Halina T. Kobryn

Most human‐carnivore conflicts arise from the impact of predation on livestock. In Australian rangelands, considerable resources are allocated to constructing exclusion fences and implementing control measures to manage dingo populations for sustainable livestock enterprise. Assessing the effectiveness of these measures is crucial for justifying the investment. We used a replicated experimental design to examine the effect of landscape‐scale dingo‐proof exclusion fences (‘cell‐fencing’) on activity and population density of dingoes in the Southern Rangelands of Western Australia. We monitored dingo populations for 22–24 months across six study sites nested within a landscape of about 75,000 km2 and defined ‘fence level’ as the number of dingo‐proof fences enclosing each study site. We used camera trap capture rate (number of independent capture events per 100 trap nights) as a metric for dingo activity (including the availability of resources as other potential covariates), estimated dingo density using spatially explicit mark‐resight models, and tested the relationship between capture rate and estimated density of dingoes for each study site. Significant variation in both metrics was observed between sites and across time. Fence level and prey occurrence significantly influenced dingo activity. The annual mean dingo density estimate across study sites was below two dingoes per 100 km2 (i.e., 0.02 dingoes per km2; the maximum value believed to be compatible with small livestock) at only one study site in the first year, but it was higher across all sites during the second year of monitoring. Dingo activity correlated with estimated dingo density at only two sites, suggesting differences in dingo behaviour and detection across the six study sites. This study provides experimental evidence that camera trap capture rate is not a reliable method for assessing variations in the population size of dingoes. These results have implications for monitoring outcomes of dingo control programs across Australia.
This study addresses a critical question: How reliable is the activity metric (here we used camera trap capture rate) to assess variations in population size of dingoes across diverse habitats in Australia? Through experimental evidence, we demonstrate that activity metrics can lead to inaccuracies in assessing changes in dingo population size. Our findings highlight the need to assess dingo population size from identified individuals, which is particularly relevant for effective dingo control programs across Australia.

Context: Cockburn Sound is the most intensively used embayment in Western Australia (WA), including industrial use as well as a wide range of recreational activities and associated values. The Western Australia Environmental Protection Authority identified general recreational use as a significant component of the social and aesthetic values of Cockburn Sound that pre-dates its industrial development. Consequently, Cockburn Sound is a highly contested and increasingly congested space. While Cockburn Sound hosts a range of recreational activities, much of the management attention is on recreational fishing while non-fishing recreational activities have received relatively less attention. Therefore, this project focused on understanding non-fishing recreational activities and values in the Sound. Mapping non fishing recreational use activities and associated values provides spatially explicit information on how Cockburn Sound is used and valued through a broad range of activities that represent the complex public recreational use context for Cockburn Sound management and the Westport development.

Project Aims:
• Identify the range and spatial extent of non-fishing recreational activities and associated values
• Provide an economic valuation for key recreational sites identified by the PPGIS process
• Provide a detailed understanding of non-fishing recreational activities and values

Method A public participation GIS (PPGIS) approach was used to map the variety and types of non-fishing recreational activities and associated values in Cockburn Sound, Western Australia. An online questionnaire was developed using the Maptionnaire online PPGIS survey tool as a platform (Maptionnaire 2022). The questionnaire gathered respondent data including demographics, frequency of visit and mode of travel to Cockburn Sound. Respondents used an interactive map to place specific points and/or lines relating to a recreational activity they undertake in Cockburn Sound. Water-based and land-based activities were mapped separately by respondents during the survey. Respondents could place as many activities as lines or points as they wished. Respondents also indicated one or more values they associated with each of the recreational activities they mapped. The activities and values were selected by respondents from drop-down lists. The lists were developed by the project team based on a review of relevant literature. A travel cost model approach was used to evaluate the monetary value attributable to recreational use of key sites in Cockburn Sound. The PPGIS questionnaire was distributed online between August 2022 and February 2023 using a range of methods including recreational clubs distributing online via their social media platforms and member contact lists, notices with a QR code placed in local community centres and businesses, and the WAMSI social media platforms.

Key Findings The questionnaire received 597 responses and a total of 31 non-fishing recreational activities were identified and mapped in Cockburn Sound including 16 land-based activities and 15 water-based activities. A considerable proportion of survey respondents were members of a club or organization associated with the recreational activity mapped by the respondent (approximately 75%).

The northern end of the study area (Woodman Point Reserve) was most frequently visited by survey respondents for both land and water-based recreational activities. This likely to be related to accessibility and facilities in this area of the Sound.

Mapped land-based activities were concentrated at the northern (Woodman Point Reserve), and southern (Rockingham foreshore and Cape Peron) areas of the Sound with an additional concentration adjacent to and just south of the Beeliar Regional Park shoreline area.

Mapped water-based activities covered the entire Cockburn Sound area as well as areas to the west of Garden Island.

The entire study area was associated with one or more recreational activity values. The most commonly allocated values included ‘have fun’, ‘improve physical health’ and ‘socialise with friends and family’.

The travel cost analysis was restricted by the small number of respondents providing the required data for each activity in each zone defined for the analysis. In person intercept surveys would provide more comprehensive data but project budget limitations meant this method was not possible.

Some activities had adequate data, including horse riding/exercising, beach activities and walking/running activities. The estimated value of a trip to the Naval Base horse beach was $14.75 per trip, which was relatively high compared to other beach activity value studies. The estimated value of a trip for beach activities was between $6.74 and $7.35 per trip. Walking and running activities were valued between $3.19 and $4.09 per trip.

Online PPGIS tools enable collection of data from a large and/or dispersed population within a limited time frame and budget. However, there is a trade-off between acquiring a large enough sample within a short time frame and the depth and quality of the data.

Conclusions Both land and water-based recreational users value the entire Cockburn Sound area to fulfil a diverse set of activities. This means the recreational carrying capacity of the region may be relatively high in this respect. However, there are several specialised and spatially focused recreational activities which should be considered in planning decisions.

Demand for ecological restoration of Earth's degraded ecosystems has increased significantly since the adoption of The Kunming-Montreal Global Biodiversity Framework in December 2022, with target 2 aiming to ensure that at least 30% of degraded ecosystems are under effective restoration by 2030. More recently, in December 2023, the Australian Parliament introduced the Nature Repair Act, which establishes a framework for the world's first legislated, national, voluntary biodiversity market. How can the effectiveness of these ambitious targets be measured? Natural Capital Accounting (NCA) provides a framework to measure changes in ecosystem condition that is applicable across ecosystems and potentially catalogue effects of restoration interventions to drive investment, improvement to practice, and ultimately, to better protect the Earth's ecosystems. However, the framework has not been tested in this context. In this progressive approach, we populated the leading global NCA framework with ecological data to quantify changes in ecosystem condition after restoration. In principle, NCA is fit for purpose, however, methodological refinements and ecological expertise are needed to unlock its full potential. These tweaks will facilitate adoption and standardisation of reporting as efforts ramp up to meet ambitious global restoration targets.

Spatial planning and environmental management are expected to adopt participatory processes. However, the needed spatial data on social values of ecosystem services are limited, especially for marine spatial planning for large, remote coastal areas, and the collection of such information can be time and resource intensive. Crowdsourcing techniques are cost efficient sources of social values data, but must meet the information needs of planners and managers with sufficient confidence. We evaluated the reliability of crowdsourced social values data by assessing the agreement between geotagged photos posted to the social media platform Flickr and data from an online public participation GIS (PPGIS) survey conducted to support marine spatial planning in the Kimberley region of Western Australia.

Flickr could not represent all of the social values mapped in the PPGIS dataset, was notably dominated by scenic values, and under-represented the importance of recreational fishing and Aboriginal cultural values. The Flickr dataset was more affected by accessibility from settlements and transportation infrastructure (roads, boat ramps) and more restricted spatially. Maximum entropy (maxent) distribution models developed to explore the socioecological drivers determining where social values occur also highlighted that Flickr and PPGIS samples provide different perspectives on social values, even after accounting for differences in sampling intensity. The Flickr dataset suggested that the social values occurred under narrower ranges of socioecological conditions, and the PPGIS dataset was more likely to find protected areas to be valued, likely because participants believe protected areas to support those social values, but may not themselves pursue them there.

Flickr and PPGIS crowdsourced datasets provide different perspectives on the spatial distribution of social values for several reasons: They differ in their spatial and demographic biases, as well as their measurement of revealed vs. stated preferences. Flickr is most effective at representing social values that are easily photographed and interpretable in photos, and may not capture some information needs of managers. PPGIS is under greater investigator control but, because stated preferences can be disconnected from actual use of the sites mapped, may be best suited for assessing management preferences and social acceptability. With understanding of the nuances of these datasets, crowdsourced social values data can be applied most appropriately to support successful planning outcomes.

The red fox (Vulpes vulpes) is one of the most adaptable carnivorans, thriving in cities across the globe. We used GPS-tracking of five suburban foxes across high-density residential suburbs of Perth, Western Australia to quantify (1) their habitat selection and (2) home range area. All five foxes showed statistically significant avoidance of residential locations (p < 0.001) and preference for parkland (p < 0.001), with native vegetation reserves, golf courses, and water reserves showing disproportionately greater use. Landuse category also influenced their movements, with foxes moving quickest (i.e., commuting) in proximity to roads and slowest (i.e., foraging) when they were further from roads. Three females had core home ranges (50% autocorrelated-corrected kernel density estimate; AKDEc) averaging 37 ± 20 ha or 95% AKDEc averaging 208 ± 196 ha. One male had a 95 ha core home range and 349 ha 95% AKDEc but the other male covered an area ~ 20 times this: using a 371 ha core home range and 7,368 ha 95% AKDEc. The extensive movement patterns we describe are likely to be common for urban foxes, with half of published home range estimates for urban foxes (principally based on VHF data) excluding data for ‘lost’ individuals or animals that showed ‘excursions’. It is likely that the home range estimates for these urban exploiters have therefore been grossly underestimated to date. Further application of GPS trackers that allow remote download will vastly improve our understanding of habitat preference and exploitation of resources by urban foxes.

Context: Predation of layer chickens is a major issue for free-range egg producers. Using livestock guardian dogs (LGD) to protect free-ranging poultry is a possible option for producers, although there is little published literature regarding how the dogs protect chickens.

Aims: This case study was conducted at a free-range egg production farm in Western Australia, where red foxes (Vulpes vulpes) were a common predator of chickens prior to introducing Maremma LGD. We investigated LGD responses to experimental cues that might indicate fox incursion (fox urine and calls).

Methods: Four dogs were GPS tracked and monitored using camera traps. Over the first week, experimental fox cues were set out around the paddock boundaries, alternating with ‘non-cue’ experimental control nights. We recorded whether the LGD altered (1) their space use, (2) activity patterns (movement speed), or (3) behaviour in response to these cues. We also recorded (4) distances between LGD from known sightings of foxes.

Key results: The Maremmas appeared to work independently of each other, covering separate areas. There was no significant difference in overnight home range area by experimental fox cue treatment, but there was a significant (P < 0.001) treatment × dog interaction term for distance moved. Three dogs spent most of their time at night around the chicken shelters and generally increased distances moved on experimental fox cue nights. The fourth dog was more bonded to people and did not alter its movements. Paradoxically, dogs rested more and barked less on experimental fox cue nights; however, we recorded foxes on camera traps placed around the chicken shelters on 17 of the 23 nights of monitoring, and the high background activity level of foxes on this property compromised our experimental control (nights without experimental fox cues). The dogs did not move towards known fox sightings.

Conclusions: The Maremmas in this trial closely guarded the chicken shelters rather than maintaining the entire paddock as a predator-exclusion zone.

Implications: Understanding how guardian dogs behave when challenged by potential predators will help increase producers’ confidence in the efficacy of these dogs as a viable method to protect livestock from predation threat.

Understanding species’ distribution patterns and the environmental and ecological interactions that drive them is fundamental for biodiversity conservation. Data deficiency exists in areas that are difficult to access, or where resources are limited. We use a broad-scale, non-targeted dataset to describe dolphin distribution and habitat suitability in remote north Western Australia, where there is a paucity of data to adequately inform species management. From 1,169 opportunistic dolphin sightings obtained from 10 dugong aerial surveys conducted over a four-year period, there were 661 Indo-Pacific bottlenose dolphin (Tursiops aduncus), 191 Australian humpback dolphin (Sousa sahulensis), nine Australian snubfin dolphin (Orcaella heinsohni), 16 Stenella sp., one killer whale (Orcinus orca), one false killer whale (Pseudorca crassidens), and 290 unidentified dolphin species sightings. Maximum Entropy (MaxEnt) habitat suitability models identified shallow intertidal areas around mainland coast, islands and shoals as important areas for humpback dolphins. In contrast, bottlenose dolphins are more likely to occur further offshore and at greater depths, suggesting niche partitioning between these two sympatric species. Bottlenose dolphin response to sea surface temperature is markedly different between seasons (positive in May; negative in October) and probably influenced by the Leeuwin Current, a prominent oceanographic feature. Our findings support broad marine spatial planning, impact assessment and the design of future surveys, which would benefit from the collection of high-resolution digital images for species identification verification. A substantial proportion of data were removed due to uncertainties resulting from non-targeted observations and this is likely to have reduced model performance. We highlight the importance of considering climatic and seasonal fluctuations in interpreting distribution patterns and species interactions in assuming habitat suitability.

The Ningaloo Reef, Australia’s longest fringing reef, is uniquely positioned in the NW region of the continent, with clear, oligotrophic waters, relatively low human impacts, and a high level of protection through the World Heritage Site and its marine park status. Non-invasive optical sensors, which seamlessly derive bathymetry and bottom reflectance, are ideally suited for mapping and monitoring shallow reefs such as Ningaloo. Using an existing airborne hyperspectral survey, we developed a new, geomorphic layer for the reef for depths down to 20 m, through an object-oriented classification that combines topography and benthic cover. We demonstrate the classification approach using three focus areas in the northern region of the Muiron Islands, the central part around Point Maud, and Gnaraloo Bay in the south. Topographic mapping combined aspect, slope, and depth into 18 classes and, unsurprisingly, allocated much of the area into shallow, flat lagoons, and highlighted narrow, deeper channels that facilitate water circulation. There were five distinct geomorphic classes of coral-algal mosaics in different topographic settings. Our classifications provide a useful baseline for stratifying ecological field surveys, designing monitoring programmes, and assessing reef resilience from current and future threats.