Telemetry reveals existing marine protected areas are worse than random for protecting the foraging habitat of threatened shy albatross (Thalassarche cauta )

The ambiguous role of partially protected marine protected areas in Australia: Results from a systematic literature review

Marine protected areas (MPAs) are an important tool in helping to protect biodiversity in the oceans. Recent ratification of the Kunming-Montreal Global Biodiversity Framework (GBF) has ensured that globally we are committed to effectively protecting 30% of the world's oceans by 2030, in MPAs. In Australia there is considerable interest in the potential benefits that partially protected areas (PPAs) may provide. However, a consistent definition of a PPA is currently lacking, and urgently needed to conduct quantitative analyses of PPAs. We conducted a systematic literature review to understand the current knowledge surrounding PPAs and their potential benefits. We define a PPA, characterise PPA implementation in Australia, and present results for the outcomes of PPAs in terms of ecological, economic, and social indicators. Our review suggests that although 45% of Australia's marine environment is within MPAs, 61% of MPAs provide only partial protection. The Northern Territory (100%), New South Wales (81%), and Queensland (79.8%) have the highest percentage of MPAs that are partially protected, compared to Tasmania which has the smallest percentage of partially protected MPAs (13.12%). Tasmania also has the smallest percentage cover of MPAs (6.49% state waters). Most PPA management plans did not contain quantifiable Key Performance Indicators (KPIs) to be able to effectively monitor the progress of these PPAs against the stated outcomes. We find the benefits of PPAs to be ambiguous: PPAs generally provide benefits when compared to 'open' ocean, however this is not a consistent result. There are no PPAs that provide greater overall benefits when compared to fully protected MPAs. Only one state (South Australia) and the Commonwealth (Australian Marine Parks) are collecting publicly available baseline data to facilitate quantitative monitoring of PPAs. Contrary to fisheries management, there were no plans of action if the declared MPAs and PPAs failed to meet their declared objectives and goals. Some PPAs within Australia appear to be incompatible with conservation priorities according to the recent "MPA Guide" classification framework. This study highlights the need for clearer management rationale and plans for PPAs in Australia, as these comprise the majority of MPAs in Australia's Exclusive Economic Zone.

Individual consistency in the localised foraging behaviour of shy albatross (Thalassarche cauta)

Quantifying the intra- and interindividual variation that exists within a population can provide meaningful insights into a population's vulnerability and response to rapid environmental change. We characterise the foraging behaviour of 308 trips taken by 96 shy albatross (Thalassarche cauta) from Albatross Island across seven consecutive years. At a population level, incubating shy albatross exploited a consistent area within ca. 500 km radius of their breeding colony. During half of the trips, individuals utilised the closest shelf break to the west of the colony, where upwelling events have been reported. The other half of the trips were exclusively within the neritic zone, utilising a variety of locations within the Bass Strait. Furthermore, we found evidence of individual consistency to geographic locations, with subsequent trips by an individual more similar than random trips from all individuals in our data, both within and between years (G-test, p < .05). Between-individual variation in foraging behaviour was not meaningfully explained by age (linear regression, p > .05) or sex (t-test, p > .05) for any metric, suggesting that other intrinsic individual factors are accounting for between-individual variation in foraging trips. A localised foraging distribution is unusual for albatross, which, combined with high variation in space use between individuals demonstrated here, suggests that this species is accessing adequate resources near the colony. Overall, these findings suggest that incubating shy albatross from Albatross Island exhibit tendencies of a generalist population comprised of uniquely specialised individuals. These results suggest that this species is operating below its biological capacity in this fast-warming area and provide a baseline from which to assess future change.

Privately protected areas increase global protected area coverage and connectivity

Privately protected areas (PPAs) are increasing in number and extent. Yet, we know little about their contribution to conservation and how this compares to other forms of protected area (PA). We address this gap by assessing the contribution of 17,561 PPAs to the coverage, complementarity and connectivity of existing PA networks in 15 countries across 5 continents. We find that PPAs (1) are three times more likely to be in biomes with <10% of their area protected than are other PA governance types and twice as likely to be in areas with the greatest human disturbance; (2) that they protect a further 1.2% of key biodiversity areas; (3) that they account for 3.4% of land under protection; and (4) that they increase PA network connectivity by 7.05%. Our results demonstrate the unique and significant contributions that PPAs can make to the conservation estate and that PPAs deserve more attention, recognition and resources for better design and implementation.

Where did they not go? Considerations for generating pseudo-absences for telemetry-based habitat models

BACKGROUND

Habitat suitability models give insight into the ecological drivers of species distributions and are increasingly common in management and conservation planning. Telemetry data can be used in habitat models to describe where animals were present, however this requires the use of presence-only modeling approaches or the generation of 'pseudo-absences' to simulate locations where animals did not go. To highlight considerations for generating pseudo-absences for telemetry-based habitat models, we explored how different methods of pseudo-absence generation affect model performance across species' movement strategies, model types, and environments.

METHODS

We built habitat models for marine and terrestrial case studies, Northeast Pacific blue whales (Balaenoptera musculus) and African elephants (Loxodonta africana). We tested four pseudo-absence generation methods commonly used in telemetry-based habitat models: (1) background sampling; (2) sampling within a buffer zone around presence locations; (3) correlated random walks beginning at the tag release location; (4) reverse correlated random walks beginning at the last tag location. Habitat models were built using generalised linear mixed models, generalised additive mixed models, and boosted regression trees.

RESULTS

We found that the separation in environmental niche space between presences and pseudo-absences was the single most important driver of model explanatory power and predictive skill. This result was consistent across marine and terrestrial habitats, two species with vastly different movement syndromes, and three different model types. The best-performing pseudo-absence method depended on which created the greatest environmental separation: background sampling for blue whales and reverse correlated random walks for elephants. However, despite the fact that models with greater environmental separation performed better according to traditional predictive skill metrics, they did not always produce biologically realistic spatial predictions relative to known distributions.

CONCLUSIONS

Habitat model performance may be positively biased in cases where pseudo-absences are sampled from environments that are dissimilar to presences. This emphasizes the need to carefully consider spatial extent of the sampling domain and environmental heterogeneity of pseudo-absence samples when developing habitat models, and highlights the importance of scrutinizing spatial predictions to ensure that habitat models are biologically realistic and fit for modeling objectives.