Adaptive Management of Migratory Birds Under Sea Level Rise

International audienceThe best practice method for managing ecological systems under uncertainty is adaptive management (AM), an iterative process of reducing uncertainty while simultaneously optimizing a management objective. Existing solution methods used for AM problems assume that the system dynamics are stationary, i.e., described by one of a set of pre-defined models. In reality ecological systems are rarely stationary and evolve over time. Importantly, the effects of climate change on populations are unlikely to be captured by stationary models. Practitioners need efficient algorithms to implement AM on real-world problems. AM can be formulated as a hidden model Markov Decision Process (hmMDP), which allows the state space to be factored and shows promise for the rapid resolution of large problems. We provide an ecological dataset and performance metrics for the AM of a network of shorebird species utilizing the East Asian-Australasian flyway given uncertainty about the rate of sea level rise. The non-stationary system is modelled as a stationary POMDP containing hidden alternative models with known probabilities of transition between them. We challenge the POMDP community to exploit the simplifications allowed by structuring the AM problem as an hmMDP and improve our benchmark solutions

Assessing carbon stocks using indigenous peoples' field measurements in Amazonian Guyana

Accurate estimations of carbon stocks across large tracts of tropical forests are key for participation in programs promoting avoided deforestation and carbon sequestration, such as the UN REDD+ framework. Trained local technicians can provide such data, and this, combined with satellite imagery, allows robust carbon stock estimation across vegetation classes and large areas. In the first comprehensive survey in Guyana conducted by indigenous people, ground data from 21 study sites in the Rupununi region were used to estimate above ground tree carbon density across a diversity of ecosystems and land use types. Carbon stocks varied between village sites from 1Tg to 22.7Tg, and these amounts were related to stem density and diameter. This variation was correlated with vegetation type across the region, with savannas holding on average 14MgCha-1 and forests 153MgCha-1. The results indicated that previous estimates based on remotely sensed data for this area may be inaccurate (under estimations). There were also differences in carbon densities between village sites and uninhabited control areas, which are presumably driven by community use. Recruiting local technicians for field work allowed (a) large amounts of ground data to be collected for a wide region otherwise hard to access, and (b) ensured that local people were directly involved in Guyana's Low Carbon Development Strategy as part of REDD+. This is the first such comprehensive survey of carbon stocks, carbon density and vegetation types over a large area in Guyana, one of the first countries to develop such a program. The potential inclusion of forests held by indigenous peoples in REDD+ programs is a global issue: we clearly show that indigenous people are capable of assessing and monitoring carbon on their lands

Limited flexibility in departure timing of migratory passerines at the East-Mediterranean flyway

The rapid pace of current global warming lead to the advancement of spring migration in the majority of long-distance migratory bird species. While data on arrival timing to breeding grounds in Europe is plentiful, information from the African departure sites are scarce. Here we analysed changes in arrival timing at a stopover site in Israel and any links to Enhanced Vegetation Index (EVI) on the species-specific African non-breeding range in three migratory passerines between 2000–2017. Differences in wing length between early and late arriving individuals were also examined as a proxy for migration distance. We found that male redstart, but not females, advanced arrival to stopover site, but interestingly, not as a response to EVI phenology. Blackcap and barred warbler did not shift arrival timing significantly, although the arrival of blackcap was dependent on EVI. Barred warbler from the early arrival phase had longer wings, suggesting different populations. Our study further supports the existence species-specific migration decisions and inter-sexual differences, which may be triggered by both exogenous (local vegetation condition) and endogenous cues. Given rapid rate of changes in environmental conditions at higher latitudes, some migrants may experience difficulty in the race to match global changes to ensure their survival

A case of metastatic cancer with markedly elevated PSA level that was not detected by repeat prostate biopsy

BACKGROUND: Prostate-specific antigen (PSA) is a widely used specific tumor marker for prostate cancer. We experienced a case of metastatic prostate cancer that was difficult to detect by repeat prostate biopsy despite a markedly elevated serum PSA level. CASE PRESENTATION: A 64-year-old man was referred to our hospital with lumbar back pain and an elevated serum PSA level of 2036 ng/mL. Computed tomography, bone scintigraphy, and magnetic resonance imaging showed systemic lymph node and osteoblastic bone metastases. Digital rectal examination revealed a small, soft prostate without nodules. Ten-core transrectal prostate biopsy yielded negative results. Androgen deprivation therapy (ADT) was started because of the patient’s severe symptoms. Twelve-core repeat transrectal prostate biopsy performed 2 months later, and transurethral resection biopsy performed 5 months later, both yielded negative results. The patient refused further cancer screening because ADT effectively relieved his symptoms. His PSA level initially decreased to 4.8 ng/mL, but he developed castration-resistant prostate cancer 7 months after starting ADT. He died 21 months after the initial prostate biopsy from disseminated intravascular coagulation. CONCLUSION: CUP remains a considerable challenge in clinical oncology. Biopsies of metastatic lesions and multimodal approaches were helpful in this case

Implications of global environmental change for the burden of snakebite.

Snakebite envenoming is a set of intoxication diseases that disproportionately affect people of poor socioeconomic backgrounds in tropical countries. As it is highly dependent on the environment its burden is expected to shift spatially with global anthropogenic environmental (climate, land use) and demographic change. The mechanisms underlying the changes to snakebite epidemiology are related to factors of snakes and humans. The distribution and abundance of snakes are expected to change with global warming via their thermal tolerance, while rainfall may affect the timing of key activities like feeding and reproduction. Human population growth is the primary cause of land-use change, which may impact snakes at smaller spatial scales than climate via habitat and biodiversity loss (e.g. prey availability). Human populations, on the other hand, could experience novel patterns and morbidity of snakebite envenoming, both as a result of snake responses to environmental change and due to the development of agricultural adaptations to climate change, socioeconomic and cultural changes, development and availability of better antivenoms, personal protective equipment, and mechanization of agriculture that mediate risk of encounters with snakes and their outcomes. The likely global effects of environmental and demographic change are thus context-dependent and could encompass both increasing and or snakebite burden (incidence, number of cases or morbidity), exposing new populations to snakes in temperate areas due to "tropicalization", or by land use change-induced snake biodiversity loss, respectively. Tackling global change requires drastic measures to ensure large-scale ecosystem functionality. However, as ecosystems represent the main source of venomous snakes their conservation should be accompanied by comprehensive public health campaigns. The challenges associated with the joint efforts of biodiversity conservation and public health professionals should be considered in the global sustainability agenda in a wider context that applies to neglected tropical and zoonotic and emerging diseases

Preoperative Butyrylcholinesterase Level as an Independent Predictor of Overall Survival in Clear Cell Renal Cell Carcinoma Patients Treated with Nephrectomy

The prognostic factors for the overall survival (OS) of clear cell renal cell carcinoma (ccRCC) patients treated with nephrectomy are not well defined. In the present study, we investigated the prognostic significance of preoperative butyrylcholinesterase (BChE) levels in 400 ccRCC patients undergoing radical or partial nephrectomy from 1992 to 2013 at our institution. Univariate and multivariate analyses were performed to determine the clinical factors associated with OS. Among the enrolled patients, 302 were diagnosed with organ-confined disease only (T1-2N0M0), 16 with lymph node metastases, and 56 with distant metastases. The median preoperative BChE level was 250 U/L (normal range, 168–470 U/L), and median follow-up period was 36 months. The 3-year OS rate in patients with preoperative BChE levels of ≥100 U/L was significantly higher than in those with levels of <100 U/L (89.3% versus 77.7%, P=0.004). On univariate analysis, performance status; anemia; hypoalbuminemia; preoperative levels of BChE, corrected calcium, and C-reactive protein; and distant metastasis status were significantly associated with OS. Multivariate analysis revealed that preoperative BChE levels and distant metastasis status were significantly associated with OS. Our findings suggest a possible role of preoperative BChE levels as an independent predictor of OS after nephrectomy in ccRCC patients

A mechanistic model of snakebite as a zoonosis: Envenoming incidence is driven by snake ecology, socioeconomics and its impacts on snakes.

Snakebite is the only WHO-listed, not infectious neglected tropical disease (NTD), although its eco-epidemiology is similar to that of zoonotic infections: envenoming occurs after a vertebrate host contacts a human. Accordingly, snakebite risk represents the interaction between snake and human factors, but their quantification has been limited by data availability. Models of infectious disease transmission are instrumental for the mitigation of NTDs and zoonoses. Here, we represented snake-human interactions with disease transmission models to approximate geospatial estimates of snakebite incidence in Sri Lanka, a global hotspot. Snakebites and envenomings are described by the product of snake and human abundance, mirroring directly transmitted zoonoses. We found that human-snake contact rates vary according to land cover (surrogate of occupation and socioeconomic status), the impacts of humans and climate on snake abundance, and by snake species. Our findings show that modelling snakebite as zoonosis provides a mechanistic eco-epidemiological basis to understand snakebites, and the possible implications of global environmental and demographic change for the burden of snakebite

Effects of global change on snakebite envenoming incidence up to 2050: a modelling assessment

Background Human activities are driving climate, land cover, and population change (global change), and shifting the baseline geographical distribution of snakebite. The interacting effects of global change on snakes and communities at risk of snakebite are poorly understood, limiting capacity to anticipate and manage future changes in snakebite risk. Methods In this modelling study, we projected how global change will affect snakebite envenoming incidence in Sri Lanka, as a model system that has a high incidence of snakebite. We used the shared socioeconomic pathway (SSP) scenario analysis framework to integrate forecasts across the domains of: climate change (historical trend from WorldClim plus three underlying regional circulation models [RCMs] in the Coordinated Regional Downscaling Experiment-South Asia repository, with two emissions pathways [representative concentration pathways RCP4.5 and RCP8.5]); land cover change (Dyna-CLUE model); and human population density change (based on Gridded Population of the World data) from Jan 1, 2010 to Dec 31, 2050. Forecasts were integrated under three different development scenarios: a sustainability pathway (SSP1 and no further emissions), a middle-of-the-road pathway (SSP2 and RCP4.5), and a fossil-fuelled pathway (SSP5 and RCP8.5). For SSP2 and SSP5, we nested three different RCMs (CNRM-CM5, GFDL-CCM3, and MPI-ESM-LR; mean averaged to represent consensus) to account for variability in climate predictions. Data were used as inputs to a mechanistic model that predicted snakebite envenoming incidence based on human–snake contact patterns. Findings From 2010 to 2050, at the national level, envenoming incidence in Sri Lanka was projected to decrease by 12·0–23·0%, depending on the scenario. The rate of decrease in envenoming incidence was higher in SSP5-RCP8.5 than in SSP1 and SSP2-RCP4.5. Change in envenoming incidence was heterogenous across the country. In SSP1, incidence decreased in urban areas expected to have population growth, and with land cover changes towards anthropised classes. In SSP2-RCP4.5 and SSP5-RCP8.5, most areas were projected to have decreases in incidence (SSP5-RCP8.5 showing the largest area with incidence reductions), while areas such as the central highlands and the north of the country showed localised increases. In the model, decreases occurred with human population growth, land use change towards anthropised classes (potentially shifting occupational risk factors), and decreasing abundance of some snake species, potentially due to global warming and reduced climatic and habitat suitability, with displacement of some snake species. Interpretation Snakebite envenoming incidence was projected to decrease overall in the coming decades in Sri Lanka, but with an apparent emerging conflict with sustainability objectives. Therefore, efforts to mitigate snakebite envenoming incidence will need to consider the potential impacts of sustainability interventions, particularly related to climate and land use change and in areas where increases in incidence are projected. In view of global change, neglected tropical diseases and public health issues related to biodiversity, such as snakebite, should be managed collaboratively by both environment and health stakeholders

Integrating human behavior and snake ecology with agent-based models to predict snakebite in high risk landscapes.

Snakebite causes more than 1.8 million envenoming cases annually and is a major cause of death in the tropics especially for poor farmers. While both social and ecological factors influence the chance encounter between snakes and people, the spatio-temporal processes underlying snakebites remain poorly explored. Previous research has focused on statistical correlates between snakebites and ecological, sociological, or environmental factors, but the human and snake behavioral patterns that drive the spatio-temporal process have not yet been integrated into a single model. Here we use a bottom-up simulation approach using agent-based modelling (ABM) parameterized with datasets from Sri Lanka, a snakebite hotspot, to characterise the mechanisms of snakebite and identify risk factors. Spatio-temporal dynamics of snakebite risks are examined through the model incorporating six snake species and three farmer types (rice, tea, and rubber). We find that snakebites are mainly climatically driven, but the risks also depend on farmer types due to working schedules as well as species present in landscapes. Snake species are differentiated by both distribution and by habitat preference, and farmers are differentiated by working patterns that are climatically driven, and the combination of these factors leads to unique encounter rates for different landcover types as well as locations. Validation using epidemiological studies demonstrated that our model can explain observed patterns, including temporal patterns of snakebite incidence, and relative contribution of bites by each snake species. Our predictions can be used to generate hypotheses and inform future studies and decision makers. Additionally, our model is transferable to other locations with high snakebite burden as well