Emergence potential of mosquito-borne arboviruses from the Florida Everglades

The Greater Everglades Region of South Florida is one of the largest natural wetlands and the only subtropical ecosystem found in the continental United States. Mosquitoes are seasonally abundant in the Everglades where several potentially pathogenic mosquito-borne arboviruses are maintained in natural transmission cycles involving vector-competent mosquitoes and reservoir-competent vertebrate hosts. The fragile nature of this ecosystem is vulnerable to many sources of environmental change, including a wetlands restoration project, climate change, invasive species and residential development. In this study, we obtained baseline data on the distribution and abundance of both mosquitos and arboviruses occurring in the southern Everglades region during the summer months of 2013, when water levels were high, and in 2014, when water levels were low. A total of 367,060 mosquitoes were collected with CO2-baited CDC light traps at 105 collection sites stratified among the major landscape features found in Everglades National Park, Big Cypress National Preserve, Fakahatchee State Park Preserve and Picayune State Forest, an area already undergoing restoration. A total of 2,010 pools of taxonomically identified mosquitoes were cultured for arbovirus isolation and identification. Seven vertebrate arboviruses were isolated: Everglades virus, Tensaw virus, Shark River virus, Gumbo Limbo virus, Mahogany Hammock virus, Keystone virus, and St. Louis encephalitis virus. Except for Tensaw virus, which was absent in 2013, the remaining viruses were found to be most prevalent in hardwood hammocks and in Fakahatchee, less prevalent in mangroves and pinelands, and absent in cypress and sawgrass. In contrast, in the summer of 2014 when water levels were lower, these arboviruses were far less prevalent and only found in hardwood hammocks, but Tensaw virus was present in cypress, sawgrass, pinelands, and a recently burned site. Major environmental changes are anticipated in the Everglades, many of which will result in increased water levels. How these might lead to the emergence of arboviruses potentially pathogenic to both humans and wildlife is discussed.

Reproducing complex simulations of economic impacts of climate change with lower-cost emulators

Process-based models are powerful tools for simulating the economic impacts of climate change, but they are computationally expensive. In order to project climate-change impacts under various scenarios, produce probabilistic ensembles, conduct online coupled simulations, or explore pathways by numerical optimization, the computational and implementation cost of economic impact calculations should be reduced. To do so, in this study, we developed various emulators that mimic the behaviours of simulation models, namely economic models coupled with bio/physical-process-based impact models, by statistical regression techniques. Their performance was evaluated for multiple sectors and regions. Among the tested emulators, those composed of artificial neural networks, which can incorporate non-linearities and interactions between variables, performed better particularly when finer input variables were available. Although simple functional forms were effective for approximating general tendencies, complex emulators are necessary if the focus is regional or sectoral heterogeneity. Since the computational cost of the developed emulators is sufficiently small, they could be used to explore future scenarios related to climate-change policies. The findings of this study could also help researchers design their own emulators in different situations.

Reproducing complex simulations of economic impacts of climate change with lower-cost emulators

In order to project climate-change impacts under a wide-range of scenarios or conduct on-line coupled simulations, the computational and implementation cost of economic impact calculations should be reduced. To do so, in this study, we developed various emulators that mimic simulation outputs, namely economic models coupled with bio/physical process-based impact models. Their performance was evaluated for multiple sectors and regions. Among the tested emulators, those composed of artificial neural networks, which can incorporate nonlinearities and interactions between variables, performed better particularly when finer input variables were available. Although simple functional forms were effective for approximating general tendencies, complex emulators are necessary if the focus is regional or sectoral heterogeneity. The developed emulators could be used to explore future scenarios related to climate-change policies, and the findings of this study could also help researchers design their own emulators under different situations.

Warming temperatures could expose more than 1.3 billion new people to Zika virus risk by 2050

In the aftermath of the 2015 pandemic of Zika virus, concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we use a model of thermal bounds on Zika virus (ZIKV) transmission to project climate change impacts on transmission suitability risk by mid-century (a generation into the future). In the worst-case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.Author SummaryFirst discovered in Uganda in the 1950s, Zika virus (ZIKV) is a new threat to global health security. The virus is spread primarily by female Aedes mosquitoes, with occasional sexual transmission in humans, and can cause Zika congenital syndrome (which includes fetal abnormalities like microcephaly) when women are infected during pregnancy. Our study is the first to quantify how many people may be exposed to temperatures suitable for ZIKV transmission in a changing climate. In the worst-case scenario, by 2050, climate change could expose more than 1.3 billion people worldwide to temperatures suitable for transmission - for the first time. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people.

Perimeter Entropy and its Application to Climate Change

Periphery phenomenon and its theory are introduced briefly; herein perimeter set is defined; and perimeter entropy is presented mathematically. By using precipitation and evaporation data over the middle and lower reaches of the Yangtze River, the perimeter entropy was computed. Analysis points out that with perimeter entropy study one can project climate change in advance

The CAVEheAT project: climate change, thermal niche and conservation of subterranean biodiversity

One of the main challenges in disciplines such as ecology, biogeography, conservation and evolutionary biology is to understand and predict how species will respond to environmental changes, especially within a climate change context. We focus on the deep subterranean environment to minimize uncertainties in predictions, because it is one of the few ecosystems in nature whose environmental conditions are as homogeneous as those in the laboratory and their species cannot accommodate to changing conditions by behavioural plasticity, dispersal or microhabitat use (i.e., their only possibility to cope with climate change is to persist in situ). The hypotheses established for this project are based on the exciting results obtained in some of our previous studies, in which, we found that different subterranean beetle species living under different environmental conditions have identical/similar narrow thermal tolerance ranges, suggesting a lack of evolutionary adjustment to ambient temperature for these species. This could be due to the loss of some of the physiological mechanisms related to thermal tolerance, with a likely high metabolic cost, in a stable environment but with severe resource restrictions. However, the question that remains is to what extent this surprising narrow and homogeneous thermal niche is common for the whole subterranean biodiversity, and how this issue could determine the fate of subterranean biodiversity to climate change. In this project, we are testing for the generality of these exciting previous findings by studying the thermal niche (species acclimation abilities and thermal tolerances) of different lineages of cave beetles with different degrees of specialization to subterranean environments and from different geographical areas (Pyrenees and Cantabrian Mountains) (Suppl. material 1).

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

The quantification of climate change impacts on several human activities depends on reliable weather data series, without gaps and long enough to build up future climate. Based on that, this study aimed to evaluate the performance of temperature-based models for estimating global solar radiation and gridded databases (AgCFSR, AgMERRA, NASA/POWER, and XAVIER) as alternative ways for filling gaps in historical weather series (1980–2009) in Brazil and to project climate change scenarios based on measured and gridded weather data. Projections for mid- and end-of-century periods (2040–2069 and 2070–2099), using seven global climate models from CMIP5 under intermediate (RCP4.5) and high (RCP8.5) emission scenarios, were performed. The Bristow–Campbell model was the one that best estimated solar radiation, whereas the XAVIER gridded database was the closest to observed weather data. Future climate projections, under RCP4.5 and RCP8.5 scenarios, as expected, showed warmer conditions for all scenarios over Brazil. On the contrary, rainfall projections are more uncertain. Despite that, the rainfall amounts will be reduced in the North-Northeast region and increased in Southern Brazil. No significant differences between projections using the observed and XAVIER gridded database were observed; therefore, such a database showed to be reliable for both to fill gaps and to generate climate change scenarios.

Inaction on climate change projected to reduce European life expectancy

Climate change-related excess mortality estimates clearly demonstrate a dramatic impact on public health and human mortality. However, life expectancy at birth is more easily communicated and understood by the public. By properly situating climate change mortality within the contexts of life expectancy, we better represent the cost of climate change on longevity. In this paper, we convert excess mortality estimates due to increases in extreme weather from climate change into potential reductions in life expectancy at birth in thirty-one European countries. We project climate change extremes to reduce life expectancy at birth by 0.24 years for the average European country with differences in excess of 1.0 years in some countries by the end of the century. We only estimate the impact of mortality directly related to climate extremes, making our estimates conservative. Thus, the cost of inaction on climate change could approach, and likely to exceed, one year of life in some European countries.