ResearchPad - surface-temperature Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Why do biting horseflies prefer warmer hosts? tabanids can escape easier from warmer targets]]> Blood-sucking horseflies (tabanids) prefer warmer (sunlit, darker) host animals and generally attack them in sunshine, the reason for which was unknown until now. Recently, it was hypothesized that blood-seeking female tabanids prefer elevated temperatures, because their wing muscles are quicker and their nervous system functions better at a warmer body temperature brought about by warmer microclimate, and thus they can more successfully avoid the host’s parasite-repelling reactions by prompt takeoffs. To test this hypothesis, we studied in field experiments the success rate of escape reactions of tabanids that landed on black targets as a function of the target temperature, and measured the surface temperature of differently coloured horses with thermography. We found that the escape success of tabanids decreased with decreasing target temperature, that is escape success is driven by temperature. Our results explain the behaviour of biting horseflies that they prefer warmer hosts against colder ones. Since in sunshine the darker the host the warmer its body surface, our results also explain why horseflies prefer sunlit dark (brown, black) hosts against bright (beige, white) ones, and why these parasites attack their hosts usually in sunshine, rather than under shaded conditions.

<![CDATA[Effect of internal surface structure of the north wall on Chinese solar greenhouse thermal microclimate based on computational fluid dynamics]]>

Chinese solar greenhouses are unique facility agriculture buildings and widely used in northeastern China, providing a favorable requirement for crop growth. The north wall configurations play an essential role in heat storage and thermal insulation and directly affect the management of the internal environment. This research is devoted to further improve the thermal performance of the greenhouse and explore the potential of the north wall. A mathematical model was designed to investigate the concave-convex wall configurations based on computational fluid dynamics. Four passive heat-storage north walls were analyzed by using the same constituent materials, including a plane wall, a vertical wall, a horizontal wall and an alveolate wall. The numerical model was validated by experimental measurements. The temperature distributions of the north walls were examined and a comparative analysis of the heat storage-release capabilities was carried out. The results showed that the heat-storage capacity of the north wall is affected by the surface structure. Moreover, the critical factor influencing the air temperature is the sum of the heat load released by the wall and the energy increment of greenhouse air. The results suggested that the alveolate wall has preferable thermal accumulation capacity. The concave-convex wall configurations have a wider range of heat transfer performance along the thickness direction, while the plane wall has a superior thermal environment. This study provides a basic theoretical reference to rationally design the internal surface structures of the north wall.

<![CDATA[A low-cost, autonomous mobile platform for limnological investigations, supported by high-resolution mesoscale airborne imagery]]>

Two complementary measurement systems—built upon an autonomous floating craft and a tethered balloon—for lake research and monitoring are presented. The autonomous vehicle was assembled on a catamaran for stability, and is capable of handling a variety of instrumentation for in situ and near-surface measurements. The catamaran hulls, each equipped with a small electric motor, support rigid decks for arranging equipment. An electric generator provides full autonomy for about 8 h. The modular power supply and instrumentation data management systems are housed in two boxes, which enable rapid setup. Due to legal restrictions in Switzerland (where the craft is routinely used), the platform must be observed from an accompanying boat while in operation. Nevertheless, the control system permits fully autonomous operation, with motion controlled by speed settings and waypoints, as well as obstacle detection. On-board instrumentation is connected to a central hub for data storage, with real-time monitoring of measurements from the accompanying boat. Measurements from the floating platform are complemented by mesoscale imaging from an instrument package attached to a He-filled balloon. The aerial package records thermal and RGB imagery, and transmits it in real-time to a ground station. The balloon can be tethered to the autonomous catamaran or to the accompanying boat. Missions can be modified according to imagery and/or catamaran measurements. Illustrative results showing the surface thermal variations of Lake Geneva demonstrate the versatility of the combined floating platform/balloon imagery system setup for limnological investigations.

<![CDATA[Systematically false positives in early warning signal analysis]]>

Many systems in various scientific fields like medicine, ecology, economics or climate science exhibit so-called critical transitions, through which a system abruptly changes from one state to a different state. Typical examples are epileptic seizures, changes in the climate system or catastrophic shifts in ecosystems. In order to predict imminent critical transitions, a mathematical apparatus called early warning signals has been developed and this method is used successfully in many scientific areas. However, not all critical transitions can be detected by this approach (false negative) and the appearance of early warning signals does not necessarily proof that a critical transition is imminent (false positive). Furthermore, there are whole classes of systems that always show early warning signals, even though they do not feature critical transitions. In this study we identify such classes in order to provide a safeguard against a misinterpretation of the results of an early warning signal analysis of such systems. Furthermore, we discuss strategies to avoid such systematic false positives and test our theoretical insights by applying them to real world data.

<![CDATA[Warming seas increase cold-stunning events for Kemp’s ridley sea turtles in the northwest Atlantic]]>

Since the 1970s, the magnitude of turtle cold-stun strandings have increased dramatically within the northwestern Atlantic. Here, we examine oceanic, atmospheric, and biological factors that may affect the increasing trend of cold-stunned Kemp’s ridleys in Cape Cod Bay, Massachusetts, United States of America. Using machine learning and Bayesian inference modeling techniques, we demonstrate higher cold-stunning years occur when the Gulf of Maine has warmer sea surface temperatures in late October through early November. Surprisingly, hatchling numbers in Mexico, a proxy for population abundance, was not identified as an important factor. Further, using our Bayesian count model and forecasted sea surface temperature projections, we predict more than 2,300 Kemp’s ridley turtles may cold-stun annually by 2031 as sea surface temperatures continue to increase within the Gulf of Maine. We suggest warmer sea surface temperatures may have modified the northerly distribution of Kemp’s ridleys and act as an ecological bridge between the Gulf Stream and nearshore waters. While cold-stunning may currently account for a minor proportion of juvenile mortality, we recommend continuing efforts to rehabilitate cold-stunned individuals to maintain population resiliency for this critically endangered species in the face of a changing climate and continuing anthropogenic threats.

<![CDATA[Satellite image fusion to detect changing surface permeability and emerging urban heat islands in a fast-growing city]]>

Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of Urban Heat Islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they mostly involve time consuming and expensive field studies and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and temperature and UHI emergence in a fast growing city, i.e. Tirunelveli, Tamilnadu, India. IRS-LISSIII and Landsat-7 ETM+ imageries were fused for 2007 and 2017, and classified using a Rotation Forest (RF) algorithm. Surface permeability and temperature were then quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Finally, we assessed the relationship between SAVI and LST for entire Tirunelveli as well as for each LULC zone, and also detected UHI emergence hot spots using a SAVI-LST combined metric. Our fused images exhibited higher classification accuracies, i.e. overall kappa coefficient values, than non-fused images. We observed an overall increase in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall and also for almost all LULC zones. The LST values showed an overall increase of surface temperature in Tirunelveli with the highest increase for urban built-up areas between 2007 and 2017. LST also exhibited a strong negative association with SAVI. Southeastern built-up areas in Tirunelveli were depicted as a potential UHI hotspot, with a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability, temperature and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.

<![CDATA[Experimental study on frost-formation characteristics on cold surface of arched copper sample]]>

The present work investigates the process of frosting formation on arched copper samples with different surface temperatures, calculated the thickness of the frost layer by using the scale method, and analyzed frost lodging, melting, and other phenomena that appeared during the frost-formation process. The results showed that the frosting process on an arched surface can be divided into ice-film formation, rapid growth of the frost layer, and stable growth of the frost layer. Meanwhile, the phenomena of frost-branch breakage, lodging, and melting were observed. The surface temperature had a large effect on the frost formation and thickness of the frost layer, e.g., the formation time of the ice film on a surface at -5°C was the longest (~135 s), the frost layer formed on a surface at -20°C was the thickest (~660 μm). When microscopic observation of the frosting process was accompanied by calculation of the frost-layer thickness, it could be seen that the appearance of the frost branches was affected by the different thermal conductivities of the frost layers, undulating surface of the ice film, and temperature difference between the layers. The changes in the frost branches and the soft surface of the frost layer also affected the growth of the frost layer. The findings of this study are expected to provide guidelines for optimization of conventional defrosting methods.

<![CDATA[Impacts of El Niño-Southern Oscillation on the wheat market: A global dynamic analysis]]>

Although the widespread influence of the El Niño-Southern Oscillation (ENSO) occurrences on crop yields of the main agricultural commodities is well known, the global socio-economic consequences of ENSO still remain uncertain. Given the global importance of wheat for global consumption by providing 20% of global calories and nourishment, the monitoring and prediction of ENSO-induced variations in the worldwide wheat market are essential for allowing national governments to manage the associated risks and to ensure the supplies of wheat for consumers, including the underprivileged. To this end, we propose a global dynamic model for the analysis of ENSO impacts on wheat yield anomalies, export prices, exports and stock-to-use ratios. Our framework focuses on seven countries/regions: the six main wheat-exporting countries—the United States, Argentina, Australia, Canada, the EU, and the group of the main Black Sea export countries, i.e. Russia, Ukraine, and Kazakhstan—plus the rest of the world. The study shows that La Niña exerts, on average, a stronger and negative impact on wheat yield anomalies, exports and stock-to-use ratios than El Niño. In contrast, wheat export prices are positively related to La Niña occurrences evidencing, once again, its steady impact in both the short and long run. Our findings emphasize the importance of the two ENSO extreme phases for the worldwide wheat market.

<![CDATA[Do the Brazilian sardine commercial landings respond to local ocean circulation?]]>

It has been reported that sea surface temperature (SST) anomalies, flow intensity and mesoscale ocean processes, all affect sardine production, both in eastern and western boundary current systems. Here we tested the hypothesis whether extreme high and low commercial landings of the Brazilian sardine fisheries in the South Brazil Bight (SBB) are sensitive to different oceanic conditions. An ocean model (ROMS) and an individual based model (Ichthyop) were used to assess the relationship between oceanic conditions during the spawning season and commercial landings of the Brazilian sardine one year later. Model output was compared with remote sensing and analysis data showing good consistency. Simulations indicate that mortality of eggs and larvae by low temperature prior to maximum and minimum landings are significantly higher than mortality caused by offshore advection. However, when periods of maximum and minimum sardine landings are compared with respect to these causes of mortality no significant differences were detected. Results indicate that mortality caused by prevailing oceanic conditions at early life stages alone can not be invoked to explain the observed extreme commercial landings of the Brazilian sardine. Likely influencing factors include starvation and predation interacting with the strategy of spawning “at the right place and at the right time”.

<![CDATA[Geostatistical modelling of malaria indicator survey data to assess the effects of interventions on the geographical distribution of malaria prevalence in children less than 5 years in Uganda]]>


Malaria burden in Uganda has declined disproportionately among regions despite overall high intervention coverage across all regions. The Uganda Malaria Indicator Survey (MIS) 2014–15 was the second nationally representative survey conducted to provide estimates of malaria prevalence among children less than 5 years, and to track the progress of control interventions in the country. In this present study, 2014–15 MIS data were analysed to assess intervention effects on malaria prevalence in Uganda among children less than 5 years, assess intervention effects at regional level, and estimate geographical distribution of malaria prevalence in the country.


Bayesian geostatistical models with spatially varying coefficients were used to determine the effect of interventions on malaria prevalence at national and regional levels. Spike-and-slab variable selection was used to identify the most important predictors and forms. Bayesian kriging was used to predict malaria prevalence at unsampled locations.


Indoor Residual Spraying (IRS) and Insecticide Treated Nets (ITN) ownership had a significant but varying protective effect on malaria prevalence. However, no effect was observed for Artemisinin Combination-based Therapies (ACTs). Environmental factors, namely, land cover, rainfall, day and night land surface temperature, and area type were significantly associated with malaria prevalence. Malaria prevalence was higher in rural areas, increased with the child’s age, and decreased with higher household socioeconomic status and higher level of mother’s education. The highest prevalence of malaria in children less than 5 years was predicted for regions of East Central, North East and West Nile, whereas the lowest was predicted in Kampala and South Western regions, and in the mountainous areas in Mid-Western and Mid-Eastern regions.


IRS and ITN ownership are important interventions against malaria prevalence in children less than 5 years in Uganda. The varying effects of the interventions calls for selective implementation of control tools suitable to regional ecological settings. To further reduce malaria burden and sustain malaria control in Uganda, current tools should be supplemented by health system strengthening, and socio-economic development.

<![CDATA[A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile]]>

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making.

<![CDATA[Automated measurement of cattle surface temperature and its correlation with rectal temperature]]>

The body temperature of cattle varies regularly with both the reproductive cycle and disease status. Establishing an automatic method for monitoring body temperature may facilitate better management of reproduction and disease control in cattle. Here, we developed an Automatic Measurement System for Cattle’s Surface Temperature (AMSCST) to measure the temperature of metatarsus by attaching a special shell designed to fit the anatomy of cattle’s hind leg. Using AMSCST, the surface temperature (ST) on the metatarsus of the hind leg was successively measured during 24 hours a day with an interval of one hour in three tested seasons. Based on ST and rectal temperature (RT) detected by AMSCST and mercury thermometer, respectively, a linear mixed model was established, regarding both the time point and seasonal factors as the fixed effects. Unary linear correlation and Bland-Altman analysis results indicated that the temperatures measured by AMSCST were closely correlated to those measured by mercury thermometer (R2 = 0.998), suggesting that the AMSCST is an accurate and reliable way to detect cattle’s body temperature. Statistical analysis showed that the differences of STs among the three seasons, or among the different time points were significant (P<0.05), and the differences of RTs among the different time points were similarly significant (P<0.05). The prediction accuracy of the mixed model was verified by 10-fold cross validation. The average difference between measured RT and predicted RT was about 0.10 ± 0.10°C with the association coefficient of 0.644, indicating the feasibility of this model in measuring cattle body temperature. Therefore, an automated technology for accurately measuring cattle body temperature was accomplished by inventing an optimal device and establishing the AMSCST system.

<![CDATA[On the Challenge of Interpreting Census Data: Insights from a Study of an Endangered Pinniped]]>

Population monitoring is vital for conservation and management. However, simple counts of animals can be misleading and this problem is exacerbated in seals (pinnipeds) where individuals spend much time foraging away from colonies. We analyzed a 13-year-series of census data of Galapagos sea lions (Zalophus wollebaeki) from the colony of Caamaño, an islet in the center of the Galapagos archipelago where a large proportion of animals was individually marked. Based on regular resighting efforts during the cold, reproductive (cold-R; August to January) and the warm, non-reproductive (warm-nR; February to May) season, we document changes in numbers for different sex and age classes. During the cold-R season the number of adults increased as the number of newborn pups increased. Numbers were larger in the morning and evening than around mid-day and not significantly influenced by tide levels. More adults frequented the colony during the warm-nR season than the cold-R season. Raw counts suggested a decline in numbers over the 13 years, but Lincoln-Petersen (LP-) estimates (assuming a closed population) did not support that conclusion. Raw counts and LP estimates were not significantly correlated, demonstrating the overwhelming importance of variability in attendance patterns of individuals. The probability of observing a given adult in the colony varied between 16% (mean for cold-R season) and 23% (warm-nR season) and may be much less for independent 2 to 4 year olds. Dependent juveniles (up to the age of about 2 years) are observed much more frequently ashore (35% during the cold-R and 50% during the warm-nR seasons). Simple counts underestimate real population size by a factor of 4–6 and may lead to erroneous conclusions about trends in population size.

<![CDATA[Bayesian Space-Time Patterns and Climatic Determinants of Bovine Anaplasmosis]]>

The space-time pattern and environmental drivers (land cover, climate) of bovine anaplasmosis in the Midwestern state of Kansas was retrospectively evaluated using Bayesian hierarchical spatio-temporal models and publicly available, remotely-sensed environmental covariate information. Cases of bovine anaplasmosis positively diagnosed at Kansas State Veterinary Diagnostic Laboratory (n = 478) between years 2005–2013 were used to construct the models, which included random effects for space, time and space-time interaction effects with defined priors, and fixed-effect covariates selected a priori using an univariate screening procedure. The Bayesian posterior median and 95% credible intervals for the space-time interaction term in the best-fitting covariate model indicated a steady progression of bovine anaplasmosis over time and geographic area in the state. Posterior median estimates and 95% credible intervals derived for covariates in the final covariate model indicated land surface temperature (minimum), relative humidity and diurnal temperature range to be important risk factors for bovine anaplasmosis in the study. The model performance measured using the Area Under the Curve (AUC) value indicated a good performance for the covariate model (> 0.7). The relevance of climatological factors for bovine anaplasmosis is discussed.

<![CDATA[Incubation Temperature during Fetal Development Influences Morphophysiological Characteristics and Preferred Ambient Temperature of Chicken Hatchlings]]>

Skin and feather characteristics, which play a critical role in body temperature maintenance, can be affected by incubation circumstances, such as incubation temperature. However, no study to date has assessed the influence of incubation temperature during the fetal stage on morphometric characteristics and vascular development of the skin, feather characteristics, and their relationship to hormone levels and preferred temperature in later life in chickens. Broiler breeder eggs were exposed to low (36°C), control (37.5°C), or high (39°C) temperatures (treatments LT, CK, and HT, respectively) from day 13 of incubation onward, because it is known that the endocrine axes are already established at this time. During this period, eggshell temperature of HT eggs (38.8±0.33°C) was higher than of LT (37.4±0.08°C) and CK eggs (37.8 ±0.15°C). The difference between eggshell and incubator air temperature diminished with the increasing incubation temperature, and was approximately zero for HT. HT hatchlings had higher surface temperature on the head, neck, and back, and thinner and more vascularized skin than did CK and LT hatchlings. No differences were found among treatments for body weight, total feather weight, number and length of barbs, barbule length, and plasma T4 concentration. LT hatchlings showed lower plasma T3 and GH, as well as lower T3/T4 ratio and decreased vascularity in the neck, back, and thigh skin compared to CK hatchlings. On the other hand, HT hatchlings had decreased skin thickness and increased vascularity, and preferred a higher ambient temperature compared to CK and HT hatchlings. In addition, for all treatments, surface temperature on the head was higher than of the other body regions. We conclude that changes in skin thickness and vascularity, as well as changes in thyroid and growth hormone levels, are the result of embryonic strategies to cope with higher or lower than normal incubation temperatures. Additionally exposure to increased temperature during incubation is an environmental factor that can exert early-life influence on ambient temperature preference of broiler hatchlings in later life.

<![CDATA[A New Model for Temperature Jump at a Fluid-Solid Interface]]>

The problem presented involves the development of a new analytical model for the general fluid-solid temperature jump. To the best of our knowledge, there are no analytical models that provide the accurate predictions of the temperature jump for both gas and liquid systems. In this paper, a unified model for the fluid-solid temperature jump has been developed based on our adsorption model of the interfacial interactions. Results obtained from this model are validated with available results from the literature.

<![CDATA[Alteration of stream temperature by natural and artificial beaver dams]]>

Beaver are an integral component of hydrologic, geomorphic, and biotic processes within North American stream systems, and their propensity to build dams alters stream and riparian structure and function to the benefit of many aquatic and terrestrial species. Recognizing this, beaver relocation efforts and/or application of structures designed to mimic the function of beaver dams are increasingly being utilized as effective and cost-efficient stream and riparian restoration approaches. Despite these verities, the notion that beaver dams negatively impact stream habitat remains common, specifically the assumption that beaver dams increase stream temperatures during summer to the detriment of sensitive biota such as salmonids. In this study, we tracked beaver dam distributions and monitored water temperature throughout 34 km of stream for an eight-year period between 2007 and 2014. During this time the number of natural beaver dams within the study area increased by an order of magnitude, and an additional 4 km of stream were subject to a restoration manipulation that included installing a high-density of Beaver Dam Analog (BDA) structures designed to mimic the function of natural beaver dams. Our observations reveal several mechanisms by which beaver dam development may influence stream temperature regimes; including longitudinal buffering of diel summer temperature extrema at the reach scale due to increased surface water storage, and creation of cool—water channel scale temperature refugia through enhanced groundwater—surface water connectivity. Our results suggest that creation of natural and/or artificial beaver dams could be used to mitigate the impact of human induced thermal degradation that may threaten sensitive species.

<![CDATA[Long-Range Correlations of Global Sea Surface Temperature]]>

Scaling behaviors of the global monthly sea surface temperature (SST) derived from 1870–2009 average monthly data sets of Hadley Centre Sea Ice and SST (HadISST) are investigated employing detrended fluctuation analysis (DFA). The global SST fluctuations are found to be strong positively long-range correlated at all pertinent time-intervals. The value of scaling exponent is larger in the tropics than those in the intermediate latitudes of the northern and southern hemispheres. DFA leads to the scaling exponent α = 0.87 over the globe (60°S~60°N), northern hemisphere (0°N~60°N), and southern hemisphere (0°S~60°S), α = 0.84 over the intermediate latitude of southern hemisphere (30°S~60°S), α = 0.81 over the intermediate latitude of northern hemisphere (30°N~60°N) and α = 0.90 over the tropics 30°S~30°N [fluctuation F(s) ~ sα], which the fluctuations of monthly SST anomaly display long-term correlated behaviors. Furthermore, the larger the standard deviation is, the smaller long-range correlations (LRCs) of SST in the corresponding regions, especially in three distinct upwelling areas. After the standard deviation is taken into account, an index χ = α * σ is introduced to obtain the spatial distributions of χ. There exists an obvious change of global SST in central east and northern Pacific and the northwest Atlantic. This may be as a clue on predictability of climate and ocean variabilities.

<![CDATA[Foraging Behavior of Subantarctic Fur Seals Supports Efficiency of a Marine Reserve’s Design]]>

Foraging behaviour of marine top predators is increasingly being used to identify areas of ecological importance. This is largely enabled by the ability of many such species to forage extensively in search of prey that is often concentrated in oceanographically productive areas. To identify important habitat in the Southern Indian Ocean within and around South Africa’s Prince Edward Islands’ Marine Protected Area (MPA), satellite transmitters were deployed on 12 lactating Subantarctic fur seals Arctocephalus tropicalis at Prince Edward Island (PEI) itself. Switching state space models were employed to correct ARGOS tracks and estimate behavioural states for locations along predicted tracks, namely travelling or area restricted search (ARS). A random forest model showed that distance from the study colony, longitude and distance from the Subantarctic Front were the most important predictors of suitable foraging habitat (inferred from ARS). Model-predicted suitable habitat occurred within the MPA in relatively close access to the colony during summer and autumn, but shifted northwards concurrently with frontal movements in winter and spring. The association of ARS with the MPA during summer-autumn was highly significant, highlighting the effectiveness of the recently declared reserve’s design for capturing suitable foraging habitat for this and probably other marine top predator species.

<![CDATA[Coral Reefs and People in a High-CO2 World: Where Can Science Make a Difference to People?]]>

Reefs and People at Risk

Increasing levels of carbon dioxide in the atmosphere put shallow, warm-water coral reef ecosystems, and the people who depend upon them at risk from two key global environmental stresses: 1) elevated sea surface temperature (that can cause coral bleaching and related mortality), and 2) ocean acidification. These global stressors: cannot be avoided by local management, compound local stressors, and hasten the loss of ecosystem services. Impacts to people will be most grave where a) human dependence on coral reef ecosystems is high, b) sea surface temperature reaches critical levels soonest, and c) ocean acidification levels are most severe. Where these elements align, swift action will be needed to protect people’s lives and livelihoods, but such action must be informed by data and science.

An Indicator Approach

Designing policies to offset potential harm to coral reef ecosystems and people requires a better understanding of where CO2-related global environmental stresses could cause the most severe impacts. Mapping indicators has been proposed as a way of combining natural and social science data to identify policy actions even when the needed science is relatively nascent. To identify where people are at risk and where more science is needed, we map indicators of biological, physical and social science factors to understand how human dependence on coral reef ecosystems will be affected by globally-driven threats to corals expected in a high-CO2 world. Western Mexico, Micronesia, Indonesia and parts of Australia have high human dependence and will likely face severe combined threats. As a region, Southeast Asia is particularly at risk. Many of the countries most dependent upon coral reef ecosystems are places for which we have the least robust data on ocean acidification. These areas require new data and interdisciplinary scientific research to help coral reef-dependent human communities better prepare for a high CO2 world.