Adaptive management of Ramsar wetlands

Abstract The Macquarie Marshes are one of Australia’s iconic wetlands, recognised for their international importance, providing habitat for some of the continent’s more important waterbird breeding sites as well as complex and extensive flood-dependent vegetation communities. Part of the area is recognised as a wetland of international importance, under the Ramsar Convention. River regulation has affected their resilience, which may increase with climate change. Counteracting these impacts, the increased amount of environmental flow provided to the wetland through the buy-back and increased wildlife allocation have redressed some of the impacts of river regulation. This project assists in the development of an adaptive management framework for this Ramsar-listed wetland. It brings together current management and available science to provide an informed hierarchy of objectives that incorporates climate change adaptation and assists transparent management. The project adopts a generic approach allowing the framework to be transferred to other wetlands, including Ramsar-listed wetlands, supplied by rivers ranging from highly regulated to free flowing. The integration of management with science allows key indicators to be monitored that will inform management and promote increasingly informed decisions. The project involved a multi-disciplinary team of scientists and managers working on one of the more difficult challenges for Australia, exacerbated by increasing impacts of climate change on flows and inundation patterns

Testing a global standard for quantifying species recovery and assessing conservation impact.

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard

Using historical data to highlight population declines in the iconic Australian platypus

Long-term population data is essential for accurately assessing species status and for the correct management of endangered species. However, not all species are easily monitored and have been historically overlooked, giving inadequate data to form population estimates. Analysis of historical data is a relatively new technique for conservation management, often providing long-term population changes which would be otherwise undetectable using contemporary ecological monitoring. In this study we investigated long-term population changes for the iconic Australia platypus (Ornithorhynchus anatinus), by collating 257 years of historical data from newspaper archives, museums, natural history books, explorer journals and national Atlas data (1760-2017). The platypus is the most evolutionarily distinct mammal alive today, being the only member of the Ornithorhynchidae family and one of only five extant monotreme species that exist worldwide. The semi-aquatic mammal is endemic to creeks and rivers in eastern Australia and is threatened by river regulation and degradation, crayfish netting, predation, and pollution across its range. Despite the evolutionary uniqueness of the platypus, surprisingly little is known about its conservation status. The nocturnal and cryptic nature of the platypus, and the scarcity of long-term monitoring studies, has limited our capacity to assess changes in distribution and abundance, both historically and in more recent research. Thus, the conservation status of ‘near threatened’ (IUCN), and ‘least concern’ (Australian state legislation), may not reflect the true ecological status of the platypus. Our historical analyses suggest historical platypus abundances far exceeded current observations. Further, our comprehensive assessment of distributional change suggests a range decline for the platypus. Periods of decline and low population numbers have resulted in an intergenerational loss of knowledge on platypus abundances, leading to the perception that these lower contemporary abundances are representative of baseline populations. This study highlights long-term declines in platypus populations, essential information for accurately assessing the conservation status of the platypus and for future management strategies of this declining iconic Australia mammal.peerReviewe

Detecting a paradox

The platypus has intrigued and baffled scientists for centuries. In 1799, when the first pelt was examined by zoologist George Shaw in London, its bizarre appearance led to it being thought a hoax – a paradoxical mash-up of a duck’s bill and feet, a beaver’s tail, and an otter’s body. When no stitching was found, the specimen was accepted, ushering in an overhaul of mammalian classification. More than 200 years later, this elusive monotreme still confounds. Researchers such as Tamielle Brunt from Wildlife Queensland, Josh Griffiths from EnivroDNA, and Gilad Bino from the Platypus Conservation Initiative are tasked with understanding how this species survives, the threats it faces, and how many individuals remain in the wild. They’re aided in their mission by a new technology: eDNA

Using atlas data for large scale conservation strategies: a case study of NSWs mammals

Global threatening processes such as habitat loss, overexploitation, invasive species, and climate change are driving many species to extinction at an alarming rate. This has particularly affected mammal populations across Australia where mammal extinctions over the past two centuries have been the highest in the world. Setting aside areas for protection is the principle strategy for safeguarding against biodiversity and maintaining ecosystem processes. Identifying areas for protection requires comprehensive knowledge of species distributions, where relative comparisons can be made over large scales. Spatially explicit datasets, such as atlases, harbour the greatest potential of large-scale information of biodiversity. These however, are seldom fully utilised for large-scale conservation initiatives and management. This thesis provides concepts, methods, and operational guidelines for conservation efforts using large data over extensive scales. To achieve this, I utilised NSWs atlas data and focused on records of native terrestrial mammals. Chapter 1 provides an overview of global threats, conservation strategies, and specifically the state of Australias mammals. In chapter 2, I demonstrated how atlas data, collated at multiple spatial scales can be used to rank survey methods best suited for the detection of each mammal species. This approach provides a methodological process used to identify efficient monitoring strategies tailored for unique species inventories at regional and bioregional scales. Chapter 3 tests the efficacy of the existing Australian bioregional framework for representing mammal species within protected areas. The bioregional framework, which primarily relies on vegetation communities, is used to measure representation of biodiversity and prioritise new inclusions to the national protected area network. The chapter presents an alternative approach for prioritisation driven by mammal assemblages, using patterns co-occurring species. Results and performance for mammal representation are then assessed against the bioregional framework. Chapter 4 builds upon identified mammal assemblages to model anticipated effects of climate change on whole assemblages simultaneously and identify climate-resilient faunal communities. Identified areas are then used within to prioritise land for additions to the existing protected area network, given impacts of climate change on mammalian distributions. Chapter 5 examines the ecological and evolutionary mechanisms shaping Australias mammal community assemblages. By exploring trait interactions across spatial scales, a more precise scaling for evolving determinants of niche overlap are made. This provides unique insight into the evolutionary pathways and their rates, allowing identification of the scales in which these operate in shaping present-day communities. Finally, in Chapter 6, I summarise the research presented in the thesis and discuss directions for future work

Appendix B. Calibrated parameters used in the Sacramento rainfall runoff model.

Calibrated parameters used in the Sacramento rainfall runoff model

Average irreplaceability scores, when prioritising for a representation target of 80% of waterbird abundance for each of the 52 waterbird species, simultaneously across all species and (A) across all years 1983–2012; (B) during wet years; and (C) during dry years.

<p>Average irreplaceability scores, when prioritising for a representation target of 80% of waterbird abundance for each of the 52 waterbird species, simultaneously across all species and (A) across all years 1983–2012; (B) during wet years; and (C) during dry years.</p

Wetland complexes in the Murray-Darling Basin identified as priorities when setting an 80% representation targets for each of the 52 waterbird species, simultaneously across all species, across all years (overall), during dry and wet years, along with total and average (±95% CI) waterbird abundances estimated during the aerial surveys of waterbirds in eastern Australia.

<p>† Likely driven by high occurrence of Silver gull</p><p>Wetland complexes in the Murray-Darling Basin identified as priorities when setting an 80% representation targets for each of the 52 waterbird species, simultaneously across all species, across all years (overall), during dry and wet years, along with total and average (±95% CI) waterbird abundances estimated during the aerial surveys of waterbirds in eastern Australia.</p

Posterior mean coefficient (estimated using Bayesian Model Averaging) of total annual flows in the Murray-Darling Basin, against irreplaceability scores (IrSc) of each planning unit (PU), 1983–2012.

<p>Posterior mean coefficient (estimated using Bayesian Model Averaging) of total annual flows in the Murray-Darling Basin, against irreplaceability scores (IrSc) of each planning unit (PU), 1983–2012.</p