International Assessments of the Vulnerability of the Coastal Zone to Climate Change, Including an Australian Perspective

Australia, and considers global, and in some cases national, assessments of vulnerability to climate change to evaluate the implications for the Australian coast, or to assess the applicability of particular approaches and methods to Australia. Climate change vulnerability assessment aims at assisting policymakers in adequately responding to the challenge of climate change by investigating how projected changes in the Earth\u27s climate may affect natural systems and human activities. Generally studies consider, exposure or susceptibility of natural coastal systems, the effect on socio-economic systems (“impact assessment”), and/or how human actions may reduce adverse effects of climate change on those systems or activities (“adaptation assessment”, a measure of adaptive capacity). The framework for a climate change vulnerability assessment depends on the system under consideration, stressors, responses (effects), and actions (adaptation). It is important that each assessment is undertaken at the relevant spatial and temporal scales, and the results are often appropriate only at those scales

Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB)

Bovine TB is a major problem for the agricultural industry in several countries. TB can be contracted and spread by species other than cattle and this can cause a problem for disease control. In the UK and Ireland, badgers are a recognised reservoir of infection and there has been substantial discussion about potential control strategies. We present a coupling of individual based models of bovine TB in badgers and cattle, which aims to capture the key details of the natural history of the disease and of both species at approximately county scale. The model is spatially explicit it follows a very large number of cattle and badgers on a different grid size for each species and includes also winter housing. We show that the model can replicate the reported dynamics of both cattle and badger populations as well as the increasing prevalence of the disease in cattle. Parameter space used as input in simulations was swept out using Latin hypercube sampling and sensitivity analysis to model outputs was conducted using mixed effect models. By exploring a large and computationally intensive parameter space we show that of the available control strategies it is the frequency of TB testing and whether or not winter housing is practised that have the most significant effects on the number of infected cattle, with the effect of winter housing becoming stronger as farm size increases. Whether badgers were culled or not explained about 5%, while the accuracy of the test employed to detect infected cattle explained less than 3% of the variance in the number of infected cattle

Recommendations for Next‐Generation Ground Magnetic Perturbation Validation

Data‐model validation of ground magnetic perturbation forecasts, specifically of the time rate of change of surface magnetic field, dB/dt, is a critical task for model development and for mitigation of geomagnetically induced current effects. While a current, community‐accepted standard for dB/dt validation exists (Pulkkinen et al., 2013), it has several limitations that prevent more complete understanding of model capability. This work presents recommendations from the International Forum for Space Weather Capabilities Assessment Ground Magnetic Perturbation Working Team for creating a next‐generation validation suite. Four recommendations are made to address the existing suite: greatly expand the number of ground observatories used, expand the number of events included in the suite from six to eight, generate metrics as a function of magnetic local time, and generate metrics as a function of activity type. For each of these, implementation details are explored. Limitations and future considerations are also discussed.Plain Language SummarySpace weather forecast models of magnetic field perturbations are important for protecting the power grid and other vulnerable infrastructure. These models must be validated by comparing their predictions to observations. This paper makes recommendations for how future models should be validated in order to best test their capabilities.Key PointsWe present a new validation suite for models of ground magnetic perturbations, dB/dt, of interest for geomagnetically induced currentsThe existing standard remains useful but provides limited information, so an expanded set of metrics is defined hereThis work is a result of the International Forum for Space Weather Capabilities Assessment and represents a new community consensusPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147786/1/swe20777_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147786/2/swe20777.pd

Dynamics of direct inter-pack encounters in endangered African wild dogs

Aggressive encounters may have important life history consequences due to the potential for injury and death, disease transmission, dispersal opportunities or exclusion from key areas of the home range. Despite this, little is known of their detailed dynamics, mainly due to the difficulties of directly observing encounters in detail. Here, we describe detailed spatial dynamics of inter-pack encounters in African wild dogs (Lycaon pictus), using data from custom-built high-resolution GPS collars in 11 free-ranging packs. On average, each pack encountered another pack approximately every 7 weeks and met each neighbour twice each year. Surprisingly, intruders were more likely to win encounters (winning 78.6% of encounters by remaining closer to the site in the short term). However, intruders did tend to move farther than residents toward their own range core in the short-term (1 h) post-encounter, and if this were used to indicate losing an encounter, then the majority (73.3%) of encounters were won by residents. Surprisingly, relative pack size had little effect on encounter outcome, and injuries were rare (<15% of encounters). These results highlight the difficulty of remotely scoring encounters involving mobile participants away from static defendable food resources. Although inter-pack range overlap was reduced following an encounter, encounter outcome did not seem to drive this, as both packs shifted their ranges post-encounter. Our results indicate that inter-pack encounters may be lower risk than previously suggested and do not appear to influence long-term movement and ranging

Optimizing the automated recognition of individual animals to support population monitoring

Reliable estimates of population size and demographic rates are central to assessing the status of threatened species. However, obtaining individual-based demographic rates requires long-term data, which is often costly and difficult to collect. Photographic data offer an inexpensive, noninvasive method for individual-based monitoring of species with unique markings, and could therefore increase available demographic data for many species. However, selecting suitable images and identifying individuals from photographic catalogs is prohibitively time-consuming. Automated identification software can significantly speed up this process. Nevertheless, automated methods for selecting suitable images are lacking, as are studies comparing the performance of the most prominent identification software packages. In this study, we develop a framework that automatically selects images suitable for individual identification, and compare the performance of three commonly used identification software packages; Hotspotter, I3S-Pattern, and WildID. As a case study, we consider the African wild dog, Lycaon pictus, a species whose conservation is limited by a lack of cost-effective large-scale monitoring. To evaluate intraspecific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat coloration patterns. The process of selecting suitable images was automated using convolutional neural networks that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. Hotspotter had the highest image-matching accuracy for both populations. However, the accuracy was significantly lower for the Kenyan population (62%), compared to the Zimbabwean population (88%). Our automated image preprocessing has immediate application for expanding monitoring based on image matching. However, the difference in accuracy between populations highlights that population-specific detection rates are likely and may influence certainty in derived statistics. For species such as the African wild dog, where monitoring is both challenging and expensive, automated individual recognition could greatly expand and expedite conservation efforts

Local Cattle and Badger Populations Affect the Risk of Confirmed Tuberculosis in British Cattle Herds

Background: The control of bovine tuberculosis (bTB) remains a priority on the public health agenda in Great Britain, after launching in 1998 the Randomised Badger Culling Trial (RBCT) to evaluate the effectiveness of badger (Meles meles) culling as a control strategy. Our study complements previous analyses of the RBCT data (focusing on treatment effects) by presenting analyses of herd-level risks factors associated with the probability of a confirmed bTB breakdown in herds within each treatment: repeated widespread proactive culling, localized reactive culling and no culling (survey-only). Methodology/Principal Findings: New cases of bTB breakdowns were monitored inside the RBCT areas from the end of the first proactive badger cull to one year after the last proactive cull. The risk of a herd bTB breakdown was modeled using logistic regression and proportional hazard models adjusting for local farm-level risk factors. Inside survey-only and reactive areas, increased numbers of active badger setts and cattle herds within 1500 m of a farm were associated with an increased bTB risk. Inside proactive areas, the number of M. bovis positive badgers initially culled within 1500 m of a farm was the strongest predictor of the risk of a confirmed bTB breakdown. Conclusions/Significance: The use of herd-based models provide insights into how local cattle and badger populations affect the bTB breakdown risks of individual cattle herds in the absence of and in the presence of badger culling. These measures of local bTB risks could be integrated into a risk-based herd testing programme to improve the targeting o

Holocene evolution of a barrier island system, Ria Formosa, South Portugal

Holocene evolution of the Ria Formosa barrier island system was studied through the examination of a large subsurface dataset acquired from 191 boreholes and five seismic refraction profiles. Two boreholes with total depths of 26 and 16.5 m were selected for a multi-proxy detailed laboratory analysis, including mean grain size distribution, organic matter (OM) content, color variation, shell identification, and benthic foraminifera assemblages. Selected cores are thought to be representative of the identified depositional sub-basins. Subsurface age data from 16 AMS C-14 dated samples were plotted against depth and resulted in a coherent age model of sedimentary infill. The system evolution was largely controlled by sediment availability, accommodation space, and Holocene sea level rise, first at a rapid rate of 7 mm/yr from 10 kcal yr BP to 7.25 kcal yr BP, followed by a slowdown to 1.1 mm/yr until present. A conceptual model for the origin and Holocene evolution of the Ria Formosa barrier island system implies three main steps, leading to the present system geomorphology: (1) marine flooding of incised palaeovalleys by the rapid transgression of palaeovalleys in the early Holocene(2) development of a proto-barrier island chain perched on Pleistocene detritic headlands and steeper interfluve areas during the early to middle Holoceneand (3) full development of the barrier islands chain and enclosing of the coastal lagoon, followed by the maturation of the system with subsequent siltation and salt marsh expansion from the middle Holocene until present. The onset of barrier system formation dates back to ca. 8 kcal yr BP, predating previously proposed age.SIHER project [PTDC/CTE-GIX112236/2009]EU Erasmus Mundus Joint Doctorate in Marine and Coastal Management (MACOMA) fellowship grant, under University of AlgarveEU Erasmus Mundus Joint Doctorate in Marine and Coastal Management (MACOMA) fellowship grant, under University of Cadi

Toward Human-Carnivore Coexistence: Understanding Tolerance for Tigers in Bangladesh

Fostering local community tolerance for endangered carnivores, such as tigers (Panthera tigris), is a core component of many conservation strategies. Identification of antecedents of tolerance will facilitate the development of effective tolerance-building conservation action and secure local community support for, and involvement in, conservation initiatives. We use a stated preference approach for measuring tolerance, based on the ‘Wildlife Stakeholder Acceptance Capacity’ concept, to explore villagers’ tolerance levels for tigers in the Bangladesh Sundarbans, an area where, at the time of the research, human-tiger conflict was severe. We apply structural equation modeling to test an a priori defined theoretical model of tolerance and identify the experiential and psychological basis of tolerance in this community. Our results indicate that beliefs about tigers and about the perceived current tiger population trend are predictors of tolerance for tigers. Positive beliefs about tigers and a belief that the tiger population is not currently increasing are both associated with greater stated tolerance for the species. Contrary to commonly-held notions, negative experiences with tigers do not directly affect tolerance levels; instead, their effect is mediated by villagers’ beliefs about tigers and risk perceptions concerning human-tiger conflict incidents. These findings highlight a need to explore and understand the socio-psychological factors that encourage tolerance towards endangered species. Our research also demonstrates the applicability of this approach to tolerance research to a wide range of socio-economic and cultural contexts and reveals its capacity to enhance carnivore conservation efforts worldwide

Winners and losers as mangrove, coral and seagrass ecosystems respond to sea-level rise in Solomon Islands

A 2007 earthquake in the western Solomon Islands resulted in a localised subsidence event in which sea level (relative to the previous coastal settings) rose approximately 30-70 cm, providing insight into impacts of future rapid changes to sea level on coastal ecosystems. Here, we show that increasing sea level by 30-70 cm can have contrasting impacts on mangrove, seagrass and coral reef ecosystems. Coral reef habitats were the clear winners with a steady lateral growth from 2006-2014, yielding a 157% increase in areal coverage over seven years. Mangrove ecosystems, on the other hand, suffered the largest impact through a rapid dieback of 35% (130 ha) of mangrove forest in the study area after subsidence. These forests, however, had partially recovered seven years after the earthquake albeit with a different community structure. The shallow seagrass ecosystems demonstrated the most dynamic response to relative shifts in sea level with both losses and gains in areal extent at small scales of 10-100 m. The results of this study emphasize the importance of considering the impacts of sea-level rise within a complex landscape in which winners and losers may vary over time and space