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Possingham, H.

Publications and source records attributed to Possingham, H..

9 recordsLinked to original sources

A typology of Australian terrestrial bird communities

AimIncreasing interest in holistic measurement of the response of fauna communities to interventions requires suitable community condition metrics. However, the development of such metrics is hindered by the absence of broad-scale typologies at suitable spatial and ecological resolutions. We aimed to derive a preliminary typology of terrestrial bird communities for Australia, based on bird co-occurrence data, and describe and map the likely distribution of each community type across the continent. LocationMainland Australia, continental islands Time period1973-2022 Major taxa studiedAves MethodsWe used fine-scale co-occurrence data from standard 2-ha surveys in BirdLife Australias citizen-science database. After filtering to reduce bias, we used hierarchical clustering followed by iterative consultation with experts to identify reliably distinct and recognisable terrestrial bird communities across Australia. We used Maxent to model the likely distributions of each community, and developed community descriptions based on each communitys composition and distribution. ResultsThe resultant typology included 29 reliably distinct and recognisable bird communities with major clusters corresponding with seven broad geographical regions. The distributions of bird communities did not correspond tightly to the boundaries of major vegetation groups, with most communities occurring across multiple vegetation types. Main ConclusionsOur preliminary typology of bird communities provides a standard classification at a continental scale. It newly defines distinct bird communities as entities for which condition benchmarks can be established to allow assessment of their conservation status and monitoring of change over time. Refinement will enable cryptic communities in areas with sparse data to be identified. The method could be translated to other regions where adequate coverage of data in the form of standardised surveys of fauna are available. Vast biodiversity datasets delivered through citizen science programs provide the opportunity to develop such typologies for fauna communities, as a precursor to developing targeted and informative community condition metrics.

ecology↗

Penguin tracking data for effective conservation in marine spatial planning

Understanding the spatial-temporal marine habits is crucial to conserving air-breathing marine animals that breed on islands and forage at sea. This study, focusing on little penguins from Phillip Island, Australia, employed tracking data to identify vital foraging areas during breeding season. Long-term data from sub-colonies and breeding stages were analysed using 50%, 75%, and 90% kernel utilisation distributions (KUDs). Breeding success, classified as low, average, or high, guided the exploration of site, year, and breeding stage-specific habitats. Using Marxan, a widely used conservation planning tool, the study proposes both static and dynamic spatial-temporal scenarios for protection based on KUDs. The dynamic approach, requiring less space than the static strategy, was more efficient and likely more acceptable to stakeholders. The study underscores the need for comprehensive data in conservation plans, as relying on one nesting sites data might miss essential foraging areas for penguins in other locations. This study demonstrates the efficacy of animal tracking data in spatial conservation prioritisation and marine spatial planning. The dynamic areas frequented emerged as a strategy to safeguard core regions at sea, offering insights to improve the conservation of iconic species like little penguins and promoting the health of islands and the entire marine ecosystem.

ecology↗

A report card methodology to showcase progress towards threatened species recovery

Among the conservation community, it is well known that Earths mass species extinction crisis is getting worse. Yet, an often neglected problem is the need for effectively communicating the species extinction crisis to diverse audiences in ways that catalyse immediate action. Here we generated a streamlined threatened species recovery report card methodology, which combined two input indicators including planning and funding, one output indicator capturing habitat protection, and one outcome indicator which highlights threatened species trajectories, to provide simple scores for all Australian threatened species. We show that just 41 (2.3%) of species achieved an A grade for the input indicator (i.e., recovery plans and federal funding), 240 (13.3%) achieved a C grade, and 1,521 (84.4%) achieved an F. Five hundred and twenty nine (29.3%) species achieved an A for the output indicator (i.e, habitat protection), 130 (7.2%) achieved a B, 158 (8.8%) achieved a C, 189 (10.5%) achieved a D, 212 (11.8%) achieved an E, and 584 (32.4%) achieved a F. While five (0.3%) species achieved an A for the output indicator (i.e., threat status improvement), every other species (99.7%) achieved an F. We provide a method to combine scores to test how individual jurisdictions are tracking and show that Australia is achieving an F for the input and outcome indicators, and a D for the output indicator. While the threatened species recovery report card highlighted a clear failure in many federal environmental legislation responsibilities, it provides a baseline from which different governments can track policy progress and outlines clear direction for immediate improvement including developing adequate recovery plans, funding the actions in the recovery plans, protecting habitat from further destruction, verifying recovery through monitoring and evaluation of species trajectories, and supporting transparency and collaboration on the execution on the plans through an improved data infrastructure. Without an immediate step change in how Australia communicates and faces its species crisis, we will leave a tragic legacy of extinction and fail our obligations to future generations of Australians, and the international community.

scientific communication and education↗

Prioritizing Management for Cumulative Impacts

Determining where environmental management is best applied, either through regulating single sectors of human activities or across sectors, is complicated by interactions between human impacts and the environment. In this article, we show how an explicit representation of human-environment interactions can help, via "impact networks" including activities (e.g. shipping), stressors (e.g. ship strikes), species (e.g. humpback whales) or ecosystem services (e.g. marine recreation). Impact networks can enable the identification of "leverage nodes", which, if present, can direct managers to the activities and stressors crucial for reducing risk to important ecosystem components. Exploring an impact network for a coastal ecosystem in British Columbia, Canada, we seek to identify these leverage nodes using a new approach employing Bayesian Belief Networks of risks to ecosystems. In so doing, we address three key questions: (1) Do leverage nodes exist? (2) Do management plans for species correctly identify leverage nodes? (3) Does the management of leverage nodes for certain species realize benefits for other species and ecosystem services? We show that there are several leverage nodes across all species investigated, and show that preconceptions about the regulation of risk to species can misidentify leverage nodes, potentially leading to ineffective management. Notably, we show that managing fisheries does not reduce overall risk to herring whereas managing diverse cumulative impacts including nutrient runoff, oil spills, and marine debris can reduce risk to herring, additional species, and related ecosystem services. Thus, by targeting leverage nodes, managers can efficiently mitigate risks for whole communities, ecosystems, and ecosystem services.

ecology↗

An objective-based prioritization approach to improve trophic complexity through ecological restoration

O_LIReassembling ecological communities and rebuilding habitats through active restoration treatments requires curating the selection of plant species to use in seeding and planting mixes. Ideally, these mixes should be assembled based on attributes that support ecosystem function and services, promote plant and animal species interactions and ecological networks in restoration while balancing project constraints. Despite these critical considerations, it is common for species mixes to be selected opportunistically. Reframing the selection of seed mixes for restoration around ecological objectives is essential for success but accessible methods and tools are needed to support this effort. C_LIO_LIWe developed a framework to optimize species seed mixes based on prioritizing plant species attributes to best support different objectives for ecosystem functions, services, and trophic relationships such as pollination, seed dispersal, and herbivory. We compared results to approaches where plant species are selected to represent plant taxonomic richness, dominant species, and at random. We tested our framework for 176 plant species found in European alpine grasslands and identified 163 associated attributes affiliated to trophic relationships, ecosystem functions, and services. C_LIO_LIIn all cases, trophic relationships, ecosystem functions, and services can be captured more efficiently through objective-based prioritization using the functional identity of plant species. Solutions (plant species lists) can be compared quantitatively, in terms of costs, species, or objectives. We confirm that a random draw of plant species from the regional plant species pool cannot be assumed to support other trophic groups and ecosystem functions and services. C_LIO_LISynthesis and Applications. Our framework is presented as a proof of concept to help restoration practitioners better apply quantitative decision-support to plant species selection in order to meet ecological restoration outcomes. Our approach may be tailored to any restoration initiative and habitat where seeding or planting mixes will be applied in active treatments. As global priority and resources are increasingly placed into restoration, this approach could be advanced to help make efficient decisions for many stages of the restoration process. C_LI

ecology↗

Uneven protection of persistent giant kelp forest in the Northeast Pacific Ocean

In most regions, the distribution of marine forests and the efficacy of their protection is unknown. We mapped the persistence of giant kelp forests across ten degrees of latitude in the Northeast Pacific Ocean and found that 7.7% of giant kelp is fully protected, with decreasing percentages from north to south. Sustainability goals should prioritize kelp mapping and monitoring, while protection and climate adaption targets should account for habitat dynamics.

ecology↗

Deforestation and bird habitat loss in Colombia

Tropical forests harbor most of the planets terrestrial biodiversity, and their loss means destruction of habitat for many species. Tropical deforestation continues at high rates in many regions, but it is often reported only in terms of area lost or its impacts on high-profile threatened species. We estimated the impact of both past and projected future deforestation on habitat extent for the entire assemblage of forest-dependent birds across Colombia, the country with more bird species than any other. Of the 550 forest-dependent species analysed, Almost all (n=536; 96.5%) had lost habitat, and 18% had lost at least half of their habitat by 2015. We used the recently developed Loss Index (LI) to capture the severity of habitat loss for the forest bird assemblage, discovering that the current LI for Colombia is 35, which means 35% of bird species have lost at least 35% of their habitat. The national LI for Colombia is projected to rise to 43 by 2040 if recent forest loss trends continue. There were large regional differences; Caribe had an LI of 82 while for the Pacific it was 14. A threat assessment for the regionally endemic species in the country showed that 12 (30%) of the species that are projected to lose 50% or more of their historical habitat by 2040 are not currently classified as threatened by the IUCN, suggesting that there are many species that are not listed but that face an imminent extinction threat from habitat loss. This extensive habitat depletion affecting entire species assemblages has significant implications for tropical forest ecosystems, and risks eroding ecosystem function and ecosystem service provision.

ecology↗

Only 40% of the world's forests are in good health

Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remains poorly quantified and mapped. By integrating data on observed and inferred human pressures and an index of lost connectivity, we generate the first globally-consistent, continuous index of forest condition as determined by degree of anthropogenic modification. Globally, only 17.4 million km2 of forest (40.5%) have high landscape level integrity (mostly found in Canada, Russia, the Amazon, Central Africa and New Guinea) and only 27% of this area is found in nationally-designated protected areas. Of the forest in protected areas, only 56% has high landscape level integrity. Ambitious policies that prioritize the retention of forest integrity, especially in the most intact areas, are now urgently needed alongside current efforts aimed at halting deforestation and restoring the integrity of forests globally.

ecology↗

A Theory For Ecological Survey Methods To Map Individual Distributions

Spatially-explicit approaches are widely recommended for ecosystem management. The quality of the data, such as presence/absence or habitat maps, affects the management actions recommended, and is, therefore, key to management success. However, available data are often biased and incomplete. Previous studies have advanced ways to resolve data bias and missing data, but questions remain about how we design ecological surveys to develop a dataset through field surveys. Ecological surveys may have multiple spatial scales, including the spatial extent of the target ecosystem (observation window), the resolution for mapping individual distributions (mapping unit), and the survey area within each mapping unit (sampling unit). We developed an ecological survey method for mapping individual distributions by applying spatially-explicit stochastic models. We used spatial point processes to describe individual spatial placements using either random or clustering processes. We then designed ecological surveys with different spatial scales and individual detectability. We found that the choice of mapping unit affected the presence mapped fraction, and the fraction of the total individuals covered by the presence mapped patches. Tradeoffs were found between these quantities and the map resolution, associated with equivalent asymptotic behaviors for both metrics at sufficiently small and large mapping unit scales. Our approach enabled consideration of the effect of multiple spatial scales in surveys, and estimation of the survey outcomes such as the presence mapped fraction and the number of individuals situated in the presence detected units. The developed theory may facilitate management decision-making and inform the design of monitoring and data gathering.

ecology↗