Charles Darwin University

The first public product of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) is its Conceptual Framework. This conceptual and analytical tool, presented here in detail, will underpin all IPBES functions and provide structure and comparability to the syntheses that IPBES will produce at different spatial scales, on different themes, and in different regions. Salient innovative aspects of the IPBES Conceptual Framework are its transparent and participatory construction process and its explicit consideration of diverse scientific disciplines, stakeholders, and knowledge systems, including indigenous and local knowledge. Because the focus on co-construction of integrative knowledge is shared by an increasing number of initiatives worldwide, this framework should be useful beyond IPBES, for the wider research and knowledge-policy communities working on the links between nature and people, such as natural, social and engineering scientists, policy-makers at different levels, and decision-makers in different sectors of society.

Population limitation is a fundamental tenet of ecology, but the relative roles of exogenous and endogenous mechanisms remain unquantified for most species. Here we used multi-model inference (MMI), a form of model averaging, based on information theory (Akaike's Information Criterion) to evaluate the relative strength of evidence for density-dependent and density-independent population dynamical models in long-term abundance time series of 1198 species. We also compared the MMI results to more classic methods for detecting density dependence: Neyman-Pearson hypothesis-testing and best-model selection using the Bayesian Information Criterion or cross-validation. Using MMI on our large database, we show that density dependence is a pervasive feature of population dynamics (median MMI support for density dependence = 74.7-92.2%), and that this holds across widely different taxa. The weight of evidence for density dependence varied among species but increased consistently, with the number of generations monitored. Best-model selection methods yielded similar results to MMI (a density-dependent model was favored in 66.2-93.9% of species time series), while the hypothesis-testing methods detected density dependence less frequently (32.6-49.8%). There were no obvious differences in the prevalence of density dependence across major taxonomic groups under any of the statistical methods used. These results underscore the value of using multiple modes of analysis to quantify the relative empirical support for a set of working hypotheses that encompass a range of realistic population dynamical behaviors.

The rapid expansion of human activities threatens ocean-wide biodiversity. Numerous marine animal populations have declined, yet it remains unclear whether these trends are symptomatic of a chronic accumulation of global marine extinction risk. We present the first systematic analysis of threat for a globally distributed lineage of 1,041 chondrichthyan fishes-sharks, rays, and chimaeras. We estimate that one-quarter are threatened according to IUCN Red List criteria due to overfishing (targeted and incidental). Large-bodied, shallow-water species are at greatest risk and five out of the seven most threatened families are rays. Overall chondrichthyan extinction risk is substantially higher than for most other vertebrates, and only one-third of species are considered safe. Population depletion has occurred throughout the world's ice-free waters, but is particularly prevalent in the Indo-Pacific Biodiversity Triangle and Mediterranean Sea. Improved management of fisheries and trade is urgently needed to avoid extinctions and promote population recovery. DOI: http://dx.doi.org/10.7554/eLife.00590.001.

Species distribution models (SDMs) are increasingly proposed to support conservation decision making. However, evidence of SDMs supporting solutions for on-ground conservation problems is still scarce in the scientific literature. Here, we show that successful examples exist but are still largely hidden in the grey literature, and thus less accessible for analysis and learning. Furthermore, the decision framework within which SDMs are used is rarely made explicit. Using case studies from biological invasions, identification of critical habitats, reserve selection and translocation of endangered species, we propose that SDMs may be tailored to suit a range of decision-making contexts when used within a structured and transparent decision-making process. To construct appropriate SDMs to more effectively guide conservation actions, modellers need to better understand the decision process, and decision makers need to provide feedback to modellers regarding the actual use of SDMs to support conservation decisions. This could be facilitated by individuals or institutions playing the role of 'translators' between modellers and decision makers. We encourage species distribution modellers to get involved in real decision-making processes that will benefit from their technical input; this strategy has the potential to better bridge theory and practice, and contribute to improve both scientific knowledge and conservation outcomes.

Machine learning techniques are being widely used to develop an intrusion detection system (IDS) for detecting and classifying cyberattacks at the network-level and the host-level in a timely and automatic manner. However, many challenges arise since malicious attacks are continually changing and are occurring in very large volumes requiring a scalable solution. There are different malware datasets available publicly for further research by cyber security community. However, no existing study has shown the detailed analysis of the performance of various machine learning algorithms on various publicly available datasets. Due to the dynamic nature of malware with continuously changing attacking methods, the malware datasets available publicly are to be updated systematically and benchmarked. In this paper, a deep neural network (DNN), a type of deep learning model, is explored to develop a flexible and effective IDS to detect and classify unforeseen and unpredictable cyberattacks. The continuous change in network behavior and rapid evolution of attacks makes it necessary to evaluate various datasets which are generated over the years through static and dynamic approaches. This type of study facilitates to identify the best algorithm which can effectively work in detecting future cyberattacks. A comprehensive evaluation of experiments of DNNs and other classical machine learning classifiers are shown on various publicly available benchmark malware datasets. The optimal network parameters and network topologies for DNNs are chosen through the following hyperparameter selection methods with KDDCup 99 dataset. All the experiments of DNNs are run till 1,000 epochs with the learning rate varying in the range [0.01-0.5]. The DNN model which performed well on KDDCup 99 is applied on other datasets, such as NSL-KDD, UNSW-NB15, Kyoto, WSN-DS, and CICIDS 2017, to conduct the benchmark. Our DNN model learns the abstract and high-dimensional feature representation of the IDS data by passing them into many hidden layers. Through a rigorous experimental testing, it is confirmed that DNNs perform well in comparison with the classical machine learning classifiers. Finally, we propose a highly scalable and hybrid DNNs framework called scale-hybrid-IDS-AlertNet which can be used in real-time to effectively monitor the network traffic and host-level events to proactively alert possible cyberattacks.

, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

This paper explores the phenomena of the emergence of the use of artificial intelligence in teaching and learning in higher education. It investigates educational implications of emerging technologies on the way students learn and how institutions teach and evolve. Recent technological advancements and the increasing speed of adopting new technologies in higher education are explored in order to predict the future nature of higher education in a world where artificial intelligence is part of the fabric of our universities. We pinpoint some challenges for institutions of higher education and student learning in the adoption of these technologies for teaching, learning, student support, and administration and explore further directions for research.

Melioidosis, caused by the gram-negative saprophyte Burkholderia pseudomallei, is a disease of public health importance in southeast Asia and northern Australia that is associated with high case-fatality rates in animals and humans. It has the potential for epidemic spread to areas where it is not endemic, and sporadic case reports elsewhere in the world suggest that as-yet-unrecognized foci of infection may exist. Environmental determinants of this infection, apart from a close association with rainfall, are yet to be elucidated. The sequencing of the genome of a strain of B. pseudomallei has recently been completed and will help in the further identification of virulence factors. The presence of specific risk factors for infection, such as diabetes, suggests that functional neutrophil defects are important in the pathogenesis of melioidosis; other studies have defined virulence factors (including a type III secretion system) that allow evasion of killing mechanisms by phagocytes. There is a possible role for cell-mediated immunity, but repeated environmental exposure does not elicit protective humoral or cellular immunity. A vaccine is under development, but economic constraints may make vaccination an unrealistic option for many regions of endemicity. Disease manifestations are protean, and no inexpensive, practical, and accurate rapid diagnostic tests are commercially available; diagnosis relies on culture of the organism. Despite the introduction of ceftazidime- and carbapenem-based intravenous treatments, melioidosis is still associated with a significant mortality attributable to severe sepsis and its complications. A long course of oral eradication therapy is required to prevent relapse. Studies exploring the role of preventative measures, earlier clinical identification, and better management of severe sepsis are required to reduce the burden of this disease.

Understanding the scale, location and nature conservation values of the lands over which Indigenous Peoples exercise traditional rights is central to implementation of several global conservation and climate agreements. However, spatial information on Indigenous lands has never been aggregated globally. Here, using publicly available geospatial resources, we show that Indigenous Peoples manage or have tenure rights over at least ~38 million km2 in 87 countries or politically distinct areas on all inhabited continents. This represents over a quarter of the world’s land surface, and intersects about 40% of all terrestrial protected areas and ecologically intact landscapes (for example, boreal and tropical primary forests, savannas and marshes). Our results add to growing evidence that recognizing Indigenous Peoples’ rights to land, benefit sharing and institutions is essential to meeting local and global conservation goals. The geospatial analysis presented here indicates that collaborative partnerships involving conservation practitioners, Indigenous Peoples and governments would yield significant benefits for conservation of ecologically valuable landscapes, ecosystems and genes for future generations. Land management and ownership by Indigenous Peoples are critical components of conservation strategies, but information on these has previously never been aggregated. Here, global data is compiled to show that Indigenous Peoples have tenure rights or manage a quarter of the world’s land area and 40% of all protected areas and intact ecosystems.

Lebel, L., J. M. Anderies, B. Campbell, C. Folke, S. Hatfield-Dodds, T. P. Hughes. and J. Wilson. 2006. Governance and the capacity to manage resilience in regional social-ecological systems. Ecology and Society 11(1): 19. https://doi.org/10.5751/ES-01606-110119

There is controversy concerning the role of genetic factors in species extinctions. Many authors have asserted that species are usually driven to extinction before genetic factors have time to impact them, but few studies have seriously addressed this issue. If this assertion is true, there will be little difference in genetic diversity between threatened and taxonomically related nonthreatened species. We compared average heterozygosities in 170 threatened taxa with those in taxonomically related nonthreatened taxa in a comprehensive metaanalysis. Heterozygosity was lower in threatened taxa in 77% of comparisons, a highly significant departure from the predictions of the no genetic impact hypothesis. Heterozygosity was on average 35% lower (median 40%) in threatened taxa than in related nonthreatened ones. These differences in heterozygosity indicate lowered evolutionary potential, compromised reproductive fitness, and elevated extinction risk in the wild. Independent evidence from stochastic computer projections has demonstrated that inbreeding depression elevates extinction risk for threatened species in natural habitats when all other threatening processes are included in the models. Thus, most taxa are not driven to extinction before genetic factors affect them adversely.

The world is under pressure from the novel COVID-19 pandemic. Indonesia is the fourth most populous country in the world and predicted to be affected significantly over a longer time period. Our paper aims to provide detailed reporting and analyses of the present rapid responses to COVID-19, between January and March 2020, in Indonesia. We particularly highlight responses taken by the governments, non-government organisations and the community. We outline gaps and limitations in the responses, based on our rapid analysis of media contents, from government speeches and reports, social and mass media platforms. We present five recommendations toward more rapid, effective, and comprehensive responses.

Abstract Policies aiming to preserve vegetated coastal ecosystems (VCE; tidal marshes, mangroves and seagrasses) to mitigate greenhouse gas emissions require national assessments of blue carbon resources. Here, we present organic carbon (C) storage in VCE across Australian climate regions and estimate potential annual CO 2 emission benefits of VCE conservation and restoration. Australia contributes 5–11% of the C stored in VCE globally (70–185 Tg C in aboveground biomass, and 1,055–1,540 Tg C in the upper 1 m of soils). Potential CO 2 emissions from current VCE losses are estimated at 2.1–3.1 Tg CO 2 -e yr -1 , increasing annual CO 2 emissions from land use change in Australia by 12–21%. This assessment, the most comprehensive for any nation to-date, demonstrates the potential of conservation and restoration of VCE to underpin national policy development for reducing greenhouse gas emissions.

Photoplethysmography (PPG) is used to estimate the skin blood flow using infrared light. Researchers from different domains of science have become increasingly interested in PPG because of its advantages as non-invasive, inexpensive, and convenient diagnostic tool. Traditionally, it measures the oxygen saturation, blood pressure, cardiac output, and for assessing autonomic functions. Moreover, PPG is a promising technique for early screening of various atherosclerotic pathologies and could be helpful for regular GP-assessment but a full understanding of the diagnostic value of the different features is still lacking. Recent studies emphasise the potential information embedded in the PPG waveform signal and it deserves further attention for its possible applications beyond pulse oximetry and heart-rate calculation. Therefore, this overview discusses different types of artifact added to PPG signal, characteristic features of PPG waveform, and existing indexes to evaluate for diagnoses. Keywords: Photoplethysmography, acceleration plethysmogram, second derivative plethysmogram, digital volume pulse, ageing, artery, autonomic function, blood pressure, cardiovascular, heart rate, pulse wave analysis, vascular disease

This paper presents results from a comparative analysis of environmental income from approximately 8000 households in 24 developing countries collected by research partners in CIFOR's Poverty Environment Network (PEN). Environmental income accounts for 28% of total household income, 77% of which comes from natural forests. Environmental income shares are higher for low-income households, but differences across income quintiles are less pronounced than previously thought. The poor rely more heavily on subsistence products such as wood fuels and wild foods, and on products harvested from natural areas other than forests. In absolute terms environmental income is approximately five times higher in the highest income quintile, compared to the two lowest quintiles.

Climate change will have far-reaching impacts on biodiversity, including increasing extinction rates. Current approaches to quantifying such impacts focus on measuring exposure to climatic change and largely ignore the biological differences between species that may significantly increase or reduce their vulnerability. To address this, we present a framework for assessing three dimensions of climate change vulnerability, namely sensitivity, exposure and adaptive capacity; this draws on species' biological traits and their modeled exposure to projected climatic changes. In the largest such assessment to date, we applied this approach to each of the world's birds, amphibians and corals (16,857 species). The resulting assessments identify the species with greatest relative vulnerability to climate change and the geographic areas in which they are concentrated, including the Amazon basin for amphibians and birds, and the central Indo-west Pacific (Coral Triangle) for corals. We found that high concentration areas for species with traits conferring highest sensitivity and lowest adaptive capacity differ from those of highly exposed species, and we identify areas where exposure-based assessments alone may over or under-estimate climate change impacts. We found that 608-851 bird (6-9%), 670-933 amphibian (11-15%), and 47-73 coral species (6-9%) are both highly climate change vulnerable and already threatened with extinction on the IUCN Red List. The remaining highly climate change vulnerable species represent new priorities for conservation. Fewer species are highly climate change vulnerable under lower IPCC SRES emissions scenarios, indicating that reducing greenhouse emissions will reduce climate change driven extinctions. Our study answers the growing call for a more biologically and ecologically inclusive approach to assessing climate change vulnerability. By facilitating independent assessment of the three dimensions of climate change vulnerability, our approach can be used to devise species and area-specific conservation interventions and indices. The priorities we identify will strengthen global strategies to mitigate climate change impacts.

Summary Resprouting as a response to disturbance is now widely recognized as a key functional trait among woody plants and as the basis for the persistence niche. However, the underlying mechanisms that define resprouting responses to disturbance are poorly conceptualized. Resprouting ability is constrained by the interaction of the disturbance regime that depletes the buds and resources needed to fund resprouting, and the environment that drives growth and resource allocation. We develop a b uds‐ p rotection‐ r esources ( BPR ) framework for understanding resprouting in fire‐prone ecosystems, based on bud bank location, bud protection, and how buds are resourced. Using this framework we go beyond earlier emphases on basal resprouting and highlight the importance of apical, epicormic and below‐ground resprouting to the persistence niche. The BPR framework provides insights into: resprouting typologies that include both fire resisters (i.e. survive fire but do not resprout) and fire resprouters; the methods by which buds escape fire effects, such as thick bark; and the predictability of community assembly of resprouting types in relation to site productivity, disturbance regime and competition. Furthermore, predicting the consequences of global change is enhanced by the BPR framework because it potentially forecasts the retention or loss of above‐ground biomass. Contents Summary 19 I. Introduction 20 II. Resprouters rather than ‘sprouters’ 21 III. How do plants resprout? 21 IV. Life‐history consequences of resprouting 27 V. Environmental constraints on resprouting 28 VI. Resprouting, community patterns and assembly 29 VII. Global change, carbon storage and resprouting 30 VIII. Conclusions 31 Acknowledgements 31 References 32

The highly distinctive and mostly endemic Australian land mammal fauna has suffered an extraordinary rate of extinction (>10% of the 273 endemic terrestrial species) over the last ∼200 y: in comparison, only one native land mammal from continental North America became extinct since European settlement. A further 21% of Australian endemic land mammal species are now assessed to be threatened, indicating that the rate of loss (of one to two extinctions per decade) is likely to continue. Australia's marine mammals have fared better overall, but status assessment for them is seriously impeded by lack of information. Much of the loss of Australian land mammal fauna (particularly in the vast deserts and tropical savannas) has been in areas that are remote from human population centers and recognized as relatively unmodified at global scale. In contrast to general patterns of extinction on other continents where the main cause is habitat loss, hunting, and impacts of human development, particularly in areas of high and increasing human population pressures, the loss of Australian land mammals is most likely due primarily to predation by introduced species, particularly the feral cat, Felis catus, and European red fox, Vulpes vulpes, and changed fire regimes.

Conservation assessment is a rapidly evolving discipline whose stated goal is the design of networks of protected areas that represent and ensure the persistence of nature (i.e., species, habitats, and environmental processes) by separating priority areas from the activities that degrade or destroy them. Nevertheless, despite a burgeoning scientific literature that ever refines these techniques for allocating conservation resources, it is widely believed that conservation assessments are rarely translated into actions that actually conserve nature. We reviewed the conservation assessment literature in peer-reviewed journals and conducted survey questionnaires of the authors of these studies. Two-thirds of conservation assessments published in the peer-reviewed scientific literature do not deliver conservation action, primarily because most researchers never plan for implementation. This research-implementation gap between conservation science and real-world action is a genuine phenomenon and is a specific example of the "knowing-doing gap" that is widely recognized in management science. Given the woefully inadequate resources allocated for conservation, our findings raise questions over the utility of conservation assessment science, as currently practiced, to provide useful, pragmatic solutions to conservation planning problems. A reevaluation of the conceptual and operational basis of conservation planning research is urgently required. We recommend the following actions for beginning a process for bridging the research-implementation gap in conservation planning: (1) acknowledge the research-implementation gap is real, (2) source research questions from practitioners, (3) situate research within a broader conservation planning model, (4) expand the social dimension of conservation assessments, (5) support conservation plans with transdisciplinary social learning institutions, (6) reward academics for societal engagement and implementation, and (7) train students in skills for "doing" conservation.

Plasmodium vivax threatens almost 40% of the world's population, resulting in 132-391 million clinical infections each year. Most of these cases originate from Southeast Asia and the Western Pacific, although a significant number also occurs in Africa and South America. Although often regarded as causing a benign and self-limiting infection, there is increasing evidence that the overall burden, economic impact, and severity of disease from P. vivax have been underestimated. Malaria control strategies have had limited success and are confounded by the lack of access to reliable diagnosis, emergence of multidrug resistant isolates, the parasite's ability to transmit early in the course of disease and relapse from dormant liver stages at varying time intervals after the initial infection. Progress in reducing the burden of disease will require improved access to reliable diagnosis and effective treatment of both blood-stage and latent parasites, and more detailed characterization of the epidemiology, morbidity, and economic impact of vivax malaria. Without these, vivax malaria will continue to be neglected by ministries of health, policy makers, researchers, and funding bodies.