the percent variables represent the environmental for shown data The models. cross-validated ten-fold across value AUC test deviation) and the mean (± standard constructeach variable used to full model..
44 TECHNICAL REPORT 3 • JULY 2015
Landscape Connectivity Assessment: Hunter, Central and Lower North Coast SOIL
9.22 3.55 6.28 8.00 7.51 0.14
14.54 10.45
FORESTS
SCLEROPHYLL SCLEROPHYLL
WET WET 1.30 0.00 1.12 3.50 0.74 3.04 8.31 4.58 RAINFORESTS
0.54 0.00 0.44 2.29 4.09 1.37 3.88
25.09
LFORESTS
SCLEROPHYL SCLEROPHYL
DRY DRY 0.40 3.81 6.57 0.01 4.50
16.41 11.73 10.72
VEGETATION FINAL FINAL
4.00 0.00 6.76 6.34 0.44 2.93
19.22 19.78 WETNESS
1.44 0.05 5.84 1.35 1.88 1.86 4.07
10.82 RUGG1000
2.41 0.37 4.35 8.89 1.85 5.72 1.48 6.56 SLOPE
3.78 1.43 8.36 9.68 2.19 3.30 1.38 9.93
RAIN SEASONAL_
3.99 7.66 7.67
11.97 68.68 19.15 37.05 14.34 MEAN_RAIN
3.88
40.80 12.32 17.83 11.01 37.07 11.22 21.24 TEST AUC TEST 0.98 (0.01)
0.96 (0.004)
0.937 (0.005) 0.998 (0.001) 0.909 (0.021) 0.911 (0.032) 0.912 (0.017) 0.952 (0.038) N.RECORDS 24 62 43 23 22 176 374 148 TABLE 9 CONTINUED 9 TABLE EECS White box yellow box blakely’s red gum woodland red blakely’s box yellow box White Warkworth sands woodland in the Sydney Basin in the Sydney sands woodland Warkworth bioregion Swamp sclerophyll forest on coastal floodplains of the on coastal forest sclerophyll Swamp Basin and SouthNSW North East Corner Sydney Coast bioregion Swamp oak floodplain forest of the NSW Northforest Coast oak floodplain Swamp bioregion Basin and South East Corner Sydney Subtropical coastal floodplain forest of the NSW Northforest floodplain coastal Subtropical bioregion Coast River flat eucalypt forest on coastal floodplains of the on forest eucalypt River flat Basin and SouthNSW North East Corner Sydney Coast bioregion Ribbon gum mountain gum snow gum grassy forest forest gum grassy Ribbon gum snow gum mountain of the New England tableland bioregion woodland Pittwater and Wagstaffe spotted gum forest in the forest gum spotted Wagstaffe and Pittwater Basin bioregion Sydney
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POSTAL ADDRESS: Hunter Councils Inc. Environment Division PO Box 3137 Thornton NSW 2322 www.hccrems.com.au