Queensland Department of Environment and Science

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.

Abstract Grassland ecosystems cover a large portion of Earths’ surface and contain substantial amounts of soil organic carbon. Previous work has established that these soil carbon stocks are sensitive to management and land use changes: grazing, species composition, and mineral nutrient availability can lead to losses or gains of soil carbon. Because of the large annual carbon fluxes into and out of grassland systems, there has been growing interest in how changes in management might shift the net balance of these flows, stemming losses from degrading grasslands or managing systems to increase soil carbon stocks (i.e., carbon sequestration). A synthesis published in 2001 assembled data from hundreds of studies to document soil carbon responses to changes in management. Here we present a new synthesis that has integrated data from the hundreds of studies published after our previous work. These new data largely confirm our earlier conclusions: improved grazing management, fertilization, sowing legumes and improved grass species, irrigation, and conversion from cultivation all tend to lead to increased soil C, at rates ranging from 0.105 to more than 1 Mg C·ha −1 ·yr −1 . The new data include assessment of three new management practices: fire, silvopastoralism, and reclamation, although these studies are limited in number. The main area in which the new data are contrary to our previous synthesis is in conversion from native vegetation to grassland, where we find that across the studies the average rate of soil carbon stock change is low and not significant. The data in this synthesis confirm that improving grassland management practices and conversion from cropland to grassland improve soil carbon stocks.

Summary Allometric equations are currently used to estimate above‐ground biomass (AGB) based on the indirect relationship with tree parameters. Terrestrial laser scanning (TLS) can measure the canopy structure in 3D with high detail. In this study, we develop an approach to estimate AGB from TLS data, which does not need any prior information about allometry. We compare these estimates against destructively harvested AGB estimates and AGB derived from allometric equations. We also evaluate tree parameters, diameter at breast height (DBH) and tree height, estimated from traditional field inventory and TLS data. Tree height, DBH and AGB data are collected through traditional forest inventory, TLS and destructive sampling of 65 trees in a native Eucalypt Open Forest in Victoria, Australia. Single trees are extracted from the TLS data and quantitative structure models are used to estimate the tree volume directly from the point cloud data. AGB is inferred from these volumes and basic density information and is then compared with the estimates derived from allometric equations and destructive sampling. AGB estimates derived from TLS show a high agreement with the reference values from destructive sampling, with a concordance correlation coefficient (CCC) of 0·98. The agreement between AGB estimates from allometric equations and the reference is lower (CCC = 0·68–0·78). Our TLS approach shows a total AGB overestimation of 9·68% compared to an underestimation of 36·57–29·85% for the allometric equations. The error for AGB estimates using allometric equations increases exponentially with increasing DBH, whereas the error for AGB estimates from TLS is not dependent on DBH. The TLS method does not rely on indirect relationships with tree parameters or calibration data and shows better agreement with the reference data compared to estimates from allometric equations. Using 3D data also enables us to look at the height distributions of AGB, and we demonstrate that 80% of the AGB at plot level is located in the lower 60% of the trees for a Eucalypt Open Forest. This method can be applied in many forest types and can assist in the calibration and validation of broad‐scale biomass maps.

Abstract Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system 1 . Remote-sensing estimates to quantify carbon losses from global forests 2–5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced 6 and satellite-derived approaches 2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea 2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

Intermittently flowing streams and rivers should be recognized, afforded protection, and better managed.

Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST) in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP) area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30 °C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth) on LST and consequently to devise appropriate policy measures.

The green turtle, Chelonia mydas, is a circumglobal species and a primary herbivore in marine ecosystems. Overexploitation as a food resource for human populations has resulted in drastic declines or extinction of green turtle populations in the Greater Caribbean. Attempts to manage the remaining populations on a sustainable basis are hampered by insufficient knowledge of demographic parameters. In particular, compensatory responses resulting from density-dependent effects have not been evaluated for any sea turtle population and thus have not been explicitly included in any population models. Growth rates of immature green turtles were measured during an 18-yr study in Union Creek, a wildlife reserve in the southern Bahamas. We have evaluated the growth data for both straight carapace length (SCL) and body mass with nonparametric regression models that had one response variable (absolute growth rate) and five potential covariates: sex, site, year, mean size, and recapture interval. The SCL model of size-specific growth rates was a good fit to the data and accounted for 59% of the variance. The body-mass model was not a good fit to the data, accounting for only 26% of the variance. In the SCL model, sex, site, year, and mean size all had significant effects, whereas recapture interval did not. We used results of the SCL model to evaluate a density-dependent effect on somatic growth rates. Over the 18 yr of our study, relative population density underwent a sixfold increase followed by a threefold decrease in Union Creek as a result of natural immigration and emigration. Three lines of evidence support a density-dependent effect. First, there is a significant inverse correlation between population density and mean annual growth rate. Second, the condition index (mass/(SCL)3) of green turtles in Union Creek is positively correlated with mean annual growth rates and was negatively correlated with population density, indicating that the green turtles were nutrient limited during periods of low growth and high population densities. Third, the population in Union Creek fluctuated around carrying capacity during our study and thus was at levels likely to experience density-dependent effects that could be measured. We estimate the carrying capacity of pastures of the seagrass Thalassia testudinum, the major diet plant of the green turtle, as a range from 122 to 4439 kg green turtles/ha or 16–586 million 50-kg green turtles in the Caribbean. Because green turtle populations are probably regulated by food limitation under natural conditions, carrying capacity can serve as a baseline to estimate changes in green turtle populations in the Caribbean since pre-Columbian times and to set a goal for recovery for these depleted populations. Finally, we compare the growth functions for green turtle populations in the Atlantic and Pacific oceans. Not only does the form of the size-specific growth functions differ between the two regions (monotonic declining in the Atlantic and nonmonotonic in the Pacific), but also small juvenile green turtles in the Atlantic have substantially higher growth rates than those in the Pacific. Research is needed to evaluate the causes of these differences, but our results indicate that demographic parameters between ocean basins should only be extrapolated with great caution.

Temporary rivers and streams that naturally cease to flow and dry up can be found on every continent. Many other water courses that were once perennial now also have temporary flow regimes due to the effects of water extraction for human use or as a result of changes in land use and climate. The dry beds of these temporary rivers are an integral part of river landscapes. We discuss their importance in human culture and their unique diversity of aquatic, amphibious, and terrestrial biota. We also describe their role as seed and egg banks for aquatic biota, as dispersal corridors and temporal ecotones linking wet and dry phases, and as sites for the storage and processing of organic matter and nutrients. In light of these valuable functions, dry riverbeds need to be fully integrated into river management policies and monitoring programs. We also identify key knowledge gaps and suggest research questions concerning the values of dry riverbeds.

Despite concerns regarding the environmental impacts of microplastics, knowledge of the incidence and levels of synthetic particles in large marine vertebrates is lacking. Here, we utilize an optimized enzymatic digestion methodology, previously developed for zooplankton, to explore whether synthetic particles could be isolated from marine turtle ingesta. We report the presence of synthetic particles in every turtle subjected to investigation (n = 102) which included individuals from all seven species of marine turtle, sampled from three ocean basins (Atlantic [ATL]: n = 30, four species; Mediterranean (MED): n = 56, two species; Pacific (PAC): n = 16, five species). Most particles (n = 811) were fibres (ATL: 77.1% MED: 85.3% PAC: 64.8%) with blue and black being the dominant colours. In lesser quantities were fragments (ATL: 22.9%: MED: 14.7% PAC: 20.2%) and microbeads (4.8%; PAC only; to our knowledge the first isolation of microbeads from marine megavertebrates). Fourier transform infrared spectroscopy (FT-IR) of a subsample of particles (n = 169) showed a range of synthetic materials such as elastomers (MED: 61.2%; PAC: 3.4%), thermoplastics (ATL: 36.8%: MED: 20.7% PAC: 27.7%) and synthetic regenerated cellulosic fibres (SRCF; ATL: 63.2%: MED: 5.8% PAC: 68.9%). Synthetic particles being isolated from species occupying different trophic levels suggest the possibility of multiple ingestion pathways. These include exposure from polluted seawater and sediments and/or additional trophic transfer from contaminated prey/forage items. We assess the likelihood that microplastic ingestion presents a significant conservation problem at current levels compared to other anthropogenic threats.

Several recommendations have been proposed for detecting land use and land cover change (LULCC) on the environment from, observed climatic records and to modeling to improve its understanding and its impacts on climate. Researchers need to detect LULCCs accurately at appropriate scales within a specified time period to better understand their impacts on climate and provide improved estimates of future climate. The US Climate Reference Network (USCRN) can be helpful in monitoring impacts of LULCC on near-surface atmospheric conditions, including temperature. The USCRN measures temperature, precipitation, solar radiation, and ground or skin temperature. It is recommended that the National Climatic Data Center (NCDC) and other climate monitoring agencies develop plans and seek funds to address any monitoring biases that are identified and for which detailed analyses have not been completed.

Abstract Aim Comparative analyses of fire regimes at large geographical scales can potentially identify ecological and climatic controls of fire. Here we describe A ustralia's broad fire regimes, and explore interrelationships and trade‐offs between fire regime components. We postulate that fire regime patterns will be governed by trade‐offs between moisture, productivity, fire frequency and fire intensity. Location Australia. Methods We reclassified a vegetation map of A ustralia, defining classes based on typical fuel and fire types. Classes were intersected with a climate classification to derive a map of ‘fire regime niches’. Using expert elicitation and a literature search, we validated each niche and characterized typical and extreme fire intensities and return intervals. Satellite‐derived active fire detections were used to determine seasonal patterns of fire activity. Results Fire regime characteristics are closely related to the latitudinal gradient in summer monsoon activity. Frequent low‐intensity fires occur in the monsoonal north, and infrequent, high‐intensity fires in the temperate south, demonstrating a trade‐off between frequency and intensity: that is, very high‐intensity fires are only associated with very low‐frequency fire regimes in the high biomass eucalypt forests of southern A ustralia. While these forests occasionally experience extremely intense fires (> 50,000 kW m −1 ), such regimes are exceptional, with most of the continent dominated by grass fuels, typically burning with lower intensity (< 5000 kW m −1 ). Main conclusions Australia's fire regimes exhibit a coherent pattern of frequent, grass‐fuelled fires in many differing vegetation types. While eucalypts are a quintessential A ustralian entity, their contribution as a dominant driver of high‐intensity fire regimes, via their litter and bark fuels, is restricted to the forests of the continent's southern and eastern extremities. Our analysis suggests that the foremost driver of fire regimes at the continental scale is not productivity, as postulated conceptually, but the latitudinal gradient in summer monsoon rainfall activity.

Multi-temporal satellite imagery can be composited over a season (or other time period) to produce imagery which is representative of that period, using techniques which will reduce contamination by cloud and other problems. For the purposes of vegetation monitoring, a commonly used technique is the Maximum NDVI Composite, used in conjunction with variety of other constraints. The current paper proposes an alternative based on the medoid (in reflectance space) over the time period (the medoid is a multi-dimensional analogue of the median), which is robust against extreme values, and appears to be better at producing imagery which is representative of the time period. For each pixel, the medoid is always selected from the available dates, so the result is always a single observation for that pixel, thus preserving relationships between bands. The method is applied to Landsat TM/ETM+ imagery to create seasonal reflectance images (four per year), with the aim being a regular time series of reflectance values which captures the variability at seasonal time scales. Analysis of the seasonal reflectance values suggests that resulting temporal image composites are more representative of the time series than the maximum NDVI seasonal composite.

Focusing on woody vegetation in Queensland, Australia, the study aimed to establish whether the relationship between Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) HH and HV backscattering coefficients and above ground biomass (AGB) was consistent within and between structural formations (forests, woodlands and open woodlands, including scrub). Across these formations, 2781 plot-based measurements (from 1139 sites) of tree diameters by species were collated, from which AGB was estimated using generic allometric equations. For Queensland, PALSAR fine beam dual (FBD) 50 m strip data for 2007 were provided through the Japanese Space Exploration Agency's (JAXA) Kyoto and Carbon (K&C) Initiative, with up to 3 acquisitions available for each Reference System for Planning (RSP) paths. When individual strips acquired over Queensland were combined, `banding' was evident within the resulting mosaics, with this attributed to enhanced L-band backscatter following rainfall events in some areas. Reference to Advanced Microwave Scanning Radiometer-EOS (AMSR-E) data indicated that strips with enhanced L-band backscatter corresponded to areas with increased effective vegetation water content (kg m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> ) and, to a lesser extent, soil moisture (g cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> ). Regardless of moisture conditions, L-band HV topographically normalized backscattering intensities backscatter (σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> ) increased asymptotically with AGB, with the saturation level being greatest for forests and least for open woodlands. However, under conditions of relative maximum surface moisture, L-band HV and HH σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> was enhanced by as much as 2.5 and 4.0 dB respectively, particularly for forests of lower AGB, with this resulting in an overall reduction in dynamic range. The saturation level also reduced at L-band HH for forests and woodlands but remained similar for open woodlands. Differences in the rate of increase in both L-band HH and HV σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> with AGB were observed between forests and the woodland categories (for both relatively wet and dry conditions) with these attributed, in part, to differences in the size class distribution and stem density between non-remnant (secondary) forests and remnant woodlands of lower AGB. The study concludes that PALSAR data acquired when surface moisture and rainfall are minimal allow better estimation of the AGB of woody vegetation and that retrieval algorithms ideally need to consider differences in surface moisture conditions and vegetation structure.

The detection of clinically relevant disease-specific biomolecules, including nucleic acids, circulating tumor cells, proteins, antibodies, and extracellular vesicles, has been indispensable to understand their functions in disease diagnosis and prognosis. Therefore, a biosensor for the robust, ultrasensitive, and selective detection of these low-abundant biomolecules in body fluids (blood, urine, and saliva) is emerging in current clinical research. In recent years, nanomaterials, especially superparamagnetic nanomaterials, have played essential roles in biosensing due to their intrinsic magnetic, electrochemical, and optical properties. However, engineered multicomponent magnetic nanoparticle-based current biosensors that offer the advantages of excellent stability in a complex biomatrix; easy and alterable biorecognition of ligands, antibodies, and receptor molecules; and unified point-of-care integration have yet to be achieved. This review introduces the recent advances in superparamagnetic nanostructures for electrochemical and optical biosensing for disease-specific biomarkers. This review emphasizes the synthesis, biofunctionalization, and intrinsic properties of nanomaterials essential for robust, ultrasensitive biosensing. With a particular emphasis on nanostructure-based electrochemical and optical detection of disease-specific biomarkers such as nucleic acids (DNA and RNA), proteins, autoantibodies, and cells, this review also chronicles the needs and challenges of nanoarchitecture-based detection. These summaries provide further insights for researchers to inspire their future work on the development of nanostructures for integrating into biosensing and devices for a broad field of applications in analytical sensing and in clinic.

Given the potential vulnerability of sea turtles to climate change, a growing number of studies are predicting how various climatic processes will affect their nesting grounds. However, these studies are limited by scale, because they predict how a single climatic process will affect sea turtles but processes are likely to occur simultaneously and cause cumulative effects. This study addresses the need for a structured approach to investigate how multiple climatic processes may affect a turtle population. Here, we use a vulnerability assessment framework to assess the cumulative impact of various climatic processes on the nesting grounds used by the northern Great Barrier Reef (nGBR) green turtle population. Further, we manipulate the variables from this framework to allow users to investigate how mitigating different climatic processes individually or simultaneously can influence the vulnerability of the nesting grounds. Our assessment indicates that nesting grounds closer to the equator, such as Bramble Cay and Milman Island, are the most vulnerable to climate change. In the short-term (by 2030), sea level rise will cause the most impact on the nesting grounds used by the nGBR green turtle population. However, in the longer term, by 2070 sand temperatures will reach levels above the upper transient range and the upper thermal threshold and cause relatively more impact on the nGBR green turtle population. Thus, in the long term, a reduction of impacts from sea-level rise may not be sufficient, as rookeries will start to experience high vulnerability values from increased temperature. Thus, in the long term, reducing the threats from increased temperature may provide a greater return in conservation investment than mitigating the impacts from other climatic processes. Indeed, our results indicate that if the impacts from increased temperature are mitigated, the vulnerability values of almost all rookeries will be reduced to low levels.

INTRODUCTION: Despite recent advances in our knowledge and treatment strategies in Peyronie's Disease (PD), much remained unknown about this disease. AIM: To provide a clinical framework and key guideline statements to assist clinicians in an evidence-based management of PD. METHODS: A systematic literature search was conducted to identify published literature relevant to PD. The search included all relevant articles published up to June 2015, including preclinical studies and published guidelines. References used in the text were assessed according to their level of evidence, and guideline recommendations were graded based on the Oxford Centre for Evidence-Based Medicine Levels of Evidence. Owing to the paucity of larger series and randomized placebo-controlled trials with regard to surgical intervention, guideline statements are provided as clinical principle or expert opinion. MAIN OUTCOME MEASURES: This literature was discussed at a panel meeting, and selected articles with the highest evidence available were used to create consensus guideline statements for the Fourth International Consultation on Sexual Medicine guidelines on PD. RESULTS: In addition to existing Third International Consultation on Sexual Medicine guidelines on PD, seven new summary recommendations were created. CONCLUSION: A greater understanding of the scientific basis of PD is greatly needed to address our understanding of the pathophysiology, clinical epidemiology, psychosocial, and diagnostic assessment as well as treatment strategies.

Summary 1. Stream ecosystem health monitoring and reporting need to be developed in the context of an adaptive process that is clearly linked to identified values and objectives, is informed by rigorous science, guides management actions and is responsive to changing perceptions and values of stakeholders. To be effective, monitoring programmes also need to be underpinned by an understanding of the probable causal factors that influence the condition or health of important environmental assets and values. This is often difficult in stream and river ecosystems where multiple stressors, acting at different spatial and temporal scales, interact to affect water quality, biodiversity and ecosystem processes. 2. In this article, we describe the development of a freshwater monitoring programme in South East Queensland, Australia, and how this has been used to report on ecosystem health at a regional scale and to guide investments in catchment protection and rehabilitation. We also discuss some of the emerging science needs to identify the appropriate scale and spatial arrangement of rehabilitation to maximise river ecosystem health outcomes and, at the same time, derive other benefits downstream. 3. An objective process was used to identify potential indicators of stream ecosystem health and then test these across a known catchment land‐use disturbance gradient. From the 75 indicators initially tested, 22 from five indicator groups (water quality, ecosystem metabolism, nutrient cycling, invertebrates and fish) responded strongly to the disturbance gradient, and 16 were subsequently recommended for inclusion in the monitoring programme. The freshwater monitoring programme was implemented in 2002, funded by local and State government authorities, and currently involves the assessment of over 120 sites, twice per year. This information, together with data from a similar programme on the region’s estuarine and coastal marine waters, forms the basis of an annual report card that is presented in a public ceremony to local politicians and the broader community. 4. Several key lessons from the SEQ Healthy Waterways Programme are likely to be transferable to other regional programmes aimed at improving aquatic ecosystem health, including the importance of a shared common vision, the involvement of committed individuals, a cooperative approach, the need for defensible science and effective communication. 5. Thematic implications : this study highlights the use of conceptual models and objective testing of potential indicators against a known disturbance gradient to develop a freshwater ecosystem health monitoring programme that can diagnose the probable causes of degradation from multiple stressors and identify the appropriate spatial scale for rehabilitation or protection. This approach can lead to more targeted management investments in catchment protection and rehabilitation, greater public confidence that limited funds are being well spent and better outcomes for stream and river ecosystem health.

Context Many Australian mammal species are highly susceptible to predation by introduced domestic cats (Felis catus) and European red foxes (Vulpes vulpes). These predators have caused many extinctions and have driven large distributional and population declines for many more species. The serendipitous occurrence of, and deliberate translocations of mammals to, ‘havens’ (cat- and fox-free offshore islands, and mainland fenced exclosures capable of excluding cats and foxes) has helped avoid further extinction. Aims The aim of this study was to conduct a stocktake of current island and fenced havens in Australia and assess the extent of their protection for threatened mammal taxa that are most susceptible to cat and fox predation. Methods Information was collated from diverse sources to document (1) the locations of havens and (2) the occurrence of populations of predator-susceptible threatened mammals (naturally occurring or translocated) in those havens. The list of predator-susceptible taxa (67 taxa, 52 species) was based on consensus opinion from &amp;gt;25 mammal experts. Key results Seventeen fenced and 101 island havens contain 188 populations of 38 predator-susceptible threatened mammal taxa (32 species). Island havens cover a larger cumulative area than fenced havens (2152 km2 versus 346 km2), and reach larger sizes (largest island 325 km2, with another island of 628 km2 becoming available from 2018; largest fence: 123 km2). Islands and fenced havens contain similar numbers of taxa (27 each), because fenced havens usually contain more taxa per haven. Populations within fences are mostly translocated (43 of 49; 88%). Islands contain translocated populations (30 of 139; 22%); but also protect in situ (109) threatened mammal populations. Conclusions Havens are used increasingly to safeguard threatened predator-susceptible mammals. However, 15 such taxa occur in only one or two havens, and 29 such taxa (43%) are not represented in any havens. The taxon at greatest risk of extinction from predation, and in greatest need of a haven, is the central rock-rat (Zyzomys pedunculatus). Implications Future investment in havens should focus on locations that favour taxa with no (or low) existing haven representation. Although havens can be critical for avoiding extinctions in the short term, they cover a minute proportion of species’ former ranges. Improved options for controlling the impacts of cats and foxes at landscape scales must be developed and implemented.

Summary Climate change and land‐use change are having substantial impacts on biodiversity world‐wide, but few studies have considered the impact of these factors together. If the combined effects of climate and land‐use change are greater than the effects of each threat individually, current conservation management strategies may be inefficient and/or ineffective. This is particularly important with respect to freshwater ecosystems because freshwater biodiversity has declined faster than either terrestrial or marine biodiversity over the last three decades. This is the first study to model the independent and combined effects of climate change and land‐use change on freshwater macroinvertebrates and fish. Using a case study in south‐east Q ueensland, A ustralia, we built a B ayesian belief network populated with a combination of field data, simulations, existing models and expert judgment. Different land‐use and climate scenarios were used to make predictions on how the richness of freshwater macroinvertebrates and fish is likely to respond in future. We discovered little change in richness averaged across the region, but identified important impacts and effects at finer scales. High nutrients and high runoff as a result of urbanization combined with high nutrients and high water temperature as a result of climate change and were the leading drivers of potential declines in macroinvertebrates and fish at fine scales. Synthesis and applications . This is the first study to separate out the constituent drivers of impacts on biodiversity that result from climate change and land‐use change. Mitigation requires management actions that reduce in‐stream nutrients, slows terrestrial runoff and provides shade, to improve the resilience of biodiversity in streams. Encouragingly, the restoration of riparian habitats is identified as an important buffering tool that can mitigate the negative effects of climate change and land‐use change.

Mass spectrometry imaging (MSI) enables the spatial distributions of molecules possessing different mass-to-charge ratios to be mapped within complex environments revealing regional changes at the molecular level. Even at high mass resolving power, however, these images often reflect the summed distribution of multiple isomeric molecules, each potentially possessing a unique distribution coinciding with distinct biological function(s) and metabolic origin. Herein, this chemical ambiguity is addressed through an innovative combination of ozone-induced dissociation reactions with MSI, enabling the differential imaging of isomeric lipid molecules directly from biological tissues. For the first time, we demonstrate both double bond- and sn-positional isomeric lipids exhibit distinct spatial locations within tissue. This MSI approach enables researchers to unravel local lipid molecular complexity based on both exact elemental composition and isomeric structure directly from tissues.