Climates Past, Present, and Yet-to-Come Shape Climate Change Vulnerabilities.
Nadeau, Christopher P; Urban, Mark C; Bridle, Jon R
2017-10-01
Climate change is altering life at multiple scales, from genes to ecosystems. Predicting the vulnerability of populations to climate change is crucial to mitigate negative impacts. We suggest that regional patterns of spatial and temporal climatic variation scaled to the traits of an organism can predict where and why populations are most vulnerable to climate change. Specifically, historical climatic variation affects the sensitivity and response capacity of populations to climate change by shaping traits and the genetic variation in those traits. Present and future climatic variation can affect both climate change exposure and population responses. We provide seven predictions for how climatic variation might affect the vulnerability of populations to climate change and suggest key directions for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.
Phylogenetic approaches reveal biodiversity threats under climate change
NASA Astrophysics Data System (ADS)
González-Orozco, Carlos E.; Pollock, Laura J.; Thornhill, Andrew H.; Mishler, Brent D.; Knerr, Nunzio; Laffan, Shawn W.; Miller, Joseph T.; Rosauer, Dan F.; Faith, Daniel P.; Nipperess, David A.; Kujala, Heini; Linke, Simon; Butt, Nathalie; Külheim, Carsten; Crisp, Michael D.; Gruber, Bernd
2016-12-01
Predicting the consequences of climate change for biodiversity is critical to conservation efforts. Extensive range losses have been predicted for thousands of individual species, but less is known about how climate change might impact whole clades and landscape-scale patterns of biodiversity. Here, we show that climate change scenarios imply significant changes in phylogenetic diversity and phylogenetic endemism at a continental scale in Australia using the hyper-diverse clade of eucalypts. We predict that within the next 60 years the vast majority of species distributions (91%) across Australia will shrink in size (on average by 51%) and shift south on the basis of projected suitable climatic space. Geographic areas currently with high phylogenetic diversity and endemism are predicted to change substantially in future climate scenarios. Approximately 90% of the current areas with concentrations of palaeo-endemism (that is, places with old evolutionary diversity) are predicted to disappear or shift their location. These findings show that climate change threatens whole clades of the phylogenetic tree, and that the outlined approach can be used to forecast areas of biodiversity losses and continental-scale impacts of climate change.
An Empirical Approach to Predicting Effects of Climate Change on Stream Water Chemistry
NASA Astrophysics Data System (ADS)
Olson, J. R.; Hawkins, C. P.
2014-12-01
Climate change may affect stream solute concentrations by three mechanisms: dilution associated with increased precipitation, evaporative concentration associated with increased temperature, and changes in solute inputs associated with changes in climate-driven weathering. We developed empirical models predicting base-flow water chemistry from watershed geology, soils, and climate for 1975 individual stream sites across the conterminous USA. We then predicted future solute concentrations (2065 and 2099) by applying down-scaled global climate model predictions to these models. The electrical conductivity model (EC, model R2 = 0.78) predicted mean increases in EC of 19 μS/cm by 2065 and 40 μS/cm by 2099. However predicted responses for individual streams ranged from a 43% decrease to a 4x increase. Streams with the greatest predicted decreases occurred in the southern Rocky Mountains and Mid-West, whereas southern California and Sierra Nevada streams showed the greatest increases. Generally, streams in dry areas underlain by non-calcareous rocks were predicted to be the most vulnerable to increases in EC associated with climate change. Predicted changes in other water chemistry parameters (e.g., Acid Neutralization Capacity (ANC), SO4, and Ca) were similar to EC, although the magnitude of ANC and SO4 change was greater. Predicted changes in ANC and SO4 are in general agreement with those changes already observed in seven locations with long term records.
Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist
2011-01-01
Climate change will likely have dramatic impacts on forest health because many forest trees could become maladapted to climate. Furthermore, climate change will have additional impacts on forest health through changes in the distribution and severity of forest disease. Methods are needed to predict the influence of climate change on forest disease so that appropriate...
Mountain landscapes offer few opportunities for high-elevation tree species migration
Bell, David M.; Bradford, John B.; Lauenroth, William K.
2014-01-01
Climate change is anticipated to alter plant species distributions. Regional context, notably the spatial complexity of climatic gradients, may influence species migration potential. While high-elevation species may benefit from steep climate gradients in mountain regions, their persistence may be threatened by limited suitable habitat as land area decreases with elevation. To untangle these apparently contradictory predictions for mountainous regions, we evaluated the climatic suitability of four coniferous forest tree species of the western United States based on species distribution modeling (SDM) and examined changes in climatically suitable areas under predicted climate change. We used forest structural information relating to tree species dominance, productivity, and demography from an extensive forest inventory system to assess the strength of inferences made with a SDM approach. We found that tree species dominance, productivity, and recruitment were highest where climatic suitability (i.e., probability of species occurrence under certain climate conditions) was high, supporting the use of predicted climatic suitability in examining species risk to climate change. By predicting changes in climatic suitability over the next century, we found that climatic suitability will likely decline, both in areas currently occupied by each tree species and in nearby unoccupied areas to which species might migrate in the future. These trends were most dramatic for high elevation species. Climatic changes predicted over the next century will dramatically reduce climatically suitable areas for high-elevation tree species while a lower elevation species, Pinus ponderosa, will be well positioned to shift upslope across the region. Reductions in suitable area for high-elevation species imply that even unlimited migration would be insufficient to offset predicted habitat loss, underscoring the vulnerability of these high-elevation species to climatic changes.
Future Climate Change Will Favour Non-Specialist Mammals in the (Sub)Arctics
Hof, Anouschka R.; Jansson, Roland; Nilsson, Christer
2012-01-01
Arctic and subarctic (i.e., [sub]arctic) ecosystems are predicted to be particularly susceptible to climate change. The area of tundra is expected to decrease and temperate climates will extend further north, affecting species inhabiting northern environments. Consequently, species at high latitudes should be especially susceptible to climate change, likely experiencing significant range contractions. Contrary to these expectations, our modelling of species distributions suggests that predicted climate change up to 2080 will favour most mammals presently inhabiting (sub)arctic Europe. Assuming full dispersal ability, most species will benefit from climate change, except for a few cold-climate specialists. However, most resident species will contract their ranges if they are not able to track their climatic niches, but no species is predicted to go extinct. If climate would change far beyond current predictions, however, species might disappear. The reason for the relative stability of mammalian presence might be that arctic regions have experienced large climatic shifts in the past, filtering out sensitive and range-restricted taxa. We also provide evidence that for most (sub)arctic mammals it is not climate change per se that will threaten them, but possible constraints on their dispersal ability and changes in community composition. Such impacts of future changes in species communities should receive more attention in literature. PMID:23285098
Recent ecological responses to climate change support predictions of high extinction risk
Maclean, Ilya M. D.; Wilson, Robert J.
2011-01-01
Predicted effects of climate change include high extinction risk for many species, but confidence in these predictions is undermined by a perceived lack of empirical support. Many studies have now documented ecological responses to recent climate change, providing the opportunity to test whether the magnitude and nature of recent responses match predictions. Here, we perform a global and multitaxon metaanalysis to show that empirical evidence for the realized effects of climate change supports predictions of future extinction risk. We use International Union for Conservation of Nature (IUCN) Red List criteria as a common scale to estimate extinction risks from a wide range of climate impacts, ecological responses, and methods of analysis, and we compare predictions with observations. Mean extinction probability across studies making predictions of the future effects of climate change was 7% by 2100 compared with 15% based on observed responses. After taking account of possible bias in the type of climate change impact analyzed and the parts of the world and taxa studied, there was less discrepancy between the two approaches: predictions suggested a mean extinction probability of 10% across taxa and regions, whereas empirical evidence gave a mean probability of 14%. As well as mean overall extinction probability, observations also supported predictions in terms of variability in extinction risk and the relative risk associated with broad taxonomic groups and geographic regions. These results suggest that predictions are robust to methodological assumptions and provide strong empirical support for the assertion that anthropogenic climate change is now a major threat to global biodiversity. PMID:21746924
Recent ecological responses to climate change support predictions of high extinction risk.
Maclean, Ilya M D; Wilson, Robert J
2011-07-26
Predicted effects of climate change include high extinction risk for many species, but confidence in these predictions is undermined by a perceived lack of empirical support. Many studies have now documented ecological responses to recent climate change, providing the opportunity to test whether the magnitude and nature of recent responses match predictions. Here, we perform a global and multitaxon metaanalysis to show that empirical evidence for the realized effects of climate change supports predictions of future extinction risk. We use International Union for Conservation of Nature (IUCN) Red List criteria as a common scale to estimate extinction risks from a wide range of climate impacts, ecological responses, and methods of analysis, and we compare predictions with observations. Mean extinction probability across studies making predictions of the future effects of climate change was 7% by 2100 compared with 15% based on observed responses. After taking account of possible bias in the type of climate change impact analyzed and the parts of the world and taxa studied, there was less discrepancy between the two approaches: predictions suggested a mean extinction probability of 10% across taxa and regions, whereas empirical evidence gave a mean probability of 14%. As well as mean overall extinction probability, observations also supported predictions in terms of variability in extinction risk and the relative risk associated with broad taxonomic groups and geographic regions. These results suggest that predictions are robust to methodological assumptions and provide strong empirical support for the assertion that anthropogenic climate change is now a major threat to global biodiversity.
Separating sensitivity from exposure in assessing extinction risk from climate change.
Dickinson, Maria G; Orme, C David L; Suttle, K Blake; Mace, Georgina M
2014-11-04
Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species' risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species' risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species' sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species' extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species' extinction risk.
Separating sensitivity from exposure in assessing extinction risk from climate change
Dickinson, Maria G.; Orme, C. David L.; Suttle, K. Blake; Mace, Georgina M.
2014-01-01
Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species' risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species' risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species' sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species' extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species' extinction risk. PMID:25367429
Deborah M. Finch
2012-01-01
Recent research and species distribution modeling predict large changes in the distributions of species and vegetation types in the western interior of the United States in response to climate change. This volume reviews existing climate models that predict species and vegetation changes in the western United States, and it synthesizes knowledge about climate change...
Predicted impacts of climate change on malaria transmission in West Africa
NASA Astrophysics Data System (ADS)
Yamana, T. K.; Eltahir, E. A. B.
2014-12-01
Increases in temperature and changes in precipitation due to climate change are expected to alter the spatial distribution of malaria transmission. This is especially true in West Africa, where malaria prevalence follows the current north-south gradients in temperature and precipitation. We assess the skill of GCMs at simulating past and present climate in West Africa in order to select the most credible climate predictions for the periods 2030-2060 and 2070-2100. We then use the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a mechanistic model of malaria transmission, to translate the predicted changes in climate into predicted changes availability of mosquito breeding sites, mosquito populations, and malaria prevalence. We investigate the role of acquired immunity in determining a population's response to changes in exposure to the malaria parasite.
Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges
Mangabeira Albernaz, Ana Luisa
2016-01-01
Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map’s coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions. PMID:27618445
Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges.
Zanin, Marina; Mangabeira Albernaz, Ana Luisa
2016-01-01
Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map's coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions.
Do We Need Better Climate Predictions to Adapt to a Changing Climate? (Invited)
NASA Astrophysics Data System (ADS)
Dessai, S.; Hulme, M.; Lempert, R.; Pielke, R., Jr.
2009-12-01
Based on a series of international scientific assessments, climate change has been presented to society as a major problem that needs urgently to be tackled. The science that underpins these assessments has been pre-dominantly from the realm of the natural sciences and central to this framing have been ‘projections’ of future climate change (and its impacts on environment and society) under various greenhouse gas emissions scenarios and using a variety of climate model predictions with embedded assumptions. Central to much of the discussion surrounding adaptation to climate change is the claim - explicit or implicit - that decision makers need accurate and increasingly precise assessments of future impacts of climate change in order to adapt successfully. If true, this claim places a high premium on accurate and precise climate predictions at a range of geographical and temporal scales; such predictions therefore become indispensable, and indeed a prerequisite for, effective adaptation decision-making. But is effective adaptation tied to the ability of the scientific enterprise to predict future climate with accuracy and precision? If so, this may impose a serious and intractable limit on adaptation. This paper proceeds in three sections. It first gathers evidence of claims that climate prediction is necessary for adaptation decision-making. This evidence is drawn from peer-reviewed literature and from published science funding strategies and government policy in a number of different countries. The second part discusses the challenges of climate prediction and why science will consistently be unable to provide accurate and precise predictions of future climate relevant for adaptation (usually at the local/regional level). Section three discusses whether these limits to future foresight represent a limit to adaptation, arguing that effective adaptation need not be limited by a general inability to predict future climate. Given the deep uncertainties involved in climate prediction (and even more so in the prediction of climate impacts) and given that climate is usually only one factor in decisions aimed at climate adaptation, we conclude that the ‘predict and provide’ approach to science in support of climate change adaptation is largely flawed. We consider other important areas of public policy fraught with uncertainty - e.g. earthquake risk, national security, public health - where such a ‘predict and provide’ approach is not attempted. Instead of relying on an approach which has climate prediction (and consequent risk assessment) at its heart - which because of the associated epistemological limits to prediction will consequently act as an apparent limit to adaptation - we need to view adaptation differently, in a manner that opens up options for decision making under uncertainty. We suggest an approach which examines the robustness of adaptation strategies/policies/activities to the myriad of uncertainties that face us in the future, only one of which is the state of climate.
Sutton, William B.; Barrett, Kyle; Moody, Allison T.; Loftin, Cynthia S.; deMaynadier, Phillip G.; Nanjappa, Priya
2015-01-01
Global climate change represents one of the most extensive and pervasive threats to wildlife populations. Amphibians, specifically salamanders, are particularly susceptible to the effects of changing climates due to their restrictive physiological requirements and low vagility; however, little is known about which landscapes and species are vulnerable to climate change. Our study objectives included, (1) evaluating species-specific predictions (based on 2050 climate projections) and vulnerabilities to climate change and (2) using collective species responses to identify areas of climate refugia for conservation priority salamanders in the northeastern United States. All evaluated salamander species were projected to lose a portion of their climatic niche. Averaged projected losses ranged from 3%–100% for individual species, with the Cow Knob Salamander (Plethodon punctatus), Cheat Mountain Salamander (Plethodon nettingi), Shenandoah Mountain Salamander (Plethodon virginia), Mabee’s Salamander (Ambystoma mabeei), and Streamside Salamander (Ambystoma barbouri) predicted to lose at least 97% of their landscape-scale climatic niche. The Western Allegheny Plateau was predicted to lose the greatest salamander climate refugia richness (i.e., number of species with a climatically-suitable niche in a landscape patch), whereas the Central Appalachians provided refugia for the greatest number of species during current and projected climate scenarios. Our results can be used to identify species and landscapes that are likely to be further affected by climate change and potentially resilient habitats that will provide consistent climatic conditions in the face of environmental change.
Predicting extinctions as a result of climate change
Mark W. Schwartz; Louis R. Iverson; Anantha M. Prasad; Stephen N. Matthews; Raymond J. O' Connor; Raymond J. O' Connor
2006-01-01
Widespread extinction is a predicted ecological consequence of global warming. Extinction risk under climate change scenarios is a function of distribution breadth. Focusing on trees and birds of the eastern United States, we used joint climate and environment models to examine fit and climate change vulnerability as a function of distribution breadth. We found that...
Enhancing seasonal climate prediction capacity for the Pacific countries
NASA Astrophysics Data System (ADS)
Kuleshov, Y.; Jones, D.; Hendon, H.; Charles, A.; Cottrill, A.; Lim, E.-P.; Langford, S.; de Wit, R.; Shelton, K.
2012-04-01
Seasonal and inter-annual climate variability is a major factor in determining the vulnerability of many Pacific Island Countries to climate change and there is need to improve weekly to seasonal range climate prediction capabilities beyond what is currently available from statistical models. In the seasonal climate prediction project under the Australian Government's Pacific Adaptation Strategy Assistance Program (PASAP), we describe a comprehensive project to strengthen the climate prediction capacities in National Meteorological Services in 14 Pacific Island Countries and East Timor. The intent is particularly to reduce the vulnerability of current services to a changing climate, and improve the overall level of information available assist with managing climate variability. Statistical models cannot account for aspects of climate variability and change that are not represented in the historical record. In contrast, dynamical physics-based models implicitly include the effects of a changing climate whatever its character or cause and can predict outcomes not seen previously. The transition from a statistical to a dynamical prediction system provides more valuable and applicable climate information to a wide range of climate sensitive sectors throughout the countries of the Pacific region. In this project, we have developed seasonal climate outlooks which are based upon the current dynamical model POAMA (Predictive Ocean-Atmosphere Model for Australia) seasonal forecast system. At present, meteorological services of the Pacific Island Countries largely employ statistical models for seasonal outlooks. Outcomes of the PASAP project enhanced capabilities of the Pacific Island Countries in seasonal prediction providing National Meteorological Services with an additional tool to analyse meteorological variables such as sea surface temperatures, air temperature, pressure and rainfall using POAMA outputs and prepare more accurate seasonal climate outlooks.
Timing and Prediction of Climate Change and Hydrological Impacts: Periodicity in Natural Variations
Hydrological impacts from climate change are of principal interest to water resource policy-makers and practicing engineers, and predictive climatic models have been extensively investigated to quantify the impacts. In palaeoclmatic investigations, climate proxy evidence has une...
A linear regression model for predicting PNW estuarine temperatures in a changing climate
Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...
Impact of climate change on mercury concentrations and deposition in the eastern United States.
Megaritis, Athanasios G; Murphy, Benjamin N; Racherla, Pavan N; Adams, Peter J; Pandis, Spyros N
2014-07-15
The global-regional climate-air pollution modeling system (GRE-CAPS) was applied over the eastern United States to study the impact of climate change on the concentration and deposition of atmospheric mercury. Summer and winter periods (300 days for each) were simulated, and the present-day model predictions (2000s) were compared to the future ones (2050s) assuming constant emissions. Climate change affects Hg(2+) concentrations in both periods. On average, atmospheric Hg(2+) levels are predicted to increase in the future by 3% in summer and 5% in winter respectively due to enhanced oxidation of Hg(0) under higher temperatures. The predicted concentration change of Hg(2+) was found to vary significantly in space due to regional-scale changes in precipitation, ranging from -30% to 30% during summer and -20% to 40% during winter. Particulate mercury, Hg(p) has a similar spatial response to climate change as Hg(2+), while Hg(0) levels are not predicted to change significantly. In both periods, the response of mercury deposition to climate change varies spatially with an average predicted increase of 6% during summer and 4% during winter. During summer, deposition increases are predicted mostly in the western parts of the domain while mercury deposition is predicted to decrease in the Northeast and also in many areas in the Midwest and Southeast. During winter mercury deposition is predicted to change from -30% to 50% mainly due to the changes in rainfall and the corresponding changes in wet deposition. Copyright © 2014 Elsevier B.V. All rights reserved.
Sheridan, Jennifer A; Caruso, Nicholas M; Apodaca, Joseph J; Rissler, Leslie J
2018-01-01
Changes in body size and breeding phenology have been identified as two major ecological consequences of climate change, yet it remains unclear whether climate acts directly or indirectly on these variables. To better understand the relationship between climate and ecological changes, it is necessary to determine environmental predictors of both size and phenology using data from prior to the onset of rapid climate warming, and then to examine spatially explicit changes in climate, size, and phenology, not just general spatial and temporal trends. We used 100 years of natural history collection data for the wood frog, Lithobates sylvaticus with a range >9 million km 2 , and spatially explicit environmental data to determine the best predictors of size and phenology prior to rapid climate warming (1901-1960). We then tested how closely size and phenology changes predicted by those environmental variables reflected actual changes from 1961 to 2000. Size, phenology, and climate all changed as expected (smaller, earlier, and warmer, respectively) at broad spatial scales across the entire study range. However, while spatially explicit changes in climate variables accurately predicted changes in phenology, they did not accurately predict size changes during recent climate change (1961-2000), contrary to expectations from numerous recent studies. Our results suggest that changes in climate are directly linked to observed phenological shifts. However, the mechanisms driving observed body size changes are yet to be determined, given the less straightforward relationship between size and climate factors examined in this study. We recommend that caution be used in "space-for-time" studies where measures of a species' traits at lower latitudes or elevations are considered representative of those under future projected climate conditions. Future studies should aim to determine mechanisms driving trends in phenology and body size, as well as the impact of climate on population density, which may influence body size.
Woody plants and the prediction of climate-change impacts on bird diversity.
Kissling, W D; Field, R; Korntheuer, H; Heyder, U; Böhning-Gaese, K
2010-07-12
Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically structured, mainly owing to uncertainties in projected precipitation changes. We conclude that assessments of future species responses to climate change are very sensitive to current uncertainties in regional climate-change projections, and to the inclusion or not of time-lagged interacting taxa. We expect even stronger effects for more specialized plant-animal associations. Given the slow response time of woody plant distributions to climate change, current estimates of future biodiversity of many animal taxa may be both biased and too optimistic.
NASA Astrophysics Data System (ADS)
Renner, M.; Bernhofer, C.
2012-08-01
The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2012) introduced the climate change impact hypothesis (CCUW), which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (the Budyko approach of Roderick and Farquhar, 2011, and the CCUW) with data of more than 400 basins distributed over the continental United States. We first estimate the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949 to 2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect to changes in climate. Next, we test the ability of both approaches to predict climate impacts on streamflow by splitting the data into two periods. We (i) analyse the long-term average changes in hydro-climatology and (ii) derive a statistical classification of potential climate and basin change impacts based on the significance of observed changes in runoff, precipitation and potential evapotranspiration. Then we (iii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iv) evaluate the predictions by (v) using the statistical classification scheme and (vi) a conceptual approach to separate the impacts of changes in climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to assess the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow of the majority of basins in the US is dominated by an increase in precipitation. It is further evident that impacts of changes in basin characteristics appear simultaneously with climate changes. There are coherent spatial patterns with catchments where basin changes compensate for climatic changes being dominant in the western and central parts of the US. A hot spot of basin changes leading to excessive runoff is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as much as the observed change signal. Although the CCUW and the Budyko approach yield similar predictions for most basins, the data of water-limited basins support the Budyko framework rather than the CCUW approach, which is known to be invalid under limiting climatic conditions.
Life history trade-off moderates model predictions of diversity loss from climate change.
Moor, Helen
2017-01-01
Climate change can trigger species range shifts, local extinctions and changes in diversity. Species interactions and dispersal capacity are important mediators of community responses to climate change. The interaction between multispecies competition and variation in dispersal capacity has recently been shown to exacerbate the effects of climate change on diversity and to increase predictions of extinction risk dramatically. Dispersal capacity, however, is part of a species' overall ecological strategy and are likely to trade off with other aspects of its life history that influence population growth and persistence. In plants, a well-known example is the trade-off between seed mass and seed number. The presence of such a trade-off might buffer the diversity loss predicted by models with random but neutral (i.e. not impacting fitness otherwise) differences in dispersal capacity. Using a trait-based metacommunity model along a warming climatic gradient the effect of three different dispersal scenarios on model predictions of diversity change were compared. Adding random variation in species dispersal capacity caused extinctions by the introduction of strong fitness differences due an inherent property of the dispersal kernel. Simulations including a fitness-equalising trade-off based on empirical relationships between seed mass (here affecting dispersal distance, establishment probability, and seedling biomass) and seed number (fecundity) maintained higher initial species diversity and predicted lower extinction risk and diversity loss during climate change than simulations with variable dispersal capacity. Large seeded species persisted during climate change, but developed lags behind their climate niche that may cause extinction debts. Small seeded species were more extinction-prone during climate change but tracked their niches through dispersal and colonisation, despite competitive resistance from residents. Life history trade-offs involved in coexistence mechanisms may increase community resilience to future climate change and are useful guides for model development.
Predicting phenology by integrating ecology, evolution and climate science
Pau, Stephanie; Wolkovich, Elizabeth M.; Cook, Benjamin I.; Davies, T. Jonathan; Kraft, Nathan J.B.; Bolmgren, Kjell; Betancourt, Julio L.; Cleland, Elsa E.
2011-01-01
Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology — the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.
A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change.
Ashraf, M Irfan; Meng, Fan-Rui; Bourque, Charles P-A; MacLean, David A
2015-01-01
Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm(2) 5-year(-1) and volume: 0.0008 m(3) 5-year(-1)). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm(2) 5-year(-1) and 0.0393 m(3) 5-year(-1) in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling.
A Novel Modelling Approach for Predicting Forest Growth and Yield under Climate Change
Ashraf, M. Irfan; Meng, Fan-Rui; Bourque, Charles P.-A.; MacLean, David A.
2015-01-01
Global climate is changing due to increasing anthropogenic emissions of greenhouse gases. Forest managers need growth and yield models that can be used to predict future forest dynamics during the transition period of present-day forests under a changing climatic regime. In this study, we developed a forest growth and yield model that can be used to predict individual-tree growth under current and projected future climatic conditions. The model was constructed by integrating historical tree growth records with predictions from an ecological process-based model using neural networks. The new model predicts basal area (BA) and volume growth for individual trees in pure or mixed species forests. For model development, tree-growth data under current climatic conditions were obtained using over 3000 permanent sample plots from the Province of Nova Scotia, Canada. Data to reflect tree growth under a changing climatic regime were projected with JABOWA-3 (an ecological process-based model). Model validation with designated data produced model efficiencies of 0.82 and 0.89 in predicting individual-tree BA and volume growth. Model efficiency is a relative index of model performance, where 1 indicates an ideal fit, while values lower than zero means the predictions are no better than the average of the observations. Overall mean prediction error (BIAS) of basal area and volume growth predictions was nominal (i.e., for BA: -0.0177 cm2 5-year-1 and volume: 0.0008 m3 5-year-1). Model variability described by root mean squared error (RMSE) in basal area prediction was 40.53 cm2 5-year-1 and 0.0393 m3 5-year-1 in volume prediction. The new modelling approach has potential to reduce uncertainties in growth and yield predictions under different climate change scenarios. This novel approach provides an avenue for forest managers to generate required information for the management of forests in transitional periods of climate change. Artificial intelligence technology has substantial potential in forest modelling. PMID:26173081
Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.
Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J
2018-01-01
Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.
Consequences of past climate change for species engaged in obligatory interactions
NASA Astrophysics Data System (ADS)
Blatrix, Rumsaïs; McKey, Doyle; Born, Céline
2013-07-01
Obligatory interactions between species are fundamental to ecosystem functioning and are expected to be particularly sensitive to climate change. Although the effect of past and current climate changes on individual species has been thoroughly investigated, their effect on obligatory interactions has been overlooked. In this review, we present predictions about the effects of climate change on obligatory interactions and illustrate these predictions with examples from the literature. We focus on abrupt past climate change, especially during the Quaternary, because knowing past responses is useful for understanding and predicting the response of organisms and ecosystems to the current climate change. We also pinpoint the need for better time calibration of demographic events from genetic data, and for more studies focused on particularly suitable biological models. We hope that this review will stimulate interaction between the earth sciences and the life sciences on this timely topic.
Ruiz-Navarro, Ana; Gillingham, Phillipa K; Britton, J Robert
2016-09-01
Predictions of species responses to climate change often focus on distribution shifts, although responses can also include shifts in body sizes and population demographics. Here, shifts in the distributional ranges ('climate space'), body sizes (as maximum theoretical body sizes, L∞) and growth rates (as rate at which L∞ is reached, K) were predicted for five fishes of the Cyprinidae family in a temperate region over eight climate change projections. Great Britain was the model area, and the model species were Rutilus rutilus, Leuciscus leuciscus, Squalius cephalus, Gobio gobio and Abramis brama. Ensemble models predicted that the species' climate spaces would shift in all modelled projections, with the most drastic changes occurring under high emissions; all range centroids shifted in a north-westerly direction. Predicted climate space expanded for R. rutilus and A. brama, contracted for S. cephalus, and for L. leuciscus and G. gobio, expanded under low-emission scenarios but contracted under high emissions, suggesting the presence of some climate-distribution thresholds. For R. rutilus, A. brama, S. cephalus and G. gobio, shifts in their climate space were coupled with predicted shifts to significantly smaller maximum body sizes and/or faster growth rates, aligning strongly to aspects of temperature-body size theory. These predicted shifts in L∞ and K had considerable consequences for size-at-age per species, suggesting substantial alterations in population age structures and abundances. Thus, when predicting climate change outcomes for species, outputs that couple shifts in climate space with altered body sizes and growth rates provide considerable insights into the population and community consequences, especially for species that cannot easily track their thermal niches. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Rohr, Jason R; Raffel, Thomas R; Blaustein, Andrew R; Johnson, Pieter T J; Paull, Sara H; Young, Suzanne
2013-01-01
Controversy persists regarding the contributions of climate change to biodiversity losses, through its effects on the spread and emergence of infectious diseases. One of the reasons for this controversy is that there are few mechanistic studies that explore the links among climate change, infectious disease, and declines of host populations. Given that host-parasite interactions are generally mediated by physiological responses, we submit that physiological models could facilitate the prediction of how host-parasite interactions will respond to climate change, and might offer theoretical and terminological cohesion that has been lacking in the climate change-disease literature. We stress that much of the work on how climate influences host-parasite interactions has emphasized changes in climatic means, despite a hallmark of climate change being changes in climatic variability and extremes. Owing to this gap, we highlight how temporal variability in weather, coupled with non-linearities in responses to mean climate, can be used to predict the effects of climate on host-parasite interactions. We also discuss the climate variability hypothesis for disease-related declines, which posits that increased unpredictable temperature variability might provide a temporary advantage to pathogens because they are smaller and have faster metabolisms than their hosts, allowing more rapid acclimatization following a temperature shift. In support of these hypotheses, we provide case studies on the role of climatic variability in host population declines associated with the emergence of the infectious diseases chytridiomycosis, withering syndrome, and malaria. Finally, we present a mathematical model that provides the scaffolding to integrate metabolic theory, physiological mechanisms, and large-scale spatiotemporal processes to predict how simultaneous changes in climatic means, variances, and extremes will affect host-parasite interactions. However, several outstanding questions remain to be answered before investigators can accurately predict how changes in climatic means and variances will affect infectious diseases and the conservation status of host populations.
Projected climate-induced faunal change in the Western Hemisphere
Lawler, J.J.; Shafer, S.L.; White, D.; Kareiva, P.; Maurer, E.P.; Blaustein, A.R.; Bartlein, P.J.
2009-01-01
Climate change is predicted to be one of the greatest drivers of ecological change in the coming century. Increases in temperature over the last century have clearly been linked to shifts in species distributions. Given the magnitude of projected future climatic changes, we can expect even larger range shifts in the coming century. These changes will, in turn, alter ecological communities and the functioning of ecosystems. Despite the seriousness of predicted climate change, the uncertainty in climate-change projections makes it difficult for conservation managers and planners to proactively respond to climate stresses. To address one aspect of this uncertainty, we identified predictions of faunal change for which a high level of consensus was exhibited by different climate models. Specifically, we assessed the potential effects of 30 coupled atmosphere-ocean general circulation model (AOGCM) future-climate simulations on the geographic ranges of 2954 species of birds, mammals, and amphibians in the Western Hemisphere. Eighty percent of the climate projections based on a relatively low greenhouse-gas emissions scenario result in the local loss of at least 10% of the vertebrate fauna over much of North and South America. The largest changes in fauna are predicted for the tundra, Central America, and the Andes Mountains where, assuming no dispersal constraints, specific areas are likely to experience over 90% turnover, so that faunal distributions in the future will bear little resemblance to those of today. ?? 2009 by the Ecological Society of America.
NASA Astrophysics Data System (ADS)
Montaldo, N.; Oren, R.
2017-12-01
Over the past century, climate change is affecting precipitation regimes across the world. In the Mediterranean regions there is a persistent trend of precipitation and runoff decreases, generating a desertification process. Given the past winter precipitation shifts, the impacts on evapotranspiration (ET) need to be carefully evaluated, and the compelling question is what will be the impact of future climate change scenarios (predicting changes of precipitation and vapor pressure deficit, VPD) on evapotranspiration and water yield? Looking for the key elements of the climate change that are impacting annual ET, we investigate main climate conditions (e.g. precipitation and VPD) and basin physiographic properties contributing to annual ET. We propose a simplified model for annual ET predictions that accounts for the strong meteo seasonality typical of Mediterranean climates, using the steady state assumption of the basin water balance at mean annual scale. We investigate the Sardinia case study because the position of the island of Sardinia in the center of the western Mediterranean Sea basin and its low urbanization and human activity make Sardinia a perfect reference laboratory for Mediterranean hydrologic studies. Sardinian runoff decreased drastically over the 1975-2010 period, with mean yearly runoff reduced by more than 40% compared to the previous 1922-1974 period, and most yearly runoff in the Sardinian basins (70% on average) is produced by winter precipitation due to the seasonality typical of the Mediterranean climate regime. The use of our proposed model allows to predict future ET and water yield using future climate scenarios. We use the future climate scenarios predicted by Global climate models (GCM) in the Fifth Assessment report of the Intergovernmental Panel on Climate Change (IPCC), and we select most reliable models testing the past GCM predictions with historical data. Contrasting shifts of precipitation (both positive and negative) are predicted in the future scenarios by GCMs but these changes will produce significant changes (level of significance > 90%) only in runoff and not in ET. Surprisingly, we show that ET is insensitive to intra-annual rainfall distribution changes, and is insensitive to VPD scenario changes.
Liu, Xuan; Guo, Zhongwei; Ke, Zunwei; Wang, Supen; Li, Yiming
2011-01-01
Background Anthropogenically-induced climate change can alter the current climatic habitat of non-native species and can have complex effects on potentially invasive species. Predictions of the potential distributions of invasive species under climate change will provide critical information for future conservation and management strategies. Aquatic ecosystems are particularly vulnerable to invasive species and climate change, but the effect of climate change on invasive species distributions has been rather neglected, especially for notorious global invaders. Methodology/Principal Findings We used ecological niche models (ENMs) to assess the risks and opportunities that climate change presents for the red swamp crayfish (Procambarus clarkii), which is a worldwide aquatic invasive species. Linking the factors of climate, topography, habitat and human influence, we developed predictive models incorporating both native and non-native distribution data of the crayfish to identify present areas of potential distribution and project the effects of future climate change based on a consensus-forecast approach combining the CCCMA and HADCM3 climate models under two emission scenarios (A2a and B2a) by 2050. The minimum temperature from the coldest month, the human footprint and precipitation of the driest quarter contributed most to the species distribution models. Under both the A2a and B2a scenarios, P. clarkii shifted to higher latitudes in continents of both the northern and southern hemispheres. However, the effect of climate change varied considerately among continents with an expanding potential in Europe and contracting changes in others. Conclusions/Significance Our findings are the first to predict the impact of climate change on the future distribution of a globally invasive aquatic species. We confirmed the complexities of the likely effects of climate change on the potential distribution of globally invasive species, and it is extremely important to develop wide-ranging and effective control measures according to predicted geographical shifts and changes. PMID:21479188
Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha; Thompson, Jill; Zimmerman, Jess K; Murphy, Lora
2018-01-01
Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate. © 2017 John Wiley & Sons Ltd.
Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha C.; Thompson, Jill; Zimmerman, Jess K.; Murphy, Lora
2018-01-01
Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.
Fournier-Level, Alexandre; Perry, Emily O.; Wang, Jonathan A.; Braun, Peter T.; Migneault, Andrew; Cooper, Martha D.; Metcalf, C. Jessica E.; Schmitt, Johanna
2016-01-01
Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico “resurrection experiments” showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640
Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna
2016-05-17
Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation.
Ned B. Klopfenstein; Mee-Sook Kim; John W. Hanna; Bryce A. Richardson; John E. Lundquist
2009-01-01
Predicting climate change influences on forest diseases will foster forest management practices that minimize adverse impacts of diseases. Precise locations of accurately identified pathogens and hosts must be documented and spatially referenced to determine which climatic factors influence species distribution. With this information, bioclimatic models can predict the...
Wei Wu; James S. Clark; James M. Vose
2012-01-01
Predicting long-term consequences of climate change on hydrologic processes has been limited due to the needs to accommodate the uncertainties in hydrological measurements for calibration, and to account for the uncertainties in the models that would ingest those calibrations and uncertainties in climate predictions as basis for hydrological predictions. We implemented...
Tropical and Extratropical Cyclone Damages under Climate Change
NASA Astrophysics Data System (ADS)
Ranson, M.; Kousky, C.; Ruth, M.; Jantarasami, L.; Crimmins, A.; Tarquinio, L.
2014-12-01
This paper provides the first quantitative synthesis of the rapidly growing literature on future tropical and extratropical cyclone losses under climate change. We estimate a probability distribution for the predicted impact of changes in global surface air temperatures on future storm damages, using an ensemble of 296 estimates of the temperature-damage relationship from twenty studies. Our analysis produces three main empirical results. First, we find strong but not conclusive support for the hypothesis that climate change will cause damages from tropical cyclones and wind storms to increase, with most models (84 and 92 percent, respectively) predicting higher future storm damages due to climate change. Second, there is substantial variation in projected changes in losses across regions. Potential changes in damages are greatest in the North Atlantic basin, where the multi-model average predicts that a 2.5°C increase in global surface air temperature would cause hurricane damages to increase by 62 percent. The ensemble predictions for Western North Pacific tropical cyclones and European wind storms (extratropical cyclones) are approximately one third of that magnitude. Finally, our analysis shows that existing models of storm damages under climate change generate a wide range of predictions, ranging from moderate decreases to very large increases in losses.
Segurado, Pedro; Branco, Paulo; Jauch, Eduardo; Neves, Ramiro; Ferreira, M Teresa
2016-08-15
Climate change will predictably change hydrological patterns and processes at the catchment scale, with impacts on habitat conditions for fish. The main goal of this study is to assess how shifts in fish habitat favourability under climate change scenarios are affected by hydrological stressors. The interplay between climate and hydrological stressors has important implications in river management under climate change because management actions to control hydrological parameters are more feasible than controlling climate. This study was carried out in the Tamega catchment of the Douro basin. A set of hydrological stressor variables were generated through a process-based modelling based on current climate data (2008-2014) and also considering a high-end future climate change scenario. The resulting parameters, along with climatic and site-descriptor variables were used as explanatory variables in empirical habitat models for nine fish species using boosted regression trees. Models were calibrated for the whole Douro basin using 254 fish sampling sites and predictions under future climate change scenarios were made for the Tamega catchment. Results show that models using climatic variables but not hydrological stressors produce more stringent predictions of future favourability, predicting more distribution contractions or stronger range shifts. The use of hydrological stressors strongly influences projections of habitat favourability shifts; the integration of these stressors in the models thinned shifts in range due to climate change. Hydrological stressors were retained in the models for most species and had a high importance, demonstrating that it is important to integrate hydrology in studies of impacts of climate change on freshwater fishes. This is a relevant result because it means that management actions to control hydrological parameters in rivers will have an impact on the effects of climate change and may potentially be helpful to mitigate its negative effects on fish populations and assemblages. Copyright © 2016 Elsevier B.V. All rights reserved.
Role of Climate Change in Global Predictions of Future Tropospheric Ozone and Aerosols
NASA Technical Reports Server (NTRS)
Liao, Hong; Chen, Wei-Ting; Seinfeld, John H.
2006-01-01
A unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies general circulation model II is applied to simulate an equilibrium CO2-forced climate in the year 2100 to examine the effects of climate change on global distributions of tropospheric ozone and sulfate, nitrate, ammonium, black carbon, primary organic carbon, secondary organic carbon, sea salt, and mineral dust aerosols. The year 2100 CO2 concentration as well as the anthropogenic emissions of ozone precursors and aerosols/aerosol precursors are based on the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) A2. Year 2100 global O3 and aerosol burdens predicted with changes in both climate and emissions are generally 5-20% lower than those simulated with changes in emissions alone; as exceptions, the nitrate burden is 38% lower, and the secondary organic aerosol burden is 17% higher. Although the CO2-driven climate change alone is predicted to reduce the global O3 concentrations over or near populated and biomass burning areas because of slower transport, enhanced biogenic hydrocarbon emissions, decomposition of peroxyacetyl nitrate at higher temperatures, and the increase of O3 production by increased water vapor at high NOx levels. The warmer climate influences aerosol burdens by increasing aerosol wet deposition, altering climate-sensitive emissions, and shifting aerosol thermodynamic equilibrium. Climate change affects the estimates of the year 2100 direct radiative forcing as a result of the climate-induced changes in burdens and different climatological conditions; with full gas-aerosol coupling and accounting for ozone and direct radiative forcings by the O2, sulfate, nitrate, black carbon, and organic carbon are predicted to be +0.93, -0.72, -1.0, +1.26, and -0.56 W m(exp -2), respectively, using present-day climate and year 2100 emissions, while they are predicted to be +0.76, -0.72, 0.74, +0.97, and -0.58 W m(exp -2), respectively, with year 2100 climate and emissions.
Rohr, Jason R.; Raffel, Thomas R.; Blaustein, Andrew R.; Johnson, Pieter T. J.; Paull, Sara H.; Young, Suzanne
2013-01-01
Controversy persists regarding the contributions of climate change to biodiversity losses, through its effects on the spread and emergence of infectious diseases. One of the reasons for this controversy is that there are few mechanistic studies that explore the links among climate change, infectious disease, and declines of host populations. Given that host–parasite interactions are generally mediated by physiological responses, we submit that physiological models could facilitate the prediction of how host–parasite interactions will respond to climate change, and might offer theoretical and terminological cohesion that has been lacking in the climate change–disease literature. We stress that much of the work on how climate influences host–parasite interactions has emphasized changes in climatic means, despite a hallmark of climate change being changes in climatic variability and extremes. Owing to this gap, we highlight how temporal variability in weather, coupled with non-linearities in responses to mean climate, can be used to predict the effects of climate on host–parasite interactions. We also discuss the climate variability hypothesis for disease-related declines, which posits that increased unpredictable temperature variability might provide a temporary advantage to pathogens because they are smaller and have faster metabolisms than their hosts, allowing more rapid acclimatization following a temperature shift. In support of these hypotheses, we provide case studies on the role of climatic variability in host population declines associated with the emergence of the infectious diseases chytridiomycosis, withering syndrome, and malaria. Finally, we present a mathematical model that provides the scaffolding to integrate metabolic theory, physiological mechanisms, and large-scale spatiotemporal processes to predict how simultaneous changes in climatic means, variances, and extremes will affect host–parasite interactions. However, several outstanding questions remain to be answered before investigators can accurately predict how changes in climatic means and variances will affect infectious diseases and the conservation status of host populations. PMID:27293606
Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.
2014-01-01
Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.
Aguilée, Robin; Raoul, Gaël; Rousset, François; Ronce, Ophélie
2016-01-01
Species may survive climate change by migrating to track favorable climates and/or adapting to different climates. Several quantitative genetics models predict that species escaping extinction will change their geographical distribution while keeping the same ecological niche. We introduce pollen dispersal in these models, which affects gene flow but not directly colonization. We show that plant populations may escape extinction because of both spatial range and ecological niche shifts. Exact analytical formulas predict that increasing pollen dispersal distance slows the expected spatial range shift and accelerates the ecological niche shift. There is an optimal distance of pollen dispersal, which maximizes the sustainable rate of climate change. These conclusions hold in simulations relaxing several strong assumptions of our analytical model. Our results imply that, for plants with long distance of pollen dispersal, models assuming niche conservatism may not accurately predict their future distribution under climate change. PMID:27621443
Aguilée, Robin; Raoul, Gaël; Rousset, François; Ronce, Ophélie
2016-09-27
Species may survive climate change by migrating to track favorable climates and/or adapting to different climates. Several quantitative genetics models predict that species escaping extinction will change their geographical distribution while keeping the same ecological niche. We introduce pollen dispersal in these models, which affects gene flow but not directly colonization. We show that plant populations may escape extinction because of both spatial range and ecological niche shifts. Exact analytical formulas predict that increasing pollen dispersal distance slows the expected spatial range shift and accelerates the ecological niche shift. There is an optimal distance of pollen dispersal, which maximizes the sustainable rate of climate change. These conclusions hold in simulations relaxing several strong assumptions of our analytical model. Our results imply that, for plants with long distance of pollen dispersal, models assuming niche conservatism may not accurately predict their future distribution under climate change.
Disease in a more variable and unpredictable climate
NASA Astrophysics Data System (ADS)
McMahon, T. A.; Raffel, T.; Rohr, J. R.; Halstead, N.; Venesky, M.; Romansic, J.
2014-12-01
Global climate change is shifting the dynamics of infectious diseases of humans and wildlife with potential adverse consequences for disease control. Despite this, the role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial. Climate change is expected to increase climate variability in addition to increasing mean temperatures, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments and field data on disease-associated frog declines in Latin America support this framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was inconsistent with the pattern of Bd growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. Consistent with our laboratory experiments, increased regional temperature variability associated with global El Niño climatic events was the best predictor of widespread amphibian losses in the genus Atelopus. Thus, incorporating the effects of small-scale temporal variability in climate can greatly improve our ability to predict the effects of climate change on disease.
Life history trade-off moderates model predictions of diversity loss from climate change
2017-01-01
Climate change can trigger species range shifts, local extinctions and changes in diversity. Species interactions and dispersal capacity are important mediators of community responses to climate change. The interaction between multispecies competition and variation in dispersal capacity has recently been shown to exacerbate the effects of climate change on diversity and to increase predictions of extinction risk dramatically. Dispersal capacity, however, is part of a species’ overall ecological strategy and are likely to trade off with other aspects of its life history that influence population growth and persistence. In plants, a well-known example is the trade-off between seed mass and seed number. The presence of such a trade-off might buffer the diversity loss predicted by models with random but neutral (i.e. not impacting fitness otherwise) differences in dispersal capacity. Using a trait-based metacommunity model along a warming climatic gradient the effect of three different dispersal scenarios on model predictions of diversity change were compared. Adding random variation in species dispersal capacity caused extinctions by the introduction of strong fitness differences due an inherent property of the dispersal kernel. Simulations including a fitness-equalising trade-off based on empirical relationships between seed mass (here affecting dispersal distance, establishment probability, and seedling biomass) and seed number (fecundity) maintained higher initial species diversity and predicted lower extinction risk and diversity loss during climate change than simulations with variable dispersal capacity. Large seeded species persisted during climate change, but developed lags behind their climate niche that may cause extinction debts. Small seeded species were more extinction-prone during climate change but tracked their niches through dispersal and colonisation, despite competitive resistance from residents. Life history trade-offs involved in coexistence mechanisms may increase community resilience to future climate change and are useful guides for model development. PMID:28520770
Genetically informed ecological niche models improve climate change predictions.
Ikeda, Dana H; Max, Tamara L; Allan, Gerard J; Lau, Matthew K; Shuster, Stephen M; Whitham, Thomas G
2017-01-01
We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change. © 2016 John Wiley & Sons Ltd.
Palmer, Georgina; Hill, Jane K.; Brereton, Tom M.; Brooks, David R.; Chapman, Jason W.; Fox, Richard; Oliver, Tom H.; Thomas, Chris D.
2015-01-01
The responses of animals and plants to recent climate change vary greatly from species to species, but attempts to understand this variation have met with limited success. This has led to concerns that predictions of responses are inherently uncertain because of the complexity of interacting drivers and biotic interactions. However, we show for an exemplar group of 155 Lepidoptera species that about 60% of the variation among species in their abundance trends over the past four decades can be explained by species-specific exposure and sensitivity to climate change. Distribution changes were less well predicted, but nonetheless, up to 53% of the variation was explained. We found that species vary in their overall sensitivity to climate and respond to different components of the climate despite ostensibly experiencing the same climate changes. Hence, species have undergone different levels of population “forcing” (exposure), driving variation among species in their national-scale abundance and distribution trends. We conclude that variation in species’ responses to recent climate change may be more predictable than previously recognized. PMID:26601276
Majda, Andrew J; Abramov, Rafail; Gershgorin, Boris
2010-01-12
Climate change science focuses on predicting the coarse-grained, planetary-scale, longtime changes in the climate system due to either changes in external forcing or internal variability, such as the impact of increased carbon dioxide. The predictions of climate change science are carried out through comprehensive, computational atmospheric, and oceanic simulation models, which necessarily parameterize physical features such as clouds, sea ice cover, etc. Recently, it has been suggested that there is irreducible imprecision in such climate models that manifests itself as structural instability in climate statistics and which can significantly hamper the skill of computer models for climate change. A systematic approach to deal with this irreducible imprecision is advocated through algorithms based on the Fluctuation Dissipation Theorem (FDT). There are important practical and computational advantages for climate change science when a skillful FDT algorithm is established. The FDT response operator can be utilized directly for multiple climate change scenarios, multiple changes in forcing, and other parameters, such as damping and inverse modelling directly without the need of running the complex climate model in each individual case. The high skill of FDT in predicting climate change, despite structural instability, is developed in an unambiguous fashion using mathematical theory as guidelines in three different test models: a generic class of analytical models mimicking the dynamical core of the computer climate models, reduced stochastic models for low-frequency variability, and models with a significant new type of irreducible imprecision involving many fast, unstable modes.
Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub
Renwick, Katherine M.; Curtis, Caroline; Kleinhesselink, Andrew R.; Schlaepfer, Daniel R.; Bradley, Bethany A.; Aldridge, Cameron L.; Poulter, Benjamin; Adler, Peter B.
2018-01-01
A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.
Zhang, Ke; de Almeida Castanho, Andrea D; Galbraith, David R; Moghim, Sanaz; Levine, Naomi M; Bras, Rafael L; Coe, Michael T; Costa, Marcos H; Malhi, Yadvinder; Longo, Marcos; Knox, Ryan G; McKnight, Shawna; Wang, Jingfeng; Moorcroft, Paul R
2015-02-20
There is considerable interest in understanding the fate of the Amazon over the coming century in the face of climate change, rising atmospheric CO 2 levels, ongoing land transformation, and changing fire regimes within the region. In this analysis, we explore the fate of Amazonian ecosystems under the combined impact of these four environmental forcings using three terrestrial biosphere models (ED2, IBIS, and JULES) forced by three bias-corrected IPCC AR4 climate projections (PCM1, CCSM3, and HadCM3) under two land-use change scenarios. We assess the relative roles of climate change, CO 2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change are primarily determined by the direction and severity of projected changes in regional precipitation: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%. However, the models predict that CO 2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and, as a result, sustain high biomass forests, even under the driest climate scenario. Land-use change and climate-driven changes in fire frequency are predicted to cause additional aboveground biomass loss and reductions in forest extent. The relative impact of land use and fire dynamics compared to climate and CO 2 impacts varies considerably, depending on both the climate and land-use scenario, and on the terrestrial biosphere model used, highlighting the importance of improved quantitative understanding of all four factors - climate change, CO 2 fertilization effects, fire, and land use - to the fate of the Amazon over the coming century. © 2015 John Wiley & Sons Ltd.
Kane, Kristin; Debinski, Diane M.; Anderson, Chris; Scasta, John D.; Engle, David M.; Miller, James R.
2017-01-01
Grassland loss has been extensive worldwide, endangering the associated biodiversity and human well-being that are both dependent on these ecosystems. Ecologists have developed approaches to restore grassland communities and many have been successful, particularly where soils are rich, precipitation is abundant, and seeds of native plant species can be obtained. However, climate change adds a new filter needed in planning grassland restoration efforts. Potential responses of species to future climate conditions must also be considered in planning for long-term resilience. We demonstrate this methodology using a site-specific model and a maximum entropy approach to predict changes in habitat suitability for 33 grassland plant species in the tallgrass prairie region of the U.S. using the Intergovernmental Panel on Climate Change scenarios A1B and A2. The A1B scenario predicts an increase in temperature from 1.4 to 6.4°C, whereas the A2 scenario predicts temperature increases from 2 to 5.4°C and much greater CO2 emissions than the A1B scenario. Both scenarios predict these changes to occur by the year 2100. Model projections for 2040 under the A1B scenario predict that all but three modeled species will lose ~90% of their suitable habitat. Then by 2080, all species except for one will lose ~90% of their suitable habitat. Models run using the A2 scenario predict declines in habitat for just four species by 2040, but models predict that by 2080, habitat suitability will decline for all species. The A2 scenario appears based on our results to be the less severe climate change scenario for our species. Our results demonstrate that many common species, including grasses, forbs, and shrubs, are sensitive to climate change. Thus, grassland restoration alternatives should be evaluated based upon the long-term viability in the context of climate change projections and risk of plant species loss. PMID:28536591
Climate change and maize yield in Iowa
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, Hong; Twine, Tracy E.; Girvetz, Evan
Climate is changing across the world, including the major maize-growing state of Iowa in the USA. To maintain crop yields, farmers will need a suite of adaptation strategies, and choice of strategy will depend on how the local to regional climate is expected to change. Here we predict how maize yield might change through the 21 st century as compared with late 20 th century yields across Iowa, USA, a region representing ideal climate and soils for maize production that contributes substantially to the global maize economy. To account for climate model uncertainty, we drive a dynamic ecosystem model withmore » output from six climate models and two future climate forcing scenarios. Despite a wide range in the predicted amount of warming and change to summer precipitation, all simulations predict a decrease in maize yields from late 20 th century to middle and late 21 st century ranging from 15% to 50%. Linear regression of all models predicts a 6% state-averaged yield decrease for every 1°C increase in warm season average air temperature. When the influence of moisture stress on crop growth is removed from the model, yield decreases either remain the same or are reduced, depending on predicted changes in warm season precipitation. Lastly, our results suggest that even if maize were to receive all the water it needed, under the strongest climate forcing scenario yields will decline by 10-20% by the end of the 21 st century.« less
Climate change and maize yield in Iowa
Xu, Hong; Twine, Tracy E.; Girvetz, Evan
2016-05-24
Climate is changing across the world, including the major maize-growing state of Iowa in the USA. To maintain crop yields, farmers will need a suite of adaptation strategies, and choice of strategy will depend on how the local to regional climate is expected to change. Here we predict how maize yield might change through the 21 st century as compared with late 20 th century yields across Iowa, USA, a region representing ideal climate and soils for maize production that contributes substantially to the global maize economy. To account for climate model uncertainty, we drive a dynamic ecosystem model withmore » output from six climate models and two future climate forcing scenarios. Despite a wide range in the predicted amount of warming and change to summer precipitation, all simulations predict a decrease in maize yields from late 20 th century to middle and late 21 st century ranging from 15% to 50%. Linear regression of all models predicts a 6% state-averaged yield decrease for every 1°C increase in warm season average air temperature. When the influence of moisture stress on crop growth is removed from the model, yield decreases either remain the same or are reduced, depending on predicted changes in warm season precipitation. Lastly, our results suggest that even if maize were to receive all the water it needed, under the strongest climate forcing scenario yields will decline by 10-20% by the end of the 21 st century.« less
Impacts of climate change on distributions and diversity of ungulates on the Tibetan Plateau.
Luo, Zhenhua; Jiang, Zhigang; Tang, Songhua
2015-01-01
Climate change has significant impacts on species' distributions and diversity patterns. Understanding range shifts and changes in richness gradients under climate change is crucial for conservation. The Tibetan Plateau, home to wild yak, chiru, and kiang, contains a biome with many endemic ungulates. It is highly sensitive to climate change and a region that merits particular attention with regard to the impacts of global climate change on its biomes. Maximum entropy approaches were used to estimate current and future potential distributions, in response to climate change, for 22 ungulate species. We used three general circulation (MK3, HADCM3, MIROC3_2-MED) and three emissions scenarios (Bl, A1B, A2) to derive estimated future measurements of 14 environmental variables over three time periods (2020, 2050, 2080), and then modeled species distributions using these predicted environmental measurements for each time period under two dispersal hypotheses (full and zero, respectively). This resulted in a total of 6160 prediction models. We found that these ungulates, on average, may lose 30-50% of their distributional areas, depending on the dispersal scenarios. In addition, 55-68% of the ungulate species were predicted to become locally endangered under the different dispersal assumptions, 23-32% to become locally critically endangered, and 4-7 endemic species to become globally endangered. Furthermore, ungulate species ranges may experience average poleward shifts of ~300 km. We also predict west-to-east reductions in species richness: southeastern mountainous areas currently have the highest species richness, but are predicted to face the greatest diversity losses, whereas the northern areas are predicted to see increasing numbers of ungulate species in the 21st century. Our study indicates much more severe range reductions of ungulates on the Tibetan Plateau than those anticipated elsewhere in the world, and species richness patterns will change dramatically with climate change. For conservation, we suggest (1) securing existing protected areas, and (2) establishing new nature reserves to counterbalance climate change impacts.
Yamana, Teresa K; Eltahir, Elfatih A B
2013-10-01
Climate change is expected to affect the distribution of environmental suitability for malaria transmission by altering temperature and rainfall patterns; however, the local and global impacts of climate change on malaria transmission are uncertain. We assessed the effect of climate change on malaria transmission in West Africa. We coupled a detailed mechanistic hydrology and entomology model with climate projections from general circulation models (GCMs) to predict changes in vectorial capacity, an indication of the risk of human malaria infections, resulting from changes in the availability of mosquito breeding sites and temperature-dependent development rates. Because there is strong disagreement in climate predictions from different GCMs, we focused on the GCM projections that produced the best and worst conditions for malaria transmission in each zone of the study area. Simulation-based estimates suggest that in the desert fringes of the Sahara, vectorial capacity would increase under the worst-case scenario, but not enough to sustain transmission. In the transitional zone of the Sahel, climate change is predicted to decrease vectorial capacity. In the wetter regions to the south, our estimates suggest an increase in vectorial capacity under all scenarios. However, because malaria is already highly endemic among human populations in these regions, we expect that changes in malaria incidence would be small. Our findings highlight the importance of rainfall in shaping the impact of climate change on malaria transmission in future climates. Even under the GCM predictions most conducive to malaria transmission, we do not expect to see a significant increase in malaria prevalence in this region.
Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima; Mader, Helmut; Kraml, Julia
2012-01-01
Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.
NASA Astrophysics Data System (ADS)
Lucas, S. E.
2016-12-01
The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). This poster will present the recently funded CVP projects on improving the understanding Atlantic Meridional Overturning Circulation (AMOC), its impact on decadal predictability, and its relationship with the overall climate system.
NASA Astrophysics Data System (ADS)
Kuleshov, Yuriy; Jones, David; Hendon, Harry; Charles, Andrew; Shelton, Kay; de Wit, Roald; Cottrill, Andrew; Nakaegawa, Toshiyuki; Atalifo, Terry; Prakash, Bipendra; Seuseu, Sunny; Kaniaha, Salesa
2013-04-01
Over the past few years, significant progress in developing climate science for the Pacific has been achieved through a number of research projects undertaken under the Australian government International Climate Change Adaptation Initiative (ICCAI). Climate change has major impact on Pacific Island Countries and advancement in understanding past, present and futures climate in the region is vital for island nation to develop adaptation strategies to their rapidly changing environment. This new science is now supporting new services for a wide range of stakeholders in the Pacific through the National Meteorological Agencies of the region. Seasonal climate prediction is particularly important for planning in agriculture, tourism and other weather-sensitive industries, with operational services provided by all National Meteorological Services in the region. The interaction between climate variability and climate change, for example during droughts or very warm seasons, means that much of the early impacts of climate change are being felt through seasonal variability. A means to reduce these impacts is to improve forecasts to support decision making. Historically, seasonal climate prediction has been developed based on statistical past relationship. Statistical methods relate meteorological variables (e.g. temperature and rainfall) to indices which describe large-scale environment (e.g. ENSO indices) using historical data. However, with observed climate change, statistical approaches based on historical data are getting less accurate and less reliable. Recognising the value of seasonal forecasts, we have used outputs of a dynamical model POAMA (Predictive Ocean Atmosphere Model for Australia), to develop web-based information tools (http://poama.bom.gov.au/experimental/pasap/index.shtml) which are now used by climate services in 15 partner countries in the Pacific for preparing seasonal climate outlooks. Initial comparison conducted during 2012 has shown that the predictive skill of POAMA is consistently higher than skill of statistical-based method. Presently, under the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program, we are developing dynamical model-based seasonal climate prediction for climate extremes. Of particular concern are tropical cyclones which are the most destructive weather systems that impact on coastal areas of Australia and Pacific Island Countries. To analyse historical cyclone data, we developed a consolidate archive for the Southern Hemisphere and North-Western Pacific (http://www.bom.gov.au/cyclone/history/tracks/). Using dynamical climate models (POAMA and Japan Meteorological Agency's model), we work on improving accuracy of seasonal forecasts of tropical cyclone activity for the regions of Western Pacific. Improved seasonal climate prediction based on dynamical models will further enhance climate services in Australia and Pacific Island Countries.
Integrating environmental and genetic effects to predict responses of tree populations to climate.
Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N
2010-01-01
Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.
Prediction technologies for assessment of climate change impacts
USDA-ARS?s Scientific Manuscript database
Temperatures, precipitation, and weather patterns are changing, in response to increasing carbon dioxide in the atmosphere. With these relatively rapid changes, existing soil erosion prediction technologies that rely upon climate stationarity are potentially becoming less reliable. This is especiall...
A multi-model framework for simulating wildlife population response to land-use and climate change
McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.
2008-01-01
Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.
Population response to climate change: linear vs. non-linear modeling approaches.
Ellis, Alicia M; Post, Eric
2004-03-31
Research on the ecological consequences of global climate change has elicited a growing interest in the use of time series analysis to investigate population dynamics in a changing climate. Here, we compare linear and non-linear models describing the contribution of climate to the density fluctuations of the population of wolves on Isle Royale, Michigan from 1959 to 1999. The non-linear self excitatory threshold autoregressive (SETAR) model revealed that, due to differences in the strength and nature of density dependence, relatively small and large populations may be differentially affected by future changes in climate. Both linear and non-linear models predict a decrease in the population of wolves with predicted changes in climate. Because specific predictions differed between linear and non-linear models, our study highlights the importance of using non-linear methods that allow the detection of non-linearity in the strength and nature of density dependence. Failure to adopt a non-linear approach to modelling population response to climate change, either exclusively or in addition to linear approaches, may compromise efforts to quantify ecological consequences of future warming.
Means and extremes: building variability into community-level climate change experiments.
Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula
2013-06-01
Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.
NASA Astrophysics Data System (ADS)
Renner, M.; Bernhofer, C.
2011-12-01
The prediction of climate effects on terrestrial ecosystems and water resources is one of the major research questions in hydrology. Conceptual water-energy balance models can be used to gain a first order estimate of how long-term average streamflow is changing with a change in water and energy supply. A common framework for investigation of this question is based on the Budyko hypothesis, which links hydrological response to aridity. Recently, Renner et al. (2011) introduced the CCUW hypothesis, which is based on the assumption that the total efficiency of the catchment ecosystem to use the available water and energy for actual evapotranspiration remains constant even under climate changes. Here, we confront the climate sensitivity approaches (including several versions of Budyko's approach and the CCUW) with data of more than 400 basins distributed over the continental United States. We first map an estimate of the sensitivity of streamflow to changes in precipitation using long-term average data of the period 1949-2003. This provides a hydro-climatic status of the respective basins as well as their expected proportional effect on changes in climate. Next, by splitting the data in two periods, we (i) analyse the long-term average changes in hydro-climatolgy, we (ii) use the different climate sensitivity methods to predict the change in streamflow given the observed changes in water and energy supply and (iii) we apply a quantitative approach to separate the impacts of changes in the long-term average climate from basin characteristics change on streamflow. This allows us to evaluate the observed changes in streamflow as well as to evaluate the impact of basin changes on the validity of climate sensitivity approaches. The apparent increase of streamflow in the majority of basins in the US is dominated by a climate trend towards increased humidity. It is further evident that impacts of changes in basin characteristics appear in parallel with climate changes. There are coherent spatial patterns with basins of increasing catchment efficiency being dominant in the western and central parts of the US. A hot spot of decreasing efficiency is found within the US Midwest. The impact of basin changes on the prediction is large and can be twice as the observed change signal. However, we find that both, the CCUW hypothesis and the approaches using the Budyko hypothesis, show minimal deviations between observed and predicted changes in streamflow for basins where a dominance of climatic changes and low influences of basin changes have been found. Thus, climate sensitivity methods can be regarded as valid tools if we expect climate changes only and neglect any direct anthropogenic influences.
Merrill, Scott C; Peairs, Frank B
2017-02-01
Models describing the effects of climate change on arthropod pest ecology are needed to help mitigate and adapt to forthcoming changes. Challenges arise because climate data are at resolutions that do not readily synchronize with arthropod biology. Here we explain how multiple sources of climate and weather data can be synthesized to quantify the effects of climate change on pest phenology. Predictions of phenological events differ substantially between models that incorporate scale-appropriate temperature variability and models that do not. As an illustrative example, we predicted adult emergence of a pest of sunflower, the sunflower stem weevil Cylindrocopturus adspersus (LeConte). Predictions of the timing of phenological events differed by an average of 11 days between models with different temperature variability inputs. Moreover, as temperature variability increases, developmental rates accelerate. Our work details a phenological modeling approach intended to help develop tools to plan for and mitigate the effects of climate change. Results show that selection of scale-appropriate temperature data is of more importance than selecting a climate change emission scenario. Predictions derived without appropriate temperature variability inputs will likely result in substantial phenological event miscalculations. Additionally, results suggest that increased temperature instability will lead to accelerated pest development. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.
WEPPCAT is an on-line tool that provides a flexible capability for creating user-determined climate change scenarios for assessing the potential impacts of climate change on sediment loading to streams using the USDA’s Water Erosion Prediction Project (WEPP) Model. In combination...
Amburgey, Staci M.; Miller, David A. W.; Grant, Evan H. Campbell; Rittenhouse, Tracy A. G.; Benard, Michael F.; Richardson, Jonathan L.; Urban, Mark C.; Hughson, Ward; Brand, Adrianne B,; Davis, Christopher J.; Hardin, Carmen R.; Paton, Peter W. C.; Raithel, Christopher J.; Relyea, Rick A.; Scott, A. Floyd; Skelly, David K.; Skidds, Dennis E.; Smith, Charles K.; Werner, Earl E.
2018-01-01
Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs (Lithobates sylvaticus) in North America. Using long-term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long-term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species-interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate.
Nielsen, Uffe N; Wall, Diana H
2013-03-01
The polar regions are experiencing rapid climate change with implications for terrestrial ecosystems. Here, despite limited knowledge, we make some early predictions on soil invertebrate community responses to predicted twenty-first century climate change. Geographic and environmental differences suggest that climate change responses will differ between the Arctic and Antarctic. We predict significant, but different, belowground community changes in both regions. This change will be driven mainly by vegetation type changes in the Arctic, while communities in Antarctica will respond to climate amelioration directly and indirectly through changes in microbial community composition and activity, and the development of, and/or changes in, plant communities. Climate amelioration is likely to allow a greater influx of non-native species into both the Arctic and Antarctic promoting landscape scale biodiversity change. Non-native competitive species could, however, have negative effects on local biodiversity particularly in the Arctic where the communities are already species rich. Species ranges will shift in both areas as the climate changes potentially posing a problem for endemic species in the Arctic where options for northward migration are limited. Greater soil biotic activity may move the Arctic towards a trajectory of being a substantial carbon source, while Antarctica could become a carbon sink. © 2013 Blackwell Publishing Ltd/CNRS.
Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost
2012-02-01
We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The 'evolving metacommunity' framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats.
Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost
2012-01-01
We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The ‘evolving metacommunity’ framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats. PMID:25568038
ERIC Educational Resources Information Center
Barwell, Richard
2013-01-01
Climate change is one of the most pressing issues of the 21st Century. Mathematics is involved at every level of understanding climate change, including the description, prediction and communication of climate change. As a highly complex issue, climate change is an example of "post-normal" science -- it is urgent, complex and involves a…
Inman, Richard D.; Esque, Todd C.; Nussear, Kenneth E.; Leitner, Philip; Matocq, Marjorie D.; Weisberg, Peter J.; Dilts, Thomas E.
2016-01-01
Predicting changes in species distributions under a changing climate is becoming widespread with the use of species distribution models (SDMs). The resulting predictions of future potential habitat can be cast in light of planned land use changes, such as urban expansion and energy development to identify areas with potential conflict. However, SDMs rarely incorporate an understanding of dispersal capacity, and therefore assume unlimited dispersal in potential range shifts under uncertain climate futures. We use SDMs to predict future distributions of the Mojave ground squirrel, Xerospermophilus mohavensis Merriam, and incorporate partial dispersal models informed by field data on juvenile dispersal to assess projected impact of climate change and energy development on future distributions of X. mohavensis. Our models predict loss of extant habitat, but also concurrent gains of new habitat under two scenarios of future climate change. Under the B1 emissions scenario- a storyline describing a convergent world with emphasis on curbing greenhouse gas emissions- our models predicted losses of up to 64% of extant habitat by 2080, while under the increased greenhouse gas emissions of the A2 scenario, we suggest losses of 56%. New potential habitat may become available to X. mohavensis, thereby offsetting as much as 6330 km2 (50%) of the current habitat lost. Habitat lost due to planned energy development was marginal compared to habitat lost from changing climates, but disproportionately affected current habitat. Future areas of overlap in potential habitat between the two climate change scenarios are identified and discussed in context of proposed energy development.
Evaluating Urban Resilience to Climate Change: A Multi-Sector Approach (External Review Draft)
Climate change impacts are diverse, long-term, and not easily predictable. Adapting to climate change requires making context specific and forward-looking decisions regarding a variety of climate change impacts and vulnerabilities when the future is highly uncertain. EPA scientis...
Predicting Vulnerabilities of North American Shorebirds to Climate Change
Galbraith, Hector; DesRochers, David W.; Brown, Stephen; Reed, J. Michael
2014-01-01
Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at–risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners–in–Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90%) taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower–risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change. PMID:25268907
Predicting vulnerabilities of North American shorebirds to climate change.
Galbraith, Hector; DesRochers, David W; Brown, Stephen; Reed, J Michael
2014-01-01
Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at-risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners-in-Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90%) taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower-risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change.
The Rate of Seasonal Changes in Temperature Alters Acclimation of Performance under Climate Change.
Nilsson-Örtman, Viktor; Johansson, Frank
2017-12-01
How the ability to acclimate will impact individual performance and ecological interactions under climate change remains poorly understood. Theory predicts that the benefit an organism can gain from acclimating depends on the rate at which temperatures change relative to the time it takes to induce beneficial acclimation. Here, we present a conceptual model showing how slower seasonal changes under climate change can alter species' relative performance when they differ in acclimation rate and magnitude. To test predictions from theory, we performed a microcosm experiment where we reared a mid- and a high-latitude damselfly species alone or together under the rapid seasonality currently experienced at 62°N and the slower seasonality predicted for this latitude under climate change and measured larval growth and survival. To separate acclimation effects from fixed thermal responses, we simulated growth trajectories based on species' growth rates at constant temperatures and quantified how much and how fast species needed to acclimate to match the observed growth trajectories. Consistent with our predictions, the results showed that the midlatitude species had a greater capacity for acclimation than the high-latitude species. Furthermore, since acclimation occurred at a slower rate than seasonal temperature changes, the midlatitude species had a small growth advantage over the high-latitude species under the current seasonality but a greater growth advantage under the slower seasonality predicted for this latitude under climate change. In addition, the two species did not differ in survival under the current seasonality, but the midlatitude species had higher survival under the predicted climate change scenario, possibly because rates of cannibalism were lower when smaller heterospecifics were present. These findings highlight the need to incorporate acclimation rates in ecological models.
Data-Conditioned Distributions of Groundwater Recharge Under Climate Change Scenarios
NASA Astrophysics Data System (ADS)
McLaughlin, D.; Ng, G. C.; Entekhabi, D.; Scanlon, B.
2008-12-01
Groundwater recharge is likely to be impacted by climate change, with changes in precipitation amounts altering moisture availability and changes in temperature affecting evaporative demand. This could have major implications for sustainable aquifer pumping rates and contaminant transport into groundwater reservoirs in the future, thus making predictions of recharge under climate change very important. Unfortunately, in dry environments where groundwater resources are often most critical, low recharge rates are difficult to resolve due to high sensitivity to modeling and input errors. Some recent studies on climate change and groundwater have considered recharge using a suite of general circulation model (GCM) weather predictions, an obvious and key source of uncertainty. This work extends beyond those efforts by also accounting for uncertainty in other land-surface model inputs in a probabilistic manner. Recharge predictions are made using a range of GCM projections for a rain-fed cotton site in the semi-arid Southern High Plains region of Texas. Results showed that model simulations using a range of unconstrained literature-based parameter values produce highly uncertain and often misleading recharge rates. Thus, distributional recharge predictions are found using soil and vegetation parameters conditioned on current unsaturated zone soil moisture and chloride concentration observations; assimilation of observations is carried out with an ensemble importance sampling method. Our findings show that the predicted distribution shapes can differ for the various GCM conditions considered, underscoring the importance of probabilistic analysis over deterministic simulations. The recharge predictions indicate that the temporal distribution (over seasons and rain events) of climate change will be particularly critical for groundwater impacts. Overall, changes in recharge amounts and intensity were often more pronounced than changes in annual precipitation and temperature, thus suggesting high susceptibility of groundwater systems to future climate change. Our approach provides a probabilistic sensitivity analysis of recharge under potential climate changes, which will be critical for future management of water resources.
Lambert, Emily; Pierce, Graham J; Hall, Karen; Brereton, Tom; Dunn, Timothy E; Wall, Dave; Jepson, Paul D; Deaville, Rob; MacLeod, Colin D
2014-06-01
There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio-climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs "hindcasting" of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species-specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white-beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time-scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies. © 2014 John Wiley & Sons Ltd.
Niraula, Rewati; Meixner, Thomas; Norman, Laura M.
2015-01-01
Land use/land cover (LULC) and climate changes are important drivers of change in streamflow. Assessing the impact of LULC and climate changes on streamflow is typically done with a calibrated and validated watershed model. However, there is a debate on the degree of calibration required. The objective of this study was to quantify the variation in estimated relative and absolute changes in streamflow associated with LULC and climate changes with different calibration approaches. The Soil and Water Assessment Tool (SWAT) was applied in an uncalibrated (UC), single outlet calibrated (OC), and spatially-calibrated (SC) mode to compare the relative and absolute changes in streamflow at 14 gaging stations within the Santa Cruz River Watershed in southern Arizona, USA. For this purpose, the effect of 3 LULC, 3 precipitation (P), and 3 temperature (T) scenarios were tested individually. For the validation period, Percent Bias (PBIAS) values were >100% with the UC model for all gages, the values were between 0% and 100% with the OC model and within 20% with the SC model. Changes in streamflow predicted with the UC and OC models were compared with those of the SC model. This approach implicitly assumes that the SC model is “ideal”. Results indicated that the magnitude of both absolute and relative changes in streamflow due to LULC predicted with the UC and OC results were different than those of the SC model. The magnitude of absolute changes predicted with the UC and SC models due to climate change (both P and T) were also significantly different, but were not different for OC and SC models. Results clearly indicated that relative changes due to climate change predicted with the UC and OC were not significantly different than that predicted with the SC models. This result suggests that it is important to calibrate the model spatially to analyze the effect of LULC change but not as important for analyzing the relative change in streamflow due to climate change. This study also indicated that model calibration in not necessary to determine the direction of change in streamflow due to LULC and climate change.
CLIMATE CHANGE IN THAILAND AND ITS POTENTIAL IMPACT ON RICE YIELD
Because of the uncertainties surrounding prediction of climate change, it is common to employ climate scenarios to estimate its impacts on a system. Climate scenarios are sets of climatic perturbations used with models to test system sensitivity to projected changes. In this stud...
Predicting responses to climate change requires all life-history stages.
Zeigler, Sara
2013-01-01
In Focus: Radchuk, V., Turlure, C. & Schtickzelle, N. (2013) Each life stage matters: the importance of assessing response to climate change over the complete life cycle in butterflies. Journal of Animal Ecology, 82, 275-285. Population-level responses to climate change depend on many factors, including unexpected interactions among life history attributes; however, few studies examine climate change impacts over complete life cycles of focal species. Radchuk, Turlure & Schtickzelle () used experimental and modelling approaches to predict population dynamics for the bog fritillary butterfly under warming scenarios. Although they found that warming improved fertility and survival of all stages with one exception, populations were predicted to decline because overwintering larvae, whose survival declined with warming, were disproportionately important contributors to population growth. This underscores the importance of considering all life history stages in analyses of climate change's effects on population dynamics. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.
Fordham, Damien A; Mellin, Camille; Russell, Bayden D; Akçakaya, Reşit H; Bradshaw, Corey J A; Aiello-Lammens, Matthew E; Caley, Julian M; Connell, Sean D; Mayfield, Stephen; Shepherd, Scoresby A; Brook, Barry W
2013-10-01
Evidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. © 2013 John Wiley & Sons Ltd.
Assessing vulnerability of giant pandas to climate change in the Qinling Mountains of China.
Li, Jia; Liu, Fang; Xue, Yadong; Zhang, Yu; Li, Diqiang
2017-06-01
Climate change might pose an additional threat to the already vulnerable giant panda ( Ailuropoda melanoleuca ). Effective conservation efforts require projections of vulnerability of the giant panda in facing climate change and proactive strategies to reduce emerging climate-related threats. We used the maximum entropy model to assess the vulnerability of giant panda to climate change in the Qinling Mountains of China. The results of modeling included the following findings: (1) the area of suitable habitat for giant pandas was projected to decrease by 281 km 2 from climate change by the 2050s; (2) the mean elevation of suitable habitat of giant panda was predicted to shift 30 m higher due to climate change over this period; (3) the network of nature reserves protect 61.73% of current suitable habitat for the species, and 59.23% of future suitable habitat; (4) current suitable habitat mainly located in Chenggu, Taibai, and Yangxian counties (with a total area of 987 km 2 ) was predicted to be vulnerable. Assessing the vulnerability of giant panda provided adaptive strategies for conservation programs and national park construction. We proposed adaptation strategies to ameliorate the predicted impacts of climate change on giant panda, including establishing and adjusting reserves, establishing habitat corridors, improving adaptive capacity to climate change, and strengthening monitoring of giant panda.
A new framework for climate sensitivity and prediction: a modelling perspective
NASA Astrophysics Data System (ADS)
Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank
2016-03-01
The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time-scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's response theory to predict the impact of an arbitrary CO2 forcing scenario on the global surface temperature of a general circulation model. Response theory puts the concept of climate sensitivity on firm theoretical grounds, and addresses rigorously the problem of predictability at different time-scales. Conceptually, these results show that performing climate change experiments with general circulation models is a well defined problem from a physical and mathematical point of view. Practically, these results show that considering one single CO2 forcing scenario is enough to construct operators able to predict the response of climatic observables to any other CO2 forcing scenario, without the need to perform additional numerical simulations. We also introduce a general relationship between climate sensitivity and climate response at different time scales, thus providing an explicit definition of the inertia of the system at different time scales. This technique allows also for studying systematically, for a large variety of forcing scenarios, the time horizon at which the climate change signal (in an ensemble sense) becomes statistically significant. While what we report here refers to the linear response, the general theory allows for treating nonlinear effects as well. These results pave the way for redesigning and interpreting climate change experiments from a radically new perspective.
Predicting future coexistence in a North American ant community
Bewick, Sharon; Stuble, Katharine L; Lessard, Jean-Phillipe; Dunn, Robert R; Adler, Frederick R; Sanders, Nathan J
2014-01-01
Global climate change will remodel ecological communities worldwide. However, as a consequence of biotic interactions, communities may respond to climate change in idiosyncratic ways. This makes predictive models that incorporate biotic interactions necessary. We show how such models can be constructed based on empirical studies in combination with predictions or assumptions regarding the abiotic consequences of climate change. Specifically, we consider a well-studied ant community in North America. First, we use historical data to parameterize a basic model for species coexistence. Using this model, we determine the importance of various factors, including thermal niches, food discovery rates, and food removal rates, to historical species coexistence. We then extend the model to predict how the community will restructure in response to several climate-related changes, such as increased temperature, shifts in species phenology, and altered resource availability. Interestingly, our mechanistic model suggests that increased temperature and shifts in species phenology can have contrasting effects. Nevertheless, for almost all scenarios considered, we find that the most subordinate ant species suffers most as a result of climate change. More generally, our analysis shows that community composition can respond to climate warming in nonintuitive ways. For example, in the context of a community, it is not necessarily the most heat-sensitive species that are most at risk. Our results demonstrate how models that account for niche partitioning and interspecific trade-offs among species can be used to predict the likely idiosyncratic responses of local communities to climate change. PMID:24963378
Climate change and vector-borne diseases of public health significance.
Ogden, Nicholas H
2017-10-16
There has been much debate as to whether or not climate change will have, or has had, any significant effect on risk from vector-borne diseases. The debate on the former has focused on the degree to which occurrence and levels of risk of vector-borne diseases are determined by climate-dependent or independent factors, while the debate on the latter has focused on whether changes in disease incidence are due to climate at all, and/or are attributable to recent climate change. Here I review possible effects of climate change on vector-borne diseases, methods used to predict these effects and the evidence to date of changes in vector-borne disease risks that can be attributed to recent climate change. Predictions have both over- and underestimated the effects of climate change. Mostly under-estimations of effects are due to a focus only on direct effects of climate on disease ecology while more distal effects on society's capacity to control and prevent vector-borne disease are ignored. There is increasing evidence for possible impacts of recent climate change on some vector-borne diseases but for the most part, observed data series are too short (or non-existent), and impacts of climate-independent factors too great, to confidently attribute changing risk to climate change. © Crown copyright 2017.
Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions
Fox, Naomi J.; Marion, Glenn; Davidson, Ross S.; White, Piran C. L.; Hutchings, Michael R.
2012-01-01
Simple Summary Parasitic helminths represent one of the most pervasive challenges to livestock, and their intensity and distribution will be influenced by climate change. There is a need for long-term predictions to identify potential risks and highlight opportunities for control. We explore the approaches to modelling future helminth risk to livestock under climate change. One of the limitations to model creation is the lack of purpose driven data collection. We also conclude that models need to include a broad view of the livestock system to generate meaningful predictions. Abstract Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed. PMID:26486780
NASA Astrophysics Data System (ADS)
Werth, D. W.; O'Steen, L.; Chen, K.; Altinakar, M. S.; Garrett, A.; Aleman, S.; Ramalingam, V.
2010-12-01
Global climate change has the potential for profound impacts on society, and poses significant challenges to government and industry in the areas of energy security and sustainability. Given that the ability to exploit energy resources often depends on the climate, the possibility of climate change means we cannot simply assume that the untapped potential of today will still exist in the future. Predictions of future climate are generally based on global climate models (GCMs) which, due to computational limitations, are run at spatial resolutions of hundreds of kilometers. While the results from these models can predict climatic trends averaged over large spatial and temporal scales, their ability to describe the effects of atmospheric phenomena that affect weather on regional to local scales is inadequate. We propose the use of several optimized statistical downscaling techniques that can infer climate change at the local scale from coarse resolution GCM predictions, and apply the results to assess future sustainability for two sources of energy production dependent on adequate water resources: nuclear power (through the dissipation of waste heat from cooling towers, ponds, etc.) and hydroelectric power. All methods will be trained with 20th century data, and applied to data from the years 2040-2049 to get the local-scale changes. Models of cooling tower operation and hydropower potential will then use the downscaled data to predict the possible changes in energy production, and the implications of climate change on plant siting, design, and contribution to the future energy grid can then be examined.
How Do Marine Pelagic Species Respond to Climate Change? Theories and Observations
NASA Astrophysics Data System (ADS)
Beaugrand, Grégory; Kirby, Richard R.
2018-01-01
In this review, we show how climate affects species, communities, and ecosystems, and why many responses from the species to the biome level originate from the interaction between the species’ ecological niche and changes in the environmental regime in both space and time. We describe a theory that allows us to understand and predict how marine species react to climate-induced changes in ecological conditions, how communities form and are reconfigured, and so how biodiversity is arranged and may respond to climate change. Our study shows that the responses of species to climate change are therefore intelligible—that is, they have a strong deterministic component and can be predicted.
Howe, P D; Bryant, S R; Shreeve, T G
2007-10-01
We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.
The predictive state: Science, territory and the future of the Indian climate.
Mahony, Martin
2014-02-01
Acts of scientific calculation have long been considered central to the formation of the modern nation state, yet the transnational spaces of knowledge generation and political action associated with climate change seem to challenge territorial modes of political order. This article explores the changing geographies of climate prediction through a study of the ways in which climate change is rendered knowable at the national scale in India. The recent controversy surrounding an erroneous prediction of melting Himalayan glaciers by the Intergovernmental Panel on Climate Change provides a window onto the complex and, at times, antagonistic relationship between the Panel and Indian political and scientific communities. The Indian reaction to the error, made public in 2009, drew upon a national history of contestation around climate change science and corresponded with the establishment of a scientific assessment network, the Indian Network for Climate Change Assessment, which has given the state a new platform on which to bring together knowledge about the future climate. I argue that the Indian Network for Climate Change Assessment is indicative of the growing use of regional climate models within longer traditions of national territorial knowledge-making, allowing a rescaling of climate change according to local norms and practices of linking scientific knowledge to political action. I illustrate the complex co-production of the epistemic and the normative in climate politics, but also seek to show how co-productionist understandings of science and politics can function as strategic resources in the ongoing negotiation of social order. In this case, scientific rationalities and modes of environmental governance contribute to the contested epistemic construction of territory and the evolving spatiality of the modern nation state under a changing climate.
Uribe-Rivera, David E; Soto-Azat, Claudio; Valenzuela-Sánchez, Andrés; Bizama, Gustavo; Simonetti, Javier A; Pliscoff, Patricio
2017-07-01
Climate change is a major threat to biodiversity; the development of models that reliably predict its effects on species distributions is a priority for conservation biogeography. Two of the main issues for accurate temporal predictions from Species Distribution Models (SDM) are model extrapolation and unrealistic dispersal scenarios. We assessed the consequences of these issues on the accuracy of climate-driven SDM predictions for the dispersal-limited Darwin's frog Rhinoderma darwinii in South America. We calibrated models using historical data (1950-1975) and projected them across 40 yr to predict distribution under current climatic conditions, assessing predictive accuracy through the area under the ROC curve (AUC) and True Skill Statistics (TSS), contrasting binary model predictions against temporal-independent validation data set (i.e., current presences/absences). To assess the effects of incorporating dispersal processes we compared the predictive accuracy of dispersal constrained models with no dispersal limited SDMs; and to assess the effects of model extrapolation on the predictive accuracy of SDMs, we compared this between extrapolated and no extrapolated areas. The incorporation of dispersal processes enhanced predictive accuracy, mainly due to a decrease in the false presence rate of model predictions, which is consistent with discrimination of suitable but inaccessible habitat. This also had consequences on range size changes over time, which is the most used proxy for extinction risk from climate change. The area of current climatic conditions that was absent in the baseline conditions (i.e., extrapolated areas) represents 39% of the study area, leading to a significant decrease in predictive accuracy of model predictions for those areas. Our results highlight (1) incorporating dispersal processes can improve predictive accuracy of temporal transference of SDMs and reduce uncertainties of extinction risk assessments from global change; (2) as geographical areas subjected to novel climates are expected to arise, they must be reported as they show less accurate predictions under future climate scenarios. Consequently, environmental extrapolation and dispersal processes should be explicitly incorporated to report and reduce uncertainties in temporal predictions of SDMs, respectively. Doing so, we expect to improve the reliability of the information we provide for conservation decision makers under future climate change scenarios. © 2017 by the Ecological Society of America.
NASA Astrophysics Data System (ADS)
Daron, Joseph
2010-05-01
Exploring the reliability of model based projections is an important pre-cursor to evaluating their societal relevance. In order to better inform decisions concerning adaptation (and mitigation) to climate change, we must investigate whether or not our models are capable of replicating the dynamic nature of the climate system. Whilst uncertainty is inherent within climate prediction, establishing and communicating what is plausible as opposed to what is likely is the first step to ensuring that climate sensitive systems are robust to climate change. Climate prediction centers are moving towards probabilistic projections of climate change at regional and local scales (Murphy et al., 2009). It is therefore important to understand what a probabilistic forecast means for a chaotic nonlinear dynamic system that is subject to changing forcings. It is in this context that we present the results of experiments using simple models that can be considered analogous to the more complex climate system, namely the Lorenz 1963 and Lorenz 1984 models (Lorenz, 1963; Lorenz, 1984). Whilst the search for a low-dimensional climate attractor remains illusive (Fraedrich, 1986; Sahay and Sreenivasan, 1996) the characterization of the climate system in such terms can be useful for conceptual and computational simplicity. Recognising that a change in climate is manifest in a change in the distribution of a particular climate variable (Stainforth et al., 2007), we first establish the equilibrium distributions of the Lorenz systems for certain parameter settings. Allowing the parameters to vary in time, we investigate the dependency of such distributions to initial conditions and discuss the implications for climate prediction. We argue that the role of chaos and nonlinear dynamic behaviour ought to have more prominence in the discussion of the forecasting capabilities in climate prediction. References: Fraedrich, K. Estimating the dimensions of weather and climate attractors. J. Atmos. Sci, 43, 419-432, 1986. Lorenz, E. N. Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130-141, 1963. Lorenz, E. N. Irregularity: a fundamental property of the atmosphere. Tellus, 36A, 98-110, 1984. Murphy, J. M., D. M. H. Sexton, G. J. Jenkins, B. B. B. Booth, C. C. Brown, R. T. Clark, M. Collins, G. R. Harris, E. J. Kendon, R. A. Betts, S. J. Brown, P. Boorman, T. P. Howard, K. A. Humphrey, M. P. McCarthy, R. E. McDonald, A. Stephens, C. Wallace, R. Warren, R. Wilby, and R. A. Wood. Uk climate projections science report: Climate change projections. 2009. Sahay, A. and K. R. Sreenivasan. The search for a low-dimensional characterization of a local climate system. Phil. Trans. R. Soc. A., 354, 1715-1750, 1996. Stainforth, D. A., M. R. Allen, E. R. Tredger, and L. A. Smith. Confidence, uncertainty and decision-support relevance in climate predictions. Phil. Trans. R. Soc. A, 365, 2145-2161, 2007.
Elise Pendall; Lindsey Rustad; Josh Schimel
2008-01-01
Belowground processes, including root production and exudation, microbial activity and community dynamics, and biogeochemical cycling interact to help regulate climate change. Feedbacks associated with these processes, such as warming-enhanced decomposition rates, give rise to major uncertainties in predictions of future climate. Uncertainties associated with these...
Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C
2016-01-01
Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.
Negative impacts of climate change on cereal yields: statistical evidence from France
NASA Astrophysics Data System (ADS)
Gammans, Matthew; Mérel, Pierre; Ortiz-Bobea, Ariel
2017-05-01
In several world regions, climate change is predicted to negatively affect crop productivity. The recent statistical yield literature emphasizes the importance of flexibly accounting for the distribution of growing-season temperature to better represent the effects of warming on crop yields. We estimate a flexible statistical yield model using a long panel from France to investigate the impacts of temperature and precipitation changes on wheat and barley yields. Winter varieties appear sensitive to extreme cold after planting. All yields respond negatively to an increase in spring-summer temperatures and are a decreasing function of precipitation about historical precipitation levels. Crop yields are predicted to be negatively affected by climate change under a wide range of climate models and emissions scenarios. Under warming scenario RCP8.5 and holding growing areas and technology constant, our model ensemble predicts a 21.0% decline in winter wheat yield, a 17.3% decline in winter barley yield, and a 33.6% decline in spring barley yield by the end of the century. Uncertainty from climate projections dominates uncertainty from the statistical model. Finally, our model predicts that continuing technology trends would counterbalance most of the effects of climate change.
DOT National Transportation Integrated Search
2010-10-05
The scope, severity, and pace of : future climate change impacts are : difficult to predict. However, : observations and long-term scientific : trends indicate that the potential : impacts of a changing climate on : society and the environment will b...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-10-31
... effects of climate change on wolverines in the future. Our assessment of climate change impacts on wolverines used wolverines' snow dependence and suitable wolverine habitat and climate change models to predict future impacts of climate change on wolverine habitat suitability. Some of the commenters...
A review of climate change effects on terrestrial rangeland birds
D. M. Finch; K. E. Bagne; M. M. Friggens; D. M. Smith; K. M. Brodhead
2011-01-01
We evaluated existing literature on predicted and known climate change effects on terrestrial rangeland birds. We asked the following questions: 1) How does climate change affect birds? 2) How will birds respond to climate change? 3) Are species already responding? 4) How will habitats be impacted?
Huang, Jian-Guo; Bergeron, Yves; Berninger, Frank; Zhai, Lihong; Tardif, Jacques C.; Denneler, Bernhard
2013-01-01
Immediate phenotypic variation and the lagged effect of evolutionary adaptation to climate change appear to be two key processes in tree responses to climate warming. This study examines these components in two types of growth models for predicting the 2010–2099 diameter growth change of four major boreal species Betula papyrifera, Pinus banksiana, Picea mariana, and Populus tremuloides along a broad latitudinal gradient in eastern Canada under future climate projections. Climate-growth response models for 34 stands over nine latitudes were calibrated and cross-validated. An adaptive response model (A-model), in which the climate-growth relationship varies over time, and a fixed response model (F-model), in which the relationship is constant over time, were constructed to predict future growth. For the former, we examined how future growth of stands in northern latitudes could be forecasted using growth-climate equations derived from stands currently growing in southern latitudes assuming that current climate in southern locations provide an analogue for future conditions in the north. For the latter, we tested if future growth of stands would be maximally predicted using the growth-climate equation obtained from the given local stand assuming a lagged response to climate due to genetic constraints. Both models predicted a large growth increase in northern stands due to more benign temperatures, whereas there was a minimal growth change in southern stands due to potentially warm-temperature induced drought-stress. The A-model demonstrates a changing environment whereas the F-model highlights a constant growth response to future warming. As time elapses we can predict a gradual transition between a response to climate associated with the current conditions (F-model) to a more adapted response to future climate (A-model). Our modeling approach provides a template to predict tree growth response to climate warming at mid-high latitudes of the Northern Hemisphere. PMID:23468879
Huang, Jian-Guo; Bergeron, Yves; Berninger, Frank; Zhai, Lihong; Tardif, Jacques C; Denneler, Bernhard
2013-01-01
Immediate phenotypic variation and the lagged effect of evolutionary adaptation to climate change appear to be two key processes in tree responses to climate warming. This study examines these components in two types of growth models for predicting the 2010-2099 diameter growth change of four major boreal species Betula papyrifera, Pinus banksiana, Picea mariana, and Populus tremuloides along a broad latitudinal gradient in eastern Canada under future climate projections. Climate-growth response models for 34 stands over nine latitudes were calibrated and cross-validated. An adaptive response model (A-model), in which the climate-growth relationship varies over time, and a fixed response model (F-model), in which the relationship is constant over time, were constructed to predict future growth. For the former, we examined how future growth of stands in northern latitudes could be forecasted using growth-climate equations derived from stands currently growing in southern latitudes assuming that current climate in southern locations provide an analogue for future conditions in the north. For the latter, we tested if future growth of stands would be maximally predicted using the growth-climate equation obtained from the given local stand assuming a lagged response to climate due to genetic constraints. Both models predicted a large growth increase in northern stands due to more benign temperatures, whereas there was a minimal growth change in southern stands due to potentially warm-temperature induced drought-stress. The A-model demonstrates a changing environment whereas the F-model highlights a constant growth response to future warming. As time elapses we can predict a gradual transition between a response to climate associated with the current conditions (F-model) to a more adapted response to future climate (A-model). Our modeling approach provides a template to predict tree growth response to climate warming at mid-high latitudes of the Northern Hemisphere.
Evaluating models of climate and forest vegetation
NASA Technical Reports Server (NTRS)
Clark, James S.
1992-01-01
Understanding how the biosphere may respond to increasing trace gas concentrations in the atmosphere requires models that contain vegetation responses to regional climate. Most of the processes ecologists study in forests, including trophic interactions, nutrient cycling, and disturbance regimes, and vital components of the world economy, such as forest products and agriculture, will be influenced in potentially unexpected ways by changing climate. These vegetation changes affect climate in the following ways: changing C, N, and S pools; trace gases; albedo; and water balance. The complexity of the indirect interactions among variables that depend on climate, together with the range of different space/time scales that best describe these processes, make the problems of modeling and prediction enormously difficult. These problems of predicting vegetation response to climate warming and potential ways of testing model predictions are the subjects of this chapter.
Mustonen, Kaisa-Riikka; Mykrä, Heikki; Marttila, Hannu; Sarremejane, Romain; Veijalainen, Noora; Sippel, Kalle; Muotka, Timo; Hawkins, Charles P
2018-06-01
Air temperature at the northernmost latitudes is predicted to increase steeply and precipitation to become more variable by the end of the 21st century, resulting in altered thermal and hydrological regimes. We applied five climate scenarios to predict the future (2070-2100) benthic macroinvertebrate assemblages at 239 near-pristine sites across Finland (ca. 1200 km latitudinal span). We used a multitaxon distribution model with air temperature and modeled daily flow as predictors. As expected, projected air temperature increased the most in northernmost Finland. Predicted taxonomic richness also increased the most in northern Finland, congruent with the predicted northwards shift of many species' distributions. Compositional changes were predicted to be high even without changes in richness, suggesting that species replacement may be the main mechanism causing climate-induced changes in macroinvertebrate assemblages. Northern streams were predicted to lose much of the seasonality of their flow regimes, causing potentially marked changes in stream benthic assemblages. Sites with the highest loss of seasonality were predicted to support future assemblages that deviate most in compositional similarity from the present-day assemblages. Macroinvertebrate assemblages were also predicted to change more in headwaters than in larger streams, as headwaters were particularly sensitive to changes in flow patterns. Our results emphasize the importance of focusing protection and mitigation on headwater streams with high-flow seasonality because of their vulnerability to climate change. © 2018 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Moorcroft, P. R.; Zhang, K.; Castanho, A. D. D. A.; Galbraith, D.; Moghim, S.; Levine, N. M.; Bras, R. L.; Coe, M. T.; Costa, M. H.; Malhi, Y.; Longo, M.; Knox, R. G.; McKnight, S. L.; Wang, J.
2014-12-01
There is considerable interest and uncertainty regarding the expected fate of the Amazon over the coming century in face of the combined impacts of climate change, rising atmospheric CO2 levels, and on-going land transformation in the region. In this analysis, we explore the fate of Amazonian ecosystems under projected climate, CO2 and land-use change in the 21st century using three state-of-the-art terrestrial biosphere models (ED2, IBIS, and JULES) driven by three representative, bias-corrected GCM climate projections (PCM1, CCSM3, and HadCM3) under the SRES A2 scenario, coupled with two land-use change scenarios. We assess the relative roles of climate change, CO2 fertilization, land-use change, and fire in driving the projected changes in Amazonian biomass and forest extent. Our results indicate that the impacts of climate change depend strongly on the direction and severity of projected changes in precipitation regimes within the region: under the driest climate projection, climate change alone is predicted to reduce Amazonian forest cover by an average of 14%; however, the models predict that CO2 fertilization will enhance vegetation productivity and alleviate climate-induced increases in plant water stress, and as a result sustain high biomass forests, even under the driest climate scenario. Land-use change and changes in fire frequency are predicted cause additional aboveground live biomass loss and changes in forest extent. The relative impact of land-use and fire dynamics versus the impacts of climate and CO2 on the Amazon varies considerably, depending on both the climate and land-use scenarios used and on the terrestrial biosphere model, highlighting the importance of improved understanding of all four factors -- future climate, CO2 fertilization effects, fire and land-use -- to the fate of the Amazon over the coming century.
Climate-FVS Version 2: Content, users guide, applications, and behavior
Nicholas L. Crookston
2014-01-01
Climate change in the 21st Century is projected to cause widespread changes in forest ecosystems. Climate-FVS is a modification to the Forest Vegetation Simulator designed to take climate change into account when predicting forest dynamics at decadal to century time scales. Individual tree climate viability scores measure the likelihood that the climate at a given...
Contrasted demographic responses facing future climate change in Southern Ocean seabirds.
Barbraud, Christophe; Rivalan, Philippe; Inchausti, Pablo; Nevoux, Marie; Rolland, Virginie; Weimerskirch, Henri
2011-01-01
1. Recent climate change has affected a wide range of species, but predicting population responses to projected climate change using population dynamics theory and models remains challenging, and very few attempts have been made. The Southern Ocean sea surface temperature and sea ice extent are projected to warm and shrink as concentrations of atmospheric greenhouse gases increase, and several top predator species are affected by fluctuations in these oceanographic variables. 2. We compared and projected the population responses of three seabird species living in sub-tropical, sub-Antarctic and Antarctic biomes to predicted climate change over the next 50 years. Using stochastic population models we combined long-term demographic datasets and projections of sea surface temperature and sea ice extent for three different IPCC emission scenarios (from most to least severe: A1B, A2, B1) from general circulation models of Earth's climate. 3. We found that climate mostly affected the probability to breed successfully, and in one case adult survival. Interestingly, frequent nonlinear relationships in demographic responses to climate were detected. Models forced by future predicted climatic change provided contrasted population responses depending on the species considered. The northernmost distributed species was predicted to be little affected by a future warming of the Southern Ocean, whereas steep declines were projected for the more southerly distributed species due to sea surface temperature warming and decrease in sea ice extent. For the most southerly distributed species, the A1B and B1 emission scenarios were respectively the most and less damaging. For the two other species, population responses were similar for all emission scenarios. 4. This is among the first attempts to study the demographic responses for several populations with contrasted environmental conditions, which illustrates that investigating the effects of climate change on core population dynamics is feasible for different populations using a common methodological framework. Our approach was limited to single populations and have neglected population settlement in new favourable habitats or changes in inter-specific relations as a potential response to future climate change. Predictions may be enhanced by merging demographic population models and climatic envelope models. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.
Cold truths: how winter drives responses of terrestrial organisms to climate change.
Williams, Caroline M; Henry, Hugh A L; Sinclair, Brent J
2015-02-01
Winter is a key driver of individual performance, community composition, and ecological interactions in terrestrial habitats. Although climate change research tends to focus on performance in the growing season, climate change is also modifying winter conditions rapidly. Changes to winter temperatures, the variability of winter conditions, and winter snow cover can interact to induce cold injury, alter energy and water balance, advance or retard phenology, and modify community interactions. Species vary in their susceptibility to these winter drivers, hampering efforts to predict biological responses to climate change. Existing frameworks for predicting the impacts of climate change do not incorporate the complexity of organismal responses to winter. Here, we synthesise organismal responses to winter climate change, and use this synthesis to build a framework to predict exposure and sensitivity to negative impacts. This framework can be used to estimate the vulnerability of species to winter climate change. We describe the importance of relationships between winter conditions and performance during the growing season in determining fitness, and demonstrate how summer and winter processes are linked. Incorporating winter into current models will require concerted effort from theoreticians and empiricists, and the expansion of current growing-season studies to incorporate winter. © 2014 The Authors. Biological Reviews © 2014 Cambridge Philosophical Society.
Anderson, Jill T; Inouye, David W; McKinney, Amy M; Colautti, Robert I; Mitchell-Olds, Tom
2012-09-22
Anthropogenic climate change has already altered the timing of major life-history transitions, such as the initiation of reproduction. Both phenotypic plasticity and adaptive evolution can underlie rapid phenological shifts in response to climate change, but their relative contributions are poorly understood. Here, we combine a continuous 38 year field survey with quantitative genetic field experiments to assess adaptation in the context of climate change. We focused on Boechera stricta (Brassicaeae), a mustard native to the US Rocky Mountains. Flowering phenology advanced significantly from 1973 to 2011, and was strongly associated with warmer temperatures and earlier snowmelt dates. Strong directional selection favoured earlier flowering in contemporary environments (2010-2011). Climate change could drive this directional selection, and promote even earlier flowering as temperatures continue to increase. Our quantitative genetic analyses predict a response to selection of 0.2 to 0.5 days acceleration in flowering per generation, which could account for more than 20 per cent of the phenological change observed in the long-term dataset. However, the strength of directional selection and the predicted evolutionary response are likely much greater now than even 30 years ago because of rapidly changing climatic conditions. We predict that adaptation will likely be necessary for long-term in situ persistence in the context of climate change.
Northern protected areas will become important refuges for biodiversity tracking suitable climates.
Berteaux, Dominique; Ricard, Marylène; St-Laurent, Martin-Hugues; Casajus, Nicolas; Périé, Catherine; Beauregard, Frieda; de Blois, Sylvie
2018-03-15
The Northern Biodiversity Paradox predicts that, despite its globally negative effects on biodiversity, climate change will increase biodiversity in northern regions where many species are limited by low temperatures. We assessed the potential impacts of climate change on the biodiversity of a northern network of 1,749 protected areas spread over >600,000 km 2 in Quebec, Canada. Using ecological niche modeling, we calculated potential changes in the probability of occurrence of 529 species to evaluate the potential impacts of climate change on (1) species gain, loss, turnover, and richness in protected areas, (2) representativity of protected areas, and (3) extent of species ranges located in protected areas. We predict a major species turnover over time, with 49% of total protected land area potentially experiencing a species turnover >80%. We also predict increases in regional species richness, representativity of protected areas, and species protection provided by protected areas. Although we did not model the likelihood of species colonising habitats that become suitable as a result of climate change, northern protected areas should ultimately become important refuges for species tracking climate northward. This is the first study to examine in such details the potential effects of climate change on a northern protected area network.
Predicting effects of climate change on the composition and function of soil microbial communities
NASA Astrophysics Data System (ADS)
Dubinsky, E.; Brodie, E.; Myint, C.; Ackerly, D.; van Nostrand, J.; Bird, J.; Zhou, J.; Andersen, G.; Firestone, M.
2008-12-01
Complex soil microbial communities regulate critical ecosystem processes that will be altered by climate change. A critical step towards predicting the impacts of climate change on terrestrial ecosystems is to determine the primary controllers of soil microbial community composition and function, and subsequently evaluate climate change scenarios that alter these controllers. We surveyed complex soil bacterial and archaeal communities across a range of climatic and edaphic conditions to identify critical controllers of soil microbial community composition in the field and then tested the resulting predictions using a 2-year manipulation of precipitation and temperature using mesocosms of California annual grasslands. Community DNA extracted from field soils sampled from six different ecosystems was assayed for bacterial and archaeal communities using high-density phylogenetic microarrays as well as functional gene arrays. Correlations among the relative abundances of thousands of microbial taxa and edaphic factors such as soil moisture and nutrient content provided a basis for predicting community responses to changing soil conditions. Communities of soil bacteria and archaea were strongly structured by single environmental predictors, particularly variables related to soil water. Bacteria in the Actinomycetales and Bacilli consistently demonstrated a strong negative response to increasing soil moisture, while taxa in a greater variety of lineages responded positively to increasing soil moisture. In the climate change experiment, overall bacterial community structure was impacted significantly by total precipitation but not by plant species. Changes in soil moisture due to decreased rainfall resulted in significant and predictable alterations in community structure. Over 70% of the bacterial taxa in common with the cross-ecosystem study responded as predicted to altered precipitation, with the most conserved response from Actinobacteria. The functional consequences of these predictable changes in community composition were measured with functional arrays that detect genes involved in the metabolism of carbon, nitrogen and other elements. The response of soil microbial communities to altered precipitation can be predicted from the distribution of microbial taxa across moisture gradients.
Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions.
Fox, Naomi J; Marion, Glenn; Davidson, Ross S; White, Piran C L; Hutchings, Michael R
2012-03-06
Climate change is a driving force for livestock parasite risk. This is especially true for helminths including the nematodes Haemonchus contortus, Teladorsagia circumcincta, Nematodirus battus, and the trematode Fasciola hepatica, since survival and development of free-living stages is chiefly affected by temperature and moisture. The paucity of long term predictions of helminth risk under climate change has driven us to explore optimal modelling approaches and identify current bottlenecks to generating meaningful predictions. We classify approaches as correlative or mechanistic, exploring their strengths and limitations. Climate is one aspect of a complex system and, at the farm level, husbandry has a dominant influence on helminth transmission. Continuing environmental change will necessitate the adoption of mitigation and adaptation strategies in husbandry. Long term predictive models need to have the architecture to incorporate these changes. Ultimately, an optimal modelling approach is likely to combine mechanistic processes and physiological thresholds with correlative bioclimatic modelling, incorporating changes in livestock husbandry and disease control. Irrespective of approach, the principal limitation to parasite predictions is the availability of active surveillance data and empirical data on physiological responses to climate variables. By combining improved empirical data and refined models with a broad view of the livestock system, robust projections of helminth risk can be developed.
Aflatoxin B1 contamination in maize in Europe increases due to climate change
NASA Astrophysics Data System (ADS)
Battilani, P.; Toscano, P.; van der Fels-Klerx, H. J.; Moretti, A.; Camardo Leggieri, M.; Brera, C.; Rortais, A.; Goumperis, T.; Robinson, T.
2016-04-01
Climate change has been reported as a driver for emerging food and feed safety issues worldwide and its expected impact on the presence of mycotoxins in food and feed is of great concern. Aflatoxins have the highest acute and chronic toxicity of all mycotoxins; hence, the maximal concentration in agricultural food and feed products and their commodities is regulated worldwide. The possible change in patterns of aflatoxin occurrence in crops due to climate change is a matter of concern that may require anticipatory actions. The aim of this study was to predict aflatoxin contamination in maize and wheat crops, within the next 100 years, under a +2 °C and +5 °C climate change scenario, applying a modelling approach. Europe was virtually covered by a net, 50 × 50 km grids, identifying 2254 meshes with a central point each. Climate data were generated for each point, linked to predictive models and predictions were run consequently. Aflatoxin B1 is predicted to become a food safety issue in maize in Europe, especially in the +2 °C scenario, the most probable scenario of climate change expected for the next years. These results represent a supporting tool to reinforce aflatoxin management and to prevent human and animal exposure.
Life history and spatial traits predict extinction risk due to climate change
NASA Astrophysics Data System (ADS)
Pearson, Richard G.; Stanton, Jessica C.; Shoemaker, Kevin T.; Aiello-Lammens, Matthew E.; Ersts, Peter J.; Horning, Ned; Fordham, Damien A.; Raxworthy, Christopher J.; Ryu, Hae Yeong; McNees, Jason; Akçakaya, H. Reşit
2014-03-01
There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change based on the expectation that established assessments such as the IUCN Red List need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.
Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change.
Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien
2015-10-01
Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates.
Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change
Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien
2015-01-01
Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates. PMID:26501958
Gibson, C.A.; Meyer, J.L.; Poff, N.L.; Hay, L.E.; Georgakakos, A.
2005-01-01
We examined impacts of future climate scenarios on flow regimes and how predicted changes might affect river ecosystems. We examined two case studies: Cle Elum River, Washington, and Chattahoochee-Apalachicola River Basin, Georgia and Florida. These rivers had available downscaled global circulation model (GCM) data and allowed us to analyse the effects of future climate scenarios on rivers with (1) different hydrographs, (2) high future water demands, and (3) a river-floodplain system. We compared observed flow regimes to those predicted under future climate scenarios to describe the extent and type of changes predicted to occur. Daily stream flow under future climate scenarios was created by either statistically downscaling GCMs (Cle Elum) or creating a regression model between climatological parameters predicted from GCMs and stream flow (Chattahoochee-Apalachicola). Flow regimes were examined for changes from current conditions with respect to ecologically relevant features including the magnitude and timing of minimum and maximum flows. The Cle Elum's hydrograph under future climate scenarios showed a dramatic shift in the timing of peak flows and lower low flow of a longer duration. These changes could mean higher summer water temperatures, lower summer dissolved oxygen, and reduced survival of larval fishes. The Chattahoochee-Apalachicola basin is heavily impacted by dams and water withdrawals for human consumption; therefore, we made comparisons between pre-large dam conditions, current conditions, current conditions with future demand, and future climate scenarios with future demand to separate climate change effects and other anthropogenic impacts. Dam construction, future climate, and future demand decreased the flow variability of the river. In addition, minimum flows were lower under future climate scenarios. These changes could decrease the connectivity of the channel and the floodplain, decrease habitat availability, and potentially lower the ability of the river to assimilate wastewater treatment plant effluent. Our study illustrates the types of changes that river ecosystems might experience under future climates. Copyright ?? 2005 John Wiley & Sons, Ltd.
Caldwell, Amanda J; While, Geoffrey M; Beeton, Nicholas J; Wapstra, Erik
2015-08-01
Climatic changes are predicted to be greater in higher latitude and mountainous regions but species specific impacts are difficult to predict. This is partly due to inter-specific variance in the physiological traits which mediate environmental temperature effects at the organismal level. We examined variation in the critical thermal minimum (CTmin), critical thermal maximum (CTmax) and evaporative water loss rates (EWL) of a widespread lowland (Niveoscincus ocellatus) and two range restricted highland (N. microlepidotus and N. greeni) members of a cool temperate Tasmanian lizard genus. The widespread lowland species had significantly higher CTmin and CTmax and significantly lower EWL than both highland species. Implications of inter-specific variation in thermal tolerance for activity were examined under contemporary and future climate change scenarios. Instances of air temperatures below CTmin were predicted to decline in frequency for the widespread lowland and both highland species. Air temperatures of high altitude sites were not predicted to exceed the CTmax of either highland species throughout the 21st century. In contrast, the widespread lowland species is predicted to experience air temperatures in excess of CTmax on 1 or 2 days by three of six global circulation models from 2068-2096. To estimate climate change effects on activity we reran the thermal tolerance models using minimum and maximum temperatures selected for activity. A net gain in available activity time was predicted under climate change for all three species; while air temperatures were predicted to exceed maximum temperatures selected for activity with increasing frequency, the change was not as great as the predicted decline in air temperatures below minimum temperatures selected for activity. We hypothesise that the major effect of rising air temperatures under climate change is an increase in available activity period for both the widespread lowland and highland species. The consequences of a greater available activity period will depend on the extent to which changes in climate alters other related factors, such as the nature and level of competition between the respective species. Copyright © 2015 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kennedy, Thomas L.; Gutzler, David S.; Leung, Lai R.
2008-11-20
Regional climates are a major factor in determining the distribution of many species. Anthropogenic inputs of greenhouse gases into the atmosphere have been predicted to cause rapid climatic changes in the next 50-100 years. Species such as the Gila Trout (Onchorhynchus gilae) that have small ranges, limited dispersal capabilities, and narrow physiological tolerances will become increasingly susceptible to extinction as their climate envelope changes. This study uses a regional climate change simulation (Leung et al. 2004) to determine changes in the climate envelope for Gila Trout, which is sensitive to maximum temperature, associated with a plausible scenario for greenhouse gasmore » increases. The model predicts approximately a 2° C increase in temperature and a doubling by the mid 21st Century in the annual number of days during which temperature exceeds 37°C, and a 25% increase in the number of days above 32°C, across the current geographical range of Gila Trout. At the same time summer rainfall decreases by more than 20%. These climate changes would reduce their available habitat by decreasing the size of their climate envelope. Warmer temperatures coupled with a decrease in summer precipitation would also tend to increase the intensity and frequency of forest fires that are a major threat to their survival. The climate envelope approach utilized here could be used to assess climate change threats to other rare species with limited ranges and dispersal capabilities.« less
Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh
2017-01-01
The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...
A Climatic Stability Approach to Prioritizing Global Conservation Investments
Iwamura, Takuya; Wilson, Kerrie A.; Venter, Oscar; Possingham, Hugh P.
2010-01-01
Climate change is impacting species and ecosystems globally. Many existing templates to identify the most important areas to conserve terrestrial biodiversity at the global scale neglect the future impacts of climate change. Unstable climatic conditions are predicted to undermine conservation investments in the future. This paper presents an approach to developing a resource allocation algorithm for conservation investment that incorporates the ecological stability of ecoregions under climate change. We discover that allocating funds in this way changes the optimal schedule of global investments both spatially and temporally. This allocation reduces the biodiversity loss of terrestrial endemic species from protected areas due to climate change by 22% for the period of 2002–2052, when compared to allocations that do not consider climate change. To maximize the resilience of global biodiversity to climate change we recommend that funding be increased in ecoregions located in the tropics and/or mid-elevation habitats, where climatic conditions are predicted to remain relatively stable. Accounting for the ecological stability of ecoregions provides a realistic approach to incorporating climate change into global conservation planning, with potential to save more species from extinction in the long term. PMID:21152095
Lyam, Paul Terwase; Duque-Lazo, Joaquín; Durka, Walter; Hauenschild, Frank; Schnitzler, Jan; Michalak, Ingo; Ogundipe, Oluwatoyin Temitayo; Muellner-Riehl, Alexandra Nora
2018-01-01
Climate change is predicted to impact species' genetic diversity and distribution. We used Senegalia senegal (L.) Britton, an economically important species distributed in the Sudano-Sahelian savannah belt of West Africa, to investigate the impact of climate change on intraspecific genetic diversity and distribution. We used ten nuclear and two plastid microsatellite markers to assess genetic variation, population structure and differentiation across thirteen sites in West Africa. We projected suitable range, and potential impact of climate change on genetic diversity using a maximum entropy approach, under four different climate change scenarios. We found higher genetic and haplotype diversity at both nuclear and plastid markers than previously reported. Genetic differentiation was strong for chloroplast and moderate for the nuclear genome. Both genomes indicated three spatially structured genetic groups. The distribution of Senegalia senegal is strongly correlated with extractable nitrogen, coarse fragments, soil organic carbon stock, precipitation of warmest and coldest quarter and mean temperature of driest quarter. We predicted 40.96 to 6.34 per cent of the current distribution to favourably support the species' ecological requirements under future climate scenarios. Our results suggest that climate change is going to affect the population genetic structure of Senegalia senegal, and that patterns of genetic diversity are going to influence the species' adaptive response to climate change. Our study contributes to the growing evidence predicting the loss of economically relevant plants in West Africa in the next decades due to climate change.
Duque-Lazo, Joaquín; Durka, Walter; Hauenschild, Frank; Schnitzler, Jan; Michalak, Ingo; Ogundipe, Oluwatoyin Temitayo; Muellner-Riehl, Alexandra Nora
2018-01-01
Climate change is predicted to impact species’ genetic diversity and distribution. We used Senegalia senegal (L.) Britton, an economically important species distributed in the Sudano-Sahelian savannah belt of West Africa, to investigate the impact of climate change on intraspecific genetic diversity and distribution. We used ten nuclear and two plastid microsatellite markers to assess genetic variation, population structure and differentiation across thirteen sites in West Africa. We projected suitable range, and potential impact of climate change on genetic diversity using a maximum entropy approach, under four different climate change scenarios. We found higher genetic and haplotype diversity at both nuclear and plastid markers than previously reported. Genetic differentiation was strong for chloroplast and moderate for the nuclear genome. Both genomes indicated three spatially structured genetic groups. The distribution of Senegalia senegal is strongly correlated with extractable nitrogen, coarse fragments, soil organic carbon stock, precipitation of warmest and coldest quarter and mean temperature of driest quarter. We predicted 40.96 to 6.34 per cent of the current distribution to favourably support the species’ ecological requirements under future climate scenarios. Our results suggest that climate change is going to affect the population genetic structure of Senegalia senegal, and that patterns of genetic diversity are going to influence the species’ adaptive response to climate change. Our study contributes to the growing evidence predicting the loss of economically relevant plants in West Africa in the next decades due to climate change. PMID:29659603
Pervez, Md Shahriar; Henebry, Geoffrey M.
2015-01-01
New hydrological insights for the region: Basin average annual ET was found to be sensitive to changes in CO2 concentration and temperature, while total water yield, streamflow, and groundwater recharge were sensitive to changes in precipitation. The basin hydrological components were predicted to increase with seasonal variability in response to climate and land use change scenarios. Strong increasing trends were predicted for total water yield, streamflow, and groundwater recharge, indicating exacerbation of flooding potential during August–October, but strong decreasing trends were predicted, indicating exacerbation of drought potential during May–July of the 21st century. The model has potential to facilitate strategic decision making through scenario generation integrating climate change adaptation and hazard mitigation policies to ensure optimized allocation of water resources under a variable and changing climate.
US forest response to projected climate-related stress: a tolerance perspective.
Liénard, Jean; Harrison, John; Strigul, Nikolay
2016-08-01
Although it is widely recognized that climate change will require a major spatial reorganization of forests, our ability to predict exactly how and where forest characteristics and distributions will change has been rather limited. Current efforts to predict future distribution of forested ecosystems as a function of climate include species distribution models (for fine-scale predictions) and potential vegetation climate envelope models (for coarse-grained, large-scale predictions). Here, we develop and apply an intermediate approach wherein we use stand-level tolerances of environmental stressors to understand forest distributions and vulnerabilities to anticipated climate change. In contrast to other existing models, this approach can be applied at a continental scale while maintaining a direct link to ecologically relevant, climate-related stressors. We first demonstrate that shade, drought, and waterlogging tolerances of forest stands are strongly correlated with climate and edaphic conditions in the conterminous United States. This discovery allows the development of a tolerance distribution model (TDM), a novel quantitative tool to assess landscape level impacts of climate change. We then focus on evaluating the implications of the drought TDM. Using an ensemble of 17 climate change models to drive this TDM, we estimate that 18% of US ecosystems are vulnerable to drought-related stress over the coming century. Vulnerable areas include mostly the Midwest United States and Northeast United States, as well as high-elevation areas of the Rocky Mountains. We also infer stress incurred by shifting climate should create an opening for the establishment of forest types not currently seen in the conterminous United States. © 2016 John Wiley & Sons Ltd.
Climate Prediction Center - Outreach: 41st Annual Climate Diagnostics &
the University of Maine Climate Change Institute and School of Earth and Climate Sciences and is co (drought, heat waves, severe weather, tropical cyclones) in the framework of climate variability and change and including the use of paleoclimate data. Arctic climate variability and change, and linkages to
NASA Astrophysics Data System (ADS)
Wichmann, Matthias C.; Groeneveld, Jürgen; Jeltsch, Florian; Grimm, Volker
2005-07-01
The predicted climate change causes deep concerns on the effects of increasing temperatures and changing precipitation patterns on species viability and, in turn, on biodiversity. Models of Population Viability Analysis (PVA) provide a powerful tool to assess the risk of species extinction. However, most PVA models do not take into account the potential effects of behavioural adaptations. Organisms might adapt to new environmental situations and thereby mitigate negative effects of climate change. To demonstrate such mitigation effects, we use an existing PVA model describing a population of the tawny eagle ( Aquila rapax) in the southern Kalahari. This model does not include behavioural adaptations. We develop a new model by assuming that the birds enlarge their average territory size to compensate for lower amounts of precipitation. Here, we found the predicted increase in risk of extinction due to climate change to be much lower than in the original model. However, this "buffering" of climate change by behavioural adaptation is not very effective in coping with increasing interannual variances. We refer to further examples of ecological "buffering mechanisms" from the literature and argue that possible buffering mechanisms should be given due consideration when the effects of climate change on biodiversity are to be predicted.
Physiological plasticity increases resilience of ectothermic animals to climate change
NASA Astrophysics Data System (ADS)
Seebacher, Frank; White, Craig R.; Franklin, Craig E.
2015-01-01
Understanding how climate change affects natural populations remains one of the greatest challenges for ecology and management of natural resources. Animals can remodel their physiology to compensate for the effects of temperature variation, and this physiological plasticity, or acclimation, can confer resilience to climate change. The current lack of a comprehensive analysis of the capacity for physiological plasticity across taxonomic groups and geographic regions, however, constrains predictions of the impacts of climate change. Here, we assembled the largest database to date to establish the current state of knowledge of physiological plasticity in ectothermic animals. We show that acclimation decreases the sensitivity to temperature and climate change of freshwater and marine animals, but less so in terrestrial animals. Animals from more stable environments have greater capacity for acclimation, and there is a significant trend showing that the capacity for thermal acclimation increases with decreasing latitude. Despite the capacity for acclimation, climate change over the past 20 years has already resulted in increased physiological rates of up to 20%, and we predict further future increases under climate change. The generality of these predictions is limited, however, because much of the world is drastically undersampled in the literature, and these undersampled regions are the areas of greatest need for future research efforts.
Impacts of past and future climate change on wind energy resources in the United States
NASA Astrophysics Data System (ADS)
McCaa, J. R.; Wood, A.; Eichelberger, S.; Westrick, K.
2009-12-01
The links between climate change and trends in wind energy resources have important potential implications for the wind energy industry, and have received significant attention in recent studies. We have conducted two studies that provide insights into the potential for climate change to affect future wind power production. In one experiment, we projected changes in power capacity for a hypothetical wind farm located near Kennewick, Washington, due to greenhouse gas-induced climate change, estimated using a set of regional climate model simulations. Our results show that the annual wind farm power capacity is projected to decrease 1.3% by 2050. In a wider study focusing on wind speed instead of power, we analyzed projected changes in wind speed from 14 different climate simulations that were performed in support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Our results show that the predicted ensemble mean changes in annual mean wind speeds are expected to be modest. However, seasonal changes and changes predicted by individual models are large enough to affect the profitability of existing and future wind projects. The majority of the model simulations reveal that near-surface wind speed values are expected to shift poleward in response to the IPCC A2 emission scenario, particularly during the winter season. In the United States, most models agree that the mean annual wind speed values will increase in a region extending from the Great Lakes southward across the Midwest and into Texas. Decreased values, though, are predicted across most of the western United States. However, these predicted changes have a strong seasonal dependence, with wind speed increases over most of the United States during the winter and decreases over the northern United States during the summer.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maslowski, Wieslaw
This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate throughmore » polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.« less
Gray, Laura K; Clarke, Charles; Wint, G R William; Moran, Jonathan A
2017-01-01
Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of climatically-suitable habitat for two Nepenthes pitcher plant species in Borneo. The model results predicted an increase in area of climatically-suitable habitat for the lowland species Nepenthes rafflesiana by 2100; in contrast, the highland species Nepenthes tentaculata was predicted to undergo significant loss of climatically-suitable habitat over the same period. Based on the results of the models, we recommend that research be undertaken into practical mitigation strategies, as approximately two-thirds of Nepenthes are restricted to montane habitats. Highland species with narrow elevational ranges will be at particularly high risk, and investigation into possible mitigation strategies should be focused on them.
Gray, Laura K.; Clarke, Charles; Wint, G. R. William
2017-01-01
Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of climatically-suitable habitat for two Nepenthes pitcher plant species in Borneo. The model results predicted an increase in area of climatically-suitable habitat for the lowland species Nepenthes rafflesiana by 2100; in contrast, the highland species Nepenthes tentaculata was predicted to undergo significant loss of climatically-suitable habitat over the same period. Based on the results of the models, we recommend that research be undertaken into practical mitigation strategies, as approximately two-thirds of Nepenthes are restricted to montane habitats. Highland species with narrow elevational ranges will be at particularly high risk, and investigation into possible mitigation strategies should be focused on them. PMID:28817596
Climate change and respiratory disease: European Respiratory Society position statement.
Ayres, J G; Forsberg, B; Annesi-Maesano, I; Dey, R; Ebi, K L; Helms, P J; Medina-Ramón, M; Windt, M; Forastiere, F
2009-08-01
Climate change will affect individuals with pre-existing respiratory disease, but the extent of the effect remains unclear. The present position statement was developed on behalf of the European Respiratory Society in order to identify areas of concern arising from climate change for individuals with respiratory disease, healthcare workers in the respiratory sector and policy makers. The statement was developed following a 2-day workshop held in Leuven (Belgium) in March 2008. Key areas of concern for the respiratory community arising from climate change are discussed and recommendations made to address gaps in knowledge. The most important recommendation was the development of more accurate predictive models for predicting the impact of climate change on respiratory health. Respiratory healthcare workers also have an advocatory role in persuading governments and the European Union to maintain awareness and appropriate actions with respect to climate change, and these areas are also discussed in the position statement.
Climate Change, Nutrition, and Bottom-Up and Top-Down Food Web Processes.
Rosenblatt, Adam E; Schmitz, Oswald J
2016-12-01
Climate change ecology has focused on climate effects on trophic interactions through the lenses of temperature effects on organismal physiology and phenological asynchronies. Trophic interactions are also affected by the nutrient content of resources, but this topic has received less attention. Using concepts from nutritional ecology, we propose a conceptual framework for understanding how climate affects food webs through top-down and bottom-up processes impacted by co-occurring environmental drivers. The framework integrates climate effects on consumer physiology and feeding behavior with effects on resource nutrient content. It illustrates how studying responses of simplified food webs to simplified climate change might produce erroneous predictions. We encourage greater integrative complexity of climate change research on trophic interactions to resolve patterns and enhance predictive capacities. Copyright © 2016 Elsevier Ltd. All rights reserved.
,
1995-01-01
The Earth's global environment--its interrelated climate, land, oceans, fresh water, atmospheric and ecological systems-has changed continually throughout Earth history. Human activities are having ever-increasing effects on these systems. Sustaining our environment as population and demands for resources increase requires a sound understanding of the causes and cycles of natural change and the effects of human activities on the Earth's environmental systems. The U.S. Global Change Research Program was authorized by Congress in 1989 to provide the scientific understanding necessary to develop national and international policies concerning global environmental issues, particularly global climate change. The program addresses questions such as: what factors determine global climate; have humans already begun to change the global climate; will the climate of the future be very different; what will be the effects of climate change; and how much confidence do we have in our predictions? Through understanding, we can improve our capability to predict change, reduce the adverse effects of human activities, and plan strategies for adapting to natural and human-induced environmental change.
Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment
NASA Technical Reports Server (NTRS)
Skiles, J. W.
1995-01-01
Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation.
An ecophysiological perspective on likely giant panda habitat responses to climate change.
Zhang, Yuke; Mathewson, Paul D; Zhang, Qiongyue; Porter, Warren P; Ran, Jianghong
2018-04-01
Threatened and endangered species are more vulnerable to climate change due to small population and specific geographical distribution. Therefore, identifying and incorporating the biological processes underlying a species' adaptation to its environment are important for determining whether they can persist in situ. Correlative models are widely used to predict species' distribution changes, but generally fail to capture the buffering capacity of organisms. Giant pandas (Ailuropoda melanoleuca) live in topographically complex mountains and are known to avoid heat stress. Although many studies have found that climate change will lead to severe habitat loss and threaten previous conservation efforts, the mechanisms underlying panda's responses to climate change have not been explored. Here, we present a case study in Daxiangling Mountains, one of the six Mountain Systems that giant panda distributes. We used a mechanistic model, Niche Mapper, to explore what are likely panda habitat response to climate change taking physiological, behavioral and ecological responses into account, through which we map panda's climatic suitable activity area (SAA) for the first time. We combined SAA with bamboo forest distribution to yield highly suitable habitat (HSH) and seasonal suitable habitat (SSH), and their temporal dynamics under climate change were predicted. In general, SAA in the hottest month (July) would reduce 11.7%-52.2% by 2070, which is more moderate than predicted bamboo habitat loss (45.6%-86.9%). Limited by the availability of bamboo and forest, panda's suitable habitat loss increases, and only 15.5%-68.8% of current HSH would remain in 2070. Our method of mechanistic modeling can help to distinguish whether habitat loss is caused by thermal environmental deterioration or food loss under climate change. Furthermore, mechanistic models can produce robust predictions by incorporating ecophysiological feedbacks and minimizing extrapolation into novel environments. We suggest that a mechanistic approach should be incorporated into distribution predictions and conservation planning. © 2017 John Wiley & Sons Ltd.
Korkala, Essi A E; Hugg, Timo T; Jaakkola, Jouni J K
2014-01-01
Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%). Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%), the Semi-active (63%) and the Active (11%) and two classes among women: the Semi-active (72%) and the Active (28%). The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns.
Korkala, Essi A. E.; Hugg, Timo T.; Jaakkola, Jouni J. K.
2014-01-01
Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%). Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%), the Semi-active (63%) and the Active (11%) and two classes among women: the Semi-active (72%) and the Active (28%). The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns. PMID:25054549
Mundim, Fabiane M; Bruna, Emilio M
2016-09-01
Climate change can drive major shifts in community composition and interactions between resident species. However, the magnitude of these changes depends on the type of interactions and the biome in which they take place. We review the existing conceptual framework for how climate change will influence tropical plant-herbivore interactions and formalize a similar framework for the temperate zone. We then conduct the first biome-specific tests of how plant-herbivore interactions change in response to climate-driven changes in temperature, precipitation, ambient CO2, and ozone. We used quantitative meta-analysis to compare predicted and observed changes in experimental studies. Empirical studies were heavily biased toward temperate systems, so testing predicted changes in tropical plant-herbivore interactions was virtually impossible. Furthermore, most studies investigated the effects of CO2 with limited plant and herbivore species. Irrespective of location, most studies manipulated only one climate change factor despite the fact that different factors can act in synergy to alter responses of plants and herbivores. Finally, studies of belowground plant-herbivore interactions were also rare; those conducted suggest that climate change could have major effects on belowground subsystems. Our results suggest that there is a disconnection between the growing literature proposing how climate change will influence plant-herbivore interactions and the studies testing these predictions. General conclusions will also be hampered without better integration of above- and belowground systems, assessing the effects of multiple climate change factors simultaneously, and using greater diversity of species in experiments.
Nelson, Kären C; Palmer, Margaret A; Pizzuto, James E; Moglen, Glenn E; Angermeier, Paul L; Hilderbrand, Robert H; Dettinger, Michael; Hayhoe, Katharine
2009-01-01
Streams collect runoff, heat, and sediment from their watersheds, making them highly vulnerable to anthropogenic disturbances such as urbanization and climate change. Forecasting the effects of these disturbances using process-based models is critical to identifying the form and magnitude of likely impacts. Here, we integrate a new biotic model with four previously developed physical models (downscaled climate projections, stream hydrology, geomorphology, and water temperature) to predict how stream fish growth and reproduction will most probably respond to shifts in climate and urbanization over the next several decades. The biotic submodel couples dynamics in fish populations and habitat suitability to predict fish assemblage composition, based on readily available biotic information (preferences for habitat, temperature, and food, and characteristics of spawning) and day-to-day variability in stream conditions. We illustrate the model using Piedmont headwater streams in the Chesapeake Bay watershed of the USA, projecting ten scenarios: Baseline (low urbanization; no on-going construction; and present-day climate); one Urbanization scenario (higher impervious surface, lower forest cover, significant construction activity); four future climate change scenarios [Hadley CM3 and Parallel Climate Models under medium-high (A2) and medium-low (B2) emissions scenarios]; and the same four climate change scenarios plus Urbanization. Urbanization alone depressed growth or reproduction of 8 of 39 species, while climate change alone depressed 22 to 29 species. Almost every recreationally important species (i.e. trouts, basses, sunfishes) and six of the ten currently most common species were predicted to be significantly stressed. The combined effect of climate change and urbanization on adult growth was sometimes large compared to the effect of either stressor alone. Thus, the model predicts considerable change in fish assemblage composition, including loss of diversity. Synthesis and applications. The interaction of climate change and urban growth may entail significant reconfiguring of headwater streams, including a loss of ecosystem structure and services, which will be more costly than climate change alone. On local scales, stakeholders cannot control climate drivers but they can mitigate stream impacts via careful land use. Therefore, to conserve stream ecosystems, we recommend that proactive measures be taken to insure against species loss or severe population declines. Delays will inevitably exacerbate the impacts of both climate change and urbanization on headwater systems. PMID:19536343
Revisiting the Cassandra syndrome; the changing climate of coral reef research
NASA Astrophysics Data System (ADS)
Maynard, J. A.; Baird, A. H.; Pratchett, M. S.
2008-12-01
Climate change will be with us for decades, even with significant reductions in emissions. Therefore, predictions made with respect to climate change impacts on coral reefs need to be highly defensible to ensure credibility over the timeframes this issue demands. If not, a Cassandra syndrome could be created whereby future more well-supported predictions of the fate of reefs are neither heard nor acted upon. Herein, popularising predictions based on essentially untested assumptions regarding reefs and their capacity to cope with future climate change is questioned. Some of these assumptions include that: all corals live close to their thermal limits, corals cannot adapt/acclimatize to rapid rates of change, physiological trade-offs resulting from ocean acidification will lead to reduced fecundity, and that climate-induced coral loss leads to widespread fisheries collapse. We argue that, while there is a place for popularising worst-case scenarios, the coral reef crisis has been effectively communicated and, though this communication should be sustained, efforts should now focus on addressing critical knowledge gaps.
Conlisk, Erin; Lawson, Dawn; Syphard, Alexandra D.; Franklin, Janet; Flint, Lorraine; Flint, Alan; Regan, Helen M.
2012-01-01
A species’ response to climate change depends on the interaction of biotic and abiotic factors that define future habitat suitability and species’ ability to migrate or adapt. The interactive effects of processes such as fire, dispersal, and predation have not been thoroughly addressed in the climate change literature. Our objective was to examine how life history traits, short-term global change perturbations, and long-term climate change interact to affect the likely persistence of an oak species - Quercus engelmannii (Engelmann oak). Specifically, we combined dynamic species distribution models, which predict suitable habitat, with stochastic, stage-based metapopulation models, which project population trajectories, to evaluate the effects of three global change factors – climate change, land use change, and altered fire frequency – emphasizing the roles of dispersal and seed predation. Our model predicted dramatic reduction in Q. engelmannii abundance, especially under drier climates and increased fire frequency. When masting lowers seed predation rates, decreased masting frequency leads to large abundance decreases. Current rates of dispersal are not likely to prevent these effects, although increased dispersal could mitigate population declines. The results suggest that habitat suitability predictions by themselves may under-estimate the impact of climate change for other species and locations. PMID:22623955
Rylander, Charlotta; Odland, Jon Ø; Sandanger, Torkjel M
2011-01-01
In 2007, the Intergovernmental Panel on Climate Change (IPCC) presented a report on global warming and the impact of human activities on global warming. Later the Lancet commission identified six ways human health could be affected. Among these were not environmental factors which are also believed to be important for human health. In this paper we therefore focus on environmental factors, climate change and the predicted effects on maternal and newborn health. Arctic issues are discussed specifically considering their exposure and sensitivity to long range transported contaminants. Considering that the different parts of pregnancy are particularly sensitive time periods for the effects of environmental exposure, this review focuses on the impacts on maternal and newborn health. Environmental stressors known to affects human health and how these will change with the predicted climate change are addressed. Air pollution and food security are crucial issues for the pregnant population in a changing climate, especially indoor climate and food security in Arctic areas. The total number of environmental factors is today responsible for a large number of the global deaths, especially in young children. Climate change will most likely lead to an increase in this number. Exposure to the different environmental stressors especially air pollution will in most parts of the world increase with climate change, even though some areas might face lower exposure. Populations at risk today are believed to be most heavily affected. As for the persistent organic pollutants a warming climate leads to a remobilisation and a possible increase in food chain exposure in the Arctic and thus increased risk for Arctic populations. This is especially the case for mercury. The perspective for the next generations will be closely connected to the expected temperature changes; changes in housing conditions; changes in exposure patterns; predicted increased exposure to Mercury because of increased emissions and increased biological availability. A number of environmental stressors are predicted to increase with climate change and increasingly affecting human health. Efforts should be put on reducing risk for the next generation, thus global politics and research effort should focus on maternal and newborn health.
DeWeber, Jefferson T; Wagner, Tyler
2018-06-01
Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30-day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species' distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold-water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid-century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects. © 2018 John Wiley & Sons Ltd.
DeWeber, Jefferson T.; Wagner, Tyler
2018-01-01
Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30‐day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species’ distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold‐water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid‐century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects.
USDA-ARS?s Scientific Manuscript database
Predicted climate change impacts include increased weather variability and increased occurrences of extreme events such as drought. Such climate changes potentially affect cattle performance as well as pasture and range productivity. These climate induced risks are often coupled with variable market...
Marie Oliver; David W. Peterson; Becky Kerns
2016-01-01
Earth's climate is changing, as evidenced by warming temperatures, increased temperature variability, fluctuating precipitation patterns, and climate-related environmental disturbances. And with considerable uncertainty about the future, Forest Service land managers are now considering climate change adaptation in their planning efforts. They want practical...
Climatically-mediated landcover change: impacts on Brazilian territory.
Zanin, Marina; Tessarolo, Geiziane; Machado, Nathália; Albernaz, Ana Luisa M
2017-01-01
In the face of climate change threats, governments are drawing attention to policies for mitigating its effects on biodiversity. However, the lack of distribution data makes predictions at species level a difficult task, mainly in regions of higher biodiversity. To overcome this problem, we use native landcover as a surrogate biodiversity, because it can represent specialized habitat for species, and investigate the effects of future climate change on Brazilian biomes. We characterize the climatic niches of native landcover and use ecological niche modeling to predict the potential distribution under current and future climate scenarios. Our results highlight expansion of the distribution of open vegetation and the contraction of closed forests. Drier Brazilian biomes, like Caatinga and Cerrado, are predicted to expand their distributions, being the most resistant to climate change impacts. However, these would also be affected by losses of their closed forest enclaves and their habitat-specific or endemic species. Replacement by open vegetation and overall reductions are a considerable risk for closed forest, threatening Amazon and Atlantic forest biomes. Here, we evidence the impacts of climate change on Brazilian biomes, and draw attention to the necessity for management and attenuation plans to guarantee the future of Brazilian biodiversity.
Potential Impacts of Climate Change on Native Plant Distributions in the Falkland Islands
Upson, Rebecca; Williams, Jennifer J.; Wilkinson, Tim P.; Maclean, Ilya M. D.; McAdam, Jim H.; Moat, Justin F.
2016-01-01
The Falkland Islands are predicted to experience up to 2.2°C rise in mean annual temperature over the coming century, greater than four times the rate over the last century. Our study investigates likely vulnerabilities of a suite of range-restricted species whose distributions are associated with archipelago-wide climatic variation. We used present day climate maps calibrated using local weather data, 2020–2080 climate predictions from regional climate models, non-climate variables derived from a digital terrain model and a comprehensive database on local plant distributions. Weighted mean ensemble models were produced to assess changes in range sizes and overlaps between the current range and protected areas network. Target species included three globally threatened Falkland endemics, Nassauvia falklandica, Nastanthus falklandicus and Plantago moorei; and two nationally threatened species, Acaena antarctica and Blechnum cordatum. Our research demonstrates that temperature increases predicted for the next century have the potential to significantly alter plant distributions across the Falklands. Upland species, in particular, were found to be highly vulnerable to climate change impacts. No known locations of target upland species or the southwestern species Plantago moorei are predicted to remain environmentally suitable in the face of predicted climate change. We identify potential refugia for these species and associated gaps in the current protected areas network. Species currently restricted to the milder western parts of the archipelago are broadly predicted to expand their ranges under warmer temperatures. Our results emphasise the importance of implementing suitable adaptation strategies to offset climate change impacts, particularly site management. There is an urgent need for long-term monitoring and artificial warming experiments; the results of this study will inform the selection of the most suitable locations for these. Results are also helping inform management recommendations for the Falkland Islands Government who seek to better conserve their biodiversity and meet commitments to multi-lateral environmental agreements. PMID:27880846
Potential Impacts of Climate Change on Native Plant Distributions in the Falkland Islands.
Upson, Rebecca; Williams, Jennifer J; Wilkinson, Tim P; Clubbe, Colin P; Maclean, Ilya M D; McAdam, Jim H; Moat, Justin F
2016-01-01
The Falkland Islands are predicted to experience up to 2.2°C rise in mean annual temperature over the coming century, greater than four times the rate over the last century. Our study investigates likely vulnerabilities of a suite of range-restricted species whose distributions are associated with archipelago-wide climatic variation. We used present day climate maps calibrated using local weather data, 2020-2080 climate predictions from regional climate models, non-climate variables derived from a digital terrain model and a comprehensive database on local plant distributions. Weighted mean ensemble models were produced to assess changes in range sizes and overlaps between the current range and protected areas network. Target species included three globally threatened Falkland endemics, Nassauvia falklandica, Nastanthus falklandicus and Plantago moorei; and two nationally threatened species, Acaena antarctica and Blechnum cordatum. Our research demonstrates that temperature increases predicted for the next century have the potential to significantly alter plant distributions across the Falklands. Upland species, in particular, were found to be highly vulnerable to climate change impacts. No known locations of target upland species or the southwestern species Plantago moorei are predicted to remain environmentally suitable in the face of predicted climate change. We identify potential refugia for these species and associated gaps in the current protected areas network. Species currently restricted to the milder western parts of the archipelago are broadly predicted to expand their ranges under warmer temperatures. Our results emphasise the importance of implementing suitable adaptation strategies to offset climate change impacts, particularly site management. There is an urgent need for long-term monitoring and artificial warming experiments; the results of this study will inform the selection of the most suitable locations for these. Results are also helping inform management recommendations for the Falkland Islands Government who seek to better conserve their biodiversity and meet commitments to multi-lateral environmental agreements.
Decadal climate prediction (project GCEP).
Haines, Keith; Hermanson, Leon; Liu, Chunlei; Putt, Debbie; Sutton, Rowan; Iwi, Alan; Smith, Doug
2009-03-13
Decadal prediction uses climate models forced by changing greenhouse gases, as in the International Panel for Climate Change, but unlike longer range predictions they also require initialization with observations of the current climate. In particular, the upper-ocean heat content and circulation have a critical influence. Decadal prediction is still in its infancy and there is an urgent need to understand the important processes that determine predictability on these timescales. We have taken the first Hadley Centre Decadal Prediction System (DePreSys) and implemented it on several NERC institute compute clusters in order to study a wider range of initial condition impacts on decadal forecasting, eventually including the state of the land and cryosphere. The eScience methods are used to manage submission and output from the many ensemble model runs required to assess predictive skill. Early results suggest initial condition skill may extend for several years, even over land areas, but this depends sensitively on the definition used to measure skill, and alternatives are presented. The Grid for Coupled Ensemble Prediction (GCEP) system will allow the UK academic community to contribute to international experiments being planned to explore decadal climate predictability.
Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark
2015-01-01
Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241
Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark
2015-01-01
Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.
Ecological genomics predicts climate vulnerability in an endangered southwestern songbird.
Ruegg, Kristen; Bay, Rachael A; Anderson, Eric C; Saracco, James F; Harrigan, Ryan J; Whitfield, Mary; Paxton, Eben H; Smith, Thomas B
2018-05-09
Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher (Empidonax traillii), and find the endangered desert southwestern subspecies (E. t. extimus) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability - the mismatch between current and predicted future genotype-environment relationships - indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate-associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype-environment relationships into landscape-scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups. © 2018 John Wiley & Sons Ltd/CNRS.
Quintero, Ignacio; Wiens, John J
2013-08-01
A key question in predicting responses to anthropogenic climate change is: how quickly can species adapt to different climatic conditions? Here, we take a phylogenetic approach to this question. We use 17 time-calibrated phylogenies representing the major tetrapod clades (amphibians, birds, crocodilians, mammals, squamates, turtles) and climatic data from distributions of > 500 extant species. We estimate rates of change based on differences in climatic variables between sister species and estimated times of their splitting. We compare these rates to predicted rates of climate change from 2000 to 2100. Our results are striking: matching projected changes for 2100 would require rates of niche evolution that are > 10,000 times faster than rates typically observed among species, for most variables and clades. Despite many caveats, our results suggest that adaptation to projected changes in the next 100 years would require rates that are largely unprecedented based on observed rates among vertebrate species. © 2013 John Wiley & Sons Ltd/CNRS.
Abrupt shifts in phenology and vegetation productivity under climate extremes
USDA-ARS?s Scientific Manuscript database
Amplification of the hydrologic cycle as a consequence of global warming is predicted to increase climate variability and the frequency and severity of droughts. Predicting how ecosystems will be affected by climate change requires not only reliable forecasts of future climate, but also observationa...
Indigenous Waters: Applying the SWAT Hydrological Model to the Lumbee River Watershed
NASA Astrophysics Data System (ADS)
Painter, J.; Singh, N.; Martin, K. L.; Vose, J. M.; Wear, D. N.; Emanuel, R. E.
2016-12-01
Hydrological modeling can reveal insight about how rainfall becomes streamflow in a watershed comprising heterogeneous soils, terrain and land cover. Modeling can also help disentangle predicted impacts of climate and land use change on hydrological processes. We applied a hydrological model to the Lumbee River watershed, also known as the Lumber River Watershed, in the coastal plain of North Carolina (USA) to better understand how streamflow may be impacted by predicted climate and land use change in the mid-21st century. The Lumbee River flows through a predominantly Native American community, which may be affected by changing water resources during this period. The long-term goal of our project is to predict the effects of climate and land use change on the Lumbee River watershed and on the Native community that relies upon the river. We applied the Soil & Water Assessment Tool for ArcGIS (ArcSWAT), which was calibrated to historical climate and USGS streamflow data during the late 20th century, and we determined frequency distributions for key model parameters that best predicted streamflow during this time period. After calibrating and validating the model during the historical period, we identified land use and climate projections to represent a range of future conditions in the watershed. Specifically, we selected downscaled climate forcing data from four general circulation models running the RCP8.5 scenario. We also selected land use projections from a cornerstone scenario of the USDA Forest Service's Southern Forest Futures Project. This presentation reports on our methods for propagating parameter and climatic uncertainty through model predictions, and it reports on spatial patterns of land use change predicted by the cornerstone scenario.
Climate change likely to reduce orchid bee abundance even in climatic suitable sites.
Faleiro, Frederico Valtuille; Nemésio, André; Loyola, Rafael
2018-06-01
Studies have tested whether model predictions based on species' occurrence can predict the spatial pattern of population abundance. The relationship between predicted environmental suitability and population abundance varies in shape, strength and predictive power. However, little attention has been paid to the congruence in predictions of different models fed with occurrence or abundance data, in particular when comparing metrics of climate change impact. Here, we used the ecological niche modeling fit with presence-absence and abundance data of orchid bees to predict the effect of climate change on species and assembly level distribution patterns. In addition, we assessed whether predictions of presence-absence models can be used as a proxy to abundance patterns. We obtained georeferenced abundance data of orchid bees (Hymenoptera: Apidae: Euglossina) in the Brazilian Atlantic Forest. Sampling method consisted in attracting male orchid bees to baits of at least five different aromatic compounds and collecting the individuals with entomological nets or bait traps. We limited abundance data to those obtained by similar standard sampling protocol to avoid bias in abundance estimation. We used boosted regression trees to model ecological niches and project them into six climate models and two Representative Concentration Pathways. We found that models based on species occurrences worked as a proxy for changes in population abundance when the output of the models were continuous; results were very different when outputs were discretized to binary predictions. We found an overall trend of diminishing abundance in the future, but a clear retention of climatically suitable sites too. Furthermore, geographic distance to gained climatic suitable areas can be very short, although it embraces great variation. Changes in species richness and turnover would be concentrated in western and southern Atlantic Forest. Our findings offer support to the ongoing debate of suitability-abundance models and can be used to support spatial conservation prioritization schemes and species triage in Atlantic Forest. © 2018 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Tchebakova, Nadezhda M.; Zander, Evgeniya V.; Pyzhev, Anton I.; Parfenova, Elena I.; Soja, Amber J.
2014-05-01
Increased warming predicted from general circulation models (GCMs) by the end of the century is expected to dramatically impact Siberian forests. Both natural climate-change-caused disturbance (weather, wildfire, infestation) and anthropogenic disturbance (legal/illegal logging) has increased, and their impact on Siberian boreal forest has been mounting over the last three decades. The Siberian BioClimatic Model (SiBCliM) was used to simulate Siberian forests, and the resultant maps show a severely decreased forest that has shifted northwards and a changed composition. Predicted dryer climates would enhance the risks of high fire danger and thawing permafrost, both of which challenge contemporary ecosystems. Our current goal is to evaluate the ecological and economic consequences of climate warming, to optimise economic loss/gain effects in forestry versus agriculture, to question the relative economic value of supporting forestry, agriculture or a mixed agro-forestry at the southern forest border in central Siberia predicted to undergo the most noticeable landcover and landuse changes. We developed and used forest and agricultural bioclimatic models to predict forest shifts; novel tree species and their climatypes are introduced in a warmer climate and/or potential novel agriculture are introduced with a potential variety of crops by the end of the century. We applied two strategies to estimate climate change effects, motivated by forest disturbance. One is a genetic means of assisting trees and forests to be harmonized with a changing climate by developing management strategies for seed transfer to locations that are best ecologically suited to the genotypes in future climates. The second strategy is the establishment of agricultural lands in new forest-steppe and steppe habitats, because the forests would retreat northwards. Currently, food, forage, and biofuel crops primarily reside in the steppe and forest-steppe zones which are known to have favorable climatic and soil resources. During this century, traditional Siberian crops are predicted to gradually shift northwards and new crops, which are currently non-existent but potentially important in a warmer climate, could be introduced in the extreme south. In a future warmer climate, the economic effect of climate change impacts on agriculture was estimated based on a production function approach and the Ricardian model. The production function estimated climate impacts of temperature, precipitation and carbon dioxide levels. The Ricardian model examined climate impacts on the net rent or value of farmland at various regions. The models produced the optimal distribution of agricultural lands between crop, livestock, and forestry sectors to compensate economic losses in forestry in potential landuse areas depending on climatic change.
Beyond climate envelopes: effects of weather on regional population trends in butterflies.
WallisDeVries, Michiel F; Baxter, Wendy; Van Vliet, Arnold J H
2011-10-01
Although the effects of climate change on biodiversity are increasingly evident by the shifts in species ranges across taxonomical groups, the underlying mechanisms affecting individual species are still poorly understood. The power of climate envelopes to predict future ranges has been seriously questioned in recent studies. Amongst others, an improved understanding of the effects of current weather on population trends is required. We analysed the relation between butterfly abundance and the weather experienced during the life cycle for successive years using data collected within the framework of the Dutch Butterfly Monitoring Scheme for 40 species over a 15-year period and corresponding climate data. Both average and extreme temperature and precipitation events were identified, and multiple regression was applied to explain annual changes in population indices. Significant weather effects were obtained for 39 species, with the most frequent effects associated with temperature. However, positive density-dependence suggested climatic independent trends in at least 12 species. Validation of the short-term predictions revealed a good potential for climate-based predictions of population trends in 20 species. Nevertheless, data from the warm and dry year of 2003 indicate that negative effects of climatic extremes are generally underestimated for habitat specialists in drought-susceptible habitats, whereas generalists remain unaffected. Further climatic warming is expected to influence the trends of 13 species, leading to an improvement for nine species, but a continued decline in the majority of species. Expectations from climate envelope models overestimate the positive effects of climate change in northwestern Europe. Our results underline the challenge to include population trends in predicting range shifts in response to climate change.
Effects of climate change on marine and estuarine species will vary with attributes of the species and the spatial patterns of environmental change at the habitat and global scales. To better predict which species are at greatest risk, we are developing a knowledge base of specie...
Climate change, biotic interactions and ecosystem services
Montoya, José M.; Raffaelli, Dave
2010-01-01
Climate change is real. The wrangling debates are over, and we now need to move onto a predictive ecology that will allow managers of landscapes and policy makers to adapt to the likely changes in biodiversity over the coming decades. There is ample evidence that ecological responses are already occurring at the individual species (population) level. The challenge is how to synthesize the growing list of such observations with a coherent body of theory that will enable us to predict where and when changes will occur, what the consequences might be for the conservation and sustainable use of biodiversity and what we might do practically in order to maintain those systems in as good condition as possible. It is thus necessary to investigate the effects of climate change at the ecosystem level and to consider novel emergent ecosystems composed of new species assemblages arising from differential rates of range shifts of species. Here, we present current knowledge on the effects of climate change on biotic interactions and ecosystem services supply, and summarize the papers included in this volume. We discuss how resilient ecosystems are in the face of the multiple components that characterize climate change, and suggest which current ecological theories may be used as a starting point to predict ecosystem-level effects of climate change. PMID:20513709
Meersmans, Jeroen; Arrouays, Dominique; Van Rompaey, Anton J. J.; Pagé, Christian; De Baets, Sarah; Quine, Timothy A.
2016-01-01
Many studies have highlighted significant interactions between soil C reservoir dynamics and global climate and environmental change. However, in order to estimate the future soil organic carbon sequestration potential and related ecosystem services well, more spatially detailed predictions are needed. The present study made detailed predictions of future spatial evolution (at 250 m resolution) of topsoil SOC driven by climate change and land use change for France up to the year 2100 by taking interactions between climate, land use and soil type into account. We conclude that climate change will have a much bigger influence on future SOC losses in mid-latitude mineral soils than land use change dynamics. Hence, reducing CO2 emissions will be crucial to prevent further loss of carbon from our soils. PMID:27808169
Meersmans, Jeroen; Arrouays, Dominique; Van Rompaey, Anton J J; Pagé, Christian; De Baets, Sarah; Quine, Timothy A
2016-11-03
Many studies have highlighted significant interactions between soil C reservoir dynamics and global climate and environmental change. However, in order to estimate the future soil organic carbon sequestration potential and related ecosystem services well, more spatially detailed predictions are needed. The present study made detailed predictions of future spatial evolution (at 250 m resolution) of topsoil SOC driven by climate change and land use change for France up to the year 2100 by taking interactions between climate, land use and soil type into account. We conclude that climate change will have a much bigger influence on future SOC losses in mid-latitude mineral soils than land use change dynamics. Hence, reducing CO 2 emissions will be crucial to prevent further loss of carbon from our soils.
Climate change and species interactions: ways forward.
Angert, Amy L; LaDeau, Shannon L; Ostfeld, Richard S
2013-09-01
With ongoing and rapid climate change, ecologists are being challenged to predict how individual species will change in abundance and distribution, how biotic communities will change in structure and function, and the consequences of these climate-induced changes for ecosystem functioning. It is now well documented that indirect effects of climate change on species abundances and distributions, via climatic effects on interspecific interactions, can outweigh and even reverse the direct effects of climate. However, a clear framework for incorporating species interactions into projections of biological change remains elusive. To move forward, we suggest three priorities for the research community: (1) utilize tractable study systems as case studies to illustrate possible outcomes, test processes highlighted by theory, and feed back into modeling efforts; (2) develop a robust analytical framework that allows for better cross-scale linkages; and (3) determine over what time scales and for which systems prediction of biological responses to climate change is a useful and feasible goal. We end with a list of research questions that can guide future research to help understand, and hopefully mitigate, the negative effects of climate change on biota and the ecosystem services they provide. © 2013 New York Academy of Sciences.
Factsheet: Climate Change and Harmful Algal Blooms
Climate change is predicted to change many environmental conditions that could affect the properties of fresh and marine waters. These changes could favor the growth of harmful algal blooms and habitat changes.
Westphal, Michael F; Stewart, Joseph A E; Tennant, Erin N; Butterfield, H Scott; Sinervo, Barry
2016-01-01
Extreme weather events can provide unique opportunities for testing models that predict the effect of climate change. Droughts of increasing severity have been predicted under numerous models, thus contemporary droughts may allow us to test these models prior to the onset of the more extreme effects predicted with a changing climate. In the third year of an ongoing severe drought, surveys failed to detect neonate endangered blunt-nosed leopard lizards in a subset of previously surveyed populations where we expected to see them. By conducting surveys at a large number of sites across the range of the species over a short time span, we were able to establish a strong positive correlation between winter precipitation and the presence of neonate leopard lizards over geographic space. Our results are consistent with those of numerous longitudinal studies and are in accordance with predictive climate change models. We suggest that scientists can take immediate advantage of droughts while they are still in progress to test patterns of occurrence in other drought-sensitive species and thus provide for more robust models of climate change effects on biodiversity.
Response of Groundwater Recharge to Potential Future Climate Change in the Grand River Watershed
NASA Astrophysics Data System (ADS)
Jyrkama, M. I.; Sykes, J. F.
2004-05-01
The Grand River watershed is situated in south-western Ontario, draining an area of nearly 7000 square kilometres into Lake Erie. Approximately eighty percent of the population in the watershed derive their drinking water from groundwater sources. Quantifying the recharge input to the groundwater system and the impact of climate variability due to climate change is, therefore, essential for ensuring the quantity and sustainability of the watershed's drinking water resources in the future. The primary goal of this study is to investigate the impact of potential future climate changes on groundwater recharge in the Grand River watershed. The physically based hydrologic model HELP3 is used in conjunction with GIS to simulate the past conditions and future changes in evapotranspiration, potential surface runoff, and groundwater recharge rates as a result of projected changes in the regions climate. The climate change projections are based on the general predictions reported by the Intergovernmental Panel on Climate Change (IPCC) in 2001. Forty years of daily historical weather data are used as the reference condition. The impact of climate change on the hydrologic cycle over a forty year study period is modelled by perturbing the HELP3 model input parameters using predicted future changes in precipitation, temperature, and solar radiation. The changes in land use and vegetation cover over time were not considered in the study. The results of the study indicate that the overall simulated rate of groundwater recharge is predicted to increase in the watershed as a result of the projected future climate change. Warmer winter temperatures will reduce the extent and duration of ground frost and shift the springmelt from spring toward winter months, allowing more water to infiltrate into the ground. This results in decreased surface runoff, higher infiltration, and subsequently increased groundwater recharge. The predicted higher intensity and frequency of future precipitation will not only contribute significantly to increased surface runoff, but also results in higher evapotranspiration and groundwater recharge rates due to increased amounts of available water. Changes in the incoming solar radiation have a minimal impact on the simulated hydrologic processes. The overall simulated average annual recharge in the watershed is predicted to increase by approximately 100 mm/year over the next forty years from 189 mm/year to 289 mm/year.
Morin, Xavier; Thuiller, Wilfried
2009-05-01
Obtaining reliable predictions of species range shifts under climate change is a crucial challenge for ecologists and stakeholders. At the continental scale, niche-based models have been widely used in the last 10 years to predict the potential impacts of climate change on species distributions all over the world, although these models do not include any mechanistic relationships. In contrast, species-specific, process-based predictions remain scarce at the continental scale. This is regrettable because to secure relevant and accurate predictions it is always desirable to compare predictions derived from different kinds of models applied independently to the same set of species and using the same raw data. Here we compare predictions of range shifts under climate change scenarios for 2100 derived from niche-based models with those of a process-based model for 15 North American boreal and temperate tree species. A general pattern emerged from our comparisons: niche-based models tend to predict a stronger level of extinction and a greater proportion of colonization than the process-based model. This result likely arises because niche-based models do not take phenotypic plasticity and local adaptation into account. Nevertheless, as the two kinds of models rely on different assumptions, their complementarity is revealed by common findings. Both modeling approaches highlight a major potential limitation on species tracking their climatic niche because of migration constraints and identify similar zones where species extirpation is likely. Such convergent predictions from models built on very different principles provide a useful way to offset uncertainties at the continental scale. This study shows that the use in concert of both approaches with their own caveats and advantages is crucial to obtain more robust results and that comparisons among models are needed in the near future to gain accuracy regarding predictions of range shifts under climate change.
Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.
Steen, Valerie; Skagen, Susan K; Noon, Barry R
2014-01-01
The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971-2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981-2000 and projected future distributions to climate scenarios for 2040-2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.
A dynamic eco-evolutionary model predicts slow response of alpine plants to climate warming.
Cotto, Olivier; Wessely, Johannes; Georges, Damien; Klonner, Günther; Schmid, Max; Dullinger, Stefan; Thuiller, Wilfried; Guillaume, Frédéric
2017-05-05
Withstanding extinction while facing rapid climate change depends on a species' ability to track its ecological niche or to evolve a new one. Current methods that predict climate-driven species' range shifts use ecological modelling without eco-evolutionary dynamics. Here we present an eco-evolutionary forecasting framework that combines niche modelling with individual-based demographic and genetic simulations. Applying our approach to four endemic perennial plant species of the Austrian Alps, we show that accounting for eco-evolutionary dynamics when predicting species' responses to climate change is crucial. Perennial species persist in unsuitable habitats longer than predicted by niche modelling, causing delayed range losses; however, their evolutionary responses are constrained because long-lived adults produce increasingly maladapted offspring. Decreasing population size due to maladaptation occurs faster than the contraction of the species range, especially for the most abundant species. Monitoring of species' local abundance rather than their range may likely better inform on species' extinction risks under climate change.
Improving the forecast for biodiversity under climate change.
Urban, M C; Bocedi, G; Hendry, A P; Mihoub, J-B; Pe'er, G; Singer, A; Bridle, J R; Crozier, L G; De Meester, L; Godsoe, W; Gonzalez, A; Hellmann, J J; Holt, R D; Huth, A; Johst, K; Krug, C B; Leadley, P W; Palmer, S C F; Pantel, J H; Schmitz, A; Zollner, P A; Travis, J M J
2016-09-09
New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species' responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity. Copyright © 2016, American Association for the Advancement of Science.
Implication of global climate change on the distribution and activity of Phytophthora ramorum
Robert C. Venette
2009-01-01
Global climate change is predicted to alter the distribution and activity of several forest pathogens. Boland et al. (2004) suggested that climate change might affect pathogen establishment, rate of disease progress, and the duration of...
PROJECTED CLIMATE-INDUCED FAUNAL CHANGE IN THE WESTERN HEMISPHERE
Climate change is predicted to be one of the greatest drivers of ecological change in the coming century. Increases in temperature over the last century have clearly been linked to shifts in species distributions. Given the magnitude of projected future climatic changes, we can e...
Comparative study on Climate Change Policies in the EU and China
NASA Astrophysics Data System (ADS)
Bray, M.; Han, D.
2012-04-01
Both the EU and China are among the largest CO2 emitters in the world; their climate actions and policies have profound impacts on global climate change and may influence the activities in other countries. Evidence of climate change has been observed across Europe and China. Despite the many differences between the two regions, the European Commission and Chinese government support climate change actions. The EU has three priority areas in climate change: 1) understanding, monitoring and predicting climate change and its impact; 2) providing tools to analyse the effectiveness, cost and benefits of different policy options for mitigating climate change and adapting to its impacts; 3) improving, demonstrating and deploying existing climate friendly technologies and developing the technologies of the future. China is very vulnerable to climate change, because of its vast population, fast economic development, and fragile ecological environment. The priority policies in China are: 1) Carbon Trading Policy; 2) Financing Loan Policy (Special Funds for Renewable Energy Development); 3) Energy Efficiency Labelling Policy; 4) Subsidy Policy. In addition, China has formulated the "Energy Conservation Law", "Renewable Energy Law", "Cleaner Production Promotion Law" and "Circular Economy Promotion Law". Under the present EU Framework Programme FP7 there is a large number of funded research activities linked to climate change research. Current climate change research projects concentrate on the carbon cycle, water quality and availability, climate change predictors, predicting future climate and understanding past climates. Climate change-related scientific and technological projects in China are mostly carried out through national scientific and technological research programs. Areas under investigation include projections and impact of global climate change, the future trends of living environment change in China, countermeasures and supporting technologies of global environment change, formation mechanism and prediction theory of major climate and weather disasters in China, technologies of efficient use of clean energy, energy conservation and improvement of energy efficiency, development and utilisation technology of renewable energy and new energy. The EU recognises that developing countries, such as China and India, need to strengthen their economies through industrialisation. However this needs to be achieved at the same time as protecting the environment and sustainable use of energy. The EU has committed itself to assisting developing countries to achieve their goals in four priority areas: 1) raising the policy profile of climate change; 2) support for adaption to climate change; 3) support for mitigation of climate change; and 4) capacity development. This comparative study is part of the EU funded SPRING project which seeks to understand and assess Chinese and European competencies, with the aim of facilitating greater cooperation in future climate and environment research.
Stephen N. Matthews; Louis R. Iverson; Anantha M. Prasad; Matthew P. Peters
2011-01-01
Mounting evidence shows that organisms have already begun to respond to global climate change. Advances in our knowledge of how climate shapes species distributional patterns has helped us better understand the response of birds to climate change. However, the distribution of birds across the landscape is also driven by biotic and abiotic components, including habitat...
Urban, Mark C.; Tewksbury, Josh J.; Sheldon, Kimberly S.
2012-01-01
Most climate change predictions omit species interactions and interspecific variation in dispersal. Here, we develop a model of multiple competing species along a warming climatic gradient that includes temperature-dependent competition, differences in niche breadth and interspecific differences in dispersal ability. Competition and dispersal differences decreased diversity and produced so-called ‘no-analogue’ communities, defined as a novel combination of species that does not currently co-occur. Climate change altered community richness the most when species had narrow niches, when mean community-wide dispersal rates were low and when species differed in dispersal abilities. With high interspecific dispersal variance, the best dispersers tracked climate change, out-competed slower dispersers and caused their extinction. Overall, competition slowed the advance of colonists into newly suitable habitats, creating lags in climate tracking. We predict that climate change will most threaten communities of species that have narrow niches (e.g. tropics), vary in dispersal (most communities) and compete strongly. Current forecasts probably underestimate climate change impacts on biodiversity by neglecting competition and dispersal differences. PMID:22217718
Northward migration under a changing climate: a case study of blackgum (Nyssa Sylvatica)
Johanna Desprez; Basil V. Iannone III; Peilin Yang; Christopher M. Oswalt; Songlin Fei
2014-01-01
Species are predicted to shift their distribution ranges in response to climate change. Region-wide, empirically-based studies, however, are still limited to support these predictions. We used a model tree species, blackgum (Nyssa sylvatica), to study climate-induced range shift. Data collected from two separate sampling periods (1980s and 2007) by the USDAâs Forestry...
Towards more accurate vegetation mortality predictions
Sevanto, Sanna Annika; Xu, Chonggang
2016-09-26
Predicting the fate of vegetation under changing climate is one of the major challenges of the climate modeling community. Here, terrestrial vegetation dominates the carbon and water cycles over land areas, and dramatic changes in vegetation cover resulting from stressful environmental conditions such as drought feed directly back to local and regional climate, potentially leading to a vicious cycle where vegetation recovery after a disturbance is delayed or impossible.
Emerging trends in global freshwater availability.
Rodell, M; Famiglietti, J S; Wiese, D N; Reager, J T; Beaudoing, H K; Landerer, F W; Lo, M-H
2018-05-01
Freshwater availability is changing worldwide. Here we quantify 34 trends in terrestrial water storage observed by the Gravity Recovery and Climate Experiment (GRACE) satellites during 2002-2016 and categorize their drivers as natural interannual variability, unsustainable groundwater consumption, climate change or combinations thereof. Several of these trends had been lacking thorough investigation and attribution, including massive changes in northwestern China and the Okavango Delta. Others are consistent with climate model predictions. This observation-based assessment of how the world's water landscape is responding to human impacts and climate variations provides a blueprint for evaluating and predicting emerging threats to water and food security.
Princé, Karine; Lorrillière, Romain; Barbet-Massin, Morgane; Léger, François; Jiguet, Frédéric
2015-01-01
Climate and land use changes are key drivers of current biodiversity trends, but interactions between these drivers are poorly modeled, even though they could amplify or mitigate negative impacts of climate change. Here, we attempt to predict the impacts of different agricultural change scenarios on common breeding birds within farmland included in the potential future climatic suitable areas for these species. We used the Special Report on Emissions Scenarios (SRES) to integrate likely changes in species climatic suitability, based on species distribution models, and changes in area of farmland, based on the IMAGE model, inside future climatic suitable areas. We also developed six farmland cover scenarios, based on expert opinion, which cover a wide spectrum of potential changes in livestock farming and cropping patterns by 2050. We ran generalized linear mixed models to calibrate the effects of farmland cover and climate change on bird specific abundance within 386 small agricultural regions. We used model outputs to predict potential changes in bird populations on the basis of predicted changes in regional farmland cover, in area of farmland and in species climatic suitability. We then examined the species sensitivity according to their habitat requirements. A scenario based on extensification of agricultural systems (i.e., low-intensity agriculture) showed the greatest potential to reduce reverse current declines in breeding birds. To meet ecological requirements of a larger number of species, agricultural policies accounting for regional disparities and landscape structure appear more efficient than global policies uniformly implemented at national scale. Interestingly, we also found evidence that farmland cover changes can mitigate the negative effect of climate change. Here, we confirm that there is a potential for countering negative effects of climate change by adaptive management of landscape. We argue that such studies will help inform sustainable agricultural policies for the future.
Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola
2015-11-15
Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on river ecosystems. Copyright © 2015 Elsevier B.V. All rights reserved.
Disease and thermal acclimation in a more variable and unpredictable climate
NASA Astrophysics Data System (ADS)
Raffel, Thomas R.; Romansic, John M.; Halstead, Neal T.; McMahon, Taegan A.; Venesky, Matthew D.; Rohr, Jason R.
2013-02-01
Global climate change is shifting the distribution of infectious diseases of humans and wildlife with potential adverse consequences for disease control. As well as increasing mean temperatures, climate change is expected to increase climate variability, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments conducted in 80 independent incubators, and field data on disease-associated frog declines in Latin America, support the framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis. Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was opposite to the pattern of growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. If similar acclimation responses influence other host-parasite systems, as seems likely, then present models, which generally ignore small-scale temporal variability in climate, might provide poor predictions for climate effects on disease.
NASA Technical Reports Server (NTRS)
Chen, Wei-Ting; Liao, Hong; Seinfeld, John H.
2007-01-01
Long-lived greenhouse gases (GHGs) are the most important driver of climate change over the next century. Aerosols and tropospheric ozone (O3) are expected to induce significant perturbations to the GHG-forced climate. To distinguish the equilibrium climate responses to changes in direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and GHG between present day and year 2100, four 80-year equilibrium climates are simulated using a unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 110. Concentrations of sulfate, nitrate, primary organic (POA) carbon, secondary organic (SOA) carbon, black carbon (BC) aerosols, and tropospheric ozone for present day and year 2100 are obtained a priori by coupled chemistry-aerosol GCM simulations, with emissions of aerosols, ozone, and precursors based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) A2. Changing anthropogenic aerosols, tropospheric ozone, and GHG from present day to year 2100 is predicted to perturb the global annual mean radiative forcing by +0.18 (considering aerosol direct effects only), +0.65, and +6.54 W m(sup -2) at the tropopause, and to induce an equilibrium global annual mean surface temperature change of +0.14, +0.32, and +5.31 K, respectively, with the largest temperature response occurring at northern high latitudes. Anthropogenic aerosols, through their direct effect, are predicted to alter the Hadley circulation owing to an increasing interhemispheric temperature gradient, leading to changes in tropical precipitation. When changes in both aerosols and tropospheric ozone are considered, the predicted patterns of change in global circulation and the hydrological cycle are similar to those induced by aerosols alone. GHG-induced climate changes, such as amplified warming over high latitudes, weakened Hadley circulation, and increasing precipitation over the Tropics and high latitudes, are consistent with predictions of a number of previous GCM studies. Finally, direct radiative forcing of anthropogenic aerosols is predicted to induce strong regional cooling over East and South Asia. Wintertime rainfall over southeastern China and the Indian subcontinent is predicted to decrease because of the increased atmospheric stability and decreased surface evaporation, while the geographic distribution of precipitation is also predicted to be altered as a result of aerosol-induced changes in wind flow.
A Systems Perspective on Responses to Climate Change
The science of climate change integrates many scientific fields to explain and predict the complex effects of greenhouse gas concentrations on the planet’s energy balance, weather patterns, and ecosystems as well as economic and social systems. A changing climate requires respons...
The impacts of climate change in coastal marine systems.
Harley, Christopher D G; Randall Hughes, A; Hultgren, Kristin M; Miner, Benjamin G; Sorte, Cascade J B; Thornber, Carol S; Rodriguez, Laura F; Tomanek, Lars; Williams, Susan L
2006-02-01
Anthropogenically induced global climate change has profound implications for marine ecosystems and the economic and social systems that depend upon them. The relationship between temperature and individual performance is reasonably well understood, and much climate-related research has focused on potential shifts in distribution and abundance driven directly by temperature. However, recent work has revealed that both abiotic changes and biological responses in the ocean will be substantially more complex. For example, changes in ocean chemistry may be more important than changes in temperature for the performance and survival of many organisms. Ocean circulation, which drives larval transport, will also change, with important consequences for population dynamics. Furthermore, climatic impacts on one or a few 'leverage species' may result in sweeping community-level changes. Finally, synergistic effects between climate and other anthropogenic variables, particularly fishing pressure, will likely exacerbate climate-induced changes. Efforts to manage and conserve living marine systems in the face of climate change will require improvements to the existing predictive framework. Key directions for future research include identifying key demographic transitions that influence population dynamics, predicting changes in the community-level impacts of ecologically dominant species, incorporating populations' ability to evolve (adapt), and understanding the scales over which climate will change and living systems will respond.
NASA Astrophysics Data System (ADS)
Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Fazliev, Alexander
2017-04-01
Description and the first results of the Russian Science Foundation project "Virtual computational information environment for analysis, evaluation and prediction of the impacts of global climate change on the environment and climate of a selected region" is presented. The project is aimed at development of an Internet-accessible computation and information environment providing unskilled in numerical modelling and software design specialists, decision-makers and stakeholders with reliable and easy-used tools for in-depth statistical analysis of climatic characteristics, and instruments for detailed analysis, assessment and prediction of impacts of global climate change on the environment and climate of the targeted region. In the framework of the project, approaches of "cloud" processing and analysis of large geospatial datasets will be developed on the technical platform of the Russian leading institution involved in research of climate change and its consequences. Anticipated results will create a pathway for development and deployment of thematic international virtual research laboratory focused on interdisciplinary environmental studies. VRE under development will comprise best features and functionality of earlier developed information and computing system CLIMATE (http://climate.scert.ru/), which is widely used in Northern Eurasia environment studies. The Project includes several major directions of research listed below. 1. Preparation of geo-referenced data sets, describing the dynamics of the current and possible future climate and environmental changes in detail. 2. Improvement of methods of analysis of climate change. 3. Enhancing the functionality of the VRE prototype in order to create a convenient and reliable tool for the study of regional social, economic and political consequences of climate change. 4. Using the output of the first three tasks, compilation of the VRE prototype, its validation, preparation of applicable detailed description of climate change in Western Siberia, and dissemination of the Project results. Results of the first stage of the Project implementation are presented. This work is supported by the Russian Science Foundation grant No16-19-10257.
Uncertainty in weather and climate prediction
Slingo, Julia; Palmer, Tim
2011-01-01
Following Lorenz's seminal work on chaos theory in the 1960s, probabilistic approaches to prediction have come to dominate the science of weather and climate forecasting. This paper gives a perspective on Lorenz's work and how it has influenced the ways in which we seek to represent uncertainty in forecasts on all lead times from hours to decades. It looks at how model uncertainty has been represented in probabilistic prediction systems and considers the challenges posed by a changing climate. Finally, the paper considers how the uncertainty in projections of climate change can be addressed to deliver more reliable and confident assessments that support decision-making on adaptation and mitigation. PMID:22042896
Incorporating climate change projections into riparian restoration planning and design
Perry, Laura G.; Reynolds, Lindsay V.; Beechie, Timothy J.; Collins, Mathias J.; Shafroth, Patrick B.
2015-01-01
Climate change and associated changes in streamflow may alter riparian habitats substantially in coming decades. Riparian restoration provides opportunities to respond proactively to projected climate change effects, increase riparian ecosystem resilience to climate change, and simultaneously address effects of both climate change and other human disturbances. However, climate change may alter which restoration methods are most effective and which restoration goals can be achieved. Incorporating climate change into riparian restoration planning and design is critical to long-term restoration of desired community composition and ecosystem services. In this review, we discuss and provide examples of how climate change might be incorporated into restoration planning at the key stages of assessing the project context, establishing restoration goals and design criteria, evaluating design alternatives, and monitoring restoration outcomes. Restoration planners have access to numerous tools to predict future climate, streamflow, and riparian ecology at restoration sites. Planners can use those predictions to assess which species or ecosystem services will be most vulnerable under future conditions, and which sites will be most suitable for restoration. To accommodate future climate and streamflow change, planners may need to adjust methods for planting, invasive species control, channel and floodplain reconstruction, and water management. Given the considerable uncertainty in future climate and streamflow projections, riparian ecological responses, and effects on restoration outcomes, planners will need to consider multiple potential future scenarios, implement a variety of restoration methods, design projects with flexibility to adjust to future conditions, and plan to respond adaptively to unexpected change.
Climate change in Australian tropical rainforests: an impending environmental catastrophe.
Williams, Stephen E; Bolitho, Elizabeth E; Fox, Samantha
2003-09-22
It is now widely accepted that global climate change is affecting many ecosystems around the globe and that its impact is increasing rapidly. Many studies predict that impacts will consist largely of shifts in latitudinal and altitudinal distributions. However, we demonstrate that the impacts of global climate change in the tropical rainforests of northeastern Australia have the potential to result in many extinctions. We develop bioclimatic models of spatial distribution for the regionally endemic rainforest vertebrates and use these models to predict the effects of climate warming on species distributions. Increasing temperature is predicted to result in significant reduction or complete loss of the core environment of all regionally endemic vertebrates. Extinction rates caused by the complete loss of core environments are likely to be severe, nonlinear, with losses increasing rapidly beyond an increase of 2 degrees C, and compounded by other climate-related impacts. Mountain ecosystems around the world, such as the Australian Wet Tropics bioregion, are very diverse, often with high levels of restricted endemism, and are therefore important areas of biodiversity. The results presented here suggest that these systems are severely threatened by climate change.
Phylogeny predicts future habitat shifts due to climate change.
Kuntner, Matjaž; Năpăruş, Magdalena; Li, Daiqin; Coddington, Jonathan A
2014-01-01
Taxa may respond differently to climatic changes, depending on phylogenetic or ecological effects, but studies that discern among these alternatives are scarce. Here, we use two species pairs from globally distributed spider clades, each pair representing two lifestyles (generalist, specialist) to test the relative importance of phylogeny versus ecology in predicted responses to climate change. We used a recent phylogenetic hypothesis for nephilid spiders to select four species from two genera (Nephilingis and Nephilengys) that match the above criteria, are fully allopatric but combined occupy all subtropical-tropical regions. Based on their records, we modeled each species niche spaces and predicted their ecological shifts 20, 40, 60, and 80 years into the future using customized GIS tools and projected climatic changes. Phylogeny better predicts the species current ecological preferences than do lifestyles. By 2080 all species face dramatic reductions in suitable habitat (54.8-77.1%) and adapt by moving towards higher altitudes and latitudes, although at different tempos. Phylogeny and life style explain simulated habitat shifts in altitude, but phylogeny is the sole best predictor of latitudinal shifts. Models incorporating phylogenetic relatedness are an important additional tool to predict accurately biotic responses to global change.
Body size and activity times mediate mammalian responses to climate change.
McCain, Christy M; King, Sarah R B
2014-06-01
Model predictions of extinction risks from anthropogenic climate change are dire, but still overly simplistic. To reliably predict at-risk species we need to know which species are currently responding, which are not, and what traits are mediating the responses. For mammals, we have yet to identify overarching physiological, behavioral, or biogeographic traits determining species' responses to climate change, but they must exist. To date, 73 mammal species in North America and eight additional species worldwide have been assessed for responses to climate change, including local extirpations, range contractions and shifts, decreased abundance, phenological shifts, morphological or genetic changes. Only 52% of those species have responded as expected, 7% responded opposite to expectations, and the remaining 41% have not responded. Which mammals are and are not responding to climate change is mediated predominantly by body size and activity times (phylogenetic multivariate logistic regressions, P < 0.0001). Large mammals respond more, for example, an elk is 27 times more likely to respond to climate change than a shrew. Obligate diurnal and nocturnal mammals are more than twice as likely to respond as mammals with flexible activity times (P < 0.0001). Among the other traits examined, species with higher latitudinal and elevational ranges were more likely to respond to climate change in some analyses, whereas hibernation, heterothermy, burrowing, nesting, and study location did not influence responses. These results indicate that some mammal species can behaviorally escape climate change whereas others cannot, analogous to paleontology's climate sheltering hypothesis. Including body size and activity flexibility traits into future extinction risk forecasts should substantially improve their predictive utility for conservation and management. © 2014 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Keeley, J. E.; Syphard, A. D.
2016-12-01
Global warming is expected to exacerbate fire impacts. Predicting how climates will impact future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned, however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models are needed that predict future seasonal temperature changes if we are to forecast future fire regimes in these forests. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited, and because they are closely juxtaposed with human habitations fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science, it is far more complicated than that. Climate change is not relevant on some landscapes, but where climate is relevant the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.
Assessing the sensitivity of avian species abundance to land cover and climate
Jaymi J. LeBrun; Wayne E. Thogmartin; Frank R. Thompson; William D. Dijak; Joshua J. Millspaugh
2016-01-01
Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and...
Effects of climate change and variability on population dynamics in a long-lived shorebird.
van de Pol, Martijn; Vindenes, Yngvild; Saether, Bernt-Erik; Engen, Steinar; Ens, Bruno J; Oosterbeek, Kees; Tinbergen, Joost M
2010-04-01
Climate change affects both the mean and variability of climatic variables, but their relative impact on the dynamics of populations is still largely unexplored. Based on a long-term study of the demography of a declining Eurasian Oystercatcher (Haematopus ostralegus) population, we quantify the effect of changes in mean and variance of winter temperature on different vital rates across the life cycle. Subsequently, we quantify, using stochastic stage-structured models, how changes in the mean and variance of this environmental variable affect important characteristics of the future population dynamics, such as the time to extinction. Local mean winter temperature is predicted to strongly increase, and we show that this is likely to increase the population's persistence time via its positive effects on adult survival that outweigh the negative effects that higher temperatures have on fecundity. Interannual variation in winter temperature is predicted to decrease, which is also likely to increase persistence time via its positive effects on adult survival that outweigh the negative effects that lower temperature variability has on fecundity. Overall, a 0.1 degrees C change in mean temperature is predicted to alter median time to extinction by 1.5 times as many years as would a 0.1 degrees C change in the standard deviation in temperature, suggesting that the dynamics of oystercatchers are more sensitive to changes in the mean than in the interannual variability of this climatic variable. Moreover, as climate models predict larger changes in the mean than in the standard deviation of local winter temperature, the effects of future climatic variability on this population's time to extinction are expected to be overwhelmed by the effects of changes in climatic means. We discuss the mechanisms by which climatic variability can either increase or decrease population viability and how this might depend both on species' life histories and on the vital rates affected. This study illustrates that, for making reliable inferences about population consequences in species in which life history changes with age or stage, it is crucial to investigate the impact of climate change on vital rates across the entire life cycle. Disturbingly, such data are unavailable for most species of conservation concern.
The effects of climate change on instream nitrogen transport in the contiguous United States
NASA Astrophysics Data System (ADS)
Alam, M. J.; Goodall, J. L.
2011-12-01
Excessive nitrogen loading has caused significant environmental impacts such as eutrophication and hypoxia in waterbodies around the world. Nitrogen loading is largely dependent on nonpoint source pollution and nitrogen transport from nonpoint source pollution is greatly impacted by climate conditions. For example, increased precipitation leads to more runoff and a higher nitrogen yield. However, higher temperatures also impact nitrogen transport in that higher temperatures increase denitrification and therefore reduce nitrogen yield. The purpose of this research is to quantify potential changes in nitrogen yield for the contiguous United States under predicted climate change scenarios, specifically changes in precipitation and air temperature. The analysis was performed for high (A2) and low (B1) emission scenarios and for the year 2030, 2050 and 2090. We used 11 different IPCC (The Intergovernmental Panel on Climate Change) models predicted precipitation and temperature estimates to capture uncertainty. The SPARROW model was calibrated using historical nitrogen loading data and used to predict nitrogen yields for future climate conditions. We held nitrogen source data constant in order to isolate the impact of predicted precipitation and temperature changes for each model scenario. Preliminary results suggest an overall decrease in nitrogen yield if climate change impacts are considered in isolation. For the A2 scenario, the model results indicated an overall incremental nitrogen yield decrease of 2-17% by the year 2030, 4-26% by the year 2050, and 11-45% by the year 2090. The B1 emission scenario also indicated an incremental yield decrease, but at lesser amounts of 2-18%, 5-21% and 10-38% by the years 2030, 2050, and 2090, respectively. This decrease is mainly due to higher predicted temperatures that result in increased denitrification rates.
Misleading prioritizations from modelling range shifts under climate change
Sofaer, Helen R.; Jarnevich, Catherine S.; Flather, Curtis H.
2018-01-01
AimConservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.LocationConterminous U.S.A.Time period1977–2014.Major taxa studiedPasserine birds.MethodsWe estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.ResultsSpecies distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.Main conclusionsModels failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and frameworks continue to be refined, performance assessments and validation efforts should focus on the measures of risk and vulnerability useful for decision-making.
Competitive and demographic leverage points of community shifts under climate warming
Sorte, Cascade J. B.; White, J. Wilson
2013-01-01
Accelerating rates of climate change and a paucity of whole-community studies of climate impacts limit our ability to forecast shifts in ecosystem structure and dynamics, particularly because climate change can lead to idiosyncratic responses via both demographic effects and altered species interactions. We used a multispecies model to predict which processes and species' responses are likely to drive shifts in the composition of a space-limited benthic marine community. Our model was parametrized from experimental manipulations of the community. Model simulations indicated shifts in species dominance patterns as temperatures increase, with projected shifts in composition primarily owing to the temperature dependence of growth, mortality and competition for three critical species. By contrast, warming impacts on two other species (rendering them weaker competitors for space) and recruitment rates of all species were of lesser importance in determining projected community changes. Our analysis reveals the importance of temperature-dependent competitive interactions for predicting effects of changing climate on such communities. Furthermore, by identifying processes and species that could disproportionately leverage shifts in community composition, our results contribute to a mechanistic understanding of climate change impacts, thereby allowing more insightful predictions of future biodiversity patterns. PMID:23658199
Space can substitute for time in predicting climate-change effects on biodiversity
Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon
2013-01-01
“Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.
Space can substitute for time in predicting climate-change effects on biodiversity.
Blois, Jessica L; Williams, John W; Fitzpatrick, Matthew C; Jackson, Stephen T; Ferrier, Simon
2013-06-04
"Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.
Climate change and future fire regimes: Examples from California
Keeley, Jon E.; Syphard, Alexandra D.
2016-01-01
Climate and weather have long been noted as playing key roles in wildfire activity, and global warming is expected to exacerbate fire impacts on natural and urban ecosystems. Predicting future fire regimes requires an understanding of how temperature and precipitation interact to control fire activity. Inevitably this requires historical analyses that relate annual burning to climate variation. Fuel structure plays a critical role in determining which climatic parameters are most influential on fire activity, and here, by focusing on the diversity of ecosystems in California, we illustrate some principles that need to be recognized in predicting future fire regimes. Spatial scale of analysis is important in that large heterogeneous landscapes may not fully capture accurate relationships between climate and fires. Within climatically homogeneous subregions, montane forested landscapes show strong relationships between annual fluctuations in temperature and precipitation with area burned; however, this is strongly seasonal dependent; e.g., winter temperatures have very little or no effect but spring and summer temperatures are critical. Climate models that predict future seasonal temperature changes are needed to improve fire regime projections. Climate does not appear to be a major determinant of fire activity on all landscapes. Lower elevations and lower latitudes show little or no increase in fire activity with hotter and drier conditions. On these landscapes climate is not usually limiting to fires but these vegetation types are ignition-limited. Moreover, because they are closely juxtaposed with human habitations, fire regimes are more strongly controlled by other direct anthropogenic impacts. Predicting future fire regimes is not rocket science; it is far more complicated than that. Climate change is not relevant to some landscapes, but where climate is relevant, the relationship will change due to direct climate effects on vegetation trajectories, as well as by feedback processes of fire effects on vegetation distribution, plus policy changes in how we manage ecosystems.
Potential effects on health of global warming
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haines, A.; Parry, M.
1993-12-01
Prediction of the impacts of global climate change on health is complicated by a number of factors. These include: the difficulty in predicting regional changes in climate, the capacity for adaptation to climate change, the interactions between the effects of global climate change and a number of other key determinants of health, including population growth and poverty, and the availability of adequate preventive and curative facilities for diseases that may be effected by climate change. Nevertheless, it is of importance to consider the potential health impacts of global climate change for a number of reasons. It is also important tomore » monitor diseases which could be effected by climate change in order to detect changes in incidence as early as possible and study possible interactions with other factors. It seems likely that the possible impacts on health of climate change will be a major determinant of the degree to which policies aimed at reducing global warming are followed, as perceptions of the effect of climate change to human health and well-being are particularly likely to influence public opinion. The potential health impacts of climate change can be divided into direct (primary) and indirect (secondary and tertiary) effects. Primary effects are those related to the effect of temperature on human well-being and disease. Secondary effects include the impacts on health of changes in food production, availability of water and of sea level rise. A tertiary level of impacts can also be hypothesized.« less
Predicting evolutionary responses to climate change in the sea.
Munday, Philip L; Warner, Robert R; Monro, Keyne; Pandolfi, John M; Marshall, Dustin J
2013-12-01
An increasing number of short-term experimental studies show significant effects of projected ocean warming and ocean acidification on the performance on marine organisms. Yet, it remains unclear if we can reliably predict the impact of climate change on marine populations and ecosystems, because we lack sufficient understanding of the capacity for marine organisms to adapt to rapid climate change. In this review, we emphasise why an evolutionary perspective is crucial to understanding climate change impacts in the sea and examine the approaches that may be useful for addressing this challenge. We first consider what the geological record and present-day analogues of future climate conditions can tell us about the potential for adaptation to climate change. We also examine evidence that phenotypic plasticity may assist marine species to persist in a rapidly changing climate. We then outline the various experimental approaches that can be used to estimate evolutionary potential, focusing on molecular tools, quantitative genetics, and experimental evolution, and we describe the benefits of combining different approaches to gain a deeper understanding of evolutionary potential. Our goal is to provide a platform for future research addressing the evolutionary potential for marine organisms to cope with climate change. © 2013 John Wiley & Sons Ltd/CNRS.
Kaky, Emad; Gilbert, Francis
2017-01-01
Climate change is one of the most difficult of challenges to conserving biodiversity, especially for countries with few data on the distributions of their taxa. Species distribution modelling is a modern approach to the assessment of the potential effects of climate change on biodiversity, with the great advantage of being robust to small amounts of data. Taking advantage of a recently validated dataset, we use the medicinal plants of Egypt to identify hotspots of diversity now and in the future by predicting the effect of climate change on the pattern of species richness using species distribution modelling. Then we assess how Egypt's current Protected Area network is likely to perform in protecting plants under climate change. The patterns of species richness show that in most cases the A2a 'business as usual' scenario was more harmful than the B2a 'moderate mitigation' scenario. Predicted species richness inside Protected Areas was higher than outside under all scenarios, indicating that Egypt's PAs are well placed to help conserve medicinal plants.
Assessment of climate change impact on yield of major crops in the Banas River Basin, India.
Dubey, Swatantra Kumar; Sharma, Devesh
2018-09-01
Crop growth models like AquaCrop are useful in understanding the impact of climate change on crop production considering the various projections from global circulation models and regional climate models. The present study aims to assess the climate change impact on yield of major crops in the Banas River Basin i.e., wheat, barley and maize. Banas basin is part of the semi-arid region of Rajasthan state in India. AquaCrop model is used to calculate the yield of all the three crops for a historical period of 30years (1981-2010) and then compared with observed yield data. Root Mean Square Error (RMSE) values are calculated to assess the model accuracy in prediction of yield. Further, the calibrated model is used to predict the possible impacts of climate change and CO 2 concentration on crop yield using CORDEX-SA climate projections of three driving climate models (CNRM-CM5, CCSM4 and MPI-ESM-LR) for two different scenarios (RCP4.5 and RCP8.5) for the future period 2021-2050. RMSE values of simulated yield with respect to observed yield of wheat, barley and maize are 11.99, 16.15 and 19.13, respectively. It is predicted that crop yield of all three crops will increase under the climate change conditions for future period (2021-2050). Copyright © 2018 Elsevier B.V. All rights reserved.
The origins of computer weather prediction and climate modeling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lynch, Peter
2008-03-20
Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less
The origins of computer weather prediction and climate modeling
NASA Astrophysics Data System (ADS)
Lynch, Peter
2008-03-01
Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.
Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R
2015-04-01
Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.
Aalto, Juha; Harrison, Stephan; Luoto, Miska
2017-09-11
The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.
Fernandes, Jose A; Cheung, William W L; Jennings, Simon; Butenschön, Momme; de Mora, Lee; Frölicher, Thomas L; Barange, Manuel; Grant, Alastair
2013-08-01
Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment. © 2013 John Wiley & Sons Ltd.
Vulnerability of Breeding Waterbirds to Climate Change in the Prairie Pothole Region, U.S.A
Steen, Valerie; Skagen, Susan K.; Noon, Barry R.
2014-01-01
The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts. PMID:24927165
Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.
Steen, Valerie; Skagen, Susan K.; Noon, Barry R.
2014-01-01
The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.
NASA Astrophysics Data System (ADS)
Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.
2015-06-01
Anthropogenic climate change is projected to enrich the atmosphere with carbon dioxide, change vegetation dynamics and influence the availability of water at the catchment scale. This study combines a nonlinear model for estimating changes in leaf area index (LAI) due to climatic fluctuations with the variable infiltration capacity (VIC) hydrological model to improve catchment streamflow prediction under a changing climate. The combined model was applied to 13 gauged sub-catchments with different land cover types (crop, pasture and tree) in the Goulburn-Broken catchment, Australia, for the "Millennium Drought" (1997-2009) relative to the period 1983-1995, and for two future periods (2021-2050 and 2071-2100) and two emission scenarios (Representative Concentration Pathway (RCP) 4.5 and RCP8.5) which were compared with the baseline historical period of 1981-2010. This region was projected to be warmer and mostly drier in the future as predicted by 38 Coupled Model Intercomparison Project Phase 5 (CMIP5) runs from 15 global climate models (GCMs) and for two emission scenarios. The results showed that during the Millennium Drought there was about a 29.7-66.3 % reduction in mean annual runoff due to reduced precipitation and increased temperature. When drought-induced changes in LAI were included, smaller reductions in mean annual runoff of between 29.3 and 61.4 % were predicted. The proportional increase in runoff due to modeling LAI was 1.3-10.2 % relative to not including LAI. For projected climate change under the RCP4.5 emission scenario, ignoring the LAI response to changing climate could lead to a further reduction in mean annual runoff of between 2.3 and 27.7 % in the near-term (2021-2050) and 2.3 to 23.1 % later in the century (2071-2100) relative to modeling the dynamic response of LAI to precipitation and temperature changes. Similar results (near-term 2.5-25.9 % and end of century 2.6-24.2 %) were found for climate change under the RCP8.5 emission scenario. Incorporating climate-induced changes in LAI in the VIC model reduced the projected declines in streamflow and confirms the importance of including the effects of changes in LAI in future projections of streamflow.
Levy, Karen; Zimmerman, Julie; Elliott, Mark; Bartram, Jamie; Carlton, Elizabeth; Clasen, Thomas; Dillingham, Rebecca; Eisenberg, Joseph; Guerrant, Richard; Lantagne, Daniele; Mihelcic, James; Nelson, Kara
2016-01-01
Increased precipitation and temperature variability as well as extreme events related to climate change are predicted to affect the availability and quality of water globally. Already heavily burdened with diarrheal diseases due to poor access to water, sanitation and hygiene facilities, communities throughout the developing world lack the adaptive capacity to sufficiently respond to the additional adversity caused by climate change. Studies suggest that diarrhea rates are positively correlated with increased temperature, and show a complex relationship with precipitation. Although climate change will likely increase rates of diarrheal diseases on average, there is a poor mechanistic understanding of the underlying disease transmission processes and substantial uncertainty surrounding current estimates. This makes it difficult to recommend appropriate adaptation strategies. We review the relevant climate-related mechanisms behind transmission of diarrheal disease pathogens and argue that systems-based mechanistic approaches incorporating human, engineered and environmental components are urgently needed. We then review successful systems-based approaches used in other environmental health fields and detail one modeling framework to predict climate change impacts on diarrheal diseases and design adaptation strategies. PMID:26799810
The fate of threatened coastal dune habitats in Italy under climate change scenarios.
Prisco, Irene; Carboni, Marta; Acosta, Alicia T R
2013-01-01
Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an "indirect" plant-species-based one and a simple "direct" one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the "direct" approach was unsatisfactory, "indirect" models had a good predictive performance, highlighting the importance of using species' responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats' distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future.
The Fate of Threatened Coastal Dune Habitats in Italy under Climate Change Scenarios
Prisco, Irene; Carboni, Marta; Acosta, Alicia T. R.
2013-01-01
Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an “indirect” plant-species-based one and a simple “direct” one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the “direct” approach was unsatisfactory, “indirect” models had a good predictive performance, highlighting the importance of using species’ responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats’ distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future. PMID:23874787
Liu, Wen-Cheng; Chan, Wen-Ting
2015-12-01
Climate change is one of the key factors affecting the future microbiological water quality in rivers and tidal estuaries. A coupled 3D hydrodynamic and fecal coliform transport model was developed and applied to the Danshuei River estuarine system for predicting the influences of climate change on microbiological water quality. The hydrodynamic and fecal coliform model was validated using observational salinity and fecal coliform distributions. According to the analyses of the statistical error, predictions of the salinity and the fecal coliform concentration from the model simulation quantitatively agreed with the observed data. The validated model was then applied to predict the fecal coliform contamination as a result of climate change, including the change of freshwater discharge and the sea level rise. We found that the reduction of freshwater discharge under climate change scenarios resulted in an increase in the fecal coliform concentration. The sea level rise would decrease fecal coliform distributions because both the water level and the water volume increased. A reduction in freshwater discharge has a negative impact on the fecal coliform concentration, whereas a rising sea level has a positive influence on the fecal coliform contamination. An appropriate strategy for the effective microbiological management in tidal estuaries is required to reveal the persistent trends of climate in the future.
The Icarus challenge - Predicting vulnerability to climate change using an algorithm-based species’ trait approachHenry Lee II, Christina Folger, Deborah A. Reusser, Patrick Clinton, and Rene Graham1 U.S. EPA, Western Ecology Division, Newport, OR USA E-mail: lee.henry@ep...
Fish habitat regression under water scarcity scenarios in the Douro River basin
NASA Astrophysics Data System (ADS)
Segurado, Pedro; Jauch, Eduardo; Neves, Ramiro; Ferreira, Teresa
2015-04-01
Climate change will predictably alter hydrological patterns and processes at the catchment scale, with impacts on habitat conditions for fish. The main goals of this study are to identify the stream reaches that will undergo more pronounced flow reduction under different climate change scenarios and to assess which fish species will be more affected by the consequent regression of suitable habitats. The interplay between changes in flow and temperature and the presence of transversal artificial obstacles (dams and weirs) is analysed. The results will contribute to river management and impact mitigation actions under climate change. This study was carried out in the Tâmega catchment of the Douro basin. A set of 29 Hydrological, climatic, and hydrogeomorphological variables were modelled using a water modelling system (MOHID), based on meteorological data recorded monthly between 2008 and 2014. The same variables were modelled considering future climate change scenarios. The resulting variables were used in empirical habitat models of a set of key species (brown trout Salmo trutta fario, barbell Barbus bocagei, and nase Pseudochondrostoma duriense) using boosted regression trees. The stream segments between tributaries were used as spatial sampling units. Models were developed for the whole Douro basin using 401 fish sampling sites, although the modelled probabilities of species occurrence for each stream segment were predicted only for the Tâmega catchment. These probabilities of occurrence were used to classify stream segments into suitable and unsuitable habitat for each fish species, considering the future climate change scenario. The stream reaches that were predicted to undergo longer flow interruptions were identified and crossed with the resulting predictive maps of habitat suitability to compute the total area of habitat loss per species. Among the target species, the brown trout was predicted to be the most sensitive to habitat regression due to the interplay of flow reduction, increase of temperature and transversal barriers. This species is therefore a good indicator of climate change impacts in rivers and therefore we recommend using this species as a target of monitoring programs to be implemented in the context of climate change adaptation strategies.
Climate-Induced Boreal Forest Change: Predictions versus Current Observations
NASA Technical Reports Server (NTRS)
Soja, Amber J.; Tchebakova, Nadezda M.; French, Nancy H. F.; Flannigan, Michael D.; Shugart, Herman H.; Stocks, Brian J.; Sukhinin, Anatoly I.; Parfenova, E. I.; Chapin, F. Stuart, III; Stackhouse, Paul W., Jr.
2007-01-01
For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.
Climate change can alter predator-prey dynamics and population viability of prey.
Bastille-Rousseau, Guillaume; Schaefer, James A; Peers, Michael J L; Ellington, E Hance; Mumma, Matthew A; Rayl, Nathaniel D; Mahoney, Shane P; Murray, Dennis L
2018-01-01
For many organisms, climate change can directly drive population declines, but it is less clear how such variation may influence populations indirectly through modified biotic interactions. For instance, how will climate change alter complex, multi-species relationships that are modulated by climatic variation and that underlie ecosystem-level processes? Caribou (Rangifer tarandus), a keystone species in Newfoundland, Canada, provides a useful model for unravelling potential and complex long-term implications of climate change on biotic interactions and population change. We measured cause-specific caribou calf predation (1990-2013) in Newfoundland relative to seasonal weather patterns. We show that black bear (Ursus americanus) predation is facilitated by time-lagged higher summer growing degree days, whereas coyote (Canis latrans) predation increases with current precipitation and winter temperature. Based on future climate forecasts for the region, we illustrate that, through time, coyote predation on caribou calves could become increasingly important, whereas the influence of black bear would remain unchanged. From these predictions, demographic projections for caribou suggest long-term population limitation specifically through indirect effects of climate change on calf predation rates by coyotes. While our work assumes limited impact of climate change on other processes, it illustrates the range of impact that climate change can have on predator-prey interactions. We conclude that future efforts to predict potential effects of climate change on populations and ecosystems should include assessment of both direct and indirect effects, including climate-predator interactions.
Rashford, Benjamin S.; Adams, Richard M.; Wu, Jun; Voldseth, Richard A.; Guntenspergen, Glenn R.; Werner, Brett; Johnson, W. Carter
2016-01-01
Wetland productivity in the Prairie Pothole Region (PPR) of North America is closely linked to climate. A warmer and drier climate, as predicted, will negatively affect the productivity of PPR wetlands and the services they provide. The effect of climate change on wetland productivity, however, will not only depend on natural processes (e.g., evapotranspiration), but also on human responses. Agricultural land use, the predominant use in the PPR, is unlikely to remain static as climate change affects crop yields and prices. Land use in uplands surrounding wetlands will further affect wetland water budgets and hence wetland productivity. The net impact of climate change on wetland productivity will therefore depend on both the direct effects of climate change on wetlands and the indirect effects on upland land use. We examine the effect of climate change and land-use response on semipermanent wetland productivity by combining an economic model of agricultural land-use change with an ecological model of wetland dynamics. Our results suggest that the climate change scenarios evaluated are likely to have profound effects on land use in the North and South Dakota PPR, with wheat displacing other crops and pasture. The combined pressure of land-use and climate change significantly reduces wetland productivity. In a climate scenario with a +4 °C increase in temperature, our model predicts that almost the entire region may lack the wetland productivity necessary to support wetland-dependent species.
Megan M. Friggens; Marcus V. Warwell; Jeanne C. Chambers; Stanley G. Kitchen
2012-01-01
Experimental research and species distribution modeling predict large changes in the distributions of species and vegetation types in the Interior West due to climate change. Speciesâ responses will depend not only on their physiological tolerances but also on their phenology, establishment properties, biotic interactions, and capacity to evolve and migrate. Because...
USDA-ARS?s Scientific Manuscript database
Background/Question/Methods Ecologists are being challenged to predict ecosystem responses under changing climatic conditions. Water availability is the primary driver of ecosystem processes in temperate grasslands and shrublands, but uncertainty in the magnitude and direction of change in precipita...
Bonebrake, Timothy C; Mastrandrea, Michael D
2010-07-13
Global patterns of biodiversity and comparisons between tropical and temperate ecosystems have pervaded ecology from its inception. However, the urgency in understanding these global patterns has been accentuated by the threat of rapid climate change. We apply an adaptive model of environmental tolerance evolution to global climate data and climate change model projections to examine the relative impacts of climate change on different regions of the globe. Our results project more adverse impacts of warming on tropical populations due to environmental tolerance adaptation to conditions of low interannual variability in temperature. When applied to present variability and future forecasts of precipitation data, the tolerance adaptation model found large reductions in fitness predicted for populations in high-latitude northern hemisphere regions, although some tropical regions had comparable reductions in fitness. We formulated an evolutionary regional climate change index (ERCCI) to additionally incorporate the predicted changes in the interannual variability of temperature and precipitation. Based on this index, we suggest that the magnitude of climate change impacts could be much more heterogeneous across latitude than previously thought. Specifically, tropical regions are likely to be just as affected as temperate regions and, in some regions under some circumstances, possibly more so.
Thermal regimes of Rocky Mountain lakes warm with climate change
Roberts, James J.
2017-01-01
Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1 increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans. PMID:28683083
Thermal regimes of Rocky Mountain lakes warm with climate change
Roberts, James J.; Fausch, Kurt D.; Schmidt, Travis S.; Walters, David M.
2017-01-01
Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.
Thermal regimes of Rocky Mountain lakes warm with climate change.
Roberts, James J; Fausch, Kurt D; Schmidt, Travis S; Walters, David M
2017-01-01
Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1 increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.
Climate change, species-area curves and the extinction crisis.
Lewis, Owen T
2006-01-29
An article published in the journal Nature in January 2004-in which an international team of biologists predicted that climate change would, by 2050, doom 15-37% of the earth's species to extinction-attracted unprecedented, worldwide media attention. The predictions conflict with the conventional wisdom that habitat change and modification are the most important causes of current and future extinctions. The new extinction projections come from applying a well-known ecological pattern, the species-area relationship (SAR), to data on the current distributions and climatic requirements of 1103 species. Here, I examine the scientific basis to the claims made in the Nature article. I first highlight the potential and pitfalls of using the SAR to predict extinctions in general. I then consider the additional complications that arise when applying SAR methods specifically to climate change. I assess the extent to which these issues call into question predictions of extinctions from climate change relative to other human impacts, and highlight a danger that conservation resources will be directed away from attempts to slow and mitigate the continuing effects of habitat destruction and degradation, particularly in the tropics. I suggest that the most useful contributions of ecologists over the coming decades will be in partitioning likely extinctions among interacting causes and identifying the practical means to slow the rate of species loss.
Long-distance gene flow and adaptation of forest trees to rapid climate change
Kremer, Antoine; Ronce, Ophélie; Robledo-Arnuncio, Juan J; Guillaume, Frédéric; Bohrer, Gil; Nathan, Ran; Bridle, Jon R; Gomulkiewicz, Richard; Klein, Etienne K; Ritland, Kermit; Kuparinen, Anna; Gerber, Sophie; Schueler, Silvio
2012-01-01
Forest trees are the dominant species in many parts of the world and predicting how they might respond to climate change is a vital global concern. Trees are capable of long-distance gene flow, which can promote adaptive evolution in novel environments by increasing genetic variation for fitness. It is unclear, however, if this can compensate for maladaptive effects of gene flow and for the long-generation times of trees. We critically review data on the extent of long-distance gene flow and summarise theory that allows us to predict evolutionary responses of trees to climate change. Estimates of long-distance gene flow based both on direct observations and on genetic methods provide evidence that genes can move over spatial scales larger than habitat shifts predicted under climate change within one generation. Both theoretical and empirical data suggest that the positive effects of gene flow on adaptation may dominate in many instances. The balance of positive to negative consequences of gene flow may, however, differ for leading edge, core and rear sections of forest distributions. We propose future experimental and theoretical research that would better integrate dispersal biology with evolutionary quantitative genetics and improve predictions of tree responses to climate change. PMID:22372546
Long-distance gene flow and adaptation of forest trees to rapid climate change.
Kremer, Antoine; Ronce, Ophélie; Robledo-Arnuncio, Juan J; Guillaume, Frédéric; Bohrer, Gil; Nathan, Ran; Bridle, Jon R; Gomulkiewicz, Richard; Klein, Etienne K; Ritland, Kermit; Kuparinen, Anna; Gerber, Sophie; Schueler, Silvio
2012-04-01
Forest trees are the dominant species in many parts of the world and predicting how they might respond to climate change is a vital global concern. Trees are capable of long-distance gene flow, which can promote adaptive evolution in novel environments by increasing genetic variation for fitness. It is unclear, however, if this can compensate for maladaptive effects of gene flow and for the long-generation times of trees. We critically review data on the extent of long-distance gene flow and summarise theory that allows us to predict evolutionary responses of trees to climate change. Estimates of long-distance gene flow based both on direct observations and on genetic methods provide evidence that genes can move over spatial scales larger than habitat shifts predicted under climate change within one generation. Both theoretical and empirical data suggest that the positive effects of gene flow on adaptation may dominate in many instances. The balance of positive to negative consequences of gene flow may, however, differ for leading edge, core and rear sections of forest distributions. We propose future experimental and theoretical research that would better integrate dispersal biology with evolutionary quantitative genetics and improve predictions of tree responses to climate change. © 2012 Blackwell Publishing Ltd/CNRS.
Reside, April E; VanDerWal, Jeremy; Kutt, Alex S
2012-01-01
Identifying the species most vulnerable to extinction as a result of climate change is a necessary first step in mitigating biodiversity decline. Species distribution modeling (SDM) is a commonly used tool to assess potential climate change impacts on distributions of species. We use SDMs to predict geographic ranges for 243 birds of Australian tropical savannas, and to project changes in species richness and ranges under a future climate scenario between 1990 and 2080. Realistic predictions require recognition of the variability in species capacity to track climatically suitable environments. Here we assess the effect of dispersal on model results by using three approaches: full dispersal, no dispersal and a partial-dispersal scenario permitting species to track climate change at a rate of 30 km per decade. As expected, the projected distributions and richness patterns are highly sensitive to the dispersal scenario. Projected future range sizes decreased for 66% of species if full dispersal was assumed, but for 89% of species when no dispersal was assumed. However, realistic future predictions should not assume a single dispersal scenario for all species and as such, we assigned each species to the most appropriate dispersal category based on individual mobility and habitat specificity; this permitted the best estimates of where species will be in the future. Under this “realistic” dispersal scenario, projected ranges sizes decreased for 67% of species but showed that migratory and tropical-endemic birds are predicted to benefit from climate change with increasing distributional area. Richness hotspots of tropical savanna birds are expected to move, increasing in southern savannas and southward along the east coast of Australia, but decreasing in the arid zone. Understanding the complexity of effects of climate change on species’ range sizes by incorporating dispersal capacities is a crucial step toward developing adaptation policies for the conservation of vulnerable species. PMID:22837819
Ge, Xuezhen; He, Shanyong; Wang, Tao; Yan, Wei; Zong, Shixiang
2015-01-01
As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981-2010) and future climate warming estimates based on simulated climate data for the 2020s (2011-2040) provided by the Tyndall Center for Climate Change Research (TYN SC 2.0). Additionally, the Ecoclimatic Index (EI) values calculated for different climatic conditions (current and future, as simulated by the B2 scenario) were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas.
Ge, Xuezhen; He, Shanyong; Wang, Tao; Yan, Wei; Zong, Shixiang
2015-01-01
As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981–2010) and future climate warming estimates based on simulated climate data for the 2020s (2011–2040) provided by the Tyndall Center for Climate Change Research (TYN SC 2.0). Additionally, the Ecoclimatic Index (EI) values calculated for different climatic conditions (current and future, as simulated by the B2 scenario) were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas. PMID:26496438
Preview of Our Changing Planet. The U.S. Climate Change Science Program for Fiscal Year 2008
2007-04-01
reduce the uncertainty in predictions of the global and regional water cycle and surface climate. Sunlight not reflected back to space provides the...research elements include atmospheric composition, climate variability and change, the global water cycle , land-use and land-cover change, the global...entire planet, and researchers with the ability to better explain observed changes in the climate system. Global Water Cycle – Research associated with
PREDICTING CLIMATE-INDUCED RANGE SHIFTS FOR MAMMALS: HOW GOOD ARE THE MODELS?
In order to manage wildlife and conserve biodiversity, it is critical that we understand the potential impacts of climate change on species distributions. Several different approaches to predicting climate-induced geographic range shifts have been proposed to address this proble...
Aryal, Achyut; Shrestha, Uttam Babu; Ji, Weihong; Ale, Som B; Shrestha, Sujata; Ingty, Tenzing; Maraseni, Tek; Cockfield, Geoff; Raubenheimer, David
2016-06-01
Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator-prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy-deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate-only model shows that only 11.64% (17,190 km(2)) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km(2) (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate-only model. It is predicted that future climate may alter the predator-prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards - a species already facing energetic constraints due to the limited dietary resources in its alpine habitat. Our findings provide valuable information for extension of protected areas in future.
Climate Observations from Space
NASA Astrophysics Data System (ADS)
Briggs, Stephen
2016-07-01
The latest Global Climate Observing System (GCOS) Status Report on global climate observations, delivered to the UNFCCC COP21 in November 2016, showed how satellite data are critical for observations relating to climate. Of the 50 Essential Climate Variables (ECVs) identified by GCOS as necessary for understanding climate change, about half are derived only from satellite data while half of the remainder have a significant input from satellites. Hence data from Earth observing satellite systems are now a fundamental requirement for understanding the climate system and for managing the consequences of climate change. Following the Paris Agreement of COP21 this need is only greater. Not only will satellites have to continue to provide data for modelling and predicting climate change but also for a much wider range of actions relating to climate. These include better information on loss and damage, resilience, improved adaptation to change, and on mitigation including information on greenhouse gas emissions. In addition there is an emerging need for indicators of the risks associated with future climate change which need to be better quantified, allowing policy makers both to understand what decisions need to be taken, and to see the consequences of their actions. The presentation will set out some of the ways in which satellite data are important in all aspects of understanding, managing and predicting climate change and how they may be used to support future decisions by those responsible for policy related to managing climate change and its consequences.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Branstator, Grant
The overall aim of our project was to quantify and characterize predictability of the climate as it pertains to decadal time scale predictions. By predictability we mean the degree to which a climate forecast can be distinguished from the climate that exists at initial forecast time, taking into consideration the growth of uncertainty that occurs as a result of the climate system being chaotic. In our project we were especially interested in predictability that arises from initializing forecasts from some specific state though we also contrast this predictability with predictability arising from forecasting the reaction of the system to externalmore » forcing – for example changes in greenhouse gas concentration. Also, we put special emphasis on the predictability of prominent intrinsic patterns of the system because they often dominate system behavior. Highlights from this work include: • Development of novel methods for estimating the predictability of climate forecast models. • Quantification of the initial value predictability limits of ocean heat content and the overturning circulation in the Atlantic as they are represented in various state of the art climate models. These limits varied substantially from model to model but on average were about a decade with North Atlantic heat content tending to be more predictable than North Pacific heat content. • Comparison of predictability resulting from knowledge of the current state of the climate system with predictability resulting from estimates of how the climate system will react to changes in greenhouse gas concentrations. It turned out that knowledge of the initial state produces a larger impact on forecasts for the first 5 to 10 years of projections. • Estimation of the predictability of dominant patterns of ocean variability including well-known patterns of variability in the North Pacific and North Atlantic. For the most part these patterns were predictable for 5 to 10 years. • Determination of especially predictable patterns in the North Atlantic. The most predictable of these retain predictability substantially longer than generic patterns, with some being predictable for two decades.« less
A new paradigm for predicting zonal-mean climate and climate change
NASA Astrophysics Data System (ADS)
Armour, K.; Roe, G.; Donohoe, A.; Siler, N.; Markle, B. R.; Liu, X.; Feldl, N.; Battisti, D. S.; Frierson, D. M.
2016-12-01
How will the pole-to-equator temperature gradient, or large-scale patterns of precipitation, change under global warming? Answering such questions typically involves numerical simulations with comprehensive general circulation models (GCMs) that represent the complexities of climate forcing, radiative feedbacks, and atmosphere and ocean dynamics. Yet, our understanding of these predictions hinges on our ability to explain them through the lens of simple models and physical theories. Here we present evidence that zonal-mean climate, and its changes, can be understood in terms of a moist energy balance model that represents atmospheric heat transport as a simple diffusion of latent and sensible heat (as a down-gradient transport of moist static energy, with a diffusivity coefficient that is nearly constant with latitude). We show that the theoretical underpinnings of this model derive from the principle of maximum entropy production; that its predictions are empirically supported by atmospheric reanalyses; and that it successfully predicts the behavior of a hierarchy of climate models - from a gray radiation aquaplanet moist GCM, to comprehensive GCMs participating in CMIP5. As an example of the power of this paradigm, we show that, given only patterns of local radiative feedbacks and climate forcing, the moist energy balance model accurately predicts the evolution of zonal-mean temperature and atmospheric heat transport as simulated by the CMIP5 ensemble. These results suggest that, despite all of its dynamical complexity, the atmosphere essentially responds to energy imbalances by simply diffusing latent and sensible heat down-gradient; this principle appears to explain zonal-mean climate and its changes under global warming.
Harmon, Jason P; Barton, Brandon T
2013-09-01
The increasingly appreciated link between climate change and species interactions has the potential to help us understand and predict how organisms respond to a changing environment. As this connection grows, it becomes even more important to appreciate the mechanisms that create and control the combined effect of these factors. However, we believe one such important set of mechanisms comes from species' behavior and the subsequent trait-mediated interactions, as opposed to the more often studied density-mediated effects. Behavioral mechanisms are already well appreciated for mitigating the separate effects of the environment and species interactions. Thus, they could be at the forefront for understanding the combined effects. In this review, we (1) show some of the known behaviors that influence the individual and combined effects of climate change and species interactions; (2) conceptualize general ways behavior may mediate these combined effects; and (3) illustrate the potential importance of including behavior in our current tools for predicting climate change effects. In doing so, we hope to promote more research on behavior and other mechanistic factors that may increase our ability to accurately predict climate change effects. © 2013 New York Academy of Sciences.
NASA Astrophysics Data System (ADS)
Pesce, Marco; Critto, Andrea; Torresan, Silvia; Santini, Monia; Giubilato, Elisa; Pizzol, Lisa; Mercogliano, Paola; Zirino, Alberto; Wei, Ouyang; Marcomini, Antonio
2017-04-01
It has been recognized that the increase of atmospheric greenhouse gases (GHG) due to anthropogenic activities is causing changes in Earth's climate. Global mean temperatures are expected to rise by 0.3 to 4.8 °C by the end of the 21st century, and the water cycle to alter because of changes in global atmospheric moisture. Coastal waterbodies such as estuaries, bays and lagoons together with the ecological and socio-economic services they provide, could be among those most affected by the ongoing changes on climate. Because of their position at the land-sea interface, they are subjected to the combined changes in the physico-chemical processes of atmosphere, upstream land and coastal waters. Particularly, climate change is expected to alter phytoplankton communities by changing their climate and environmental drivers, such as temperature, precipitation, wind, solar radiation and nutrient loadings, and to exacerbate the symptoms of eutrophication events, such as hypoxia, harmful algal blooms (HAB) and loss of habitat. A better understanding of the links between climate-related drivers and phytoplankton is therefore necessary for predicting climate change impacts on aquatic ecosystems. In this context, the integration of climate scenarios and environmental models can become a valuable tool for the investigation and prediction of phytoplankton ecosystem dynamics under climate change conditions. In the last decade, the effects of climate change on the environmental distribution of nutrients and the resulting effects on aquatic ecosystems encouraged the conduction of modeling studies at a catchment scale, even though mainly are related to lake ecosystem. The further development of integrated modeling approaches and their application to other types of waterbodies such as coastal waters can be a useful contribution to increase the availability of management tools for ecological conservation and adaptation policies. Here we present the case study of the Zero river basin in Italy, one of the main contributors of freshwater and nutrients loadings to the salt-marsh Palude di Cona, a waterbody belonging to the lagoon of Venice. To predict the effects of climate change on nutrient loadings and their effects on the phytoplankton community of the receiving waterbody, we applied a methodology integrating an ensemble of GCM-RCM climate projections, the hydrological model SWAT and the ecological model AQUATOX. Climate scenarios for the study area revealed an increase of precipitations in the winter period and a decrease in the summer months, while temperature shows a significant increase over the whole year. The hydrological model SWAT predicted changes the Zero river's waterflow and nutrients' loadings. Both parameters show a tendency to increase in the winter period, and a reduction during the summer months. Simulations with AQUATOX predicted changes in the concentration of nutrients in the salt-marsh Palude di Cona, and variations in the biomass and species of the phytoplankton community. The simulation shows changes are highly species-dependent. Major changes are observed in the spring-summer period, where the abundance of warm-adapted species increase noticeably.
Model uncertainties do not affect observed patterns of species richness in the Amazon.
Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo; Loyola, Rafael
2017-01-01
Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale-patterns of species richness and species vulnerability to climate change-are affected by the inputs used to model and project species distribution. We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species.
Ensembles-based predictions of climate change impacts on bioclimatic zones in Northeast Asia
NASA Astrophysics Data System (ADS)
Choi, Y.; Jeon, S. W.; Lim, C. H.; Ryu, J.
2017-12-01
Biodiversity is rapidly declining globally and efforts are needed to mitigate this continually increasing loss of species. Clustering of areas with similar habitats can be used to prioritize protected areas and distribute resources for the conservation of species, selection of representative sample areas for research, and evaluation of impacts due to environmental changes. In this study, Northeast Asia (NEA) was classified into 14 bioclimatic zones using statistical techniques, which are correlation analysis and principal component analysis (PCA), and the iterative self-organizing data analysis technique algorithm (ISODATA). Based on these bioclimatic classification, we predicted shift of bioclimatic zones due to climate change. The input variables include the current climatic data (1960-1990) and the future climatic data of the HadGEM2-AO model (RCP 4.5(2050, 2070) and 8.5(2050, 2070)) provided by WorldClim. Using these data, multi-modeling methods including maximum likelihood classification, random forest, and species distribution modelling have been used to project the impact of climate change on the spatial distribution of bioclimatic zones within NEA. The results of various models were compared and analyzed by overlapping each result. As the result, significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward and some zones were predicted to disappear. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.
Duan, Ren-Yan; Kong, Xiao-Quan; Huang, Min-Yi; Varela, Sara; Ji, Xiang
2016-01-01
Many studies predict that climate change will cause species movement and turnover, but few have considered the effect of climate change on range fragmentation for current species and/or populations. We used MaxEnt to predict suitable habitat, fragmentation and turnover for 134 amphibian species in China under 40 future climate change scenarios spanning four pathways (RCP2.6, RCP4.5, RCP6 and RCP8.5) and two time periods (the 2050s and 2070s). Our results show that climate change may cause a major shift in spatial patterns of amphibian diversity. Amphibians in China would lose 20% of their original ranges on average; the distribution outside current ranges would increase by 15%. Suitable habitats for over 90% of species will be located in the north of their current range, for over 95% of species in higher altitudes (from currently 137-4,124 m to 286-4,396 m in the 2050s or 314-4,448 m in the 2070s), and for over 75% of species in the west of their current range. Also, our results predict two different general responses to the climate change: some species contract their ranges while moving westwards, southwards and to higher altitudes, while others expand their ranges. Finally, our analyses indicate that range dynamics and fragmentation are related, which means that the effects of climate change on Chinese amphibians might be two-folded.
Huang, Min-Yi; Varela, Sara
2016-01-01
Many studies predict that climate change will cause species movement and turnover, but few have considered the effect of climate change on range fragmentation for current species and/or populations. We used MaxEnt to predict suitable habitat, fragmentation and turnover for 134 amphibian species in China under 40 future climate change scenarios spanning four pathways (RCP2.6, RCP4.5, RCP6 and RCP8.5) and two time periods (the 2050s and 2070s). Our results show that climate change may cause a major shift in spatial patterns of amphibian diversity. Amphibians in China would lose 20% of their original ranges on average; the distribution outside current ranges would increase by 15%. Suitable habitats for over 90% of species will be located in the north of their current range, for over 95% of species in higher altitudes (from currently 137–4,124 m to 286–4,396 m in the 2050s or 314–4,448 m in the 2070s), and for over 75% of species in the west of their current range. Also, our results predict two different general responses to the climate change: some species contract their ranges while moving westwards, southwards and to higher altitudes, while others expand their ranges. Finally, our analyses indicate that range dynamics and fragmentation are related, which means that the effects of climate change on Chinese amphibians might be two-folded. PMID:27547522
Simulation of Climate Change Impacts on Wheat-Fallow Cropping Systems
USDA-ARS?s Scientific Manuscript database
Agricultural system simulation models are predictive tools for assessing climate change impacts on crop production. In this study, RZWQM2 that contains the DSSAT 4.0-CERES model was evaluated for simulating climate change impacts on wheat growth. The model was calibrated and validated using data fro...
Impact of climate change on water quality of an impaired New Mexico river
USDA-ARS?s Scientific Manuscript database
Climate change is predicted to advance runoff timing in snowmelt basins and decrease available water, particularly in arid and semi-arid regions. Researchers have suggested that the impacts of climate change will degrade water quality by reducing dilution. We use coupled snowmelt and water quality m...
Predictions for snow cover, glaciers and runoff in a changing climate
USDA-ARS?s Scientific Manuscript database
The problem of evaluating the hydrological effects of climate change has opened a new field of applications for snowmelt runoff models. The Snowmelt Runoff Model (SRM) has been used to evaluate climate change effects on basins in North America, the Swiss Alps, and the Himalayas. Snow covered area ...
Implications of Climate Change for Children in Developing Countries
ERIC Educational Resources Information Center
Hanna, Rema; Oliva, Paulina
2016-01-01
Climate change may be particularly dangerous for children in developing countries. Even today, many developing countries experience a disproportionate share of extreme weather, and they are predicted to suffer disproportionately from the effects of climate change in the future. Moreover, developing countries often have limited social safety nets,…
Climate-change driven increases in water temperature pose multiple challenges for aquatic organisms. Predictions of climate change impacts to biota typically do not account for fine-grained spatiotemporal patterns of stream networks; yet patches of cooler water within rivers c...
Federal Register 2010, 2011, 2012, 2013, 2014
2011-06-21
.... During public scoping, we may identify additional issues. Climate Change and Interior Marsh Loss A growing body of evidence indicates that accelerating climate change, associated with increasing global.... Successful conservation strategies will require an understanding of climate change and the ability to predict...
Climate Change Research - What Do We Need Really?
NASA Astrophysics Data System (ADS)
Rama Chandra Prasad, P.
2015-01-01
This research note focuses on the current climate change research scenario and discusses primarily what is required in the present global climate change conditions. Most of the climate change research and models predict adverse future conditions that have to be faced by humanity, with less emphasis on mitigation measures. Moreover, research ends as reports on the shelves of scientists and researchers and as publications in journals. At this juncture the major focus should be on research that helps in reducing the impact rather than on analysing future scenarios of climate change using different models. The article raises several questions and suggestions regards climate change research and lays emphasis on what we really need from climate change researchers.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gutowski, William J.
This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASMmore » can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes in the freshwater flux between arctic climate system components resulting from decadal changes in land and sea ice, seasonal snow, vegetation, and ocean circulation. - Changing energetics due to decadal changes in ice mass, vegetation, and air-sea interactions. - The role of small-scale atmospheric and oceanic processes that influence decadal variability. This research has been addressing modes of natural climate variability as well as extreme and rapid climate change. RASM can facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts.« less
Genomic signals of selection predict climate-driven population declines in a migratory bird.
Bay, Rachael A; Harrigan, Ryan J; Underwood, Vinh Le; Gibbs, H Lisle; Smith, Thomas B; Ruegg, Kristen
2018-01-05
The ongoing loss of biodiversity caused by rapid climatic shifts requires accurate models for predicting species' responses. Despite evidence that evolutionary adaptation could mitigate climate change impacts, evolution is rarely integrated into predictive models. Integrating population genomics and environmental data, we identified genomic variation associated with climate across the breeding range of the migratory songbird, yellow warbler ( Setophaga petechia ). Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations. Broadly, our study suggests that the integration of genomic adaptation can increase the accuracy of future species distribution models and ultimately guide more effective mitigation efforts. Copyright © 2018, American Association for the Advancement of Science.
How climate change might influence the potential distribution of weed, bushmint (Hyptis suaveolens)?
Padalia, Hitendra; Srivastava, Vivek; Kushwaha, S P S
2015-04-01
Invasive species and climate change are considered as the most serious global environmental threats. In this study, we investigated the influence of projected global climate change on the potential distribution of one of the world's most successful invader weed, bushmint (Hyptis suaveolens (L.) Poit.). We used spatial data on 20 environmental variables at a grid resolution of 5 km, and 564 presence records of bushmint from its native and introduced range. The climatic profiles of the native and invaded sites were analyzed in a multi-variate space in order to examine the differences in the position of climatic niches. Maximum Entropy (MaxEnt) model was used to predict the potential distribution of bushmint using presence records from entire range (invaded and native) along with 14 eco-physiologically relevant predictor variables. Subsequently, the trained MaxEnt model was fed with Hadley Centre Coupled Model (HadCM3) climate projections to predict potential distribution of bushmint by the year 2050 under A2a and B2a emission scenarios. MaxEnt predictions were very accurate with an Area Under Curve (AUC) value of 0.95. The results of Principal Component Analysis (PCA) indicated that climatic niche of bushmint on the invaded sites is not entirely similar to its climatic niche in the native range. A vast area spread between 34 ° 02' north and 28 ° 18' south latitudes in tropics was predicted climatically suitable for bushmint. West and middle Africa, tropical southeast Asia, and northern Australia were predicted at high invasion risk. Study indicates enlargement, retreat, or shift across bushmint's invasion range under the influence of climate change. Globally, bushmint's potential distribution might shrink in future with more shrinkage for A2a scenario than B2a. The study outcome has immense potential for undertaking effective preventive/control measures and long-term management strategies for regions/countries, which are at higher risk of bushmint's invasion.
Considerations for building climate-based species distribution models
Bucklin, David N.; Basille, Mathieu; Romañach, Stephanie; Brandt, Laura A.; Mazzotti, Frank J.; Watling, James I.
2016-01-01
Climate plays an important role in the distribution of species. A given species may adjust to new conditions in-place, move to new areas with suitable climates, or go extinct. Scientists and conservation practitioners use mathematical models to predict the effects of future climate change on wildlife and plan for a biodiverse future. This 8-page fact sheet written by David N. Bucklin, Mathieu Basille, Stephanie S. Romañach, Laura A. Brandt, Frank J. Mazzotti, and James I. Watling and published by the Department of Wildlife Ecology and Conservation explains how, with a better understanding of species distribution models, we can predict how species may respond to climate change. The models alone cannot tell us how a certain species will actually respond to changes in climate, but they can inform conservation planning that aims to allow species to both adapt in place and (for those that are able to) move to newly suitable areas. Such planning will likely minimize loss of biodiversity due to climate change.
National Scale Prediction of Soil Carbon Sequestration under Scenarios of Climate Change
NASA Astrophysics Data System (ADS)
Izaurralde, R. C.; Thomson, A. M.; Potter, S. R.; Atwood, J. D.; Williams, J. R.
2006-12-01
Carbon sequestration in agricultural soils is gaining momentum as a tool to mitigate the rate of increase of atmospheric CO2. Researchers from the Pacific Northwest National Laboratory, Texas A&M University, and USDA-NRCS used the EPIC model to develop national-scale predictions of soil carbon sequestration with adoption of no till (NT) under scenarios of climate change. In its current form, the EPIC model simulates soil C changes resulting from heterotrophic respiration and wind / water erosion. Representative modeling units were created to capture the climate, soil, and management variability at the 8-digit hydrologic unit (USGS classification) watershed scale. The soils selected represented at least 70% of the variability within each watershed. This resulted in 7,540 representative modeling units for 1,412 watersheds. Each watershed was assigned a major crop system: corn, soybean, spring wheat, winter wheat, cotton, hay, alfalfa, corn-soybean rotation or wheat-fallow rotation based on information from the National Resource Inventory. Each representative farm was simulated with conventional tillage and no tillage, and with and without irrigation. Climate change scenarios for two future periods (2015-2045 and 2045-2075) were selected from GCM model runs using the IPCC SRES scenarios of A2 and B2 from the UK Hadley Center (HadCM3) and US DOE PCM (PCM) models. Changes in mean and standard deviation of monthly temperature and precipitation were extracted from gridded files and applied to baseline climate (1960-1990) for each of the 1,412 modeled watersheds. Modeled crop yields were validated against historical USDA NASS county yields (1960-1990). The HadCM3 model predicted the most severe changes in climate parameters. Overall, there would be little difference between the A2 and B2 scenarios. Carbon offsets were calculated as the difference in soil C change between conventional and no till. Overall, C offsets during the first 30-y period (513 Tg C) are predicted to be 36% higher than those predicted during the second period. The climate projections of the PCM model had more positive impact on soil C sequestration than those predicted with the HadCM3 model.
Potential changes in forest composition could reduce impacts of climate change on boreal wildfires.
Terrier, Aurélie; Girardin, Martin P; Périé, Catherine; Legendre, Pierre; Bergeron, Yves
2013-01-01
There is general consensus that wildfires in boreal forests will increase throughout this century in response to more severe and frequent drought conditions induced by climate change. However, prediction models generally assume that the vegetation component will remain static over the next few decades. As deciduous species are less flammable than conifer species, it is reasonable to believe that a potential expansion of deciduous species in boreal forests, either occurring naturally or through landscape management, could offset some of the impacts of climate change on the occurrence of boreal wildfires. The objective of this study was to determine the potential of this offsetting effect through a simulation experiment conducted in eastern boreal North America. Predictions of future fire activity were made using multivariate adaptive regression splines (MARS) with fire behavior indices and ecological niche models as predictor variables so as to take into account the effects of changing climate and tree distribution on fire activity. A regional climate model (RCM) was used for predictions of future fire risk conditions. The experiment was conducted under two tree dispersal scenarios: the status quo scenario, in which the distribution of forest types does not differ from the present one, and the unlimited dispersal scenario, which allows forest types to expand their range to fully occupy their climatic niche. Our results show that future warming will create climate conditions that are more prone to fire occurrence. However, unlimited dispersal of southern restricted deciduous species could reduce the impact of climate change on future fire occurrence. Hence, the use of deciduous species could be a good option for an efficient strategic fire mitigation strategy aimed at reducing fire Propagation in coniferous landscapes and increasing public safety in remote populated areas of eastern boreal Canada under climate change.
Predicting the Impacts of Climate Change on Central American Agriculture
NASA Astrophysics Data System (ADS)
Winter, J. M.; Ruane, A. C.; Rosenzweig, C.
2011-12-01
Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.
Archis, Jennifer N; Akcali, Christopher; Stuart, Bryan L; Kikuchi, David; Chunco, Amanda J
2018-01-01
Anthropogenic climate change is a significant global driver of species distribution change. Although many species have undergone range expansion at their poleward limits, data on several taxonomic groups are still lacking. A common method for studying range shifts is using species distribution models to evaluate current, and predict future, distributions. Notably, many sources of 'current' climate data used in species distribution modeling use the years 1950-2000 to calculate climatic averages. However, this does not account for recent (post 2000) climate change. This study examines the influence of climate change on the eastern coral snake ( Micrurus fulvius ). Specifically, we: (1) identified the current range and suitable environment of M. fulvius in the Southeastern United States, (2) investigated the potential impacts of climate change on the distribution of M. fulvius , and (3) evaluated the utility of future models in predicting recent (2001-2015) records. We used the species distribution modeling program Maxent and compared both current (1950-2000) and future (2050) climate conditions. Future climate models showed a shift in the distribution of suitable habitat across a significant portion of the range; however, results also suggest that much of the Southeastern United States will be outside the range of current conditions, suggesting that there may be no-analog environments in the future. Most strikingly, future models were more effective than the current models at predicting recent records, suggesting that range shifts may already be occurring. These results have implications for both M. fulvius and its Batesian mimics. More broadly, we recommend future Maxent studies consider using future climate data along with current data to better estimate the current distribution.
Wetland extent and plant community composition vulnerability to climate change
Michael Nassry; Denice H. Wardrop; Anna T. Hamilton; Christopher J. Duffy; Jordan M. West
2016-01-01
The potential impact of climate change on wetland-provided ecosystem services has been largely unspecified because of the difficulty in predicting changing hydrologic conditions, which are a major driver of...
Non-climatic constraints on upper elevational plant range expansion under climate change
Brown, Carissa D.; Vellend, Mark
2014-01-01
We are limited in our ability to predict climate-change-induced range shifts by our inadequate understanding of how non-climatic factors contribute to determining range limits along putatively climatic gradients. Here, we present a unique combination of observations and experiments demonstrating that seed predation and soil properties strongly limit regeneration beyond the upper elevational range limit of sugar maple, a tree species of major economic importance. Most strikingly, regeneration beyond the range limit occurred almost exclusively when seeds were experimentally protected from predators. Regeneration from seed was depressed on soil from beyond the range edge when this soil was transplanted to sites within the range, with indirect evidence suggesting that fungal pathogens play a role. Non-climatic factors are clearly in need of careful attention when attempting to predict the biotic consequences of climate change. At minimum, we can expect non-climatic factors to create substantial time lags between the creation of more favourable climatic conditions and range expansion. PMID:25253462
How does spatial variability of climate affect catchment streamflow predictions?
Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distribute...
USDA-ARS?s Scientific Manuscript database
Drylands will experience more intense and frequent droughts and floods. Ten-year field experiments manipulating the amount and variability of precipitation suggest that we cannot predict responses of drylands to climate change based on pulse experimentation. Long-term drought experiments showed no e...
Predicting Plausible Impacts of Sets of Climate and Land Use Change Scenarios on Water Resources
Global changes in climate and land use can alTect the quantity and quality of water resources. Hence, we need a methodology to predict these ramifications. Using the Little Miami River (LMR) watershed as a case study, this paper describes a spatial analytical approach integrating...
Gale, P; Brouwer, A; Ramnial, V; Kelly, L; Kosmider, R; Fooks, A R; Snary, E L
2010-02-01
Expert opinion was elicited to undertake a qualitative risk assessment to estimate the current and future risks to the European Union (EU) from five vector-borne viruses listed by the World Organization for Animal Health. It was predicted that climate change will increase the risk of incursions of African horse sickness virus (AHSV), Crimean-Congo haemorrhagic fever virus (CCHFV) and Rift Valley fever virus (RVFV) into the EU from other parts of the world, with African swine fever virus (ASFV) and West Nile virus (WNV) being less affected. Currently the predicted risks of incursion were lowest for RVFV and highest for ASFV. Risks of incursion were considered for six routes of entry (namely vectors, livestock, meat products, wildlife, pets and people). Climate change was predicted to increase the risk of incursion from entry of vectors for all five viruses to some degree, the strongest effects being predicted for AHSV, CCHFV and WNV. This work will facilitate identification of appropriate risk management options in relation to adaptations to climate change.
Consequences of a warming climate for social organisation in sweat bees.
Schürch, Roger; Accleton, Christopher; Field, Jeremy
The progression from solitary living to caste-based sociality is commonly regarded as a major evolutionary transition. However, it has recently been shown that in some taxa, sociality may be plastic and dependent on local conditions. If sociality can be environmentally driven, the question arises as to how projected climate change will influence features of social organisation that were previously thought to be of macroevolutionary proportions. Depending on the time available in spring during which a foundress can produce worker offspring, the sweat bee Halictus rubicundus is either social or solitary. We analysed detailed foraging data in relation to climate change predictions for Great Britain to assess when and where switches from a solitary to social lifestyle may be expected. We demonstrate that worker numbers should increase throughout Great Britain under predicted climate change scenarios, and importantly, that sociality should appear in northern areas where it has never before been observed. This dramatic shift in social organisation due to climate change should lead to a bigger workforce being available for summer pollination and may contribute towards mitigating the current pollinator crisis. The sweat bee Halictus rubicundus is socially polymorphic, expressing both solitary and social forms, and is socially plastic, capable of transitioning from solitary to social forms, depending on local environmental conditions. Here, we analyse detailed foraging data in relation to climate change predictions for Great Britain to show that worker numbers and sociality both increase under predicted climate change scenarios. Especially dramatic will be the appearance of social H. rubicundus nests in the north of Britain, where previously only solitary forms are found. Particularly, if more taxa are found to be socially plastic, environmentally driven shifts in social organisation may help to mitigate future pollinator crises by providing more individuals for pollination.
Barbet-Massin, Morgane; Walther, Bruno A.; Thuiller, Wilfried; Rahbek, Carsten; Jiguet, Frédéric
2009-01-01
We modelled the present and future sub-Saharan winter distributions of 64 trans-Saharan migrant passerines to predict the potential impacts of climate change. These predictions used the recent ensemble modelling developments and the latest IPCC climatic simulations to account for possible methodological uncertainties. Results suggest that 37 species would face a range reduction by 2100 (16 of these by more than 50%); however, the median range size variation is −13 per cent (from −97 to +980%) under a full dispersal hypothesis. Range centroids were predicted to shift by 500±373 km. Predicted changes in range size and location were spatially structured, with species that winter in southern and eastern Africa facing larger range contractions and shifts. Predicted changes in regional species richness for these long-distance migrants are increases just south of the Sahara and on the Arabian Peninsula and major decreases in southern and eastern Africa. PMID:19324660
NASA Astrophysics Data System (ADS)
Lazrus, H.; Done, J.; Morss, R. E.
2017-12-01
A new branch of climate science, known as decadal prediction, seeks to predict the time-varying trajectory of climate over the next 3-30 years and not just the longer-term trends. Decadal predictions bring climate information into the time horizon of decision makers, particularly those tasked with managing water resources and floods whose master planning is often on the timescale of decades. Information from decadal predictions may help alleviate some aspects of vulnerability by helping to inform decisions that reduce drought and flood exposure and increase adaptive capacities including preparedness, response, and recovery. This presentation will highlight an interdisciplinary project - involving atmospheric and social scientists - on the development of decadal climate information and its use in decision making. The presentation will explore the skill and utility of decadal drought and flood prediction along Colorado's Front Range, an area experiencing rapid population growth and uncertain climate variability and climate change impacts. Innovative statistical and dynamical atmospheric modeling techniques explore the extent to which Colorado precipitation can be predicted on decadal scales using remote Pacific Ocean surface temperature patterns. Concurrently, stakeholder interviews with flood managers in Colorado are being used to explore the potential utility of decadal climate information. Combining the modeling results with results from the stakeholder interviews shows that while there is still significant uncertainty surrounding precipitation on decadal time scales, relevant and well communicated decadal information has potential to be useful for drought and flood management.
John Aber; Ronald P. Neilson; Steve McNulty; James M. Lenihan; Dominque Bachelet; Raymond J. Drapek
2001-01-01
The purpose of this article is to review the state of prediction of forest ecosystem response to envisioned changes in the physical and chemical climate. These results are offered as one part of the forest sector analysis of the National Assessment of the Potential Consequences of Climate Variability and Change. This article has three sections. The first offers a very...
Isaac-Renton, Miriam G; Roberts, David R; Hamann, Andreas; Spiecker, Heinrich
2014-08-01
We evaluate genetic test plantations of North American Douglas-fir provenances in Europe to quantify how tree populations respond when subjected to climate regime shifts, and we examined whether bioclimate envelope models developed for North America to guide assisted migration under climate change can retrospectively predict the success of these provenance transfers to Europe. The meta-analysis is based on long-term growth data of 2800 provenances transferred to 120 European test sites. The model was generally well suited to predict the best performing provenances along north-south gradients in Western Europe, but failed to predict superior performance of coastal North American populations under continental climate conditions in Eastern Europe. However, model projections appear appropriate when considering additional information regarding adaptation of Douglas-fir provenances to withstand frost and drought, even though the model partially fails in a validation against growth traits alone. We conclude by applying the partially validated model to climate change scenarios for Europe, demonstrating that climate trends observed over the last three decades warrant changes to current use of Douglas-fir provenances in plantation forestry throughout Western and Central Europe. © 2014 John Wiley & Sons Ltd.
Climate change in Australian tropical rainforests: an impending environmental catastrophe.
Williams, Stephen E; Bolitho, Elizabeth E; Fox, Samantha
2003-01-01
It is now widely accepted that global climate change is affecting many ecosystems around the globe and that its impact is increasing rapidly. Many studies predict that impacts will consist largely of shifts in latitudinal and altitudinal distributions. However, we demonstrate that the impacts of global climate change in the tropical rainforests of northeastern Australia have the potential to result in many extinctions. We develop bioclimatic models of spatial distribution for the regionally endemic rainforest vertebrates and use these models to predict the effects of climate warming on species distributions. Increasing temperature is predicted to result in significant reduction or complete loss of the core environment of all regionally endemic vertebrates. Extinction rates caused by the complete loss of core environments are likely to be severe, nonlinear, with losses increasing rapidly beyond an increase of 2 degrees C, and compounded by other climate-related impacts. Mountain ecosystems around the world, such as the Australian Wet Tropics bioregion, are very diverse, often with high levels of restricted endemism, and are therefore important areas of biodiversity. The results presented here suggest that these systems are severely threatened by climate change. PMID:14561301
Assessment of Human Health Vulnerability to Climate Variability and Change in Cuba
Bultó, Paulo Lázaro Ortíz; Rodríguez, Antonio Pérez; Valencia, Alina Rivero; Vega, Nicolás León; Gonzalez, Manuel Díaz; Carrera, Alina Pérez
2006-01-01
In this study we assessed the potential effects of climate variability and change on population health in Cuba. We describe the climate of Cuba as well as the patterns of climate-sensitive diseases of primary concern, particularly dengue fever. Analyses of the associations between climatic anomalies and disease patterns highlight current vulnerability to climate variability. We describe current adaptations, including the application of climate predictions to prevent disease outbreaks. Finally, we present the potential economic costs associated with future impacts due to climate change. The tools used in this study can be useful in the development of appropriate and effective adaptation options to address the increased climate variability associated with climate change. PMID:17185289
Anderson, Jill T; Gezon, Zachariah J
2015-04-01
Environmental variation often induces shifts in functional traits, yet we know little about whether plasticity will reduce extinction risks under climate change. As climate change proceeds, phenotypic plasticity could enable species with limited dispersal capacity to persist in situ, and migrating populations of other species to establish in new sites at higher elevations or latitudes. Alternatively, climate change could induce maladaptive plasticity, reducing fitness, and potentially stalling adaptation and migration. Here, we quantified plasticity in life history, foliar morphology, and ecophysiology in Boechera stricta (Brassicaceae), a perennial forb native to the Rocky Mountains. In this region, warming winters are reducing snowpack and warming springs are advancing the timing of snow melt. We hypothesized that traits that were historically advantageous in hot and dry, low-elevation locations will be favored at higher elevation sites due to climate change. To test this hypothesis, we quantified trait variation in natural populations across an elevational gradient. We then estimated plasticity and genetic variation in common gardens at two elevations. Finally, we tested whether climatic manipulations induce plasticity, with the prediction that plants exposed to early snow removal would resemble individuals from lower elevation populations. In natural populations, foliar morphology and ecophysiology varied with elevation in the predicted directions. In the common gardens, trait plasticity was generally concordant with phenotypic clines from the natural populations. Experimental snow removal advanced flowering phenology by 7 days, which is similar in magnitude to flowering time shifts over 2-3 decades of climate change. Therefore, snow manipulations in this system can be used to predict eco-evolutionary responses to global change. Snow removal also altered foliar morphology, but in unexpected ways. Extensive plasticity could buffer against immediate fitness declines due to changing climates. © 2014 John Wiley & Sons Ltd.
Using changes in agricultural utility to quantify future climate-induced risk to conservation.
Estes, Lyndon D; Paroz, Lydie-Line; Bradley, Bethany A; Green, Jonathan M H; Hole, David G; Holness, Stephen; Ziv, Guy; Oppenheimer, Michael G; Wilcove, David S
2014-04-01
Much of the biodiversity-related climate change impacts research has focused on the direct effects to species and ecosystems. Far less attention has been paid to the potential ecological consequences of human efforts to address the effects of climate change, which may equal or exceed the direct effects of climate change on biodiversity. One of the most significant human responses is likely to be mediated through changes in the agricultural utility of land. As farmers adapt their practices to changing climates, they may increase pressure on some areas that are important to conserve (conservation lands) whereas lessening it on others. We quantified how the agricultural utility of South African conservation lands may be altered by climate change. We assumed that the probability of an area being farmed is linked to the economic benefits of doing so, using land productivity values to represent production benefit and topographic ruggedness as a proxy for costs associated with mechanical workability. We computed current and future values of maize and wheat production in key conservation lands using the DSSAT4.5 model and 36 crop-climate response scenarios. Most conservation lands had, and were predicted to continue to have, low agricultural utility because of their location in rugged terrain. However, several areas were predicted to maintain or gain high agricultural utility and may therefore be at risk of near-term or future conversion to cropland. Conversely, some areas were predicted to decrease in agricultural utility and may therefore prove easier to protect from conversion. Our study provides an approximate but readily transferable method for incorporating potential human responses to climate change into conservation planning. © 2013 Society for Conservation Biology.
Supple, Megan Ann; Bragg, Jason G; Broadhurst, Linda M; Nicotra, Adrienne B; Byrne, Margaret; Andrew, Rose L; Widdup, Abigail; Aitken, Nicola C; Borevitz, Justin O
2018-04-24
As species face rapid environmental change, we can build resilient populations through restoration projects that incorporate predicted future climates into seed sourcing decisions. Eucalyptus melliodora is a foundation species of a critically endangered community in Australia that is a target for restoration. We examined genomic and phenotypic variation to make empirical based recommendations for seed sourcing. We examined isolation by distance and isolation by environment, determining high levels of gene flow extending for 500 km and correlations with climate and soil variables. Growth experiments revealed extensive phenotypic variation both within and among sampling sites, but no site-specific differentiation in phenotypic plasticity. Model predictions suggest that seed can be sourced broadly across the landscape, providing ample diversity for adaptation to environmental change. Application of our landscape genomic model to E. melliodora restoration projects can identify genomic variation suitable for predicted future climates, thereby increasing the long term probability of successful restoration. © 2018, Supple et al.
Climate Prediction Center - monthly Outlook
Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Outlooks monthly Climate Outlooks Banner OFFICIAL Forecasts June 2018 [UPDATED MONTHLY FORECASTS SERVICE CHANGE NOTICE] [EXPERIMENTAL TWO-CLASS SEASONAL FORECASTS] Text-Format Discussions Monthly Long Lead 30
Climate change impact on seaweed meadow distribution in the North Atlantic rocky intertidal
Jueterbock, Alexander; Tyberghein, Lennert; Verbruggen, Heroen; Coyer, James A; Olsen, Jeanine L; Hoarau, Galice
2013-01-01
The North-Atlantic has warmed faster than all other ocean basins and climate change scenarios predict sea surface temperature isotherms to shift up to 600 km northwards by the end of the 21st century. The pole-ward shift has already begun for many temperate seaweed species that are important intertidal foundation species. We asked the question: Where will climate change have the greatest impact on three foundational, macroalgal species that occur along North-Atlantic shores: Fucus serratus, Fucus vesiculosus, and Ascophyllum nodosum? To predict distributional changes of these key species under three IPCC (Intergovernmental Panel on Climate Change) climate change scenarios (A2, A1B, and B1) over the coming two centuries, we generated Ecological Niche Models with the program MAXENT. Model predictions suggest that these three species will shift northwards as an assemblage or “unit” and that phytogeographic changes will be most pronounced in the southern Arctic and the southern temperate provinces. Our models predict that Arctic shores in Canada, Greenland, and Spitsbergen will become suitable for all three species by 2100. Shores south of 45° North will become unsuitable for at least two of the three focal species on both the Northwest- and Northeast-Atlantic coasts by 2200. If these foundational species are unable to adapt to the rising temperatures, they will lose their centers of genetic diversity and their loss will trigger an unpredictable shift in the North-Atlantic intertidal ecosystem. PMID:23762521
NASA Astrophysics Data System (ADS)
Kuleshov, Y.; Jones, D.; Spillman, C. M.
2012-04-01
Climate change and climate extremes have a major impact on Australia and Pacific Island countries. Of particular concern are tropical cyclones and extreme ocean temperatures, the first being the most destructive events for terrestrial systems, while the latter has the potential to devastate ocean ecosystems through coral bleaching. As a practical response to climate change, under the Pacific-Australia Climate Change Science and Adaptation Planning program (PACCSAP), we are developing enhanced web-based information tools for providing seasonal forecasts for climatic extremes in the Western Pacific. Tropical cyclones are the most destructive weather systems that impact on coastal areas. Interannual variability in the intensity and distribution of tropical cyclones is large, and presently greater than any trends that are ascribable to climate change. In the warming environment, predicting tropical cyclone occurrence based on historical relationships, with predictors such as sea surface temperatures (SSTs) now frequently lying outside of the range of past variability meaning that it is not possible to find historical analogues for the seasonal conditions often faced by Pacific countries. Elevated SSTs are the primary trigger for mass coral bleaching events, which can lead to widespread damage and mortality on reef systems. Degraded coral reefs present many problems, including long-term loss of tourism and potential loss or degradation of fisheries. The monitoring and prediction of thermal stress events enables the support of a range of adaptive and management activities that could improve reef resilience to extreme conditions. Using the climate model POAMA (Predictive Ocean-Atmosphere Model for Australia), we aim to improve accuracy of seasonal forecasts of tropical cyclone activity and extreme SSTs for the regions of Western Pacific. Improved knowledge of extreme climatic events, with the assistance of tailored forecast tools, will help enhance the resilience and adaptive capacity of Australia and Pacific Island Countries under climate change. Acknowledgement The research discussed in this paper was conducted with the support of the PACCSAP supported by the AusAID and Department of Climate Change and Energy Efficiency and delivered by the Bureau of Meteorology and CSIRO.
NASA Astrophysics Data System (ADS)
Mizoguchi, M.; Matsumoto, J.; Takahashi, H. G.; Tanaka, K.; Kuwagata, T.
2015-12-01
It is important to predict climate change correctly in regional scale and to build adaptation measures and mitigation measures in the Asian monsoon region where more than 60 % of the world's population are living. The reliability of climate change prediction model is evaluated by the reproducibility of past climate in general. However, because there are many developing countries in the Asian monsoon region, adequate documentations of past climate which are needed to evaluate the climate reproducibility have not been prepared. In addition, at present it is difficult to get information on wide-area agricultural meteorological data which affect the growth of agricultural crops when considering the impact on agriculture of climate. Therefore, we have started a research project entitled "Climatic changes and evaluation of their effects on agriculture in Asian monsoon region (CAAM)" under the research framework of the Green Network of Excellence (GRENE) for the Japanese fiscal years from 2011 to 2015 supported by the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT). This project aims to improve the reliability of future climate prediction and to develop the information platform which will be useful to design adaptation and mitigation strategies in agriculture against the predicted climatic changes in Asian monsoon regions. What is GRENE?Based on the new growth strategy which was approved by the Cabinet of Japan in June 2010, Green Network of Excellence program (GRENE) has started under MEXT from FY 2011. The objectives of this program are that the domestic leading universities work together strategically and promote a comprehensive human resource development and research of the highest level in the world while sharing research resources and research goals. In the field of environmental information, it is required that universities and research institutions, which are working on issues such as adaptation to climate change, cooperate to promote the utilization of environmental information and to develop human resources while using DIAS (Data Integration and Analysis System) which has been built by MEXT.
L.R. Iverson; A.M. Prasad; S.N. Matthews; M.P. Peters
2007-01-01
Climate change is affecting an increasing number of species the world over, and evidence is mounting that these changes will continue to accelerate. There have been many studies that use a modelling approach to predict the effects of future climatic change on ecological systems, including by us (Iverson et al. 1999, Matthews et al. 2004); this modelling approach uses a...
Implications of climate change for the fishes of the British Isles.
Graham, C T; Harrod, C
2009-04-01
Recent climatic change has been recorded across the globe. Although environmental change is a characteristic feature of life on Earth and has played a major role in the evolution and global distribution of biodiversity, predicted future rates of climatic change, especially in temperature, are such that they will exceed any that has occurred over recent geological time. Climate change is considered as a key threat to biodiversity and to the structure and function of ecosystems that may already be subject to significant anthropogenic stress. The current understanding of climate change and its likely consequences for the fishes of Britain and Ireland and the surrounding seas are reviewed through a series of case studies detailing the likely response of several marine, diadromous and freshwater fishes to climate change. Changes in climate, and in particular, temperature have and will continue to affect fish at all levels of biological organization: cellular, individual, population, species, community and ecosystem, influencing physiological and ecological processes in a number of direct, indirect and complex ways. The response of fishes and of other aquatic taxa will vary according to their tolerances and life stage and are complex and difficult to predict. Fishes may respond directly to climate-change-related shifts in environmental processes or indirectly to other influences, such as community-level interactions with other taxa. However, the ability to adapt to the predicted changes in climate will vary between species and between habitats and there will be winners and losers. In marine habitats, recent changes in fish community structure will continue as fishes shift their distributions relative to their temperature preferences. This may lead to the loss of some economically important cold-adapted species such as Gadus morhua and Clupea harengus from some areas around Britain and Ireland, and the establishment of some new, warm-adapted species. Increased temperatures are likely to favour cool-adapted (e.g. Perca fluviatilis) and warm-adapted freshwater fishes (e.g. roach Rutilus rutilus and other cyprinids) whose distribution and reproductive success may currently be constrained by temperature rather than by cold-adapted species (e.g. salmonids). Species that occur in Britain and Ireland that are at the edge of their distribution will be most affected, both negatively and positively. Populations of conservation importance (e.g.Salvelinus alpinus and Coregonus spp.) may decline irreversibly. However, changes in food-web dynamics and physiological adaptation, for example because of climate change, may obscure or alter predicted responses. The residual inertia in climate systems is such that even a complete cessation in emissions would still leave fishes exposed to continued climate change for at least half a century. Hence, regardless of the success or failure of programmes aimed at curbing climate change, major changes in fish communities can be expected over the next 50 years with a concomitant need to adapt management strategies accordingly.
Lin, Li; Jin, Ling; Wang, Zhen-Heng; Cui, Zhi-Jia; Ma, Yi
2017-07-01
To predict the suitable distribution patterns of Lycium ruthenicum in the present and future under the background of climate change, and provide reference for the resources sustainable utilization and GAP standardized planting. The software of Maxent and ArcGis was used to predict the potential suitable regions and grades of L. ruthenicum in China based on the 149 distribution information, climate data of contemporary (1950-2000) and future (20-80 decade of 21 century), and considering of three greenhouse gaseous emission scenario. The results showed that:the suitable distribution regions of L. ruthenicum are mainly concentrated in Xinjiang, Qinghai, Gansu, Neimenggu, and Ningxia province in present. In addition, Shaanxi, Shanxi and Xizang are also distribution regions.The suitable distribution area of L. ruthenicum is 284.506 949×104 km2, accounted for 29.6% of the land area of China.The relatively stable area of the suitable regions accounted for 25.2% of the total suitable region area.Under the background of climate change, compared with contemporary, the total area of suitable region is reducing and moderately suitable area is increasing at different degree at the 20, 30, 40, 50, 60, 70, 80 decade of 21 century. Climate change both can change the total area of suitable regions and habitat suitability of L. ruthenicum. It could provide a strategic guidance for protection, development and utilization of L. ruthenicum though the prediction of potential suitable regions distribution of L. ruthenicum based on the mainly factor of climate change. Copyright© by the Chinese Pharmaceutical Association.
Moore, Sean; Shrestha, Sourya; Tomlinson, Kyle W.; Vuong, Holly
2012-01-01
Climate warming over the next century is expected to have a large impact on the interactions between pathogens and their animal and human hosts. Vector-borne diseases are particularly sensitive to warming because temperature changes can alter vector development rates, shift their geographical distribution and alter transmission dynamics. For this reason, African trypanosomiasis (sleeping sickness), a vector-borne disease of humans and animals, was recently identified as one of the 12 infectious diseases likely to spread owing to climate change. We combine a variety of direct effects of temperature on vector ecology, vector biology and vector–parasite interactions via a disease transmission model and extrapolate the potential compounding effects of projected warming on the epidemiology of African trypanosomiasis. The model predicts that epidemics can occur when mean temperatures are between 20.7°C and 26.1°C. Our model does not predict a large-range expansion, but rather a large shift of up to 60 per cent in the geographical extent of the range. The model also predicts that 46–77 million additional people may be at risk of exposure by 2090. Future research could expand our analysis to include other environmental factors that influence tsetse populations and disease transmission such as humidity, as well as changes to human, livestock and wildlife distributions. The modelling approach presented here provides a framework for using the climate-sensitive aspects of vector and pathogen biology to predict changes in disease prevalence and risk owing to climate change. PMID:22072451
US Climate Variability and Predictability Project
DOE Office of Scientific and Technical Information (OSTI.GOV)
Patterson, Mike
The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less
US Climate Variability and Predictability (CLIVAR) Project- Final Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Patterson, Mike
The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less
Exploiting temporal variability to understand tree recruitment response to climate change
Ines Ibanez; James S. Clark; Shannon LaDeau; Janneke Hill Ris Lambers
2007-01-01
Predicting vegetation shifts under climate change is a challenging endeavor, given the complex interactions between biotic and abiotic variables that influence demographic rates. To determine how current trends and variation in climate change affect seedling establishment, we analyzed demographic responses to spatiotemporal variation to temperature and soil moisture in...
Four cultures: new synergies for engaging society on climate change
Matthew C. Nisbet; Mark A. Hixon; Kathleen Dean Moore; Michael Nelson
2010-01-01
The scientific community has largely reached consensus that climate change is real, is exacerbated by human activities, and is causing detectable shifts in both living and non-living components of the biosphere. Yet, documenting and predicting the ecological, economic, social, and cultural consequences of climate change have not yet stimulated an appropriately strong...
Climate model diversity in the Northern Hemisphere Polar vortex response to climate change.
NASA Astrophysics Data System (ADS)
Simpson, I.; Seager, R.; Hitchcock, P.; Cohen, N.
2017-12-01
Global climate models vary widely in their predictions of the future of the Northern Hemisphere stratospheric polar vortex, with some showing a significant strengthening of the vortex, some showing a significant weakening and others displaying a response that is not outside of the range expected from internal variability alone. This inter-model spread in stratospheric predictions may account for some inter-model spread in tropospheric predictions with important implications for the storm tracks and regional climate change, particularly for the North Atlantic sector. Here, our current state of understanding of this model spread and its tropospheric impacts will be reviewed. Previous studies have proposed relationships between a models polar vortex response to climate change and its present day vortex climatology while others have demonstrated links between a models polar vortex response and changing wave activity coming up from the troposphere below under a warming climate. The extent to which these mechanisms can account for the spread in polar vortex changes exhibited by the Coupled Model Intercomparison Project, phase 5 models will be assessed. In addition, preliminary results from a series of idealized experiments with the Community Atmosphere Model will be presented. In these experiments, nudging of the stratospheric zonal mean state has been imposed to mimic the inter-model spread in the polar vortex response to climate change so that the downward influence of the spread in zonal mean stratospheric responses on the tropospheric circulation can be assessed within one model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pan, Y.
1993-01-01
Based on model approaches, three conifer species, red pine, Norway spruce and Scots pine grown in plantations at Pack Demonstration Forest, in the southeastern Adirondack mountains of New York, were chosen to study growth response to different environmental changes, including silvicultural treatments and changes in climate and chemical environment. Detailed stem analysis data provided a basis for constructing tree growth models. These models were organized into three groups: morphological, dynamic and predictive. The morphological model was designed to evaluate relationship between tree attributes and interactive influences of intrinsic and extrinsic factors on the annual increments. Three types of morphological patternsmore » have been characterized: space-time patterns of whole-stem rings, intrinsic wood deposition pattern along the tree-stem, and bolewood allocation ratio patterns along the tree-stem. The dynamic model reflects the growth process as a system which responds to extrinsic signal inputs, including fertilization pulses, spacing effects and climatic disturbance, as well as intrinsic feedback. Growth signals indicative of climatic effects were used to construct growth-climate models using both multivariate analysis and Kalman filter methods. The predictive model utilized GCMs and growth-climate relationships to forecast tree growth responses in relation to future scenarios of CO[sub 2]-induced climate change. Prediction results indicate that different conifer species have individualistic growth response to future climatic change and suggest possible changes in future growth and distribution of naturally occurring conifers in this region.« less
NASA Astrophysics Data System (ADS)
Alarcon, T.; Garcia, M. E.; Small, D. L.; Portney, K.; Islam, S.
2013-12-01
Providing water to the expanding population of megacities, which have over 10 million people, with a stressed and aging water infrastructure creates unprecedented challenges. These challenges are exacerbated by dwindling supply and competing demands, altered precipitation and runoff patterns in a changing climate, fragmented water utility business models, and changing consumer behavior. While there is an extensive literature on the effects of climate change on water resources, the uncertainty of climate change predictions continues to be high. This hinders the value of these predictions for municipal water supply planning. The ability of water utilities to meet future water needs will largely depend on their capacity to make decisions under uncertainty. Water stressors, like changes in demographics, climate, and socioeconomic patterns, have varying degrees of uncertainty. Identifying which stressors will have a greater impact on water resources, may reduce the level of future uncertainty for planning and managing water utilities. Within this context, we analyze historical and projected changes of population and climate to quantify the relative impacts of these two stressors on water resources. We focus on megacities that rely primarily on surface water resources to evaluate (a) population growth pattern from 1950-2010 and projected population for 2010-2060; (b) climate change impact on projected climate change scenarios for 2010-2060; and (c) water access for 1950-2010; projected needs for 2010-2060.
Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models
Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel
2016-01-01
Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.
Modelling impacts of climate change on arable crop diseases: progress, challenges and applications.
Newbery, Fay; Qi, Aiming; Fitt, Bruce Dl
2016-08-01
Combining climate change, crop growth and crop disease models to predict impacts of climate change on crop diseases can guide planning of climate change adaptation strategies to ensure future food security. This review summarises recent developments in modelling climate change impacts on crop diseases, emphasises some major challenges and highlights recent trends. The use of multi-model ensembles in climate change modelling and crop modelling is contributing towards measures of uncertainty in climate change impact projections but other aspects of uncertainty remain largely unexplored. Impact assessments are still concentrated on few crops and few diseases but are beginning to investigate arable crop disease dynamics at the landscape level. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Global variation in thermal tolerances and vulnerability of endotherms to climate change
Khaliq, Imran; Hof, Christian; Prinzinger, Roland; Böhning-Gaese, Katrin; Pfenninger, Markus
2014-01-01
The relationships among species' physiological capacities and the geographical variation of ambient climate are of key importance to understanding the distribution of life on the Earth. Furthermore, predictions of how species will respond to climate change will profit from the explicit consideration of their physiological tolerances. The climatic variability hypothesis, which predicts that climatic tolerances are broader in more variable climates, provides an analytical framework for studying these relationships between physiology and biogeography. However, direct empirical support for the hypothesis is mostly lacking for endotherms, and few studies have tried to integrate physiological data into assessments of species' climatic vulnerability at the global scale. Here, we test the climatic variability hypothesis for endotherms, with a comprehensive dataset on thermal tolerances derived from physiological experiments, and use these data to assess the vulnerability of species to projected climate change. We find the expected relationship between thermal tolerance and ambient climatic variability in birds, but not in mammals—a contrast possibly resulting from different adaptation strategies to ambient climate via behaviour, morphology or physiology. We show that currently most of the species are experiencing ambient temperatures well within their tolerance limits and that in the future many species may be able to tolerate projected temperature increases across significant proportions of their distributions. However, our findings also underline the high vulnerability of tropical regions to changes in temperature and other threats of anthropogenic global changes. Our study demonstrates that a better understanding of the interplay among species' physiology and the geography of climate change will advance assessments of species' vulnerability to climate change. PMID:25009066
Leaf morphology shift linked to climate change.
Guerin, Greg R; Wen, Haixia; Lowe, Andrew J
2012-10-23
Climate change is driving adaptive shifts within species, but research on plants has been focused on phenology. Leaf morphology has demonstrated links with climate and varies within species along climate gradients. We predicted that, given within-species variation along a climate gradient, a morphological shift should have occurred over time due to climate change. We tested this prediction, taking advantage of latitudinal and altitudinal variations within the Adelaide Geosyncline region, South Australia, historical herbarium specimens (n = 255) and field sampling (n = 274). Leaf width in the study taxon, Dodonaea viscosa subsp. angustissima, was negatively correlated with latitude regionally, and leaf area was negatively correlated with altitude locally. Analysis of herbarium specimens revealed a 2 mm decrease in leaf width (total range 1-9 mm) over 127 years across the region. The results are consistent with a morphological response to contemporary climate change. We conclude that leaf width is linked to maximum temperature regionally (latitude gradient) and leaf area to minimum temperature locally (altitude gradient). These data indicate a morphological shift consistent with a direct response to climate change and could inform provenance selection for restoration with further investigation of the genetic basis and adaptive significance of observed variation.
The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements
NASA Astrophysics Data System (ADS)
Lucas, S. E.; Todd, J. F.
2015-12-01
The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability - DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP.
Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models.
Bonan, Gordon B; Doney, Scott C
2018-02-02
Many global change stresses on terrestrial and marine ecosystems affect not only ecosystem services that are essential to humankind, but also the trajectory of future climate by altering energy and mass exchanges with the atmosphere. Earth system models, which simulate terrestrial and marine ecosystems and biogeochemical cycles, offer a common framework for ecological research related to climate processes; analyses of vulnerability, impacts, and adaptation; and climate change mitigation. They provide an opportunity to move beyond physical descriptors of atmospheric and oceanic states to societally relevant quantities such as wildfire risk, habitat loss, water availability, and crop, fishery, and timber yields. To achieve this, the science of climate prediction must be extended to a more multifaceted Earth system prediction that includes the biosphere and its resources. Copyright © 2018, American Association for the Advancement of Science.
Mellor, Jonathan E; Levy, Karen; Zimmerman, Julie; Elliott, Mark; Bartram, Jamie; Carlton, Elizabeth; Clasen, Thomas; Dillingham, Rebecca; Eisenberg, Joseph; Guerrant, Richard; Lantagne, Daniele; Mihelcic, James; Nelson, Kara
2016-04-01
Increased precipitation and temperature variability as well as extreme events related to climate change are predicted to affect the availability and quality of water globally. Already heavily burdened with diarrheal diseases due to poor access to water, sanitation and hygiene facilities, communities throughout the developing world lack the adaptive capacity to sufficiently respond to the additional adversity caused by climate change. Studies suggest that diarrhea rates are positively correlated with increased temperature, and show a complex relationship with precipitation. Although climate change will likely increase rates of diarrheal diseases on average, there is a poor mechanistic understanding of the underlying disease transmission processes and substantial uncertainty surrounding current estimates. This makes it difficult to recommend appropriate adaptation strategies. We review the relevant climate-related mechanisms behind transmission of diarrheal disease pathogens and argue that systems-based mechanistic approaches incorporating human, engineered and environmental components are urgently needed. We then review successful systems-based approaches used in other environmental health fields and detail one modeling framework to predict climate change impacts on diarrheal diseases and design adaptation strategies. Copyright © 2016 Elsevier B.V. All rights reserved.
USDA-ARS?s Scientific Manuscript database
Elevated CO2 concentration, temperature, and precipitation intensity driven by climate change are expected to cause significant environmental changes in the Chesapeake Bay Watershed (CBW). Although the potential effects of climate change are widely reported, few studies have been conducted to unders...
Laura P. Leites; Andrew P. Robinson; Gerald E. Rehfeldt; John D. Marshall; Nicholas L. Crookston
2012-01-01
Projected climate change will affect existing forests, as substantial changes are predicted to occur during their life spans. Species that have ample intraspecific genetic differentiation, such as Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), are expected to display population-specific growth responses to climate change. Using a mixed-effects modeling approach,...
Ayron M. Strauch; Christian P. Giardina; Richard A. MacKenzie; Chris Heider; Tom W. Giambelluca; Ed Salminen; Gregory L. Bruland
2017-01-01
Climate change is anticipated to affect freshwater resources, but baseline data on the functioning of tropical watersheds is lacking, limiting efforts that seek to predict how watershed processes, water supply, and streamflow respond to anticipated changes in climate and vegetation change, and to management. To address this data gap, we applied the distributed...
A changing climate: impacts on human exposures to O3 using ...
Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposures due to these impacts was developed by linking climate, air quality, land-use, and human exposure models. This methodology was then applied to characterize changes in predicted human exposures to O3 under multiple future scenarios. Regional climate projections for the U.S. were developed by downscaling global circulation model (GCM) scenarios for three of the Intergovernmental Panel on Climate Change’s (IPCC’s) Representative Concentration Pathways (RCPs) using the Weather Research and Forecasting (WRF) model. The regional climate results were in turn used to generate air quality (concentration) projections using the Community Multiscale Air Quality (CMAQ) model. For each of the climate change scenarios, future U.S. census-tract level population distributions from the Integrated Climate and Land Use Scenarios (ICLUS) model for four future scenarios based on the IPCC’s Special Report on Emissions Scenarios (SRES) storylines were used. These climate, air quality, and population projections were used as inputs to EPA’s Air Pollutants Exposure (APEX) model for 12 U.S. cities. Probability density functions show changes in the population distribution of 8 h maximum daily O3 exposur
The impact of future climate on historic interiors.
Lankester, Paul; Brimblecombe, Peter
2012-02-15
The socio-economic significance of climate change is widely recognised. However, its potential to affect our cultural heritage has not been discussed in detail (i.e. not explicit in IPCC 4) even though the cultural impacts of future outdoor climate have been the focus of some European Commission projects (e.g. NOAH'S ARK) and World Heritage Centre reports. Recently there have been a few projects that have examined the changing environmental threats to tangible heritage indoors (e.g. Preparing Historic Collections for Climate Change and Climate for Culture). Here we predict future indoor temperature and humidity, and damage arising from changes to climate in historic rooms in Southern England with little climate control, using simple building simulations coupled with high resolution (~5 km) climate predictions. The calculations suggest an increase in indoor temperature over the next century that is slightly less than that outdoors. Annual relative humidity shows little change, but the seasonal cycles suggest drier summers and slightly damper winters indoors. Damage from mould growth and pests is likely to increase in the future, while humidity driven dimensional change to materials (e.g. wood) should decrease somewhat. The results allow collection managers to prepare for the impact of long-term climate change, putting strategic measures in place to prevent increased damage, and thus preserve our heritage for future generations. Copyright © 2011 Elsevier B.V. All rights reserved.
A dynamic, climate-driven model of Rift Valley fever.
Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P
2016-03-31
Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.
Hybrid Zones: Windows on Climate Change
Larson, Erica L.; Harrison, Richard G.
2016-01-01
Defining the impacts of anthropogenic climate change on biodiversity and species distributions is currently a high priority. Niche models focus primarily on predicted changes in abiotic factors; however, species interactions and adaptive evolution will impact the ability of species to persist in the face of changing climate. Our review focuses on the use of hybrid zones to monitor species' responses to contemporary climate change. Monitoring hybrid zones provides insight into how range boundaries shift in response to climate change by illuminating the combined effects of species interactions and physiological sensitivity. At the same time, the semi-permeable nature of species boundaries allows us to document adaptive introgression of alleles associated with response to climate change. PMID:25982153
Rehnus, Maik; Bollmann, Kurt; Schmatz, Dirk R; Hackländer, Klaus; Braunisch, Veronika
2018-03-13
Alpine and Arctic species are considered to be particularly vulnerable to climate change, which is expected to cause habitat loss, fragmentation and-ultimately-extinction of cold-adapted species. However, the impact of climate change on glacial relict populations is not well understood, and specific recommendations for adaptive conservation management are lacking. We focused on the mountain hare (Lepus timidus) as a model species and modelled species distribution in combination with patch and landscape-based connectivity metrics. They were derived from graph-theory models to quantify changes in species distribution and to estimate the current and future importance of habitat patches for overall population connectivity. Models were calibrated based on 1,046 locations of species presence distributed across three biogeographic regions in the Swiss Alps and extrapolated according to two IPCC scenarios of climate change (RCP 4.5 & 8.5), each represented by three downscaled global climate models. The models predicted an average habitat loss of 35% (22%-55%) by 2100, mainly due to an increase in temperature during the reproductive season. An increase in habitat fragmentation was reflected in a 43% decrease in patch size, a 17% increase in the number of habitat patches and a 34% increase in inter-patch distance. However, the predicted changes in habitat availability and connectivity varied considerably between biogeographic regions: Whereas the greatest habitat losses with an increase in inter-patch distance were predicted at the southern and northern edges of the species' Alpine distribution, the greatest increase in patch number and decrease in patch size is expected in the central Swiss Alps. Finally, both the number of isolated habitat patches and the number of patches crucial for maintaining the habitat network increased under the different variants of climate change. Focusing conservation action on the central Swiss Alps may help mitigate the predicted effects of climate change on population connectivity. © 2018 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Nurhayati, E.; Koesmaryono, Y.; Impron
2017-03-01
Rice Yellow Stem Borer (YSB) is one of the major insect pests in rice plants that has high attack intensity in rice production center areas, especially in West Java. This pest is consider as holometabola insects that causes rice damage in the vegetative phase (deadheart) as well as generative phase (whitehead). Climatic factor is one of the environmental factors influence the pattern of dynamics population. The purpose of this study was to develop a predictive modeling of YSB pest dynamics population under climate change scenarios (2016-2035 period) using Dymex Model in Indramayu area, West Java. YSB modeling required two main components, namely climate parameters and YSB development lower threshold of temperature (To) to describe YSB life cycle in every phase. Calibration and validation test of models showed the coefficient of determination (R2) between the predicted results and observations of the study area were 0.74 and 0.88 respectively, which was able to illustrate the development, mortality, transfer of individuals from one stage to the next life also fecundity and YSB reproduction. On baseline climate condition, there was a tendency of population abundance peak (outbreak) occured when a change of rainfall intensity in the rainy season transition to dry season or the opposite conditions was happen. In both of application of climate change scenarios, the model outputs were generated well and able to predict the pattern of YSB population dynamics with a the increasing trend of specific population numbers, generation numbers per season and also shifting pattern of populations abundance peak in the future climatic conditions. These results can be adopted as a tool to predict outbreak and to give early warning to control YSB pest more effectively.
Rose, Hannah; Caminade, Cyril; Bolajoko, Muhammad Bashir; Phelan, Paul; van Dijk, Jan; Baylis, Matthew; Williams, Diana; Morgan, Eric R
2016-03-01
Recent climate change has resulted in changes to the phenology and distribution of invertebrates worldwide. Where invertebrates are associated with disease, climate variability and changes in climate may also affect the spatio-temporal dynamics of disease. Due to its significant impact on sheep production and welfare, the recent increase in diagnoses of ovine haemonchosis caused by the nematode Haemonchus contortus in some temperate regions is particularly concerning. This study is the first to evaluate the impact of climate change on H. contortus at a continental scale. A model of the basic reproductive quotient of macroparasites, Q0 , adapted to H. contortus and extended to incorporate environmental stochasticity and parasite behaviour, was used to simulate Pan-European spatio-temporal changes in H. contortus infection pressure under scenarios of climate change. Baseline Q0 simulations, using historic climate observations, reflected the current distribution of H. contortus in Europe. In northern Europe, the distribution of H. contortus is currently limited by temperatures falling below the development threshold during the winter months and within-host arrested development is necessary for population persistence over winter. In southern Europe, H. contortus infection pressure is limited during the summer months by increased temperature and decreased moisture. Compared with this baseline, Q0 simulations driven by a climate model ensemble predicted an increase in H. contortus infection pressure by the 2080s. In northern Europe, a temporal range expansion was predicted as the mean period of transmission increased by 2-3 months. A bimodal seasonal pattern of infection pressure, similar to that currently observed in southern Europe, emerges in northern Europe due to increasing summer temperatures and decreasing moisture. The predicted patterns of change could alter the epidemiology of H. contortus in Europe, affect the future sustainability of contemporary control strategies, and potentially drive local adaptation to climate change in parasite populations. © 2015 John Wiley & Sons Ltd.
Climate warming and Bergmann's rule through time: is there any evidence?
Teplitsky, Celine; Millien, Virginie
2014-01-01
Climate change is expected to induce many ecological and evolutionary changes. Among these is the hypothesis that climate warming will cause a reduction in body size. This hypothesis stems from Bergmann's rule, a trend whereby species exhibit a smaller body size in warmer climates, and larger body size under colder conditions in endotherms. The mechanisms behind this rule are still debated, and it is not clear whether Bergmann's rule can be extended to predict the effects of climate change through time. We reviewed the primary literature for evidence (i) of a decrease in body size in response to climate warming, (ii) that changing body size is an adaptive response and (iii) that these responses are evolutionary or plastic. We found weak evidence for changes in body size through time as predicted by Bergmann's rule. Only three studies investigated the adaptive nature of these size decreases. Of these, none reported evidence of selection for smaller size or of a genetic basis for the size change, suggesting that size decreases could be due to nonadaptive plasticity in response to changing environmental conditions. More studies are needed before firm conclusions can be drawn about the underlying causes of these changes in body size in response to a warming climate. PMID:24454554
Landuse/Landcover and Climate Change Interaction in the Derived Savannah Region of Nigeria
NASA Astrophysics Data System (ADS)
Akintuyi, A. O.; Fasona, M.; Soneye, A. S. O.
2016-12-01
The interaction of landuse/Landcover (LULC) and climate change, to a large extent, involves anthropogenic activities. This study was carried out in the derived savannah of Nigeria, a delicate ecological zone where the interaction of LULC and climate change could be well appreciated. The study evaluated coupled interaction between LULC and climate change and assessed the changes in the landuse/landcover patterns for the periods 1972, 1986, 2002 and 2010, evaluated the present (1941 - 2010) and future (2011 - 2050) variability in rainfall patterns and an attempt was made to predict the interaction between LULC and climate change during future climate. The study adopted remote sensing and GIS techniques, land change modeller and multivariate statistics The results suggest that the built up area, farmland, waterbody and woodland experienced a rapid increase of about 1,134.69%, 1,202.85%, 631.51% and 188.09%, respectively, while the forest cover, degraded surfaces and grassland lost about 19.32%, 72.76% and 0.05% respectively between 1972 and 2010. Furthermore, the study predicted 40.28% and 37.84% reduction in the forested area between 1986 and 2050 and 2010 and 2050 respectively. The study concludes that rainfall will be the major driver of LULC change within the study area under a future climate.
Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change
Longo, Marcos; Baccini, Alessandro; Phillips, Oliver L.; Lewis, Simon L.; Alvarez-Dávila, Esteban; Segalin de Andrade, Ana Cristina; Brienen, Roel J. W.; Erwin, Terry L.; Feldpausch, Ted R.; Monteagudo Mendoza, Abel Lorenzo; Nuñez Vargas, Percy; Prieto, Adriana; Silva-Espejo, Javier Eduardo; Malhi, Yadvinder; Moorcroft, Paul R.
2016-01-01
Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem’s resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest’s response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions. PMID:26711984
Ecosystem heterogeneity determines the ecological resilience of the Amazon to climate change.
Levine, Naomi M; Zhang, Ke; Longo, Marcos; Baccini, Alessandro; Phillips, Oliver L; Lewis, Simon L; Alvarez-Dávila, Esteban; Segalin de Andrade, Ana Cristina; Brienen, Roel J W; Erwin, Terry L; Feldpausch, Ted R; Monteagudo Mendoza, Abel Lorenzo; Nuñez Vargas, Percy; Prieto, Adriana; Silva-Espejo, Javier Eduardo; Malhi, Yadvinder; Moorcroft, Paul R
2016-01-19
Amazon forests, which store ∼ 50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem's resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest's response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.
Budy, Phaedra; Luecke, Chris
2014-09-01
Size dimorphism in fish populations, both its causes and consequences, has been an area of considerable focus; however, uncertainty remains whether size dimorphism is dynamic or stabilizing and about the role of exogenous factors. Here, we explored patterns among empirical vital rates, population structure, abundance and trend, and predicted the effects of climate change on populations of arctic char (Salvelinus alpinus) in two lakes. Both populations cycle dramatically between dominance by small (≤300 mm) and large (>300 mm) char. Apparent survival (Φ) and specific growth rates (SGR) were relatively high (40-96%; SGR range 0.03-1.5%) and comparable to those of conspecifics at lower latitudes. Climate change scenarios mimicked observed patterns of warming and resulted in temperatures closer to optimal for char growth (15.15 °C) and a longer growing season. An increase in consumption rates (28-34%) under climate change scenarios led to much greater growth rates (23-34%). Higher growth rates predicted under climate change resulted in an even greater predicted amplitude of cycles in population structure as well as an increase in reproductive output (Ro) and decrease in generation time (Go). Collectively, these results indicate arctic char populations (not just individuals) are extremely sensitive to small changes in the number of ice-free days. We hypothesize years with a longer growing season, predicted to occur more often under climate change, produce elevated growth rates of small char and act in a manner similar to a "resource pulse," allowing a sub-set of small char to "break through," thus setting the cycle in population structure.
Budy, Phaedra; Luecke, Chris
2014-01-01
Size dimorphism in fish populations, both its causes and consequences, has been an area of considerable focus; however, uncertainty remains whether size dimorphism is dynamic or stabilizing and about the role of exogenous factors. Here, we explored patterns among empirical vital rates, population structure, abundance and trend, and predicted the effects of climate change on populations of arctic char (Salvelinus alpinus) in two lakes. Both populations cycle dramatically between dominance by small (≤300 mm) and large (>300 mm) char. Apparent survival (Φ) and specific growth rates (SGR) were relatively high (40–96 %; SGR range 0.03–1.5 %) and comparable to those of conspecifics at lower latitudes. Climate change scenarios mimicked observed patterns of warming and resulted in temperatures closer to optimal for char growth (15.15 °C) and a longer growing season. An increase in consumption rates (28–34 %) under climate change scenarios led to much greater growth rates (23–34 %). Higher growth rates predicted under climate change resulted in an even greater predicted amplitude of cycles in population structure as well as an increase in reproductive output (Ro) and decrease in generation time (Go). Collectively, these results indicate arctic char populations (not just individuals) are extremely sensitive to small changes in the number of ice-free days. We hypothesize years with a longer growing season, predicted to occur more often under climate change, produce elevated growth rates of small char and act in a manner similar to a “resource pulse,” allowing a sub-set of small char to “break through,” thus setting the cycle in population structure.
Hararuk, Oleksandra; Smith, Matthew J; Luo, Yiqi
2015-06-01
Long-term carbon (C) cycle feedbacks to climate depend on the future dynamics of soil organic carbon (SOC). Current models show low predictive accuracy at simulating contemporary SOC pools, which can be improved through parameter estimation. However, major uncertainty remains in global soil responses to climate change, particularly uncertainty in how the activity of soil microbial communities will respond. To date, the role of microbes in SOC dynamics has been implicitly described by decay rate constants in most conventional global carbon cycle models. Explicitly including microbial biomass dynamics into C cycle model formulations has shown potential to improve model predictive performance when assessed against global SOC databases. This study aimed to data-constrained parameters of two soil microbial models, evaluate the improvements in performance of those calibrated models in predicting contemporary carbon stocks, and compare the SOC responses to climate change and their uncertainties between microbial and conventional models. Microbial models with calibrated parameters explained 51% of variability in the observed total SOC, whereas a calibrated conventional model explained 41%. The microbial models, when forced with climate and soil carbon input predictions from the 5th Coupled Model Intercomparison Project (CMIP5), produced stronger soil C responses to 95 years of climate change than any of the 11 CMIP5 models. The calibrated microbial models predicted between 8% (2-pool model) and 11% (4-pool model) soil C losses compared with CMIP5 model projections which ranged from a 7% loss to a 22.6% gain. Lastly, we observed unrealistic oscillatory SOC dynamics in the 2-pool microbial model. The 4-pool model also produced oscillations, but they were less prominent and could be avoided, depending on the parameter values. © 2014 John Wiley & Sons Ltd.
Zepp, R G; Erickson, D J; Paul, N D; Sulzberger, B
2011-02-01
Solar UV radiation, climate and other drivers of global change are undergoing significant changes and models forecast that these changes will continue for the remainder of this century. Here we assess the effects of solar UV radiation on biogeochemical cycles and the interactions of these effects with climate change, including feedbacks on climate. Such interactions occur in both terrestrial and aquatic ecosystems. While there is significant uncertainty in the quantification of these effects, they could accelerate the rate of atmospheric CO(2) increase and subsequent climate change beyond current predictions. The effects of predicted changes in climate and solar UV radiation on carbon cycling in terrestrial and aquatic ecosystems are expected to vary significantly between regions. The balance of positive and negative effects on terrestrial carbon cycling remains uncertain, but the interactions between UV radiation and climate change are likely to contribute to decreasing sink strength in many oceanic regions. Interactions between climate and solar UV radiation will affect cycling of elements other than carbon, and so will influence the concentration of greenhouse and ozone-depleting gases. For example, increases in oxygen-deficient regions of the ocean caused by climate change are projected to enhance the emissions of nitrous oxide, an important greenhouse and ozone-depleting gas. Future changes in UV-induced transformations of aquatic and terrestrial contaminants could have both beneficial and adverse effects. Taken in total, it is clear that the future changes in UV radiation coupled with human-caused global change will have large impacts on biogeochemical cycles at local, regional and global scales.
Symbiont diversity may help coral reefs survive moderate climate change.
Baskett, Marissa L; Gaines, Steven D; Nisbet, Roger M
2009-01-01
Given climate change, thermal stress-related mass coral-bleaching events present one of the greatest anthropogenic threats to coral reefs. While corals and their symbiotic algae may respond to future temperatures through genetic adaptation and shifts in community compositions, the climate may change too rapidly for coral response. To test this potential for response, here we develop a model of coral and symbiont ecological dynamics and symbiont evolutionary dynamics. Model results without variation in symbiont thermal tolerance predict coral reef collapse within decades under multiple future climate scenarios, consistent with previous threshold-based predictions. However, model results with genetic or community-level variation in symbiont thermal tolerance can predict coral reef persistence into the next century, provided low enough greenhouse gas emissions occur. Therefore, the level of greenhouse gas emissions will have a significant effect on the future of coral reefs, and accounting for biodiversity and biological dynamics is vital to estimating the size of this effect.
NASA Astrophysics Data System (ADS)
Macias-Fauria, M.; Johnson, E. A.; Forbes, B. C.; Willis, K. J.
2013-12-01
In cold ecosystems such as sub-alpine forests and forest-tundra, vegetation geographical ranges are expected to expand upward/northward in a warmer world. Such moving fronts have been predicted to 1) decrease the remaining alpine area in mountain systems, increasing fragmentation and extinction risk of many alpine taxa, and 2) fundamentally modify the energy budget of newly afforested areas, enhancing further regional warming due to a reduction in albedo. The latter is particularly significant in the forest-tundra, where changes over large regions can have regional-to-global effects on climate. An integral part of the expected range shifts is their velocity. Whereas range shifts across thermal gradients can theoretically be fast in an elevation gradient relative to climate velocity (i.e. rate of climate change) due to the short distances involved, large lags are expected over the flat forest-tundra. Mountain regions have thus been identified as buffer areas where species can track climate change, in opposition to flat terrain where climate velocity is faster. Thus, much shorter time-to-equilibrium are expected for advancing upslope sub-alpine forest than for advancing northern boreal forest. We contribute to this discussion by showing two mechanisms that might largely alter the above predictions in opposite directions: 1) In mountain regions, terrain heterogeneity not only allows for slower climate velocities, but slope processes largely affect the advance of vegetation. Indeed, such mechanisms can potentially reduce the climatic signal in vegetation distribution limits (e.g. treeline), precluding it from migrating to climatically favourable areas - since these areas occur in geologically unfavourable ones. Such seemingly local control to species range shifts was found to reduce the climate-sensitive treeline areas in the sub-alpine forest of the Canadian Rocky Mountains to ~5% at a landscape scale, fundamentally altering the predictions of vegetation response to climate warming in the region (Macias-Fauria & Johnson 20013, PNAS). 2) In the low arctic tundra, un-treed to treed landscapes have sprouted in several parts of the tundra in a matter of decades, as opposed to the previously predicted response times of several centuries for boreal forest to advance to its new climate optimum (migrational lags). This takes place not through very rapid moving fronts, but through phenotypic responses of extant vegetation with highly flexible life forms, such as woody deciduous shrubs (Salix, Alnus, Betula). The resulting vegetation response creates strong energy feedbacks while at the same time potentially further reduces the speed of northward displacement of the boreal forest, that has to compete with a new treed ecosystem (Macias-Fauria et al. 2012, Nature Climate Change). In conclusion, control of rates of migration by factors other than climate in mountain systems can largely reduce the ability of vegetation to track climate change, and emergence of structurally novel ecosystems in low arctic tundra might largely alter current predictions based on climate response of vegetation, by accelerating ecosystem change and reducing migrational rates simultaneously.
Adaptive and plastic responses of Quercus petraea populations to climate across Europe.
Sáenz-Romero, Cuauhtémoc; Lamy, Jean-Baptiste; Ducousso, Alexis; Musch, Brigitte; Ehrenmann, François; Delzon, Sylvain; Cavers, Stephen; Chałupka, Władysław; Dağdaş, Said; Hansen, Jon Kehlet; Lee, Steve J; Liesebach, Mirko; Rau, Hans-Martin; Psomas, Achilleas; Schneck, Volker; Steiner, Wilfried; Zimmermann, Niklaus E; Kremer, Antoine
2017-07-01
How temperate forests will respond to climate change is uncertain; projections range from severe decline to increased growth. We conducted field tests of sessile oak (Quercus petraea), a widespread keystone European forest tree species, including more than 150 000 trees sourced from 116 geographically diverse populations. The tests were planted on 23 field sites in six European countries, in order to expose them to a wide range of climates, including sites reflecting future warmer and drier climates. By assessing tree height and survival, our objectives were twofold: (i) to identify the source of differential population responses to climate (genetic differentiation due to past divergent climatic selection vs. plastic responses to ongoing climate change) and (ii) to explore which climatic variables (temperature or precipitation) trigger the population responses. Tree growth and survival were modeled for contemporary climate and then projected using data from four regional climate models for years 2071-2100, using two greenhouse gas concentration trajectory scenarios each. Overall, results indicated a moderate response of tree height and survival to climate variation, with changes in dryness (either annual or during the growing season) explaining the major part of the response. While, on average, populations exhibited local adaptation, there was significant clinal population differentiation for height growth with winter temperature at the site of origin. The most moderate climate model (HIRHAM5-EC; rcp4.5) predicted minor decreases in height and survival, while the most extreme model (CCLM4-GEM2-ES; rcp8.5) predicted large decreases in survival and growth for southern and southeastern edge populations (Hungary and Turkey). Other nonmarginal populations with continental climates were predicted to be severely and negatively affected (Bercé, France), while populations at the contemporary northern limit (colder and humid maritime regions; Denmark and Norway) will probably not show large changes in growth and survival in response to climate change. © 2017 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Zheng, Y.; Lv, E.; Huang, Y.
2016-12-01
Located in the hinterland of the Qinghai-Tibetan Plateau, the Three-River Headwaters region (THR) features unique eco-environmental conditions and fragile ecosystems, and is very vulnerable to climate change. To investigate the effects of climate change on the ecosystem, the Normalized Difference Vegetation Index (NDVI) was employed as an indicator to reflect the vegetation dynamics in response to climate change. This study proposed a model based on Stepwise-cluster analysis to predict the temporal and spatial distributions of NDVI values for five future years according to Global Circulation Models (GCMs) climate projections under the RCP4.5 scenario. The obtained spatial results showed very good agreements between simulations and remote sensing observations of the NDVI value for both training and validation, and the developed model demonstrated its capability of predicting the monthly changes of NDVI through representing the relationships between it and various climatic factors, including remote sensed precipitation and temperature with no, 1 and 2-month lag period. The monthly average precipitation with one-month lag period was further found to be the most important climatic factor that drives the changes of NDVI in the THR. Compared with the values of NDVI in 2000 - 2013, the predicting results indicate the values of NDVI for the THR in growing season (May to October) will decrease by 15.74% in the next 100 years, suggesting that the THR is going to experience an environmental degradation. The results also show that precipitation is the primary driving factor relative to temperature, especially the one-month-lag precipitation. Findings from this study would help policy makers draw up effective water resource and eco-environmental management strategies for adapting to climate change in the THR.
C. H. Greenberg; S. Goodrick; J. D. Austin; B. R. Parresol
2015-01-01
Hydroregimes of ephemeral wetlands affect reproductive success of many amphibian species and are sensitive to altered weather patterns associated with climate change.We used 17 years of weekly temperature, precipitation, and waterdepth measurements for eight small, ephemeral, groundwaterdriven sinkhole wetlands in Florida sandhills to develop a hydroregime predictive...
Model uncertainties do not affect observed patterns of species richness in the Amazon
Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo
2017-01-01
Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species. PMID:29023503
The threat of climate change to freshwater pearl mussel populations.
Hastie, Lee C; Cosgrove, Peter J; Ellis, Noranne; Gaywood, Martin J
2003-02-01
Changes in climate are occurring around the world and the effects on ecosystems will vary, depending on the extent and nature of these changes. In northern Europe, experts predict that annual rainfall will increase significantly, along with dramatic storm events and flooding in the next 50-100 years. Scotland is a stronghold of the endangered freshwater pearl mussel, Margaritifera margaritifera (L.), and a number of populations may be threatened. For example, large floods have been shown to adversely affect mussels, and although these stochastic events were historically rare, they may now be occurring more often as a result of climate change. Populations may also be affected by a number of other factors, including predicted changes in temperature, sea level, habitat availability, host fish stocks and human activity. In this paper, we explain how climate change may impact M. margaritifera and discuss the general implications for the conservation management of this species.
Processes Understanding of Decadal Climate Variability
NASA Astrophysics Data System (ADS)
Prömmel, Kerstin; Cubasch, Ulrich
2016-04-01
The realistic representation of decadal climate variability in the models is essential for the quality of decadal climate predictions. Therefore, the understanding of those processes leading to decadal climate variability needs to be improved. Several of these processes are already included in climate models but their importance has not yet completely been clarified. The simulation of other processes requires sometimes a higher resolution of the model or an extension by additional subsystems. This is addressed within one module of the German research program "MiKlip II - Decadal Climate Predictions" (http://www.fona-miklip.de/en/) with a focus on the following processes. Stratospheric processes and their impact on the troposphere are analysed regarding the climate response to aerosol perturbations caused by volcanic eruptions and the stratospheric decadal variability due to solar forcing, climate change and ozone recovery. To account for the interaction between changing ozone concentrations and climate a computationally efficient ozone chemistry module is developed and implemented in the MiKlip prediction system. The ocean variability and air-sea interaction are analysed with a special focus on the reduction of the North Atlantic cold bias. In addition, the predictability of the oceanic carbon uptake with a special emphasis on the underlying mechanism is investigated. This addresses a combination of physical, biological and chemical processes.
External forcing as a metronome for Atlantic multidecadal variability
NASA Astrophysics Data System (ADS)
Otterå, Odd Helge; Bentsen, Mats; Drange, Helge; Suo, Lingling
2010-10-01
Instrumental records, proxy data and climate modelling show that multidecadal variability is a dominant feature of North Atlantic sea-surface temperature variations, with potential impacts on regional climate. To understand the observed variability and to gauge any potential for climate predictions it is essential to identify the physical mechanisms that lead to this variability, and to explore the spatial and temporal characteristics of multidecadal variability modes. Here we use a coupled ocean-atmosphere general circulation model to show that the phasing of the multidecadal fluctuations in the North Atlantic during the past 600 years is, to a large degree, governed by changes in the external solar and volcanic forcings. We find that volcanoes play a particularly important part in the phasing of the multidecadal variability through their direct influence on tropical sea-surface temperatures, on the leading mode of northern-hemisphere atmosphere circulation and on the Atlantic thermohaline circulation. We suggest that the implications of our findings for decadal climate prediction are twofold: because volcanic eruptions cannot be predicted a decade in advance, longer-term climate predictability may prove challenging, whereas the systematic post-eruption changes in ocean and atmosphere may hold promise for shorter-term climate prediction.
Emergence, reductionism and landscape response to climate change
NASA Astrophysics Data System (ADS)
Harrison, Stephan; Mighall, Tim
2010-05-01
Predicting landscape response to external forcing is hampered by the non-linear, stochastic and contingent (ie dominated by historical accidents) forcings inherent in landscape evolution. Using examples from research carried out in southwest Ireland we suggest that non-linearity in landform evolution is likely to be a strong control making regional predictions of landscape response to climate change very difficult. While uncertainties in GCM projections have been widely explored in climate science much less attention has been directed by geomorphologists to the uncertainties in landform evolution under conditions of climate change and this problem may be viewed within the context of philosophical approaches to reductionsim and emergence. Understanding the present and future trajectory of landform change may also guide us to provide an enhanced appreciation of how landforms evolved in the past.
Robinson, Jason L; Fordyce, James A
2017-01-01
Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.
Predictability of North Atlantic Multidecadal Climate Variability
Griffies; Bryan
1997-01-10
Atmospheric weather systems become unpredictable beyond a few weeks, but climate variations can be predictable over much longer periods because of the coupling of the ocean and atmosphere. With the use of a global coupled ocean-atmosphere model, it is shown that the North Atlantic may have climatic predictability on the order of a decade or longer. These results suggest that variations of the dominant multidecadal sea surface temperature patterns in the North Atlantic, which have been associated with changes in climate over Eurasia, can be predicted if an adequate and sustainable system for monitoring the Atlantic Ocean exists.
Population-level genetic variation and climate change in a biodiversity hotspot
2017-01-01
Introduction Estimated future climate scenarios can be used to predict where hotspots of endemism may occur over the next century, but life history, ecological and genetic traits will be important in informing the varying responses within myriad taxa. Essential to predicting the consequences of climate change to individual species will be an understanding of the factors that drive genetic structure within and among populations. Here, I review the factors that influence the genetic structure of plant species in California, but are applicable elsewhere; existing levels of genetic variation, life history and ecological characteristics will affect the ability of an individual taxon to persist in the presence of anthropogenic change. Factors influencing the distribution of genetic variation Persistence in the face of climate change is likely determined by life history characteristics: dispersal ability, generation time, reproductive ability, degree of habitat specialization, plant–insect interactions, existing genetic diversity and availability of habitat or migration corridors. Existing levels of genetic diversity in plant populations vary based on a number of evolutionary scenarios that include endemism, expansion since the last glacial maximum, breeding system and current range sizes. Regional priorities and examples A number of well-documented examples are provided from the California Floristic Province. Some predictions can be made for the responses of plant taxa to rapid environmental changes based on geographic position, evolutionary history, existing genetic variation, and ecological amplitude. Conclusions, Solutions and Recommendations The prediction of how species will respond to climate change will require a synthesis drawing from population genetics, geography, palaeontology and ecology. The important integration of the historical factors that have shaped the distribution and existing genetic structure of California’s plant taxa will enable us to predict and prioritize the conservation of species and areas most likely to be impacted by rapid climate change, human disturbance and invasive species. PMID:28069633
Population-level genetic variation and climate change in a biodiversity hotspot.
Schierenbeck, Kristina A
2017-01-01
Estimated future climate scenarios can be used to predict where hotspots of endemism may occur over the next century, but life history, ecological and genetic traits will be important in informing the varying responses within myriad taxa. Essential to predicting the consequences of climate change to individual species will be an understanding of the factors that drive genetic structure within and among populations. Here, I review the factors that influence the genetic structure of plant species in California, but are applicable elsewhere; existing levels of genetic variation, life history and ecological characteristics will affect the ability of an individual taxon to persist in the presence of anthropogenic change. Persistence in the face of climate change is likely determined by life history characteristics: dispersal ability, generation time, reproductive ability, degree of habitat specialization, plant-insect interactions, existing genetic diversity and availability of habitat or migration corridors. Existing levels of genetic diversity in plant populations vary based on a number of evolutionary scenarios that include endemism, expansion since the last glacial maximum, breeding system and current range sizes. A number of well-documented examples are provided from the California Floristic Province. Some predictions can be made for the responses of plant taxa to rapid environmental changes based on geographic position, evolutionary history, existing genetic variation, and ecological amplitude. The prediction of how species will respond to climate change will require a synthesis drawing from population genetics, geography, palaeontology and ecology. The important integration of the historical factors that have shaped the distribution and existing genetic structure of California's plant taxa will enable us to predict and prioritize the conservation of species and areas most likely to be impacted by rapid climate change, human disturbance and invasive species. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Assessing Mammal Exposure to Climate Change in the Brazilian Amazon.
Ribeiro, Bruno R; Sales, Lilian P; De Marco, Paulo; Loyola, Rafael
2016-01-01
Human-induced climate change is considered a conspicuous threat to biodiversity in the 21st century. Species' response to climate change depends on their exposition, sensitivity and ability to adapt to novel climates. Exposure to climate change is however uneven within species' range, so that some populations may be more at risk than others. Identifying the regions most exposed to climate change is therefore a first and pivotal step on determining species' vulnerability across their geographic ranges. Here, we aimed at quantifying mammal local exposure to climate change across species' ranges. We identified areas in the Brazilian Amazon where mammals will be critically exposed to non-analogue climates in the future with different variables predicted by 15 global circulation climate forecasts. We also built a null model to assess the effectiveness of the Amazon protected areas in buffering the effects of climate change on mammals, using an innovative and more realistic approach. We found that 85% of species are likely to be exposed to non-analogue climatic conditions in more than 80% of their ranges by 2070. That percentage is even higher for endemic mammals; almost all endemic species are predicted to be exposed in more than 80% of their range. Exposure patterns also varied with different climatic variables and seem to be geographically structured. Western and northern Amazon species are more likely to experience temperature anomalies while northeastern species will be more affected by rainfall abnormality. We also observed an increase in the number of critically-exposed species from 2050 to 2070. Overall, our results indicate that mammals might face high exposure to climate change and that protected areas will probably not be efficient enough to avert those impacts.
Assessing Mammal Exposure to Climate Change in the Brazilian Amazon
Ribeiro, Bruno R.; Sales, Lilian P.; De Marco, Paulo; Loyola, Rafael
2016-01-01
Human-induced climate change is considered a conspicuous threat to biodiversity in the 21st century. Species’ response to climate change depends on their exposition, sensitivity and ability to adapt to novel climates. Exposure to climate change is however uneven within species’ range, so that some populations may be more at risk than others. Identifying the regions most exposed to climate change is therefore a first and pivotal step on determining species’ vulnerability across their geographic ranges. Here, we aimed at quantifying mammal local exposure to climate change across species’ ranges. We identified areas in the Brazilian Amazon where mammals will be critically exposed to non-analogue climates in the future with different variables predicted by 15 global circulation climate forecasts. We also built a null model to assess the effectiveness of the Amazon protected areas in buffering the effects of climate change on mammals, using an innovative and more realistic approach. We found that 85% of species are likely to be exposed to non-analogue climatic conditions in more than 80% of their ranges by 2070. That percentage is even higher for endemic mammals; almost all endemic species are predicted to be exposed in more than 80% of their range. Exposure patterns also varied with different climatic variables and seem to be geographically structured. Western and northern Amazon species are more likely to experience temperature anomalies while northeastern species will be more affected by rainfall abnormality. We also observed an increase in the number of critically-exposed species from 2050 to 2070. Overall, our results indicate that mammals might face high exposure to climate change and that protected areas will probably not be efficient enough to avert those impacts. PMID:27829036
Past climate variability and change in the Arctic and at high latitudes
Alley, Richard B.; Brigham-Grette, Julie; Miller, Gifford H.; Polyak, Leonid; ,; ,; ,
2009-01-01
Paleoclimate records play a key role in our understanding of Earth's past and present climate system and in our confidence in predicting future climate changes. Paleoclimate data help to elucidate past and present active mechanisms of climate change by placing the short instrumental record into a longer term context and by permitting models to be tested beyond the limited time that instrumental measurements have been available.
Xiaohui Feng; María Uriarte; Grizelle González; Sasha Reed; Jill Thompson; Jess K. Zimmerman; Lora Murphy
2018-01-01
Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very...
Can trait patterns along gradients predict plant community responses to climate change?
Guittar, John; Goldberg, Deborah; Klanderud, Kari; Telford, Richard J; Vandvik, Vigdis
2016-10-01
Plant functional traits vary consistently along climate gradients and are therefore potential predictors of plant community response to climate change. We test this space-for-time assumption by combining a spatial gradient study with whole-community turf transplantation along temperature and precipitation gradients in a network of 12 grassland sites in Southern Norway. Using data on eight traits for 169 species and annual vegetation censuses of 235 turfs over 5 yr, we quantify trait-based responses to climate change by comparing observed community dynamics in transplanted turfs to field-parameterized null model simulations. Three traits related to species architecture (maximum height, number of dormant meristems, and ramet-ramet connection persistence) varied consistently along spatial temperature gradients and also correlated to changes in species abundances in turfs transplanted to warmer climates. Two traits associated with resource acquisition strategy (SLA, leaf area) increased along spatial temperature gradients but did not correlate to changes in species abundances following warming. No traits correlated consistently with precipitation. Our study supports the hypothesis that spatial associations between plant traits and broad-scale climate variables can be predictive of community response to climate change, but it also suggests that not all traits with clear patterns along climate gradients will necessarily influence community response to an equal degree. © 2016 by the Ecological Society of America.
Gerald E. Rehfeldt; Nicholas L. Crookston; Cuauhtemoc Saenz-Romero; Elizabeth M. Campbell
2012-01-01
Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of...
Carvalho, Bruno M; Rangel, Elizabeth F; Ready, Paul D; Vale, Mariana M
2015-01-01
Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector's climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: "stabilization" and "high increase". Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela. These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region.
Carvalho, Bruno M.; Ready, Paul D.
2015-01-01
Vector borne diseases are susceptible to climate change because distributions and densities of many vectors are climate driven. The Amazon region is endemic for cutaneous leishmaniasis and is predicted to be severely impacted by climate change. Recent records suggest that the distributions of Lutzomyia (Nyssomyia) flaviscutellata and the parasite it transmits, Leishmania (Leishmania) amazonensis, are expanding southward, possibly due to climate change, and sometimes associated with new human infection cases. We define the vector’s climatic niche and explore future projections under climate change scenarios. Vector occurrence records were compiled from the literature, museum collections and Brazilian Health Departments. Six bioclimatic variables were used as predictors in six ecological niche model algorithms (BIOCLIM, DOMAIN, MaxEnt, GARP, logistic regression and Random Forest). Projections for 2050 used 17 general circulation models in two greenhouse gas representative concentration pathways: “stabilization” and “high increase”. Ensemble models and consensus maps were produced by overlapping binary predictions. Final model outputs showed good performance and significance. The use of species absence data substantially improved model performance. Currently, L. flaviscutellata is widely distributed in the Amazon region, with records in the Atlantic Forest and savannah regions of Central Brazil. Future projections indicate expansion of the climatically suitable area for the vector in both scenarios, towards higher latitudes and elevations. L. flaviscutellata is likely to find increasingly suitable conditions for its expansion into areas where human population size and density are much larger than they are in its current locations. If environmental conditions change as predicted, the range of the vector is likely to expand to southeastern and central-southern Brazil, eastern Paraguay and further into the Amazonian areas of Bolivia, Peru, Ecuador, Colombia and Venezuela. These areas will only become endemic for L. amazonensis, however, if they have competent reservoir hosts and transmission dynamics matching those in the Amazon region. PMID:26619186
McIntyre, Shannon; Rangel, Elizabeth F; Ready, Paul D; Carvalho, Bruno M
2017-03-24
Before 1996 the phlebotomine sand fly Lutzomyia neivai was usually treated as a synonym of the morphologically similar Lutzomyia intermedia, which has long been considered a vector of Leishmania braziliensis, the causative agent of much cutaneous leishmaniasis in South America. This report investigates the likely range changes of both sand fly species in response to a stabilisation climate change scenario (RCP4.5) and a high greenhouse gas emissions one (RCP8.5). Ecological niche modelling was used to identify areas of South America with climates currently suitable for each species, and then the future distributions of these climates were predicted based on climate change scenarios. Compared with the previous ecological niche model of L. intermedia (sensu lato) produced using the GARP algorithm in 2003, the current investigation modelled the two species separately, making use of verified presence records and additional records after 2001. Also, the new ensemble approach employed ecological niche modelling algorithms (including Maximum Entropy, Random Forests and Support Vector Machines) that have been widely adopted since 2003 and perform better than GARP, as well as using a more recent climate change model (HadGEM2) considered to have better performance at higher resolution than the earlier one (HadCM2). Lutzomyia intermedia was shown to be the more tropical of the two species, with its climatic niche defined by higher annual mean temperatures and lower temperature seasonality, in contrast to the more subtropical L. neivai. These different latitudinal ranges explain the two species' predicted responses to climate change by 2050, with L. intermedia mostly contracting its range (except perhaps in northeast Brazil) and L. neivai mostly shifting its range southwards in Brazil and Argentina. This contradicts the findings of the 2003 report, which predicted more range expansion. The different findings can be explained by the improved data sets and modelling methods. Our findings indicate that climate change will not always lead to range expansion of disease vectors such as sand flies. Ecological niche models should be species specific, carefully selected and combined in an ensemble approach.
Michael J. Case; David L. Peterson
2005-01-01
Information about the sensitivity to climate of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) is valuable because it will allow forest managers to maximize growth, better understand how carbon sequestration may change over time, and better model and predict future ecosystem responses to climatic change. We examined the effects of climatic...
Interactions of changing climate and shifts in forest composition on stand carbon balance
Chiang Jyh-Min; Louis Iverson; Anantha Prasad; Kim Brown
2006-01-01
Given that climate influences forest biogeographic distribution, many researchers have created models predicting shifts in tree species range with future climate change scenarios. The objective of this study is to investigate the forest carbon consequences of shifts in stand species composition with current and future climate scenarios using such a model.
Evaluating the sources of potential migrant species: implications under climate change
Ines Ibanez; James S. Clark; Michael C. Dietze
2008-01-01
As changes in climate become more apparent, ecologists face the challenge of predicting species responses to the new conditions. Most forecasts are based on climate envelopes (CE), correlative approaches that project future distributions on the basis of the current climate often assuming some dispersal lag. One major caveat with this approach is that it ignores the...
Potential Climate-driven Silvicultural and Agricultural Transformations in Siberia in the 21 Century
NASA Astrophysics Data System (ADS)
Tchebakova, N. M.; Parfenova, E. I.; Shvetsov, E.; Soja, A. J.
2017-12-01
Simulations of Siberian forests in a changing climate showed them to be changed in composition, decreased, and shifted northwards. Our goals were to evaluate the ecological consequences for the forests and agriculture in Siberia and to offer adaptive measures that may be undertaken to minimize negative consequences and maximize benefits from a rapidly changing environment in the socially important region of southern Siberia. We considered two strategies to estimate climate-change effects on potentially failing forests within an expanding forest-steppe ecotone. To support forestry, seed transfers from locations that are best suited to the genotypes in future climates may be applied to assist trees and forests in a changing climate. To support agriculture, in view of the growing world concerns on food safety, new farming lands may be established in a new forest-steppe ecotone with its favorable climatic and soil resources. We used our bioclimatic vegetation models of various levels: a forest type model to predict forest shifts and forest-failing lands, tree species range and their climatypes models to predict what tree species/climatype would be suitable and crop models to predict crops to introduce in potentially climate-disturbed areas in Siberia. Climate change data for the 2080s were calculated from the ensemble of 20 general circulation models of the Coupled Model Intercomparison Project phase 5 (CMIP5) and two scenarios to characterize the range of climate change: mild climate (RCP2.6 scenario) and sharp climate (RCP 8.5 scenario). By the 2080s, forest-steppe and steppe rather than forests would dominate up to half of Siberia in the warmer and dryer RCP 8.5 climate. Water stress tolerant and fire-resistant light-needled species Pinus sylvestris and Larix spp. would dominate the forest-steppe ecotone. Failing forests in a dryer climate may be maintained by moving and substituting proper climatypes from locations often hundreds of km away. Agriculture in Siberia would likely benefit from climate warming. Farming may be a choice to use lands where forests would fail. Potential croplands would be limited by suitable soils in the north and irrigation in the south. To recommend an economic strategy that would optimize economic gains/losses due to the effects of climate change will require additional research
Climate change and bark beetles of the western United States and Canada: Direct and indirect effects
Barbara J. Bentz; Jacques Regniere; Christopher J. Fettig; E. Matthew Hansen; Jane L. Hayes; Jeffrey A. Hicke; Rick G. Kelsey; Jose F. Negron; Steven J. Seybold
2010-01-01
Climatic changes are predicted to significantly affect the frequency and severity of disturbances that shape forest ecosystems. We provide a synthesis of climate change effects on native bark beetles, important mortality agents of conifers in western North America. Because of differences in temperature-dependent life-history strategies, including cold-induced mortality...
Aline Frank; Christoph Sperisen; Glenn Thomas Howe; Peter Brang; Lorenz Walthert; John Bradley St.Clair; Caroline Heiri
2017-01-01
Understanding the genecology of forest trees is critical for gene conservation, for predicting the effects of climate change and climate change adaptation, and for successful reforestation. Although common genecological patterns have emerged, species-specific details are also important. Which species are most vulnerable to climate change? Which are the most important...
Quantitative metrics for assessing predicted climate change pressure on North American tree species
Kevin M. Potter; William W. Hargrove
2013-01-01
Changing climate may pose a threat to forest tree species, forcing three potential population-level responses: toleration/adaptation, movement to suitable environmental conditions, or local extirpation. Assessments that prioritize and classify tree species for management and conservation activities in the face of climate change will need to incorporate estimates of the...
M. Friggens; K. Bagne; D. Finch; D. Falk; J. Triepke; A. Lynch
2013-01-01
Climate change creates new challenges for resource managers and decision-makers with broad and often complex effects that make it difficult to accurately predict and design management actions to minimize undesirable impacts. We review pertinent information regarding methods and approaches used to conduct climate change vulnerability assessments to reveal assumptions...
It's lonely at the top: Biodiversity at risk to loss from climate change
John L. Koprowski; Sandra L. Doumas; Melissa J. Merrick; Brittany Oleson; Erin E. Posthumus; Timothy G. Jessen; R. Nathan Gwinn
2013-01-01
Climate change is a serious immediate and long-term threat to wildlife species. State and federal agencies are working with universities and non-government organizations to predict, plan for, and mitigate such uncertainties in the future. Endemic species may be particularly at-risk as climate-induced changes impact their limited geographic ranges. The Madrean...
Projected effects of Climate-change-induced flow alterations on stream macroinvertebrate abundances.
Kakouei, Karan; Kiesel, Jens; Domisch, Sami; Irving, Katie S; Jähnig, Sonja C; Kail, Jochem
2018-03-01
Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species' response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower-mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present-day gauging data. Species' abundances were predicted for three periods: (1) baseline (1998-2017), (2) horizon 2050 (2046-2065) and (3) horizon 2090 (2080-2099) based on these empirical relationships and using high-resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low-flow conditions, leading to decreased abundances of species up to -42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower-mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate-change impacts on species abundances and can be applied to any stressor, species, or region.
PREDICTING CLIMATE-INDUCED RANGE SHIFTS: MODEL DIFFERENCES AND MODEL RELIABILITY
Predicted changes in the global climate are likely to cause large shifts in the geographic ranges of many plant and animal species. To date, predictions of future range shifts have relied on a variety of modeling approaches with different levels of model accuracy. Using a common ...
Petrů, Martina; Tielbörger, Katja
2008-04-01
The role of local adaptation and factors other than climate in determining extinction probabilities of species under climate change has not been yet explicitly studied. Here we performed a field experiment with annual plants growing along a steep climatic gradient in Israel to isolate climatic effects for local trait expression. The focus trait was seed dormancy, for which many theoretical predictions exist regarding climate-driven optimal germination behaviour. We evaluated how germination is consistent with theory, indicating local adaptation to current and changing climatic conditions, and how it varies among species and between natural and standardised soil conditions. We reciprocally sowed seeds from three or four origins for each of three annual species, Biscutella didyma, Bromus fasciculatus and Hymenocarpos circinnatus, in their home and neighbouring sowing locations along an aridity gradient. Our predictions were: lower germination fraction for seeds from more arid origins, and higher germination at wetter sowing locations for all seed origins. By sowing seeds in both local and standard soil, we separated climatic effects from local conditions. At the arid sowing location, two species supported the prediction of low germination of drier seed origins, but differences between seed origins at the other sites were not substantial. There were no clear rainfall effects on germination. Germination fractions were consistently lower on local soil than on standard soil, indicating the important role of soil type and neighbour conditions for trait expression. Local environmental conditions may override effects of climate and so should be carefully addressed in future studies testing for the potential of species to adapt or plastically respond to climate change.
Neuwald, Jennifer L; Valenzuela, Nicole
2011-03-23
Climate change is expected to disrupt biological systems. Particularly susceptible are species with temperature-dependent sex determination (TSD), as in many reptiles. While the potentially devastating effect of rising mean temperatures on sex ratios in TSD species is appreciated, the consequences of increased thermal variance predicted to accompany climate change remain obscure. Surprisingly, no study has tested if the effect of thermal variance around high-temperatures (which are particularly relevant given climate change predictions) has the same or opposite effects as around lower temperatures. Here we show that sex ratios of the painted turtle (Chrysemys picta) were reversed as fluctuations increased around low and high unisexual mean-temperatures. Unexpectedly, the developmental and sexual responses around female-producing temperatures were decoupled in a more complex manner than around male-producing values. Our novel observations are not fully explained by existing ecological models of development and sex determination, and provide strong evidence that thermal fluctuations are critical for shaping the biological outcomes of climate change.
The shaping of genetic variation in edge-of-range populations under past and future climate change
Razgour, Orly; Juste, Javier; Ibáñez, Carlos; Kiefer, Andreas; Rebelo, Hugo; Puechmaille, Sébastien J; Arlettaz, Raphael; Burke, Terry; Dawson, Deborah A; Beaumont, Mark; Jones, Gareth; Wiens, John
2013-01-01
With rates of climate change exceeding the rate at which many species are able to shift their range or adapt, it is important to understand how future changes are likely to affect biodiversity at all levels of organisation. Understanding past responses and extent of niche conservatism in climatic tolerance can help predict future consequences. We use an integrated approach to determine the genetic consequences of past and future climate changes on a bat species, Plecotus austriacus. Glacial refugia predicted by palaeo-modelling match those identified from analyses of extant genetic diversity and model-based inference of demographic history. Former refugial populations currently contain disproportionately high genetic diversity, but niche conservatism, shifts in suitable areas and barriers to migration mean that these hotspots of genetic diversity are under threat from future climate change. Evidence of population decline despite recent northward migration highlights the need to conserve leading-edge populations for spearheading future range shifts. PMID:23890483
Estimates of runoff using water-balance and atmospheric general circulation models
Wolock, D.M.; McCabe, G.J.
1999-01-01
The effects of potential climate change on mean annual runoff in the conterminous United States (U.S.) are examined using a simple water-balance model and output from two atmospheric general circulation models (GCMs). The two GCMs are from the Canadian Centre for Climate Prediction and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HAD). In general, the CCC GCM climate results in decreases in runoff for the conterminous U.S., and the HAD GCM climate produces increases in runoff. These estimated changes in runoff primarily are the result of estimated changes in precipitation. The changes in mean annual runoff, however, mostly are smaller than the decade-to-decade variability in GCM-based mean annual runoff and errors in GCM-based runoff. The differences in simulated runoff between the two GCMs, together with decade-to-decade variability and errors in GCM-based runoff, cause the estimates of changes in runoff to be uncertain and unreliable.
Sue Miller; Matt Reeves; Karen Bagne; John Tanaka
2017-01-01
Cattle production capacity on western rangelands is potentially vulnerable to climate change through impacts on the amount of forage, changes in vegetation type, heat stress, and year-to-year forage variability. The researchers in this study projected climate change effects to rangelands through 2100 and compared them to a present-day baseline to estimate vulnerability...
Predicting the Impact of Climate Change on Threatened Species in UK Waters
Jones, Miranda C.; Dye, Stephen R.; Fernandes, Jose A.; Frölicher, Thomas L.; Pinnegar, John K.; Warren, Rachel; Cheung, William W. L.
2013-01-01
Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina). PMID:23349829
Predicting the impact of climate change on threatened species in UK waters.
Jones, Miranda C; Dye, Stephen R; Fernandes, Jose A; Frölicher, Thomas L; Pinnegar, John K; Warren, Rachel; Cheung, William W L
2013-01-01
Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina).
Lessons from Earth's Deep Time
ERIC Educational Resources Information Center
Soreghan, G. S.
2005-01-01
Earth is a repository of data on climatic changes from its deep-time history. Article discusses the collection and study of these data to predict future climatic changes, the need to create national study centers for the purpose, and the necessary cooperation between different branches of science in climatic research.
Conroy, M.J.; Runge, M.C.; Nichols, J.D.; Stodola, K.W.; Cooper, R.J.
2011-01-01
The broad physical and biological principles behind climate change and its potential large scale ecological impacts on biota are fairly well understood, although likely responses of biotic communities at fine spatio-temporal scales are not, limiting the ability of conservation programs to respond effectively to climate change outside the range of human experience. Much of the climate debate has focused on attempts to resolve key uncertainties in a hypothesis-testing framework. However, conservation decisions cannot await resolution of these scientific issues and instead must proceed in the face of uncertainty. We suggest that conservation should precede in an adaptive management framework, in which decisions are guided by predictions under multiple, plausible hypotheses about climate impacts. Under this plan, monitoring is used to evaluate the response of the system to climate drivers, and management actions (perhaps experimental) are used to confront testable predictions with data, in turn providing feedback for future decision making. We illustrate these principles with the problem of mitigating the effects of climate change on terrestrial bird communities in the southern Appalachian Mountains, USA. ?? 2010 Elsevier Ltd.
Asymmetries in Climate Change Feedbacks: Why the Future may be Hotter Than you Think
NASA Astrophysics Data System (ADS)
Torn, M. S.; Harte, J.
2006-12-01
Feedbacks in the climate system are major sources of uncertainty, and climate predictions do not yet include one key set of feedbacks, namely biospheric greenhouse gas (GhG) feedbacks. Historical evidence shows that atmospheric GhG concentrations increase during periods of warming, implying a positive feedback to future climate change. We quantify this feedback for carbon dioxide (CO2) and methane (CH4) by combining the mathematics of feedback with both empirical ice-core information and general circulation model climate sensitivity. We find that a warming of 1.7-5.8°C predicted for the year 2100 is amplified to a warming commitment of 1.9-7.7°C, with the range deriving from different GCM simulations and paleo temperature records. Thus, anthropogenic emissions result in higher final GhG concentrations, and therefore more warming, than would be predicted in the absence of this feedback. Uncertainty in climate change predictions have been used as a rationale for inaction against the threat of global warming, based on a prevailing view that the uncertainties are symmetric, giving equal support to climate "optimists" (who think it will be a small problem) and "pessimists," (it will be a big problem). Our results show that even a symmetrical uncertainty in any component of feedback, whether positive or negative, produces an asymmetrical distribution of expected temperatures skewed towards higher temperature. For both reasons, the omission of key positive feedbacks and asymmetrical uncertainty from feedbacks, it is likely that the future will be hotter than we think, which implies more severe climate change impacts. Thus, these results suggest that a conservative policy approach would employ lower emission targets and tighter stabilization time horizons than would otherwise be required.
Climate change and potential impacts on bristol bay sockeye salmon populations
Scientific research has shown that climate change has already caused detectable changes to ecosystems throughout Alaska. As warming is predicted to continue, it is likely to lead to changes in marine and freshwater aquatic ecosystems and impact sockeye salmon populations in Brist...
Climate change risks and conservation implications for a threatened small-range mammal species.
Morueta-Holme, Naia; Fløjgaard, Camilla; Svenning, Jens-Christian
2010-04-29
Climate change is already affecting the distributions of many species and may lead to numerous extinctions over the next century. Small-range species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modeling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, even for rare and cryptic species. We used species distribution modeling to assess the climate sensitivity, climate change risks and conservation implications for a threatened small-range mammal species, the Iberian desman (Galemys pyrenaicus), which is a phylogenetically isolated insectivore endemic to south-western Europe. Atlas data on the distribution of G. pyrenaicus was linked to data on climate, topography and human impact using two species distribution modeling algorithms to test hypotheses on the factors that determine the range for this species. Predictive models were developed and projected onto climate scenarios for 2070-2099 to assess climate change risks and conservation possibilities. Mean summer temperature and water balance appeared to be the main factors influencing the distribution of G. pyrenaicus. Climate change was predicted to result in significant reductions of the species' range. However, the severity of these reductions was highly dependent on which predictor was the most important limiting factor. Notably, if mean summer temperature is the main range determinant, G. pyrenaicus is at risk of near total extinction in Spain under the most severe climate change scenario. The range projections for Europe indicate that assisted migration may be a possible long-term conservation strategy for G. pyrenaicus in the face of global warming. Climate change clearly poses a severe threat to this illustrative endemic species. Our findings confirm that endemic species can be highly vulnerable to a warming climate and highlight the fact that assisted migration has potential as a conservation strategy for species threatened by climate change.
Climate Change Risks and Conservation Implications for a Threatened Small-Range Mammal Species
Morueta-Holme, Naia; Fløjgaard, Camilla; Svenning, Jens-Christian
2010-01-01
Background Climate change is already affecting the distributions of many species and may lead to numerous extinctions over the next century. Small-range species are likely to be a special concern, but the extent to which they are sensitive to climate is currently unclear. Species distribution modeling, if carefully implemented, can be used to assess climate sensitivity and potential climate change impacts, even for rare and cryptic species. Methodology/Principal Findings We used species distribution modeling to assess the climate sensitivity, climate change risks and conservation implications for a threatened small-range mammal species, the Iberian desman (Galemys pyrenaicus), which is a phylogenetically isolated insectivore endemic to south-western Europe. Atlas data on the distribution of G. pyrenaicus was linked to data on climate, topography and human impact using two species distribution modeling algorithms to test hypotheses on the factors that determine the range for this species. Predictive models were developed and projected onto climate scenarios for 2070–2099 to assess climate change risks and conservation possibilities. Mean summer temperature and water balance appeared to be the main factors influencing the distribution of G. pyrenaicus. Climate change was predicted to result in significant reductions of the species' range. However, the severity of these reductions was highly dependent on which predictor was the most important limiting factor. Notably, if mean summer temperature is the main range determinant, G. pyrenaicus is at risk of near total extinction in Spain under the most severe climate change scenario. The range projections for Europe indicate that assisted migration may be a possible long-term conservation strategy for G. pyrenaicus in the face of global warming. Conclusions/Significance Climate change clearly poses a severe threat to this illustrative endemic species. Our findings confirm that endemic species can be highly vulnerable to a warming climate and highlight the fact that assisted migration has potential as a conservation strategy for species threatened by climate change. PMID:20454451
NASA Astrophysics Data System (ADS)
Choi, H. S.; Schneider, U.; Schmid, E.; Held, H.
2012-04-01
Changes to climate variability and frequency of extreme weather events are expected to impose damages to the agricultural sector. Seasonal forecasting and long range prediction skills have received attention as an option to adapt to climate change because seasonal climate and yield predictions could improve farmers' management decisions. The value of seasonal forecasting skill is assessed with a crop mix adaptation option in Spain where drought conditions are prevalent. Yield impacts of climate are simulated for six crops (wheat, barely, cotton, potato, corn and rice) with the EPIC (Environmental Policy Integrated Climate) model. Daily weather data over the period 1961 to 1990 are used and are generated by the regional climate model REMO as reference period for climate projection. Climate information and its consequent yield variability information are given to the stochastic agricultural sector model to calculate the value of climate information in the agricultural market. Expected consumers' market surplus and producers' revenue is compared with and without employing climate forecast information. We find that seasonal forecasting benefits not only consumers but also producers if the latter adopt a strategic crop mix. This mix differs from historical crop mixes by having higher shares of crops which fare relatively well under climate change. The corresponding value of information is highly sensitive to farmers' crop mix choices.
Heinemeyer, Andreas; Swindles, Graeme T
2018-05-08
Peatlands represent globally significant soil carbon stores that have been accumulating for millennia under water-logged conditions. However, deepening water-table depths (WTD) from climate change or human-induced drainage could stimulate decomposition resulting in peatlands turning from carbon sinks to carbon sources. Contemporary WTD ranges of testate amoebae (TA) are commonly used to predict past WTD in peatlands using quantitative transfer function models. Here we present, for the first time, a study comparing TA-based WTD reconstructions to instrumentally monitored WTD and hydrological model predictions using the MILLENNIA peatland model to examine past peatland responses to climate change and land management. Although there was very good agreement between monitored and modeled WTD, TA-reconstructed water table was consistently deeper. Predictions from a larger European TA transfer function data set were wetter, but the overall directional fit to observed WTD was better for a TA transfer function based on data from northern England. We applied a regression-based offset correction to the reconstructed WTD for the validation period (1931-2010). We then predicted WTD using available climate records as MILLENNIA model input and compared the offset-corrected TA reconstruction to MILLENNIA WTD predictions over an extended period (1750-1931) with available climate reconstructions. Although the comparison revealed striking similarities in predicted overall WTD patterns, particularly for a recent drier period (1965-1995), there were clear periods when TA-based WTD predictions underestimated (i.e. drier during 1830-1930) and overestimated (i.e. wetter during 1760-1830) past WTD compared to MILLENNIA model predictions. Importantly, simulated grouse moor management scenarios may explain the drier TA WTD predictions, resulting in considerable model predicted carbon losses and reduced methane emissions, mainly due to drainage. This study demonstrates the value of a site-specific and combined data-model validation step toward using TA-derived moisture conditions to understand past climate-driven peatland development and carbon budgets alongside modeling likely management impacts. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
NASA Tools for Climate Impacts on Water Resources
NASA Technical Reports Server (NTRS)
Toll, David; Doorn, Brad
2010-01-01
Climate and environmental change are expected to fundamentally alter the nation's hydrological cycle and water availability. Satellites provide global or near-global coverage using instruments, allowing for consistent, well-calibrated, and equivalent-quality data of the Earth system. A major goal for NASA climate and environmental change research is to create multi-instrument data sets to span the multi-decadal time scales of climate change and to combine these data with those from modeling and surface-based observing systems to improve process understanding and predictions. NASA and Earth science data and analyses will ultimately enable more accurate climate prediction, and characterization of uncertainties. NASA's Applied Sciences Program works with other groups, including other federal agencies, to transition demonstrated observational capabilities to operational capabilities. A summary of some of NASA tools for improved water resources management will be presented.
Belote, R Travis; Carroll, Carlos; Martinuzzi, Sebastián; Michalak, Julia; Williams, John W; Williamson, Matthew A; Aplet, Gregory H
2018-06-21
Addressing uncertainties in climate vulnerability remains a challenge for conservation planning. We evaluate how confidence in conservation recommendations may change with agreement among alternative climate projections and metrics of climate exposure. We assessed agreement among three multivariate estimates of climate exposure (forward velocity, backward velocity, and climate dissimilarity) using 18 alternative climate projections for the contiguous United States. For each metric, we classified maps into quartiles for each alternative climate projections, and calculated the frequency of quartiles assigned for each gridded location (high quartile frequency = more agreement among climate projections). We evaluated recommendations using a recent climate adaptation heuristic framework that recommends emphasizing various conservation strategies to land based on current conservation value and expected climate exposure. We found that areas where conservation strategies would be confidently assigned based on high agreement among climate projections varied substantially across regions. In general, there was more agreement in forward and backward velocity estimates among alternative projections than agreement in estimates of local dissimilarity. Consensus of climate predictions resulted in the same conservation recommendation assignments in a few areas, but patterns varied by climate exposure metric. This work demonstrates an approach for explicitly evaluating alternative predictions in geographic patterns of climate change.
Simulation of future stream alkalinity under changing deposition and climate scenarios.
Welsch, Daniel L; Cosby, B Jack; Hornberger, George M
2006-08-31
Models of soil and stream water acidification have typically been applied under scenarios of changing acidic deposition, however, climate change is usually ignored. Soil air CO2 concentrations have potential to increase as climate warms and becomes wetter, thus affecting soil and stream water chemistry by initially increasing stream alkalinity at the expense of reducing base saturation levels on soil exchange sites. We simulate this change by applying a series of physically based coupled models capable of predicting soil air CO2 and stream water chemistry. We predict daily stream water alkalinity for a small catchment in the Virginia Blue Ridge for 60 years into the future given stochastically generated daily climate values. This is done for nine different combinations of climate and deposition. The scenarios for both climate and deposition include a static scenario, a scenario of gradual change, and a scenario of abrupt change. We find that stream water alkalinity continues to decline for all scenarios (average decrease of 14.4 microeq L-1) except where climate is gradually warming and becoming more moist (average increase of 13 microeq L-1). In all other scenarios, base cation removal from catchment soils is responsible for limited alkalinity increase resulting from climate change. This has implications given the extent that acidification models are used to establish policy and legislation concerning deposition and emissions.
Collapsing avian community on a Hawaiian island.
Paxton, Eben H; Camp, Richard J; Gorresen, P Marcos; Crampton, Lisa H; Leonard, David L; VanderWerf, Eric A
2016-09-01
The viability of many species has been jeopardized by numerous negative factors over the centuries, but climate change is predicted to accelerate and increase the pressure of many of these threats, leading to extinctions. The Hawaiian honeycreepers, famous for their spectacular adaptive radiation, are predicted to experience negative responses to climate change, given their susceptibility to introduced disease, the strong linkage of disease distribution to climatic conditions, and their current distribution. We document the rapid collapse of the native avifauna on the island of Kaua'i that corresponds to changes in climate and disease prevalence. Although multiple factors may be pressuring the community, we suggest that a tipping point has been crossed in which temperatures in forest habitats at high elevations have reached a threshold that facilitates the development of avian malaria and its vector throughout these species' ranges. Continued incursion of invasive weeds and non-native avian competitors may be facilitated by climate change and could also contribute to declines. If current rates of decline continue, we predict multiple extinctions in the coming decades. Kaua'i represents an early warning for the forest bird communities on the Maui and Hawai'i islands, as well as other species around the world that are trapped within a climatic space that is rapidly disappearing.
Collapsing avian community on a Hawaiian island
Paxton, Eben H.; Camp, Richard J.; Gorresen, P. Marcos; Crampton, Lisa H.; Leonard, David L.; VanderWerf, Eric
2016-01-01
The viability of many species has been jeopardized by numerous negative factors over the centuries, but climate change is predicted to accelerate and increase the pressure of many of these threats, leading to extinctions. The Hawaiian honeycreepers, famous for their spectacular adaptive radiation, are predicted to experience negative responses to climate change, given their susceptibility to introduced disease, the strong linkage of disease distribution to climatic conditions, and their current distribution. We document the rapid collapse of the native avifauna on the island of Kaua‘i that corresponds to changes in climate and disease prevalence. Although multiple factors may be pressuring the community, we suggest that a tipping point has been crossed in which temperatures in forest habitats at high elevations have reached a threshold that facilitates the development of avian malaria and its vector throughout these species’ ranges. Continued incursion of invasive weeds and non-native avian competitors may be facilitated by climate change and could also contribute to declines. If current rates of decline continue, we predict multiple extinctions in the coming decades. Kaua‘i represents an early warning for the forest bird communities on the Maui and Hawai‘i islands, as well as other species around the world that are trapped within a climatic space that is rapidly disappearing.
An imperative need for global change research in tropical forests.
Zhou, Xuhui; Fu, Yuling; Zhou, Lingyan; Li, Bo; Luo, Yiqi
2013-09-01
Tropical forests play a crucial role in regulating regional and global climate dynamics, and model projections suggest that rapid climate change may result in forest dieback or savannization. However, these predictions are largely based on results from leaf-level studies. How tropical forests respond and feedback to climate change is largely unknown at the ecosystem level. Several complementary approaches have been used to evaluate the effects of climate change on tropical forests, but the results are conflicting, largely due to confounding effects of multiple factors. Although altered precipitation and nitrogen deposition experiments have been conducted in tropical forests, large-scale warming and elevated carbon dioxide (CO2) manipulations are completely lacking, leaving many hypotheses and model predictions untested. Ecosystem-scale experiments to manipulate temperature and CO2 concentration individually or in combination are thus urgently needed to examine their main and interactive effects on tropical forests. Such experiments will provide indispensable data and help gain essential knowledge on biogeochemical, hydrological and biophysical responses and feedbacks of tropical forests to climate change. These datasets can also inform regional and global models for predicting future states of tropical forests and climate systems. The success of such large-scale experiments in natural tropical forests will require an international framework to coordinate collaboration so as to meet the challenges in cost, technological infrastructure and scientific endeavor.
Dynamic response of airborne infections to climate change: predictions for varicella
NASA Astrophysics Data System (ADS)
Baker, R.; Mahmud, A. S.; Metcalf, C. J. E.
2017-12-01
Characterizing how climate change will alter the burden of infectious diseases has clear applications for public health policy. Despite our uniquely detailed understanding of the transmission process for directly transmitted infections, the impact of climate variables on these infections remains understudied. We develop a novel methodology for estimating the causal relationship between climate and directly transmitted infections, which combines an epidemiological model of disease transmission with panel regression techniques. Our method allows us to move beyond correlational approaches to studying the link between climate and infectious diseases. Further, we can generate semi-mechanistic projections of incidence across climate scenarios. We illustrate our approach using 30 years of reported cases of varicella, a common airborne childhood infection, across 32 states in Mexico. We find significantly increased varicella transmission in drier conditions. We use this to map potential changes in the magnitude and variability of varicella incidence in Mexico as a result of projected changes in future climate conditions. Our results indicate that the predicted decrease in humidity in Mexico towards the end of the century will increase incidence of varicella, all else equal, and that these changes in incidence will be non-uniform across the year.
Why are coast redwood and giant sequoia not where they are not?
W.J. Libby
2017-01-01
Models predicting future climates and other kinds of information are being developed to anticipate where these two species may fail, where they may continue to thrive, and where they may colonize, given changes in climate and other elements of the environment. Important elements of such predictions, among others, are: photoperiod; site qualities; changes in levels and...
Schwalm, Donelle; Epps, Clinton W; Rodhouse, Thomas J; Monahan, William B; Castillo, Jessica A; Ray, Chris; Jeffress, Mackenzie R
2016-04-01
Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species' niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species' niches, resulting in predictions that are generally limited to climate-occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place-based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence-absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981-2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local-scale differences in the realized niche of the American pika. This variation resulted in diverse and - in some cases - highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place-based approach to species distribution modeling that includes fine-scale factors when assessing current and future climate impacts on species' distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas. © 2015 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Lomax, Barry; Fraser, Wesley
2016-04-01
Understanding variations in the Earth's climate history will enhance our understanding of and capacity to predict future climate change. Importantly this information can then be used to reduce uncertainty around future climate change predictions. However to achieve this, it is necessary to develop well constrained and robustly tested palaeo-proxies. Plants are innately coupled to the atmosphere requiring both sunlight and CO2 to drive photosynthesis and carbon assimilation. When combined with their resilience and persistence, the study of plant responses to climate change in concert with the analysis of fossil plants offer the opportunity to monitor past atmospheric conditions and infer palaeoclimate change. In this presentation we highlight how this approach is leading to the development of mechanistic palaeoproxies tested on palaeobotanically relevant extant species showing that plant fossils can be used as both monitors and geochemical recorders of atmospheric changes.
Fast and Slow Precipitation Responses to Individual Climate Forcers: A PDRMIP Multimodel Study
NASA Technical Reports Server (NTRS)
Samset, B. H.; Myhre, G.; Forster, P.M.; Hodnebrog, O.; Andrews, T.; Faluvegi, G.; Flaschner, D.; Kasoar, M.; Kharin, V.; Kirkevag, A.;
2016-01-01
Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.
Thomas, Kathryn A.; Guertin, Patricia P.; Gass, Leila
2012-01-01
The authors developed spatial models of the predicted modern-day suitable habitat (SH) of 166 dominant and indicator plant species of the southwestern United States (herein referred to as the Southwest) and then conducted a coarse assessment of potential future changes in the distribution of their suitable habitat under three climate-change scenarios for two time periods. We used Maxent-based spatial modeling to predict the modern-day and future scenarios of SH for each species in an over 342-million-acre area encompassing all or parts of six states in the Southwest--Arizona, California, Colorado, Nevada, New Mexico, and Utah. Modern-day SH models were predicted by our using 26 annual and monthly average temperature and precipitation variables, averaged for the years 1971-2000. Future SH models were predicted for each species by our using six climate models based on application of the average of 16 General Circulation Models to Intergovernmental Panel on Climate Change emission scenarios B1, A1B, and A2 for two time periods, 2040 to 2069 and 2070 and 2100, referred to respectively as the 2050 and 2100 time periods. The assessment examined each species' vulnerability to loss of modern-day SH under future climate scenarios, potential to gain SH under future climate scenarios, and each species' estimated risk as a function of both vulnerability and potential gains. All 166 species were predicted to lose modern-day SH in the future climate change scenarios. In the 2050 time period, nearly 30 percent of the species lost 75 percent or more of their modern-day suitable habitat, 21 species gained more new SH than their modern-day SH, and 30 species gained less new SH than 25 percent of their modern-day SH. In the 2100 time period, nearly half of the species lost 75 percent or more of their modern-day SH, 28 species gained more new SH than their modern-day SH, and 34 gained less new SH than 25 percent of their modern-day SH. Using nine risk categories we found only two species were in the least risk category, while 20 species were in the highest risk category. The assessment showed that species respond independently to predicted climate change, suggesting that current plant assemblages may disassemble under predicted climate change scenarios. This report presents the results for each species in tables (Appendix A) and maps (14 for each species) in Appendix B.
Climate change effects on watershed hydrological and biogeochemical processes
Projected changes in climate are widely expected to alter watershed processes. However, the extent of these changes is difficult to predict because complex interactions among affected hydrological and biogeochemical processes will likely play out over many decades and spatial sc...
From climate to global change: Following the footprint of Prof. Duzheng YE's research
NASA Astrophysics Data System (ADS)
Fu, Congbin
2017-10-01
To commemorate 100 years since the birth of Professor Duzheng YE, this paper reviews the contribution of Ye and his research team to the development from climate to global change science in the past 30 or so years, including: (1) the role of climate change in global change; (2) the critical time scales and predictability of global change; (3) the sensitive regions of global change—transitional zones of climate and ecosystems; and (4) orderly human activities and adaptation to global change, with a focus on the development of a proactive strategy for adaptation to such change.
USDA-ARS?s Scientific Manuscript database
Climate gradients shape spatial variation in the richness and composition of plant communities. Given future predicted changes in climate means and variability, and likely regional variation in the magnitudes of these changes, it is important to determine how temporal variation in climate influences...
Near-coastal (0-200 depth) ecosystems and species are under threat from increasing temperatures, ocean acidification, and sea level rise. However, species vary in their vulnerability to specific climatic changes and climate impacts will vary geographically. For management to resp...
Grazing impacts on infiltration rates at Vernal Pools in the Modoc Plateau
USDA-ARS?s Scientific Manuscript database
Vernal pools are depressions of land that are seasonally inundated with water. They host rare and endemic plant and animal species and are sensitive to livestock grazing management and climate change impacts on hydrology and vegetation. Climate change forecasts predicting a hotter, drier climate sug...
NCO Production Management Branch
Climate Climate Prediction Climate Archives Weather Safety Storm Ready NOAA Central Library Photo Library Management Branch Production Management Branch About the Production Management Branch NCO REQUEST FOR CHANGE (RFC) DATABASE ACCESS NCO Request For Change (RFC) Archive [For INTERNAL Use Only] NCO Request For
Branching out: Agroforestry as a climate change mitigation and adaptation tool for agriculture
USDA-ARS?s Scientific Manuscript database
The United States and Canadian agricultural lands are being targeted to provide more environmental and economic services while at the same time their capacity to provide these services under potential climate change (CC) is being questioned. Predictions of future climate conditions include longer gr...
Pilliod, David S; Arkle, Robert S; Robertson, Jeanne M; Murphy, Melanie A; Funk, W Chris
2015-09-01
Amphibian species persisting in isolated streams and wetlands in desert environments can be susceptible to low connectivity, genetic isolation, and climate changes. We evaluated the past (1900-1930), recent (1981-2010), and future (2071-2100) climate suitability of the arid Great Basin (USA) for the Columbia spotted frog (Rana luteiventris) and assessed whether changes in surface water may affect connectivity for remaining populations. We developed a predictive model of current climate suitability and used it to predict the historic and future distribution of suitable climates. We then modeled changes in surface water availability at each time period. Finally, we quantified connectivity among existing populations on the basis of hydrology and correlated it with interpopulation genetic distance. We found that the area of the Great Basin with suitable climate conditions has declined by approximately 49% over the last century and will likely continue to decline under future climate scenarios. Climate conditions at currently occupied locations have been relatively stable over the last century, which may explain persistence at these sites. However, future climates at these currently occupied locations are predicted to become warmer throughout the year and drier during the frog's activity period (May - September). Fall and winter precipitation may increase, but as rain instead of snow. Earlier runoff and lower summer base flows may reduce connectivity between neighboring populations, which is already limited. Many of these changes could have negative effects on remaining populations over the next 50-80 years, but milder winters, longer growing seasons, and wetter falls might positively affect survival and dispersal. Collectively, however, seasonal shifts in temperature, precipitation, and stream flow patterns could reduce habitat suitability and connectivity for frogs and possibly other aquatic species inhabiting streams in this arid region.
Predictability Analysis of PM10 Concentrations in Budapest
NASA Astrophysics Data System (ADS)
Ferenczi, Zita
2013-04-01
Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.
Stress testing hydrologic models using bottom-up climate change assessment
NASA Astrophysics Data System (ADS)
Stephens, C.; Johnson, F.; Marshall, L. A.
2017-12-01
Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.
A changing climate: impacts on human exposures to O3 using an integrated modeling methodology
Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposu...
CIRUN: Climate Information Responding to User Needs
NASA Astrophysics Data System (ADS)
Busalacchi, A. J.
2009-12-01
The Earth System will experience real climate change over the next 50 years, exceeding the scope of natural climate variability. A paramount question facing society is how to adapt to this certainty of climate variability and change. In response, OSTP and NOAA are considering how comprehensive climate services would best inform decisions about adaptation. Similarly, NASA is considering the optimal configuration of the next generation of Earth, environmental, and climate observations to be deployed over the coming 10-20 years. Moreover, much of the added-value information for specific climate-related decisions will be provided by private, academic and non-governmental organizations. In this context, over the past several years the University of Maryland has established the CIRUN (Climate Information: Responding to User Needs) initiative to identify the nature of national needs for climate information and services from a decision support perspective. To date, CIRUN has brought together decisionmakers in a number of sectors to help understand their perspectives on climate with the goal of improving the usefulness of climate information, observations and prediction products to specific user communities. CIRUN began with a major workshop in October 2007 that convened 430 participants in agriculture, parks and recreation, terrestrial ecosystems, insurance/investment, energy, national security, state/local/municipal, water, human health, commerce and manufacturing, transportation, and coastal/marine sectors. Plenary speakers such as Norman Augustine, R. James Woolsey, James Mahoney, and former Senator Joseph Tydings, breakout panel sessions, and participants provided input based on the following: - How would you characterize the exposure or vulnerability to climate variability or change impacting your organization? - Does climate variability and/or change currently factor into your organization's objectives or operations? - Are any of your existing plans being affected by climate or projections of climate change? - Is your organization developing a plan for adapting to climate change? - What are your needs for climate observations, predictions, and services? Please cite one or more specific examples when possible. - Do you currently have access to the climate information your organization needs? - What next steps are needed to assure effective use of climate services in your decision making? As a result, a dialogue with various user communities and a subsequent series of more sector specific workshops has been established regarding how significantly enhanced climate observations, data management, modeling, and predictions can provide valuable decision support for business and policy decisions. In particular, CIRUN has helped - To identify how users, stakeholders, and decision makers are influenced by climate on time scales from seasons to decades - To identify the needs and requirements of users, stakeholders, and decision makers for climate information, observations, predictions, and services from global to local scales - To identify what adaptation measures are being considered in the private and public sectors, and how this might result in new classes of information for decision support - To recommend principal elements of the path forward toward more effective use of climate services in decision making.
Who Should Pick the Winners of Climate Change?
Webster, Michael S; Colton, Madhavi A; Darling, Emily S; Armstrong, Jonathan; Pinsky, Malin L; Knowlton, Nancy; Schindler, Daniel E
2017-03-01
Many conservation strategies identify a narrow subset of genotypes, species, or geographic locations that are predicted to be favored under different scenarios of future climate change. However, a focus on predicted winners, which might not prove to be correct, risks undervaluing the balance of biological diversity from which climate-change winners could otherwise emerge. Drawing on ecology, evolutionary biology, and portfolio theory, we propose a conservation approach designed to promote adaptation that is less dependent on uncertain predictions about the identity of winners and losers. By designing actions to facilitate numerous opportunities for selection across biological and environmental conditions, we can allow nature to pick the winners and increase the probability that ecosystems continue to provide services to humans and other species. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Yoneda, Minoru; Abe-Ouchi, Ayako; Kawahata, Hodaka; Yokoyama, Yusuke; Oguchi, Takashi
2014-05-01
The impact of climate change on human evolution is important and debating topic for many years. Since 2010, we have involved in a general joint project entitled "Replacement of Neanderthal by Modern Humans: Testing Evolutional Models of Learning", which based on a theoretical prediction that the cognitive ability related to individual and social learning divide fates of ancient humans in very unstable Late Pleistocene climate. This model predicts that the human populations which experienced a series of environmental changes would have higher rate of individual learners, while detailed reconstructions of global climate change have reported fluent and drastic change based on ice cores and stalagmites. However, we want to understand the difference between anatomically modern human which survived and the other archaic extinct humans including European Neanderthals and Asian Denisovans. For this purpose the global synchronized change is not useful for understanding but the regional difference in the amplitude and impact of climate change is the information required. Hence, we invited a geophysicist busing Global Circulation Model to reconstruct the climatic distribution and temporal change in a continental scale. At the same time, some geochemists and geographers construct a database of local climate changes recorded in different proxies. At last, archaeologists and anthropologists tried to interpret the emergence and disappearance of human species in Europe and Asia on the reconstructed past climate maps using some tools, such as Eco-cultural niche model. Our project will show the regional difference in climate change and related archaeological events and its impact on the evolution of learning ability of modern humans.
DOT National Transportation Integrated Search
2007-10-01
This report presents a review of economic studies for the United States and relates them to predicted impacts of climate change. The summary findings are organized by region and identify the key sectors likely affected by climate change, the main imp...
Genecological approaches to predicting the effects of climate change on plant populations
Francis F. Kilkenny
2015-01-01
Climate change threatens native plant populations and plant communities globally. It is critical that land managers have a clear understanding of climate change impacts on plant species and populations so that restoration efforts can be adjusted accordingly. This paper reviews the develop.ment and use of seed transfer guidelines for restoration in the face of global...
ERIC Educational Resources Information Center
Ates, Deniz; Teksöz, Gaye; Ertepinar, Hamide
2017-01-01
Recent studies indicate that limited understanding about causes and its potential impacts of climate change and fault beliefs by people across different countries of the world including Turkey is a real challenge. Acceptance of climate change as a real threat, believing its existence, and knowing causes and consequences are very significant for…
Climate change and public health policy: translating the science.
Braks, Marieta; van Ginkel, Rijk; Wint, William; Sedda, Luigi; Sprong, Hein
2013-12-19
Public health authorities are required to prepare for future threats and need predictions of the likely impact of climate change on public health risks. They may get overwhelmed by the volume of heterogeneous information in scientific articles and risk relying purely on the public opinion articles which focus mainly on global warming trends, and leave out many other relevant factors. In the current paper, we discuss various scientific approaches investigating climate change and its possible impact on public health and discuss their different roles and functions in unraveling the complexity of the subject. It is not our objective to review the available literature or to make predictions for certain diseases or countries, but rather to evaluate the applicability of scientific research articles on climate change to evidence-based public health decisions. In the context of mosquito borne diseases, we identify common pitfalls to watch out for when assessing scientific research on the impact of climate change on human health. We aim to provide guidance through the plethora of scientific papers and views on the impact of climate change on human health to those new to the subject, as well as to remind public health experts of its multifactorial and multidisciplinary character.
Climate Change and Public Health Policy: Translating the Science
Braks, Marieta; van Ginkel, Rijk; Wint, William; Sedda, Luigi; Sprong, Hein
2013-01-01
Public health authorities are required to prepare for future threats and need predictions of the likely impact of climate change on public health risks. They may get overwhelmed by the volume of heterogeneous information in scientific articles and risk relying purely on the public opinion articles which focus mainly on global warming trends, and leave out many other relevant factors. In the current paper, we discuss various scientific approaches investigating climate change and its possible impact on public health and discuss their different roles and functions in unraveling the complexity of the subject. It is not our objective to review the available literature or to make predictions for certain diseases or countries, but rather to evaluate the applicability of scientific research articles on climate change to evidence-based public health decisions. In the context of mosquito borne diseases, we identify common pitfalls to watch out for when assessing scientific research on the impact of climate change on human health. We aim to provide guidance through the plethora of scientific papers and views on the impact of climate change on human health to those new to the subject, as well as to remind public health experts of its multifactorial and multidisciplinary character. PMID:24452252
Hellberg, Rosalee S; Chu, Eric
2016-08-01
According to the Intergovernmental Panel on Climate Change (IPCC), warming of the climate system is unequivocal. Over the coming century, warming trends such as increased duration and frequency of heat waves and hot extremes are expected in some areas, as well as increased intensity of some storm systems. Climate-induced trends will impact the persistence and dispersal of foodborne pathogens in myriad ways, especially for environmentally ubiquitous and/or zoonotic microorganisms. Animal hosts of foodborne pathogens are also expected to be impacted by climate change through the introduction of increased physiological stress and, in some cases, altered geographic ranges and seasonality. This review article examines the effects of climatic factors, such as temperature, rainfall, drought and wind, on the environmental dispersal and persistence of bacterial foodborne pathogens, namely, Bacillus cereus, Brucella, Campylobacter, Clostridium, Escherichia coli, Listeria monocytogenes, Salmonella, Staphylococcus aureus, Vibrio and Yersinia enterocolitica. These relationships are then used to predict how future climatic changes will impact the activity of these microorganisms in the outdoor environment and associated food safety issues. The development of predictive models that quantify these complex relationships will also be discussed, as well as the potential impacts of climate change on transmission of foodborne disease from animal hosts.
A blueprint for using climate change predictions in an eco-hydrological study
NASA Astrophysics Data System (ADS)
Caporali, E.; Fatichi, S.; Ivanov, V. Y.
2009-12-01
There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for uncertainties in projections of future climate is discussed and a methodology for propagating these uncertainties into the probability density functions of changes in eco-hydrological variables is presented.
Gole, Tadesse Woldemariam; Baena, Susana
2012-01-01
Precise modelling of the influence of climate change on Arabica coffee is limited; there are no data available for indigenous populations of this species. In this study we model the present and future predicted distribution of indigenous Arabica, and identify priorities in order to facilitate appropriate decision making for conservation, monitoring and future research. Using distribution data we perform bioclimatic modelling and examine future distribution with the HadCM3 climate model for three emission scenarios (A1B, A2A, B2A) over three time intervals (2020, 2050, 2080). The models show a profoundly negative influence on indigenous Arabica. In a locality analysis the most favourable outcome is a c. 65% reduction in the number of pre-existing bioclimatically suitable localities, and at worst an almost 100% reduction, by 2080. In an area analysis the most favourable outcome is a 38% reduction in suitable bioclimatic space, and the least favourable a c. 90% reduction, by 2080. Based on known occurrences and ecological tolerances of Arabica, bioclimatic unsuitability would place populations in peril, leading to severe stress and a high risk of extinction. This study establishes a fundamental baseline for assessing the consequences of climate change on wild populations of Arabica coffee. Specifically, it: (1) identifies and categorizes localities and areas that are predicted to be under threat from climate change now and in the short- to medium-term (2020–2050), representing assessment priorities for ex situ conservation; (2) identifies ‘core localities’ that could have the potential to withstand climate change until at least 2080, and therefore serve as long-term in situ storehouses for coffee genetic resources; (3) provides the location and characterization of target locations (populations) for on-the-ground monitoring of climate change influence. Arabica coffee is confimed as a climate sensitivite species, supporting data and inference that existing plantations will be neagtively impacted by climate change. PMID:23144840
Seasonal and decadal information towards climate services: EUPORIAS
NASA Astrophysics Data System (ADS)
Buontempo, Carlo; Hewitt, Chris
2013-04-01
Societies have always faced challenges and opportunities arising from variations in climate, and have often flourished or collapsed depending on their ability to adapt to such changes. Recent advances in our understanding and ability to forecast climate variability and climate change have meant that skilful predictions are beginning to be routinely made on seasonal to decadal (s2d) timescales. Such forecasts have the potential to be of great value to a wide range of decision-making, where outcomes are strongly influenced by variations in the climate. The European Commission have recently commissioned a major four year long project (EUPORIAS) to develop prototype end-to-end climate impact prediction services operating on a seasonal to decadal timescale, and assess their value in informing decision-making. EUPORIAS commenced on 1 November 2012, coordinated by the UK Met Office leading a consortium of 24 organisations representing world-class European climate research and climate service centres, expertise in impacts assessments and seasonal predictions, two United Nations agencies, specialists in new media, and commercial companies in climate-vulnerable sectors such as energy, water and tourism. The paper describes the setup of the project, its main outcome and some of the very preliminary results.
Biophysical and Economic Uncertainty in the Analysis of Poverty Impacts of Climate Change
NASA Astrophysics Data System (ADS)
Hertel, T. W.; Lobell, D. B.; Verma, M.
2011-12-01
This paper seeks to understand the main sources of uncertainty in assessing the impacts of climate change on agricultural output, international trade, and poverty. We incorporate biophysical uncertainty by sampling from a distribution of global climate model predictions for temperature and precipitation for 2050. The implications of these realizations for crop yields around the globe are estimated using the recently published statistical crop yield functions provided by Lobell, Schlenker and Costa-Roberts (2011). By comparing these yields to those predicted under current climate, we obtain the likely change in crop yields owing to climate change. The economic uncertainty in our analysis relates to the response of the global economic system to these biophysical shocks. We use a modified version of the GTAP model to elicit the impact of the biophysical shocks on global patterns of production, consumption, trade and poverty. Uncertainty in these responses is reflected in the econometrically estimated parameters governing the responsiveness of international trade, consumption, production (and hence the intensive margin of supply response), and factor supplies (which govern the extensive margin of supply response). We sample from the distributions of these parameters as specified by Hertel et al. (2007) and Keeney and Hertel (2009). We find that, even though it is difficult to predict where in the world agricultural crops will be favorably affected by climate change, the responses of economic variables, including output and exports can be far more robust (Table 1). This is due to the fact that supply and demand decisions depend on relative prices, and relative prices depend on productivity changes relative to other crops in a given region, or relative to similar crops in other parts of the world. We also find that uncertainty in poverty impacts of climate change appears to be almost entirely driven by biophysical uncertainty.
Shrestha, Uttam Babu; Bawa, Kamaljit S.
2014-01-01
Climate change has already impacted ecosystems and species and substantial impacts of climate change in the future are expected. Species distribution modeling is widely used to map the current potential distribution of species as well as to model the impact of future climate change on distribution of species. Mapping current distribution is useful for conservation planning and understanding the change in distribution impacted by climate change is important for mitigation of future biodiversity losses. However, the current distribution of Chinese caterpillar fungus, a flagship species of the Himalaya with very high economic value, is unknown. Nor do we know the potential changes in suitable habitat of Chinese caterpillar fungus caused by future climate change. We used MaxEnt modeling to predict current distribution and changes in the future distributions of Chinese caterpillar fungus in three future climate change trajectories based on representative concentration pathways (RCPs: RCP 2.6, RCP 4.5, and RCP 6.0) in three different time periods (2030, 2050, and 2070) using species occurrence points, bioclimatic variables, and altitude. About 6.02% (8,989 km2) area of the Nepal Himalaya is suitable for Chinese caterpillar fungus habitat. Our model showed that across all future climate change trajectories over three different time periods, the area of predicted suitable habitat of Chinese caterpillar fungus would expand, with 0.11–4.87% expansion over current suitable habitat. Depending upon the representative concentration pathways, we observed both increase and decrease in average elevation of the suitable habitat range of the species. PMID:25180515
Shrestha, Uttam Babu; Bawa, Kamaljit S
2014-01-01
Climate change has already impacted ecosystems and species and substantial impacts of climate change in the future are expected. Species distribution modeling is widely used to map the current potential distribution of species as well as to model the impact of future climate change on distribution of species. Mapping current distribution is useful for conservation planning and understanding the change in distribution impacted by climate change is important for mitigation of future biodiversity losses. However, the current distribution of Chinese caterpillar fungus, a flagship species of the Himalaya with very high economic value, is unknown. Nor do we know the potential changes in suitable habitat of Chinese caterpillar fungus caused by future climate change. We used MaxEnt modeling to predict current distribution and changes in the future distributions of Chinese caterpillar fungus in three future climate change trajectories based on representative concentration pathways (RCPs: RCP 2.6, RCP 4.5, and RCP 6.0) in three different time periods (2030, 2050, and 2070) using species occurrence points, bioclimatic variables, and altitude. About 6.02% (8,989 km2) area of the Nepal Himalaya is suitable for Chinese caterpillar fungus habitat. Our model showed that across all future climate change trajectories over three different time periods, the area of predicted suitable habitat of Chinese caterpillar fungus would expand, with 0.11-4.87% expansion over current suitable habitat. Depending upon the representative concentration pathways, we observed both increase and decrease in average elevation of the suitable habitat range of the species.
The Nested Regional Climate Model: An Approach Toward Prediction Across Scales
NASA Astrophysics Data System (ADS)
Hurrell, J. W.; Holland, G. J.; Large, W. G.
2008-12-01
The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is producing unique data sets of climate change scenarios of immense interest. In addition, all simulations are archived in a form that will be readily accessible to other researchers, thus enabling a wider group to investigate these important issues.
Importance of Anthropogenic Aerosols for Climate Prediction: a Study on East Asian Sulfate Aerosols
NASA Astrophysics Data System (ADS)
Bartlett, R. E.; Bollasina, M. A.
2017-12-01
Climate prediction is vital to ensure that we are able to adapt to our changing climate. Understandably, the main focus for such prediction is greenhouse gas forcing, as this will be the main anthropogenic driver of long-term global climate change; however, other forcings could still be important. Atmospheric aerosols represent one such forcing, especially in regions with high present-day aerosol loading such as Asia; yet, uncertainty in their future emissions are under-sampled by commonly used climate forcing projections, such as the Representative Concentration Pathways (RCPs). Globally, anthropogenic aerosols exert a net cooling, but their effects show large variation at regional scales. Studies have shown that aerosols impact locally upon temperature, precipitation and hydroclimate, and also upon larger scale atmospheric circulation (for example, the Asian monsoon) with implications for climate remote from aerosol sources. We investigate how future climate could evolve differently given the same greenhouse gas forcing pathway but differing aerosol emissions. Specifically, we use climate modelling experiments (using HadGEM2-ES) of two scenarios based upon RCP2.6 greenhouse gas forcing but with large differences in sulfur dioxide emissions over East Asia. Results show that increased sulfate aerosols (associated with increased sulfur dioxide) lead to large regional cooling through aerosol-radiation and aerosol-cloud interactions. Focussing on dynamical mechanisms, we explore the consequences of this cooling for the Asian summer and winter monsoons. In addition to local temperature and precipitation changes, we find significant changes to large scale atmospheric circulation. Wave-like responses to upper-level atmospheric changes propagate across the northern hemisphere with far-reaching effects on surface climate, for example, cooling over Europe. Within the tropics, we find alterations to zonal circulation (notably, shifts in the Pacific Walker cell) and monsoon systems outside of Asia. These results indicate that anthropogenic aerosols have significant climate impacts against a background of greenhouse gas-induced climate change, and thus represent a key source of uncertainty in near-term climate projection that should be seriously considered in future climate assessments.
Establishing a Real-Money Prediction Market for Climate on Decadal Horizons
NASA Astrophysics Data System (ADS)
Roulston, M. S.; Hand, D. J.; Harding, D. W.
2016-12-01
A plan to establish a not-for-profit prediction market that will allow participants to bet on the value of selected climate variables decades into the future will be presented. It is hoped that this market will provide an objective measure of the consensus view on climate change, including information concerning the uncertainty of climate projections. The proposed design of the market and the definition of the climate variables underlying the contracts will be discussed, as well as relevant regulatory and legal issues.
NASA Technical Reports Server (NTRS)
Evans, Diane
2012-01-01
Objective 2.1.1: Improve understanding of and improve the predictive capability for changes in the ozone layer, climate forcing, and air quality associated with changes in atmospheric composition. Objective 2.1.2: Enable improved predictive capability for weather and extreme weather events. Objective 2.1.3: Quantify, understand, and predict changes in Earth s ecosystems and biogeochemical cycles, including the global carbon cycle, land cover, and biodiversity. Objective 2.1.4: Quantify the key reservoirs and fluxes in the global water cycle and assess water cycle change and water quality. Objective 2.1.5: Improve understanding of the roles of the ocean, atmosphere, land and ice in the climate system and improve predictive capability for its future evolution. Objective 2.1.6: Characterize the dynamics of Earth s surface and interior and form the scientific basis for the assessment and mitigation of natural hazards and response to rare and extreme events. Objective 2.1.7: Enable the broad use of Earth system science observations and results in decision-making activities for societal benefits.
Towards a Unified Framework in Hydroclimate Extremes Prediction in Changing Climate
NASA Astrophysics Data System (ADS)
Moradkhani, H.; Yan, H.; Zarekarizi, M.; Bracken, C.
2016-12-01
Spatio-temporal analysis and prediction of hydroclimate extremes are of paramount importance in disaster mitigation and emergency management. The IPCC special report on managing the risks of extreme events and disasters emphasizes that the global warming would change the frequency, severity, and spatial pattern of extremes. In addition to climate change, land use and land cover changes also influence the extreme characteristics at regional scale. Therefore, natural variability and anthropogenic changes to the hydroclimate system result in nonstationarity in hydroclimate variables. In this presentation recent advancements in developing and using Bayesian approaches to account for non-stationarity in hydroclimate extremes are discussed. Also, implications of these approaches in flood frequency analysis, treatment of spatial dependence, the impact of large-scale climate variability, the selection of cause-effect covariates, with quantification of model errors in extreme prediction is explained. Within this framework, the applicability and usefulness of the ensemble data assimilation for extreme flood predictions is also introduced. Finally, a practical and easy to use approach for better communication with decision-makers and emergency managers is presented.
Predictions of avian Plasmodium expansion under climate change.
Loiseau, Claire; Harrigan, Ryan J; Bichet, Coraline; Julliard, Romain; Garnier, Stéphane; Lendvai, Adám Z; Chastel, Olivier; Sorci, Gabriele
2013-01-01
Vector-borne diseases are particularly responsive to changing environmental conditions. Diurnal temperature variation has been identified as a particularly important factor for the development of malaria parasites within vectors. Here, we conducted a survey across France, screening populations of the house sparrow (Passer domesticus) for malaria (Plasmodium relictum). We investigated whether variation in remotely-sensed environmental variables accounted for the spatial variation observed in prevalence and parasitemia. While prevalence was highly correlated to diurnal temperature range and other measures of temperature variation, environmental conditions could not predict spatial variation in parasitemia. Based on our empirical data, we mapped malaria distribution under climate change scenarios and predicted that Plasmodium occurrence will spread to regions in northern France, and that prevalence levels are likely to increase in locations where transmission already occurs. Our findings, based on remote sensing tools coupled with empirical data suggest that climatic change will significantly alter transmission of malaria parasites.
Lemoine, Nathan P
2015-01-01
Climate change can profoundly alter species' distributions due to changes in temperature, precipitation, or seasonality. Migratory monarch butterflies (Danaus plexippus) may be particularly susceptible to climate-driven changes in host plant abundance or reduced overwintering habitat. For example, climate change may significantly reduce the availability of overwintering habitat by restricting the amount of area with suitable microclimate conditions. However, potential effects of climate change on monarch northward migrations remain largely unknown, particularly with respect to their milkweed (Asclepias spp.) host plants. Given that monarchs largely depend on the genus Asclepias as larval host plants, the effects of climate change on monarch northward migrations will most likely be mediated by climate change effects on Asclepias. Here, I used MaxEnt species distribution modeling to assess potential changes in Asclepias and monarch distributions under moderate and severe climate change scenarios. First, Asclepias distributions were projected to extend northward throughout much of Canada despite considerable variability in the environmental drivers of each individual species. Second, Asclepias distributions were an important predictor of current monarch distributions, indicating that monarchs may be constrained as much by the availability of Asclepias host plants as environmental variables per se. Accordingly, modeling future distributions of monarchs, and indeed any tightly coupled plant-insect system, should incorporate the effects of climate change on host plant distributions. Finally, MaxEnt predictions of Asclepias and monarch distributions were remarkably consistent among general circulation models. Nearly all models predicted that the current monarch summer breeding range will become slightly less suitable for Asclepias and monarchs in the future. Asclepias, and consequently monarchs, should therefore undergo expanded northern range limits in summer months while encountering reduced habitat suitability throughout the northern migration.
Lemoine, Nathan P.
2015-01-01
Climate change can profoundly alter species’ distributions due to changes in temperature, precipitation, or seasonality. Migratory monarch butterflies (Danaus plexippus) may be particularly susceptible to climate-driven changes in host plant abundance or reduced overwintering habitat. For example, climate change may significantly reduce the availability of overwintering habitat by restricting the amount of area with suitable microclimate conditions. However, potential effects of climate change on monarch northward migrations remain largely unknown, particularly with respect to their milkweed (Asclepias spp.) host plants. Given that monarchs largely depend on the genus Asclepias as larval host plants, the effects of climate change on monarch northward migrations will most likely be mediated by climate change effects on Asclepias. Here, I used MaxEnt species distribution modeling to assess potential changes in Asclepias and monarch distributions under moderate and severe climate change scenarios. First, Asclepias distributions were projected to extend northward throughout much of Canada despite considerable variability in the environmental drivers of each individual species. Second, Asclepias distributions were an important predictor of current monarch distributions, indicating that monarchs may be constrained as much by the availability of Asclepias host plants as environmental variables per se. Accordingly, modeling future distributions of monarchs, and indeed any tightly coupled plant-insect system, should incorporate the effects of climate change on host plant distributions. Finally, MaxEnt predictions of Asclepias and monarch distributions were remarkably consistent among general circulation models. Nearly all models predicted that the current monarch summer breeding range will become slightly less suitable for Asclepias and monarchs in the future. Asclepias, and consequently monarchs, should therefore undergo expanded northern range limits in summer months while encountering reduced habitat suitability throughout the northern migration. PMID:25705876
Climate change, soil health, and ecosystem goods and services
USDA-ARS?s Scientific Manuscript database
Worldwide, climate change is predicted to alter precipitation regimes, annual temperatures, and occurrence of severe weather events. These changes have important implications for soil health-- defined as the capacity of a soil to contribute to ecosystem function and sustain producers and consumers--...
Arctic shrubification mediates the impacts of warming climate on changes to tundra vegetation
NASA Astrophysics Data System (ADS)
Mod, Heidi K.; Luoto, Miska
2016-12-01
Climate change has been observed to expand distributions of woody plants in many areas of arctic and alpine environments—a phenomenon called shrubification. New spatial arrangements of shrubs cause further changes in vegetation via changing dynamics of biotic interactions. However, the mediating influence of shrubification is rarely acknowledged in predictions of tundra vegetation change. Here, we examine possible warming-induced landscape-level vegetation changes in a high-latitude environment using species distribution modelling (SDM), specifically concentrating on the impacts of shrubification on ambient vegetation. First, we produced estimates of current shrub and tree cover and forecasts of their expansion under climate change scenarios to be incorporated to SDMs of 116 vascular plants. Second, the predictions of vegetation change based on the models including only abiotic predictors and the models including abiotic, shrub and tree predictors were compared in a representative test area. Based on our model predictions, abundance of woody plants will expand, thus decreasing predicted species richness, amplifying species turnover and increasing the local extinction risk for ambient vegetation. However, the spatial variation demonstrated in our predictions highlights that tundra vegetation can be expected to show a wide variety of different responses to the combined effects of warming and shrubification, depending on the original plant species pool and environmental conditions. We conclude that realistic forecasts of the future require acknowledging the role of shrubification in warming-induced tundra vegetation change.
Gong, Minghao; Guan, Tianpei; Hou, Meng; Liu, Gang; Zhou, Tianyuan
2017-01-01
One way that climate change will impact animal distributions is by altering habitat suitability and habitat fragmentation. Understanding the impacts of climate change on currently threatened species is of immediate importance because complex conservation planning will be required. Here, we mapped changes to the distribution, suitability, and fragmentation of giant panda habitat under climate change and quantified the direction and elevation of habitat shift and fragmentation patterns. These data were used to develop a series of new conservation strategies for the giant panda. Qinling Mountains, Shaanxi, China. Data from the most recent giant panda census, habitat factors, anthropogenic disturbance, climate variables, and climate predictions for the year 2050 (averaged across four general circulation models) were used to project giant panda habitat in Maxent. Differences in habitat patches were compared between now and 2050. While climate change will cause a 9.1% increase in suitable habitat and 9% reduction in subsuitable habitat by 2050, no significant net variation in the proportion of suitable and subsuitable habitat was found. However, a distinct climate change-induced habitat shift of 11 km eastward by 2050 is predicted firstly. Climate change will reduce the fragmentation of suitable habitat at high elevations and exacerbate the fragmentation of subsuitable habitat below 1,900 m above sea level. Reduced fragmentation at higher elevations and worsening fragmentation at lower elevations have the potential to cause overcrowding of giant pandas at higher altitudes, further exacerbating habitat shortage in the central Qinling Mountains. The habitat shift to the east due to climate change may provide new areas for giant pandas but poses severe challenges for future conservation.
NASA Astrophysics Data System (ADS)
Ironside, K. E.; Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Shaw, J. D.; Cobb, N. S.
2008-12-01
Ponderosa pine (Pinus ponderosa var. scopulorum) is the dominant conifer in higher elevation regions of the southwestern United States. Because this species is so prominent, southwestern montane ecosystems will be significantly altered if this species is strongly affected by future climate changes. These changes could be highly challenging for land management agencies. In order to model the consequences of future climates, 20th Century recruitment events and mortality for ponderosa pine were characterized using measures of seasonal water balance (precipitation - potential evapotranspiration). These relationships, assuming they will remain unchanged, were then used to predict 21st Century changes in ponderosa pine occurrence in the southwest. Twenty-one AR4 IPCC General Circulation Model (GCM) A1B simulation results were ranked on their ability to simulate the later 20th Century (1950-2000 AD) precipitation seasonality, spatial patterns, and quantity in the western United States. Among the top ranked GCMs, five were selected for downscaling to a 4 km grid that represented a range in predictions in terms of changes in water balance. Predicted decadal changes in southwestern ponderosa pine for the 21st Century for these five climate change scenarios were calculated using a multiple quadratic logistic regression model. Similar models of other western tree species (Pinus edulis, Yucca brevifolia) predicted severe contractions, especially in the southern half of their ranges. However, the results for Ponderosa pine suggested future expansions throughout its range to both higher and lower elevations, as well as very significant expansions northward.
The ice-core record - Climate sensitivity and future greenhouse warming
NASA Technical Reports Server (NTRS)
Lorius, C.; Raynaud, D.; Jouzel, J.; Hansen, J.; Le Treut, H.
1990-01-01
The prediction of future greenhouse-gas-warming depends critically on the sensitivity of earth's climate to increasing atmospheric concentrations of these gases. Data from cores drilled in polar ice sheets show a remarkable correlation between past glacial-interglacial temperature changes and the inferred atmospheric concentration of gases such as carbon dioxide and methane. These and other palaeoclimate data are used to assess the role of greenhouse gases in explaining past global climate change, and the validity of models predicting the effect of increasing concentrations of such gases in the atmosphere.
Forecasting Impacts of Climate Change on Indicators of British Columbia's Biodiversity
NASA Astrophysics Data System (ADS)
Holmes, Keith Richard
Understanding the relationships between biodiversity and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing indirect indicators of biodiversity derived from remotely sensed imagery, we present an approach to forecast shifts in the spatial distribution of biodiversity. Indirect indicators, such as remotely sensed plant productivity metrics, representing landscape seasonality, minimum growth, and total greenness have been linked to species richness over broad spatial scales, providing unique capacity for biodiversity modeling. Our goal is to map future spatial distributions of plant productivity metrics based on expected climate change and to quantify anticipated change to park habitat in British Columbia. Using an archival dataset sourced from the Advanced Very High Resolution Radiometer (AVHRR) satellite from the years 1987 to 2007 at 1km spatial resolution, corresponding historical climate data, and regression tree modeling, we developed regional models of the relationships between climate and annual productivity growth. Historical interconnections between climate and annual productivity were coupled with three climate change scenarios modeled by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity components to the year 2065. Results indicate we can expect a warmer and wetter environment, which may lead to increased productivity in the north and higher elevations. Overall, seasonality is expected to decrease and greenness productivity metrics are expected to increase. The Coastal Mountains and high elevation edge habitats across British Columbia are forecasted to experience the greatest amount of change. In the future, protected areas may have potential higher greenness and lower seasonality as represented by indirect biodiversity indicators. The predictive model highlights potential gaps in protection along the central interior and Rocky Mountains. Protected areas are expected to experience the greatest change with indirect indicators located along mountainous elevations of British Columbia. Our indirect indicator approach to predict change in biodiversity provides resource managers with information to mitigate and adapt to future habitat dynamics. Spatially specific recommendations from our dataset provide information necessary for management. For instance, knowing there is a projected depletion of habitat representation in the East Rocky Mountains, sensitive species in the threatened Mountain Hemlock ecozone, or preservation of rare habitats in the decreasing greenness of the southern interior region is essential information for managers tasked with long term biodiversity conservation. Forecasting productivity levels, linked to the distribution of species richness, presents a novel approach for understanding the future implications of climate change on broad scale biodiversity.
NASA Astrophysics Data System (ADS)
Marhaento, H.; Booij, M. J.; Hoekstra, A. Y.
2017-12-01
Future hydrological processes in the Samin catchment (278 km2) in Java, Indonesia have been simulated using the Soil and Water Assessment Tool (SWAT) model using inputs from predicted land use distributions in the period 2030 - 2050, bias corrected Regional Climate Model (RCM) output and output of six Global Climate Models (GCMs) to include climate model uncertainty. Two land use change scenarios namely a business-as-usual (BAU) scenario, where no measures are taken to control land use change, and a controlled (CON) scenario, where the future land use follows the land use planning, were used in the simulations together with two climate change scenarios namely Representative Concentration Pathway (RCP) 4.5 and 8.5. It was predicted that in 2050 settlement and agriculture area of the study catchment will increase by 33.9% and 3.5%, respectively under the BAU scenario, whereas agriculture area and evergreen forest will increase by 15.2% and 10.2%, respectively under the CON scenario. In comparison to the baseline conditions (1983 - 2005), the predicted mean annual maximum and minimum temperature in 2030 - 2050 will increase by an average of +10C, while changes in the mean annual rainfall range from -20% to +19% under RCP 4.5 and from -25% to +15% under RCP 8.5. The results show that land use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual stream flow and surface runoff. It was observed that combination of the RCP 4.5 climate scenario and BAU land use scenario resulted in an increase of the mean annual stream flow from -7% to +64% and surface runoff from +21% to +102%, which is 40% and 60% more than when land use change is acting alone. Furthermore, under the CON scenario the annual stream flow and surface runoff could be potentially reduced by up to 10% and 30%, respectively indicating the effectiveness of applied land use planning. The findings of this study will be useful for the water resource managers to mitigate future risks associated with land use and climate changes in the study catchment. Keywords: land use change, climate change, hydrological impact assessment, Samin catchment
Challenges in predicting climate change impacts on pome fruit phenology
NASA Astrophysics Data System (ADS)
Darbyshire, Rebecca; Webb, Leanne; Goodwin, Ian; Barlow, E. W. R.
2014-08-01
Climate projection data were applied to two commonly used pome fruit flowering models to investigate potential differences in predicted full bloom timing. The two methods, fixed thermal time and sequential chill-growth, produced different results for seven apple and pear varieties at two Australian locations. The fixed thermal time model predicted incremental advancement of full bloom, while results were mixed from the sequential chill-growth model. To further investigate how the sequential chill-growth model reacts under climate perturbed conditions, four simulations were created to represent a wider range of species physiological requirements. These were applied to five Australian locations covering varied climates. Lengthening of the chill period and contraction of the growth period was common to most results. The relative dominance of the chill or growth component tended to predict whether full bloom advanced, remained similar or was delayed with climate warming. The simplistic structure of the fixed thermal time model and the exclusion of winter chill conditions in this method indicate it is unlikely to be suitable for projection analyses. The sequential chill-growth model includes greater complexity; however, reservations in using this model for impact analyses remain. The results demonstrate that appropriate representation of physiological processes is essential to adequately predict changes to full bloom under climate perturbed conditions with greater model development needed.
Ágreda, Teresa; Águeda, Beatriz; Olano, José M; Vicente-Serrano, Sergio M; Fernández-Toirán, Marina
2015-09-01
Wild fungi play a critical role in forest ecosystems, and its recollection is a relevant economic activity. Understanding fungal response to climate is necessary in order to predict future fungal production in Mediterranean forests under climate change scenarios. We used a 15-year data set to model the relationship between climate and epigeous fungal abundance and productivity, for mycorrhizal and saprotrophic guilds in a Mediterranean pine forest. The obtained models were used to predict fungal productivity for the 2021-2080 period by means of regional climate change models. Simple models based on early spring temperature and summer-autumn rainfall could provide accurate estimates for fungal abundance and productivity. Models including rainfall and climatic water balance showed similar results and explanatory power for the analyzed 15-year period. However, their predictions for the 2021-2080 period diverged. Rainfall-based models predicted a maintenance of fungal yield, whereas water balance-based models predicted a steady decrease of fungal productivity under a global warming scenario. Under Mediterranean conditions fungi responded to weather conditions in two distinct periods: early spring and late summer-autumn, suggesting a bimodal pattern of growth. Saprotrophic and mycorrhizal fungi showed differences in the climatic control. Increased atmospheric evaporative demand due to global warming might lead to a drop in fungal yields during the 21st century. © 2015 John Wiley & Sons Ltd.
Variability in response of lakes to climate change explained by surrounding watersheds
NASA Astrophysics Data System (ADS)
Råman Vinnå, Love; Wüest, Alfred; Bouffard, Damien
2017-04-01
The consequences of climate change for inland waters have been shown to vary extensively not only globally, but also on a sub-regional scale [O'Reilly et al., 2015, GRL]. Local factors affecting heating include morphology [Toffolon et al., 2014, LO], irradiance absorption [Williamson et al., 2015, SR], local weather conditions and onset of stratification [Zhong et al., 2016, LO] as well as ice conditions [Austin and Colman, 2007, GRL]. However, inland waters are often a complex web of rivers, streams, lakes and reservoirs. Thereby, to correctly assess and predict future changes in lakes/reservoirs due to climate change, it is important to consider the changes occurring in the surrounding watersheds and how they affect downstream waters. Here we evaluate the impact of climate change on rivers originating in the Swiss Alps (Aare and Rhône) and downstream located perialpine lakes (Lake Biel and Lake Geneva). We use regional predictions for air temperature increase and the subsequently expected shift in river discharge regime under the A1B emission scenario [Bey et al., 2011, CH2011; Federal Office for the Environment FOEN, 2012, CCHydro]. Focus is on predicting the changes in water temperature, particle content, stratification and deep water renewal rate using the 1D SIMSTRAT [Goudsmit et al., 2002, JGR] and Air2Stream [Toffolon and Piccolroaz, 2015, ERL] models. We show that the effect of tributaries on the reaction for downstream lakes to climate change are inversely proportional to the hydraulic residence time of the systems. We furthermore include known changes in anthropogenic thermal emissions, which in Lake Biel correspond to 2 decades of climate induced warming. Our results are put into context with future water utility plans in Lake Biel.
Sautier, Marion; Piquet, Mathilde; Duru, Michel; Martin-Clouaire, Roger
2017-05-15
Research is expected to produce knowledge, methods and tools to enhance stakeholders' adaptive capacity by helping them to anticipate and cope with the effects of climate change at their own level. Farmers face substantial challenges from climate change, from changes in the average temperatures and the precipitation regime to an increased variability of weather conditions and the frequency of extreme events. Such changes can have dramatic consequences for many types of agricultural production systems such as grassland-based livestock systems for which climate change influences the seasonality and productivity of fodder production. We present a participatory design method called FARMORE (FARM-Oriented REdesign) that allows farmers to design and evaluate adaptations of livestock systems to future climatic conditions. It explicitly considers three climate features in the design and evaluation processes: climate change, climate variability and the limited predictability of weather. FARMORE consists of a sequence of three workshops for which a pre-existing game-like platform was adapted. Various year-round forage production and animal feeding requirements must be assembled by participants with a computerized support system. In workshop 1, farmers aim to produce a configuration that satisfies an average future weather scenario. They refine or revise the previous configuration by considering a sample of the between-year variability of weather in workshop 2. In workshop 3, they explicitly take the limited predictability of weather into account. We present the practical aspects of the method based on four case studies involving twelve farmers from Aveyron (France), and illustrate it through an in-depth description of one of these case studies with three dairy farmers. The case studies shows and discusses how workshop sequencing (1) supports a design process that progressively accommodates complexity of real management contexts by enlarging considerations of climate change to climate variability and low weather predictability, and (2) increases the credibility and salience of the design method. Further enhancements of the method are outlined, especially the selection of pertinent weather scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.
Julia A. Jones; Irena F. Creed; Kendra L. Hatcher; Robert J. Warren; Mary Beth Adams; Melinda H. Benson; Emery Boose; Warren A. Brown; John L. Campbell; Alan Covich; David W. Clow; Clifford N. Dahm; Kelly Elder; Chelcy R. Ford; Nancy B. Grimm; Donald L Henshaw; Kelli L. Larson; Evan S. Miles; Kathleen M. Miles; Stephen D. Sebestyen; Adam T. Spargo; Asa B. Stone; James M. Vose; Mark W. Williams
2012-01-01
Analyses of long-term records at 35 headwater basins in the United States and Canada indicate that climate change effects on streamflow are not as clear as might be expected, perhaps because of ecosystem processes and human influences. Evapotranspiration was higher than was predicted by temperature in water-surplus ecosystems and lower than was predicted in water-...
Modeling behavioral thermoregulation in a climate change sentinel.
Moyer-Horner, Lucas; Mathewson, Paul D; Jones, Gavin M; Kearney, Michael R; Porter, Warren P
2015-12-01
When possible, many species will shift in elevation or latitude in response to rising temperatures. However, before such shifts occur, individuals will first tolerate environmental change and then modify their behavior to maintain heat balance. Behavioral thermoregulation allows animals a range of climatic tolerances and makes predicting geographic responses under future warming scenarios challenging. Because behavioral modification may reduce an individual's fecundity by, for example, limiting foraging time and thus caloric intake, we must consider the range of behavioral options available for thermoregulation to accurately predict climate change impacts on individual species. To date, few studies have identified mechanistic links between an organism's daily activities and the need to thermoregulate. We used a biophysical model, Niche Mapper, to mechanistically model microclimate conditions and thermoregulatory behavior for a temperature-sensitive mammal, the American pika (Ochotona princeps). Niche Mapper accurately simulated microclimate conditions, as well as empirical metabolic chamber data for a range of fur properties, animal sizes, and environmental parameters. Niche Mapper predicted pikas would be behaviorally constrained because of the need to thermoregulate during the hottest times of the day. We also showed that pikas at low elevations could receive energetic benefits by being smaller in size and maintaining summer pelage during longer stretches of the active season under a future warming scenario. We observed pika behavior for 288 h in Glacier National Park, Montana, and thermally characterized their rocky, montane environment. We found that pikas were most active when temperatures were cooler, and at sites characterized by high elevations and north-facing slopes. Pikas became significantly less active across a suite of behaviors in the field when temperatures surpassed 20°C, which supported a metabolic threshold predicted by Niche Mapper. In general, mechanistic predictions and empirical observations were congruent. This research is unique in providing both an empirical and mechanistic description of the effects of temperature on a mammalian sentinel of climate change, the American pika. Our results suggest that previously underinvestigated characteristics, specifically fur properties and body size, may play critical roles in pika populations' response to climate change. We also demonstrate the potential importance of considering behavioral thermoregulation and microclimate variability when predicting animal responses to climate change.
Assessing the sensitivity of avian species abundance to land cover and climate
LeBrun, Jaymi J.; Thogmartin, Wayne E.; Thompson, Frank R.; Dijak, William D.; Millspaugh, Joshua J.
2016-01-01
Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and climate on the abundance of five bird species in the Central United States that have habitat requirements ranging from grassland and shrubland to forest. We substituted space for time to examine potential impacts of a changing climate by assessing climate and land cover relationships over a broad latitudinal gradient. We found positive and negative relationships of climate and land cover factors with avian abundances. Habitat variables drove patterns of abundance in migratory and resident species, although climate was also influential in predicting abundance for some species occupying more open habitat (i.e., prairie warbler, blue-winged warbler, and northern bobwhite). Abundance of northern bobwhite increased with winter temperature and was the species exhibiting the most significant effect of climate. Models for birds primarily occupying early successional habitats performed better with a combination of habitat and climate variables whereas models of species found in contiguous forest performed best with land cover alone. These varied species-specific responses present unique challenges to land managers trying to balance species conservation over a variety of land covers. Management activities focused on increasing forest cover may play a role in mitigating effects of future climate by providing habitat refugia to species vulnerable to projected changes. Conservation efforts would be best served focusing on areas with high species abundances and an array of habitats. Future work managing forests for resilience and resistance to climate change could benefit species already susceptible to climate impacts.
Ocean Modeling and Visualization on Massively Parallel Computer
NASA Technical Reports Server (NTRS)
Chao, Yi; Li, P. Peggy; Wang, Ping; Katz, Daniel S.; Cheng, Benny N.
1997-01-01
Climate modeling is one of the grand challenges of computational science, and ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change.
Global Warming: Discussion for EOS Science Writers Workshop
NASA Technical Reports Server (NTRS)
Hansen, James E
1999-01-01
The existence of global warming this century is no longer an issue of scientific debate. But there are many important questions about the nature and causes of long-term climate change, th roles of nature and human-made climate forcings and unforced (chaotic) climate variability, the practical impacts of climate change, and what, if anything, should be done to reduce global warming, Global warming is not a uniform increase of temperature, but rather involves at complex geographically varying climate change. Understanding of global warming will require improved observations of climate change itself and the forcing factors that can lead to climate change. The NASA Terra mission and other NASA Earth Science missions will provide key measurement of climate change and climate forcings. The strategy to develop an understanding of the causes and predictability of long-term climate change must be based on combination of observations with models and analysis. The upcoming NASA missions will make important contributions to the required observations.
Modeling the Climatic Consequences of Geoengineering
NASA Astrophysics Data System (ADS)
Somerville, R. C.
2005-12-01
The last half-century has seen the development of physically comprehensive computer models of the climate system. These models are the primary tool for making predictions of climate change due to human activities, such as emitting greenhouse gases into the atmosphere. Because scientific understanding of the climate system is incomplete, however, any climate model will necessarily have imperfections. The inevitable uncertainties associated with these models have sometimes been cited as reasons for not taking action to reduce such emissions. Climate models could certainly be employed to predict the results of various attempts at geoengineering, but many questions would arise. For example, in considering proposals to increase the planetary reflectivity by brightening parts of the land surface or by orbiting mirrors, can models be used to bound the results and to warm of unintended consequences? How could confidence limits be placed on such model results? How can climate changes due to proposed geoengineering be distinguished from natural variability? There are historical parallels on smaller scales, in which models have been employed to predict the results of attempts to alter the weather, such as the use of cloud seeding for precipitation enhancement, hail suppression and hurricane modification. However, there are also many lessons to be learned from the recent record of using models to simulate the effects of the great unintended geoengineering experiment involving greenhouse gases, now in progress. In this major research effort, the same types of questions have been studied at length. The best modern models have demonstrated an impressive ability to predict some aspects of climate change. A large body of evidence has already accumulated through comparing model predictions to many observed aspects of recent climate change, ranging from increases in ocean heat content to changes in atmospheric water vapor to reductions in glacier extent. The preponderance of expert opinion is that this evidence is now sufficient to establish the human cause of much recent climate change. Nevertheless, no model can provide detailed and fully trustworthy answers to every possible question of interest. As an example, how will the climatology of Atlantic hurricanes change as the greenhouse effect becomes stronger? Can models reliably forecast changes in the length of the hurricane season or changes in the geographical regions affected by hurricanes? The answer is no, or at least, not yet. Additionally, climate models are not based entirely on first principles, such as Newtonian physics. Instead, they have been developed primarily to simulate the present climate and relatively small departures from it. To achieve this goal, a certain amount of empiricism has been built into the models. The result has sometimes been to increase the apparent realism of models at the cost of limiting their generality. Thus, the available climate models may well be less capable of simulating a geoengineering experiment that might lead to a radically different climate. New model development may be required for this new application. The challenge is to distinguish between what models can and cannot do well. It would be irresponsible and unethical, either to undertake geoengineering projects without modeling their consequences, or to place blind faith in the models. To decide how best to model a proposed geoengineering technique requires a deep understanding of the strengths and weaknesses of climate models. The history of modeling successes and failures is a valuable guide to the wise interpretation of model results.
Novel competitors shape species' responses to climate change.
Alexander, Jake M; Diez, Jeffrey M; Levine, Jonathan M
2015-09-24
Understanding how species respond to climate change is critical for forecasting the future dynamics and distribution of pests, diseases and biological diversity. Although ecologists have long acknowledged species' direct physiological and demographic responses to climate, more recent work suggests that these direct responses can be overwhelmed by indirect effects mediated via other interacting community members. Theory suggests that some of the most dramatic impacts of community change will probably arise through the assembly of novel species combinations after asynchronous migrations with climate. Empirical tests of this prediction are rare, as existing work focuses on the effects of changing interactions between competitors that co-occur today. To explore how species' responses to climate warming depend on how their competitors migrate to track climate, we transplanted alpine plant species and intact plant communities along a climate gradient in the Swiss Alps. Here we show that when alpine plants were transplanted to warmer climates to simulate a migration failure, their performance was strongly reduced by novel competitors that could migrate upwards from lower elevation; these effects generally exceeded the impact of warming on competition with current competitors. In contrast, when we grew the focal plants under their current climate to simulate climate tracking, a shift in the competitive environment to novel high-elevation competitors had little to no effect. This asymmetry in the importance of changing competitor identity at the leading versus trailing range edges is best explained by the degree of functional similarity between current and novel competitors. We conclude that accounting for novel competitive interactions may be essential to predict species' responses to climate change accurately.
Functional consequences of climate change-induced plant species loss in a tallgrass prairie.
Craine, Joseph M; Nippert, Jesse B; Towne, E Gene; Tucker, Sally; Kembel, Steven W; Skibbe, Adam; McLauchlan, Kendra K
2011-04-01
Future climate change is likely to reduce the floristic diversity of grasslands. Yet the potential consequences of climate-induced plant species losses for the functioning of these ecosystems are poorly understood. We investigated how climate change might alter the functional composition of grasslands for Konza Prairie, a diverse tallgrass prairie in central North America. With species-specific climate envelopes, we show that a reduction in mean annual precipitation would preferentially remove species that are more abundant in the more productive lowland positions at Konza. As such, decreases in precipitation could reduce productivity not only by reducing water availability but by also removing species that inhabit the most productive areas and respond the most to climate variability. In support of this prediction, data on species abundance at Konza over 16 years show that species that are more abundant in lowlands than uplands are preferentially reduced in years with low precipitation. Climate change is likely to also preferentially remove species from particular functional groups and clades. For example, warming is forecast to preferentially remove perennials over annuals as well as Cyperaceae species. Despite these predictions, climate change is unlikely to unilaterally alter the functional composition of the tallgrass prairie flora, as many functional traits such as physiological drought tolerance and maximum photosynthetic rates showed little relationship with climate envelope parameters. In all, although climatic drying would indirectly alter grassland productivity through species loss patterns, the insurance afforded by biodiversity to ecosystem function is likely to be sustained in the face of climate change.
Simulating Climate Change in Ireland
NASA Astrophysics Data System (ADS)
Nolan, P.; Lynch, P.
2012-04-01
At the Meteorology & Climate Centre at University College Dublin, we are using the CLM-Community's COSMO-CLM Regional Climate Model (RCM) and the WRF RCM (developed at NCAR) to simulate the climate of Ireland at high spatial resolution. To address the issue of model uncertainty, a Multi-Model Ensemble (MME) approach is used. The ensemble method uses different RCMs, driven by several Global Climate Models (GCMs), to simulate climate change. Through the MME approach, the uncertainty in the RCM projections is quantified, enabling us to estimate the probability density function of predicted changes, and providing a measure of confidence in the predictions. The RCMs were validated by performing a 20-year simulation of the Irish climate (1981-2000), driven by ECMWF ERA-40 global re-analysis data, and comparing the output to observations. Results confirm that the output of the RCMs exhibit reasonable and realistic features as documented in the historical data record. Projections for the future Irish climate were generated by downscaling the Max Planck Institute's ECHAM5 GCM, the UK Met Office HadGEM2-ES GCM and the CGCM3.1 GCM from the Canadian Centre for Climate Modelling. Simulations were run for a reference period 1961-2000 and future period 2021-2060. The future climate was simulated using the A1B, A2, B1, RCP 4.5 & RCP 8.5 greenhouse gas emission scenarios. Results for the downscaled simulations show a substantial overall increase in precipitation and wind speed for the future winter months and a decrease during the summer months. The predicted annual change in temperature is approximately 1.1°C over Ireland. To date, all RCM projections are in general agreement, thus increasing our confidence in the robustness of the results.
Cryptic biodiversity loss linked to global climate change
NASA Astrophysics Data System (ADS)
Bálint, M.; Domisch, S.; Engelhardt, C. H. M.; Haase, P.; Lehrian, S.; Sauer, J.; Theissinger, K.; Pauls, S. U.; Nowak, C.
2011-09-01
Global climate change (GCC) significantly affects distributional patterns of organisms, and considerable impacts on biodiversity are predicted for the next decades. Inferred effects include large-scale range shifts towards higher altitudes and latitudes, facilitation of biological invasions and species extinctions. Alterations of biotic patterns caused by GCC have usually been predicted on the scale of taxonomically recognized morphospecies. However, the effects of climate change at the most fundamental level of biodiversity--intraspecific genetic diversity--remain elusive. Here we show that the use of morphospecies-based assessments of GCC effects will result in underestimations of the true scale of biodiversity loss. Species distribution modelling and assessments of mitochondrial DNA variability in nine montane aquatic insect species in Europe indicate that future range contractions will be accompanied by severe losses of cryptic evolutionary lineages and genetic diversity within these lineages. These losses greatly exceed those at the scale of morphospecies. We also document that the extent of range reduction may be a useful proxy when predicting losses of genetic diversity. Our results demonstrate that intraspecific patterns of genetic diversity should be considered when estimating the effects of climate change on biodiversity.
Plasticity and genetic adaptation mediate amphibian and reptile responses to climate change.
Urban, Mark C; Richardson, Jonathan L; Freidenfelds, Nicole A
2014-01-01
Phenotypic plasticity and genetic adaptation are predicted to mitigate some of the negative biotic consequences of climate change. Here, we evaluate evidence for plastic and evolutionary responses to climate variation in amphibians and reptiles via a literature review and meta-analysis. We included studies that either document phenotypic changes through time or space. Plasticity had a clear and ubiquitous role in promoting phenotypic changes in response to climate variation. For adaptive evolution, we found no direct evidence for evolution of amphibians or reptiles in response to climate change over time. However, we found many studies that documented adaptive responses to climate along spatial gradients. Plasticity provided a mixture of adaptive and maladaptive responses to climate change, highlighting that plasticity frequently, but not always, could ameliorate climate change. Based on our review, we advocate for more experiments that survey genetic changes through time in response to climate change. Overall, plastic and genetic variation in amphibians and reptiles could buffer some of the formidable threats from climate change, but large uncertainties remain owing to limited data.
Plasticity and genetic adaptation mediate amphibian and reptile responses to climate change
Urban, Mark C; Richardson, Jonathan L; Freidenfelds, Nicole A
2014-01-01
Phenotypic plasticity and genetic adaptation are predicted to mitigate some of the negative biotic consequences of climate change. Here, we evaluate evidence for plastic and evolutionary responses to climate variation in amphibians and reptiles via a literature review and meta-analysis. We included studies that either document phenotypic changes through time or space. Plasticity had a clear and ubiquitous role in promoting phenotypic changes in response to climate variation. For adaptive evolution, we found no direct evidence for evolution of amphibians or reptiles in response to climate change over time. However, we found many studies that documented adaptive responses to climate along spatial gradients. Plasticity provided a mixture of adaptive and maladaptive responses to climate change, highlighting that plasticity frequently, but not always, could ameliorate climate change. Based on our review, we advocate for more experiments that survey genetic changes through time in response to climate change. Overall, plastic and genetic variation in amphibians and reptiles could buffer some of the formidable threats from climate change, but large uncertainties remain owing to limited data. PMID:24454550
Experimental climate change weakens the insurance effect of biodiversity.
Eklöf, Johan S; Alsterberg, Christian; Havenhand, Jonathan N; Sundbäck, Kristina; Wood, Hannah L; Gamfeldt, Lars
2012-08-01
Ecosystems are simultaneously affected by biodiversity loss and climate change, but we know little about how these factors interact. We predicted that climate warming and CO (2) -enrichment should strengthen trophic cascades by reducing the relative efficiency of predation-resistant herbivores, if herbivore consumption rate trades off with predation resistance. This weakens the insurance effect of herbivore diversity. We tested this prediction using experimental ocean warming and acidification in seagrass mesocosms. Meta-analyses of published experiments first indicated that consumption rate trades off with predation resistance. The experiment then showed that three common herbivores together controlled macroalgae and facilitated seagrass dominance, regardless of climate change. When the predation-vulnerable herbivore was excluded in normal conditions, the two resistant herbivores maintained top-down control. Under warming, however, increased algal growth outstripped control by herbivores and the system became algal-dominated. Consequently, climate change can reduce the relative efficiency of resistant herbivores and weaken the insurance effect of biodiversity. © 2012 Blackwell Publishing Ltd/CNRS.
NASA Astrophysics Data System (ADS)
Samuels, Rana
Water issues are a source of tension between Israelis and Palestinians. In the and region of the Middle East, water supply is not just scarce but also uncertain: It is not uncommon for annual rainfall to be as little as 60% or as much as 125% of the multiannual average. This combination of scarcity and uncertainty exacerbates the already strained economy and the already tensed political situation. The uncertainty could be alleviated if it were possible to better forecast water availability. Such forecasting is key not only for water planning and management, but also for economic policy and for political decision making. Water forecasts at multiple time scales are necessary for crop choice, aquifer operation and investments in desalination infrastructure. The unequivocal warming of the climate system adds another level of uncertainty as global and regional water cycles change. This makes the prediction of water availability an even greater challenge. Understanding the impact of climate change on precipitation can provide the information necessary for appropriate risk assessment and water planning. Unfortunately, current global circulation models (GCMs) are only able to predict long term climatic evolution at large scales but not local rainfall. The statistics of local precipitation are traditionally predicted using historical rainfall data. Obviously these data cannot anticipate changes that result from climate change. It is therefore clear that integration of the global information about climate evolution and local historical data is needed to provide the much needed predictions of regional water availability. Currently, there is no theoretical or computational framework that enables such integration for this region. In this dissertation both a conceptual framework and a computational platform for such integration are introduced. In particular, suite of models that link forecasts of climatic evolution under different CO2 emissions scenarios to observed rainfall data from local stations are developed. These are used to develop scenarios for local rainfall statistics such as average annual amounts, dry spells, wet spells and drought persistence. This suite of models can provide information that is not attainable from existing tools in terms of its spatial and temporal resolution. Specifically, the goal is to project the impact of established global climate change scenarios in this region and, how much of the change might be mitigated by proposed CO2 reduction strategies. A major problem in this enterprise is to find the best way to integrate global climatic information with local rainfall data. From the climatologic perspective the problem is to find the right teleconnections. That is, non local or global measurable phenomena that influence local rainfall in a way that could be characterized and quantified statistically. From the computational perspective the challenge is to model these subtle, nonlinear relationships and to downscale the global effects into local predictions. Climate simulations to the year 2100 under selected climate change scenarios are used. Overall, the suite of models developed and presented can be applied to answer most questions from the different water users and planners. Farmers and the irrigation community can ask "What is the probability of rain over the next week?" Policy makers can ask "How much desalination capacity will I need to meet demand 90% of the time in the climate change scenario over the next 20 years?" Aquifer managers can ask "What is the expected recharge rate of the aquifers over the next decade?" The use of climate driven answers to these questions will help the region better prepare and adapt to future shifts in water resources and availability.
Altered seasonal climate patterns towards hotter, drier summers through the 21st century resulting from global climate change could affect the growth of coniferous forests in the Pacific Northwest (PNW) region of North America. The seasonal effects of temperature, precipitation,...
Constrained range expansion and climate change assessments
Yohay Carmel; Curtis H. Flather
2006-01-01
Modeling the future distribution of keystone species has proved to be an important approach to assessing the potential ecological consequences of climate change (Loehle and LeBlanc 1996; Hansen et al. 2001). Predictions of range shifts are typically based on empirical models derived from simple correlative relationships between climatic characteristics of occupied and...
USDA-ARS?s Scientific Manuscript database
Overdependence on fossil fuels for human energy needs continues to emitpotential greenhouse gases (GHG) into the atmosphere leading to a warmer climate over the earth. Predicting the impacts of climate change (CC) on food and fiber production systems in the future is essential for divising adaptati...
Christopher S. Balzotti; Stanley G. Kitchen; Clinton McCarthy
2016-01-01
Federal land management agencies and conservation organizations have begun incorporating climate change vulnerability assessments (CCVAs) as an important component in the management and conservation of landscapes. It is often a challenge to translate that knowledge into management plans and actions, even when research infers species risk. Predictive maps can...
Selenium deficiency risk predicted to increase under future climate change.
Jones, Gerrad D; Droz, Boris; Greve, Peter; Gottschalk, Pia; Poffet, Deyan; McGrath, Steve P; Seneviratne, Sonia I; Smith, Pete; Winkel, Lenny H E
2017-03-14
Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables. However, global concentrations of trace elements and the factors controlling their distributions are virtually unknown. We used 33,241 soil data points to model recent (1980-1999) global distributions of Selenium (Se), an essential trace element that is required for humans. Worldwide, up to one in seven people have been estimated to have low dietary Se intake. Contrary to small-scale studies, soil Se concentrations were dominated by climate-soil interactions. Using moderate climate-change scenarios for 2080-2099, we predicted that changes in climate and soil organic carbon content will lead to overall decreased soil Se concentrations, particularly in agricultural areas; these decreases could increase the prevalence of Se deficiency. The importance of climate-soil interactions to Se distributions suggests that other trace elements with similar retention mechanisms will be similarly affected by climate change.
Climate profoundly shapes forests. Forest species composition, productivity, availability of goods and services, disturbance regimes, and location on the landscape are all regulated by climate. Much research attention has focused on the problem of predicting the response of fores...
Carroll, Matthew J; Heinemeyer, Andreas; Pearce-Higgins, James W; Dennis, Peter; West, Chris; Holden, Joseph; Wallage, Zoe E; Thomas, Chris D
2015-07-31
Climate change has the capacity to alter physical and biological ecosystem processes, jeopardizing the survival of associated species. This is a particular concern in cool, wet northern peatlands that could experience warmer, drier conditions. Here we show that climate, ecosystem processes and food chains combine to influence the population performance of species in British blanket bogs. Our peatland process model accurately predicts water-table depth, which predicts abundance of craneflies (keystone invertebrates), which in turn predicts observed abundances and population persistence of three ecosystem-specialist bird species that feed on craneflies during the breeding season. Climate change projections suggest that falling water tables could cause 56-81% declines in cranefly abundance and, hence, 15-51% reductions in the abundances of these birds by 2051-2080. We conclude that physical (precipitation, temperature and topography), biophysical (evapotranspiration and desiccation of invertebrates) and ecological (food chains) processes combine to determine the distributions and survival of ecosystem-specialist predators.
Carroll, Matthew J.; Heinemeyer, Andreas; Pearce-Higgins, James W.; Dennis, Peter; West, Chris; Holden, Joseph; Wallage, Zoe E.; Thomas, Chris D.
2015-01-01
Climate change has the capacity to alter physical and biological ecosystem processes, jeopardizing the survival of associated species. This is a particular concern in cool, wet northern peatlands that could experience warmer, drier conditions. Here we show that climate, ecosystem processes and food chains combine to influence the population performance of species in British blanket bogs. Our peatland process model accurately predicts water-table depth, which predicts abundance of craneflies (keystone invertebrates), which in turn predicts observed abundances and population persistence of three ecosystem-specialist bird species that feed on craneflies during the breeding season. Climate change projections suggest that falling water tables could cause 56–81% declines in cranefly abundance and, hence, 15–51% reductions in the abundances of these birds by 2051–2080. We conclude that physical (precipitation, temperature and topography), biophysical (evapotranspiration and desiccation of invertebrates) and ecological (food chains) processes combine to determine the distributions and survival of ecosystem-specialist predators. PMID:26227623
Russell, Bayden D.; Harley, Christopher D. G.; Wernberg, Thomas; Mieszkowska, Nova; Widdicombe, Stephen; Hall-Spencer, Jason M.; Connell, Sean D.
2012-01-01
Most studies that forecast the ecological consequences of climate change target a single species and a single life stage. Depending on climatic impacts on other life stages and on interacting species, however, the results from simple experiments may not translate into accurate predictions of future ecological change. Research needs to move beyond simple experimental studies and environmental envelope projections for single species towards identifying where ecosystem change is likely to occur and the drivers for this change. For this to happen, we advocate research directions that (i) identify the critical species within the target ecosystem, and the life stage(s) most susceptible to changing conditions and (ii) the key interactions between these species and components of their broader ecosystem. A combined approach using macroecology, experimentally derived data and modelling that incorporates energy budgets in life cycle models may identify critical abiotic conditions that disproportionately alter important ecological processes under forecasted climates. PMID:21900317
Five potential consequences of climate change for invasive species.
Hellmann, Jessica J; Byers, James E; Bierwagen, Britta G; Dukes, Jeffrey S
2008-06-01
Scientific and societal unknowns make it difficult to predict how global environmental changes such as climate change and biological invasions will affect ecological systems. In the long term, these changes may have interacting effects and compound the uncertainty associated with each individual driver. Nonetheless, invasive species are likely to respond in ways that should be qualitatively predictable, and some of these responses will be distinct from those of native counterparts. We used the stages of invasion known as the "invasion pathway" to identify 5 nonexclusive consequences of climate change for invasive species: (1) altered transport and introduction mechanisms, (2) establishment of new invasive species, (3) altered impact of existing invasive species, (4) altered distribution of existing invasive species, and (5) altered effectiveness of control strategies. We then used these consequences to identify testable hypotheses about the responses of invasive species to climate change and provide suggestions for invasive-species management plans. The 5 consequences also emphasize the need for enhanced environmental monitoring and expanded coordination among entities involved in invasive-species management.
Potential impact of global climate change on malaria risk
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martens, W.J.M.; Rotmans, J.; Niessen, L.W.
The biological activity and geographic distribution of the malarial parasite and its vector are sensitive to climatic influences, especially temperature and precipitation. We have incorporated General Circulation Model-based scenarios of anthropogenic global climate change in an integrated linked-system model for predicting changes in malaria epidemic potential in the next century. The concept of the disability-adjusted life years is included to arrive at a single measure of the effect of anthropogenic climate change on the health impact of malaria. Assessment of the potential impact of global climate change on the incidence of malaria suggests a widespread increase of risk due tomore » expansion of the areas suitable for malaria transmission. This predicted increase is most pronounced at the borders of endemic malaria areas and at higher altitudes within malarial areas. The incidence of infection is sensitive to climate changes in areas of Southeast Asia, South America, and parts of Africa where the disease is less endemic; in these regions the numbers of years of healthy life lost may increase significantly. However, the simulated changes in malaria risk must be interpreted on the basis of local environmental conditions, the effects of socioeconomic developments, and malaria control programs or capabilities. 33 refs., 5 figs., 1 tab.« less
Amorim, Francisco; Carvalho, Sílvia B; Honrado, João; Rebelo, Hugo
2014-01-01
Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space. We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur. Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.
Predicting the effect of climate change on wildfire behavior and initial attack success
Jeremy S. Fried; J. Keith Gilless; William J. Riley; Tadashi J. Moody; Clara Simon de Blas; Katharine Hayhoe; Max Mortiz; Scott Stephens; Margaret Torn
2008-01-01
This study focused on how climate change-induced effects on weather will translate into changes in wildland fire severity and outcomes in California, particularly on the effectiveness of initial attack at limiting the number of fires that escape initial attack. The results indicate that subtle shifts in fire behavior of the sort that might be induced by the climate...
Anantha M. Prasad; Judith D. Gardiner; Louis R. Iverson; Stephen N. Matthews; Matthew Peters
2013-01-01
Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new...
Adapting silviculture to a changing climate in the southern United States
James M. Guldin
2014-01-01
Questions about how forests might respond to climate change are often addressed through planning, prediction, and modeling at the landscape scale. A recent synthesis of climate-change impacts on forest management and policy found that the earth is warmer than it has been in the recent past, and that 11 of the last 12 years rank among the 12 warmest since 1850 (Solomon...
MISST: The Multi-Sensor Improved Sea Surface Temperature Project
2009-06-01
climate change studies, fisheries management, and a wide range of other applications. Measurements are taken by several satellites carrying infrared and...TEMPERATURE PROJECT ABSTRACT. Sea surface temperature (SST) measurements are vital to global weather prediction, climate change studies, fisheries management...important variables related to the global ocean-atmosphere system. It is a key indicator of climate change , is widely applied to studies of upper
Matías, Luis; Linares, Juan C; Sánchez-Miranda, Ángela; Jump, Alistair S
2017-10-01
Ongoing changes in global climate are altering ecological conditions for many species. The consequences of such changes are typically most evident at the edge of a species' geographical distribution, where differences in growth or population dynamics may result in range expansions or contractions. Understanding population responses to different climatic drivers along wide latitudinal and altitudinal gradients is necessary in order to gain a better understanding of plant responses to ongoing increases in global temperature and drought severity. We selected Scots pine (Pinus sylvestris L.) as a model species to explore growth responses to climatic variability (seasonal temperature and precipitation) over the last century through dendrochronological methods. We developed linear models based on age, climate and previous growth to forecast growth trends up to year 2100 using climatic predictions. Populations were located at the treeline across a latitudinal gradient covering the northern, central and southernmost populations and across an altitudinal gradient at the southern edge of the distribution (treeline, medium and lower elevations). Radial growth was maximal at medium altitude and treeline of the southernmost populations. Temperature was the main factor controlling growth variability along the gradients, although the timing and strength of climatic variables affecting growth shifted with latitude and altitude. Predictive models forecast a general increase in Scots pine growth at treeline across the latitudinal distribution, with southern populations increasing growth up to year 2050, when it stabilizes. The highest responsiveness appeared at central latitude, and moderate growth increase is projected at the northern limit. Contrastingly, the model forecasted growth declines at lowland-southern populations, suggesting an upslope range displacement over the coming decades. Our results give insight into the geographical responses of tree species to climate change and demonstrate the importance of incorporating biogeographical variability into predictive models for an accurate prediction of species dynamics as climate changes. © 2017 John Wiley & Sons Ltd.
[Potential distribution of Panax ginseng and its predicted responses to climate change.
Zhao, Ze Fang; Wei, Hai Yan; Guo, Yan Long; Gu, Wei
2016-11-18
This study utilized Panax ginseng as the research object. Based on BioMod2 platform, with species presence data and 22 climatic variables, the potential geographic distribution of P. ginseng under the current conditions in northeast China was simulated with ten species distribution model. And then with the receiver-operating characteristic curve (ROC) as weights, we build an ensemble model, which integrated the results of 10 models, using the ensemble model, the future distributions of P. ginseng were also projected for the periods 2050s and 2070s under the climate change scenarios of RCP 8.5, RCP 6, RCP 4.5 and RCP 2.6 emission scenarios described in the Special Report on Emissions Scenarios (SRES) of IPCC (Intergovernmental Panel on Climate Change). The results showed that for the entire region of study area, under the present climatic conditions, 10.4% of the areas were identified as suitable habitats, which were mainly located in northeast Changbai Mountains area and the southeastern region of the Xiaoxing'an Mountains. The model simulations indicated that the suitable habitats would have a relatively significant change under the different climate change scenarios, and generally the range of suitable habitats would be a certain degree of decrease. Meanwhile, the goodness-of-fit, predicted ranges, and weights of explanatory variables was various for each model. And according to the goodness-of-fit, Maxent had the highest model performance, and GAM, RF and ANN were followed, while SRE had the lowest prediction accuracy. In this study we established an ensemble model, which could improve the accuracy of the existing species distribution models, and optimization of species distribution prediction results.
Climate change risk to forests in China associated with warming.
Yin, Yunhe; Ma, Danyang; Wu, Shaohong
2018-01-11
Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021-2050) to 27.62% (2071-2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.
2015-01-01
The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change. PMID:26057739
Thomson, Robin B; Alderman, Rachael L; Tuck, Geoffrey N; Hobday, Alistair J
2015-01-01
The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change.
Reconstruction of Past Mediterranean Climate
NASA Astrophysics Data System (ADS)
García-Herrera, Ricardo; Luterbacher, Jürg; Lionello, Piero; Gonzáles-Rouco, Fidel; Ribera, Pedro; Rodó, Xavier; Kull, Christoph; Zerefos, Christos
2007-02-01
First MEDCLIVAR Workshop on Reconstruction of Past Mediterranean Climate; Pablo de Olavide University, Carmona, Spain, 8-11 November 2006; Mediterranean Climate Variability and Predictability (MEDCLIVAR; http://www.medclivar.eu) is a program that coordinates and promotes research on different aspects of Mediterranean climate. The main MEDCLIVAR goals include the reconstruction of past climate, describing patterns and mechanisms characterizing climate space-time variability, extremes at different time and space scales, coupled climate model/empirical reconstruction comparisons, seasonal forecasting, and the identification of the forcings responsible for the observed changes. The program has been endorsed by CLIVAR (Climate Variability and Predictability project) and is funded by the European Science Foundation.
Impacts of Climate Change on the Global Invasion Potential of the African Clawed Frog Xenopus laevis
Ihlow, Flora; Courant, Julien; Secondi, Jean; Herrel, Anthony; Rebelo, Rui; Measey, G. John; Lillo, Francesco; De Villiers, F. André; Vogt, Solveig; De Busschere, Charlotte; Backeljau, Thierry; Rödder, Dennis
2016-01-01
By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species’ native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain. PMID:27248830
Ihlow, Flora; Courant, Julien; Secondi, Jean; Herrel, Anthony; Rebelo, Rui; Measey, G John; Lillo, Francesco; De Villiers, F André; Vogt, Solveig; De Busschere, Charlotte; Backeljau, Thierry; Rödder, Dennis
2016-01-01
By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species' native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain.
He, Yong; Wang, Hong; Qian, Budong; McConkey, Brian; DePauw, Ron
2012-01-01
Shorter growing season and water stress near wheat maturity are the main factors that presumably limit the yield potential of spring wheat due to late seeding in Saskatchewan, Canada. Advancing seeding dates can be a strategy to help producers mitigate the impact of climate change on spring wheat. It is unknown, however, how early farmers can seed while minimizing the risk of spring frost damage and the soil and machinery constraints. This paper explores early seeding dates of spring wheat on the Canadian Prairies under current and projected future climate. To achieve this, (i) weather records from 1961 to 1990 were gathered at three sites with different soil and climate conditions in Saskatchewan, Canada; (ii) four climate databases that included a baseline (treated as historic weather climate during the period of 1961-1990) and three climate change scenarios (2040-2069) developed by the Canadian global climate model (GCM) with the forcing of three greenhouse gas (GHG) emission scenarios (A2, A1B and B1); (iii) seeding dates of spring wheat (Triticum aestivum L.) under baseline and projected future climate were predicted. Compared with the historical record of seeding dates, the predicted seeding dates were advanced under baseline climate for all sites using our seeding date model. Driven by the predicted temperature increase of the scenarios compared with baseline climate, all climate change scenarios projected significantly earlier seeding dates than those currently used. Compared to the baseline conditions, there is no reduction in grain yield because precipitation increases during sensitive growth stages of wheat, suggesting that there is potential to shift seeding to an earlier date. The average advancement of seeding dates varied among sites and chosen scenarios. The Swift Current (south-west) site has the highest potential for earlier seeding (7 to 11 days) whereas such advancement was small in the Melfort (north-east, 2 to 4 days) region. The extent of projected climate change in Saskatchewan indicates that growers in this region have the potential of earlier seeding. The results obtained in this study may be used for adaptation assessments of seeding dates under possible climate change to mitigate the impact of potential warming.
Sundt-Hansen, L E; Hedger, R D; Ugedal, O; Diserud, O H; Finstad, A G; Sauterleute, J F; Tøfte, L; Alfredsen, K; Forseth, T
2018-08-01
Climate change is expected to alter future temperature and discharge regimes of rivers. These regimes have a strong influence on the life history of most aquatic river species, and are key variables controlling the growth and survival of Atlantic salmon. This study explores how the future abundance of Atlantic salmon may be influenced by climate-induced changes in water temperature and discharge in a regulated river, and investigates how negative impacts in the future can be mitigated by applying different regulated discharge regimes during critical periods for salmon survival. A spatially explicit individual-based model was used to predict juvenile Atlantic salmon population abundance in a regulated river under a range of future water temperature and discharge scenarios (derived from climate data predicted by the Hadley Centre's Global Climate Model (GCM) HadAm3H and the Max Plank Institute's GCM ECHAM4), which were then compared with populations predicted under control scenarios representing past conditions. Parr abundance decreased in all future scenarios compared to the control scenarios due to reduced wetted areas (with the effect depending on climate scenario, GCM, and GCM spatial domain). To examine the potential for mitigation of climate change-induced reductions in wetted area, simulations were run with specific minimum discharge regimes. An increase in abundance of both parr and smolt occurred with an increase in the limit of minimum permitted discharge for three of the four GCM/GCM spatial domains examined. This study shows that, in regulated rivers with upstream storage capacity, negative effects of climate change on Atlantic salmon populations can potentially be mitigated by release of water from reservoirs during critical periods for juvenile salmon. Copyright © 2018. Published by Elsevier B.V.
Tonnang, Henri E Z; Kangalawe, Richard Y M; Yanda, Pius Z
2010-04-23
Malaria is rampant in Africa and causes untold mortality and morbidity. Vector-borne diseases are climate sensitive and this has raised considerable concern over the implications of climate change on future disease risk. The problem of malaria vectors (Anopheles mosquitoes) shifting from their traditional locations to invade new zones is an important concern. The vision of this study was to exploit the sets of information previously generated by entomologists, e.g. on geographical range of vectors and malaria distribution, to build models that will enable prediction and mapping the potential redistribution of Anopheles mosquitoes in Africa. The development of the modelling tool was carried out through calibration of CLIMEX parameters. The model helped estimate the potential geographical distribution and seasonal abundance of the species in relation to climatic factors. These included temperature, rainfall and relative humidity, which characterized the living environment for Anopheles mosquitoes. The same parameters were used in determining the ecoclimatic index (EI). The EI values were exported to a GIS package for special analysis and proper mapping of the potential future distribution of Anopheles gambiae and Anophles arabiensis within the African continent under three climate change scenarios. These results have shown that shifts in these species boundaries southward and eastward of Africa may occur rather than jumps into quite different climatic environments. In the absence of adequate control, these predictions are crucial in understanding the possible future geographical range of the vectors and the disease, which could facilitate planning for various adaptation options. Thus, the outputs from this study will be helpful at various levels of decision making, for example, in setting up of an early warning and sustainable strategies for climate change and climate change adaptation for malaria vectors control programmes in Africa.
Effects of temperature change on mussel, Mytilus.
Zippay, Mackenzie L; Helmuth, Brian
2012-09-01
An increasing body of research has demonstrated the often idiosyncratic responses of organisms to climate-related factors, such as increases in air, sea and land surface temperatures, especially when coupled with non-climatic stressors. This argues that sweeping generalizations about the likely impacts of climate change on organisms and ecosystems are likely less valuable than process-based explorations that focus on key species and ecosystems. Mussels in the genus Mytilus have been studied for centuries, and much is known of their physiology and ecology. Like other intertidal organisms, these animals may serve as early indicators of climate change impacts. As structuring species, their survival has cascading impacts on many other species, making them ecologically important, in addition to their economic value as a food source. Here, we briefly review the categories of information available on the effects of temperature change on mussels within this genus. Although a considerable body of information exists about the genus in general, knowledge gaps still exist, specifically in our ability to predict how specific populations are likely to respond to the effects of multiple stressors, both climate and non-climate related, and how these changes are likely to result in ecosystem-level responses. Whereas this genus provides an excellent model for exploring the effects of climate change on natural and human-managed ecosystems, much work remains if we are to make predictions of likely impacts of environmental change on scales that are relevant to climate adaptation. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.
Climate change unlikely to increase malaria burden in West Africa
NASA Astrophysics Data System (ADS)
Yamana, Teresa K.; Bomblies, Arne; Eltahir, Elfatih A. B.
2016-11-01
The impact of climate change on malaria transmission has been hotly debated. Recent conclusions have been drawn using relatively simple biological models and statistical approaches, with inconsistent predictions. Consequently, the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5) echoes this uncertainty, with no clear guidance for the impacts of climate change on malaria transmission, yet recognizing a strong association between local climate and malaria. Here, we present results from a decade-long study involving field observations and a sophisticated model simulating village-scale transmission. We drive the malaria model using select climate models that correctly reproduce historical West African climate, and project reduced malaria burden in a western sub-region and insignificant impact in an eastern sub-region. Projected impacts of climate change on malaria transmission in this region are not of serious concern.
Linking climate change projections for an Alaskan watershed to future coho salmon production.
Leppi, Jason C; Rinella, Daniel J; Wilson, Ryan R; Loya, Wendy M
2014-06-01
Climate change is predicted to dramatically change hydrologic processes across Alaska, but estimates of how these impacts will influence specific watersheds and aquatic species are lacking. Here, we linked climate, hydrology, and habitat models within a coho salmon (Oncorhynchus kisutch) population model to assess how projected climate change could affect survival at each freshwater life stage and, in turn, production of coho salmon smolts in three subwatersheds of the Chuitna (Chuit) River watershed, Alaska. Based on future climate scenarios and projections from a three-dimensional hydrology model, we simulated coho smolt production over a 20-year span at the end of the century (2080-2100). The direction (i.e., positive vs. negative) and magnitude of changes in smolt production varied substantially by climate scenario and subwatershed. Projected smolt production decreased in all three subwatersheds under the minimum air temperature and maximum precipitation scenario due to elevated peak flows and a resulting 98% reduction in egg-to-fry survival. In contrast, the maximum air temperature and minimum precipitation scenario led to an increase in smolt production in all three subwatersheds through an increase in fry survival. Other climate change scenarios led to mixed responses, with projected smolt production increasing and decreasing in different subwatersheds. Our analysis highlights the complexity inherent in predicting climate-change-related impacts to salmon populations and demonstrates that population effects may depend on interactions between the relative magnitude of hydrologic and thermal changes and their interactions with features of the local habitat. © 2013 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
Roser-Renouf, Connie; Maibach, Edward W.; Li, Jennifer
2016-01-01
Background Climate change poses a major public health threat. A survey of U.S. local health department directors in 2008 found widespread recognition of the threat, but limited adaptive capacity, due to perceived lack of expertise and other resources. Methods We assessed changes between 2008 and 2012 in local public health departments' preparedness for the public health threats of climate change, in light of increasing national polarization on the issue, and widespread funding cutbacks for public health. A geographically representative online survey of directors of local public health departments was conducted in 2011–2012 (N = 174; response rate = 50%), and compared to the 2008 telephone survey results (N = 133; response rate = 61%). Results Significant polarization had occurred: more respondents in 2012 were certain that the threat of local climate change impacts does/does not exist, and fewer were unsure. Roughly 10% said it is not a threat, compared to 1% in 2008. Adaptation capacity decreased in several areas: perceived departmental expertise in climate change risk assessment; departmental prioritization of adaptation; and the number of adaptation-related programs and services departments provided. In 2008, directors' perceptions of local impacts predicted the number of adaptation-related programs and services their departments offered, but in 2012, funding predicted programming and directors' impact perceptions did not. This suggests that budgets were constraining directors' ability to respond to local climate change-related health threats. Results also suggest that departmental expertise may mitigate funding constraints. Strategies for overcoming these obstacles to local public health departments' preparations for climate change are discussed. PMID:26991658
Roser-Renouf, Connie; Maibach, Edward W; Li, Jennifer
2016-01-01
Climate change poses a major public health threat. A survey of U.S. local health department directors in 2008 found widespread recognition of the threat, but limited adaptive capacity, due to perceived lack of expertise and other resources. We assessed changes between 2008 and 2012 in local public health departments' preparedness for the public health threats of climate change, in light of increasing national polarization on the issue, and widespread funding cutbacks for public health. A geographically representative online survey of directors of local public health departments was conducted in 2011-2012 (N = 174; response rate = 50%), and compared to the 2008 telephone survey results (N = 133; response rate = 61%). Significant polarization had occurred: more respondents in 2012 were certain that the threat of local climate change impacts does/does not exist, and fewer were unsure. Roughly 10% said it is not a threat, compared to 1% in 2008. Adaptation capacity decreased in several areas: perceived departmental expertise in climate change risk assessment; departmental prioritization of adaptation; and the number of adaptation-related programs and services departments provided. In 2008, directors' perceptions of local impacts predicted the number of adaptation-related programs and services their departments offered, but in 2012, funding predicted programming and directors' impact perceptions did not. This suggests that budgets were constraining directors' ability to respond to local climate change-related health threats. Results also suggest that departmental expertise may mitigate funding constraints. Strategies for overcoming these obstacles to local public health departments' preparations for climate change are discussed.
Yang, Guo-Jing; Utzinger, Jürg; Lv, Shan; Qian, Ying-Jun; Li, Shi-Zhu; Wang, Qiang; Bergquist, Robert; Vounatsou, Penelope; Li, Wei; Yang, Kun; Zhou, Xiao-Nong
2010-01-01
Climate change-according to conventional wisdom-will result in an expansion of tropical parasitic diseases in terms of latitude and altitude, with vector-borne diseases particularly prone to change. However, although a significant rise in temperature occurred over the past century, there is little empirical evidence whether climate change has indeed favoured infectious diseases. This might be explained by the complex relationship between climate change and the frequency and the transmission dynamics of infectious diseases, which is characterised by nonlinear associations and countless other complex factors governing the distribution of infectious diseases. Here, we explore whether and how climate change might impact on diseases targeted by the Regional Network for Asian Schistosomiasis and Other Helminth Zoonoses (RNAS(+)). We start our review with a short summary of the current evidence-base how climate change affects the distribution of infectious diseases. Next, we introduce biology-based models for predicting the distribution of infectious diseases in a future, warmer world. Two case studies are presented: the classical RNAS(+) disease schistosomiasis and an emerging disease, angiostrongyliasis, focussing on their occurrences in the People's Republic of China. Strengths and limitations of current models for predicting the impact of climate change on infectious diseases are discussed, and we propose model extensions to include social and ecological factors. Finally, we recommend that mitigation and adaptation strategies to diminish potential negative effects of climate change need to be developed in concert with key stakeholders so that surveillance and early-warning systems can be strengthened and the most vulnerable population groups protected. Copyright 2010 Elsevier Ltd. All rights reserved.
NASA Contributions to Improve Understanding of Extreme Events in the Global Energy and Water Cycle
NASA Technical Reports Server (NTRS)
Lapenta, William M.
2008-01-01
The U.S. Climate Change Science Program (CCSP) has established the water cycle goals of the Nation's climate change program. Accomplishing these goals will require, in part, an accurate accounting of the key reservoirs and fluxes associated with the global water and energy cycle, including their spatial and temporal variability. through integration of all necessary observations and research tools, To this end, in conjunction with NASA's Earth science research strategy, the overarching long-term NASA Energy and Water Cycle Study (NEWS) grand challenge can he summarized as documenting and enabling improved, observationally based, predictions of water and energy cycle consequences of Earth system variability and change. This challenge requires documenting and predicting trends in the rate of the Earth's water and energy cycling that corresponds to climate change and changes in the frequency and intensity of naturally occurring related meteorological and hydrologic events, which may vary as climate may vary in the future. The cycling of water and energy has obvious and significant implications for the health and prosperity of our society. The importance of documenting and predicting water and energy cycle variations and extremes is necessary to accomplish this benefit to society.
Bataillon, Thomas; Galtier, Nicolas; Bernard, Aurelien; Cryer, Nicolai; Faivre, Nicolas; Santoni, Sylvain; Severac, Dany; Mikkelsen, Teis N; Larsen, Klaus S; Beier, Claus; Sørensen, Jesper G; Holmstrup, Martin; Ehlers, Bodil K
2016-07-01
Whether species can respond evolutionarily to current climate change is crucial for the persistence of many species. Yet, very few studies have examined genetic responses to climate change in manipulated experiments carried out in natural field conditions. We examined the evolutionary response to climate change in a common annelid worm using a controlled replicated experiment where climatic conditions were manipulated in a natural setting. Analyzing the transcribed genome of 15 local populations, we found that about 12% of the genetic polymorphisms exhibit differences in allele frequencies associated to changes in soil temperature and soil moisture. This shows an evolutionary response to realistic climate change happening over short-time scale, and calls for incorporating evolution into models predicting future response of species to climate change. It also shows that designed climate change experiments coupled with genome sequencing offer great potential to test for the occurrence (or lack) of an evolutionary response. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Talluto, M. V.; Boulangeat, I.; Vissault, S.; Gravel, D.
2015-12-01
Climate change is likely to push many species to the limits of their ecological niches and lead to mismatches between species ranges and local environmental conditions. Forested ecosystems in particular may have difficulty tracking climate change due to slow growth and dispersal rates. Correlative species distribution models (SDMs), commonly used to predict the response of species distributions to climate change, relate species occurrences to climate to describe the present niche; however they often project into the future without accounting for slow processes that might produce lags in the response to climate change. An alternative type of model that analyzes patch-scale colonization and extinction (C-E) rates along an environmental gradient has been successful in describing species range limits in theoretical studies. Because the model is stochastic and dynamic, it is more robust to changes in the environmental gradient than static SDMs. We applied such a model to 40 of the most abundant trees in eastern North American forests, using repeated observations across multiple decades to parameterize the C-E rates. We show that C-E rates for many species respond to climate in a manner that generates predicted range limits when the species is at equilibrium with the environment. Moreover, current distributions of many species are significantly out of equilibrium with the present climate, with predicted range limits shifted 10s to 100s of km northward from the present distribution. These results suggest that present warming has already exceeded the thermal tolerance at the southern range limits for the dominant trees of eastern North American forests, producing millions of ha of newly suitable areas north of the present distribution of these species that have not yet been colonized, as well as large southern regions where species are present but expected to be lost in the long-term as dead trees are not replaced, even if no further climate warming occurs.
Species interactions reverse grassland responses to changing climate.
Suttle, K B; Thomsen, Meredith A; Power, Mary E
2007-02-02
Predictions of ecological response to climate change are based largely on direct climatic effects on species. We show that, in a California grassland, species interactions strongly influence responses to changing climate, overturning direct climatic effects within 5 years. We manipulated the seasonality and intensity of rainfall over large, replicate plots in accordance with projections of leading climate models and examined responses across several trophic levels. Changes in seasonal water availability had pronounced effects on individual species, but as precipitation regimes were sustained across years, feedbacks and species interactions overrode autecological responses to water and reversed community trajectories. Conditions that sharply increased production and diversity through 2 years caused simplification of the food web and deep reductions in consumer abundance after 5 years. Changes in these natural grassland communities suggest a prominent role for species interactions in ecosystem response to climate change.
Adamo, Shelley A; Baker, Jillian L; Lovett, Maggie M E; Wilson, Graham
2012-12-01
Climate change will result in warmer temperatures and an increase in the frequency and severity of extreme weather events. Given that higher temperatures increase the reproductive rate of temperate zone insects, insect population growth rates are predicted to increase in the temperate zone in response to climate. This consensus, however, rests on the assumption that food is freely available. However, under conditions of limited food, the reproductive output of the Texan cricket Gryllus texensis (Cade and Otte) was highest at its current normal average temperature and declined with increasing temperature. Moreover, low food availability decreased survival during a simulated heat wave. Therefore, the effects of climate change on this species, and possibly on many others, are likely to hinge on food availability. Extrapolation from our data suggests that G. texensis will show larger yearly fluctuations in population size as climate change continues, and this will also have ecological repercussions. Only those temperate zone insects with a ready supply of food (e.g., agricultural pests) are likely to experience the predicted increase in population growth in response to climate change; food-limited species are likely to experience a population decline.
Gilman, Sarah E; Wethey, David S; Helmuth, Brian
2006-06-20
Global climate change is expected to have broad ecological consequences for species and communities. Attempts to forecast these consequences usually assume that changes in air or water temperature will translate into equivalent changes in a species' organismal body temperature. This simple change is unlikely because an organism's body temperature is determined by a complex series of interactions between the organism and its environment. Using a biophysical model, validated with 5 years of field observations, we examined the relationship between environmental temperature change and body temperature of the intertidal mussel Mytilus californianus over 1,600 km of its geographic distribution. We found that at all locations examined simulated changes in air or water temperature always produced less than equivalent changes in the daily maximum mussel body temperature. Moreover, the magnitude of body temperature change was highly variable, both within and among locations. A simulated 1 degrees C increase in air or water temperature raised the maximum monthly average of daily body temperature maxima by 0.07-0.92 degrees C, depending on the geographic location, vertical position, and temperature variable. We combined these sensitivities with predicted climate change for 2100 and calculated increases in monthly average maximum body temperature of 0.97-4.12 degrees C, depending on location and climate change scenario. Thus geographic variation in body temperature sensitivity can modulate species' experiences of climate change and must be considered when predicting the biological consequences of climate change.
Climate Ocean Modeling on Parallel Computers
NASA Technical Reports Server (NTRS)
Wang, P.; Cheng, B. N.; Chao, Y.
1998-01-01
Ocean modeling plays an important role in both understanding the current climatic conditions and predicting future climate change. However, modeling the ocean circulation at various spatial and temporal scales is a very challenging computational task.
Contrasting fire responses to climate and management: insights from two Australian ecosystems.
King, Karen J; Cary, Geoffrey J; Bradstock, Ross A; Marsden-Smedley, Jonathan B
2013-04-01
This study explores effects of climate change and fuel management on unplanned fire activity in ecosystems representing contrasting extremes of the moisture availability spectrum (mesic and arid). Simulation modelling examined unplanned fire activity (fire incidence and area burned, and the area burned by large fires) for alternate climate scenarios and prescribed burning levels in: (i) a cool, moist temperate forest and wet moorland ecosystem in south-west Tasmania (mesic); and (ii) a spinifex and mulga ecosystem in central Australia (arid). Contemporary fire activity in these case study systems is limited, respectively, by fuel availability and fuel amount. For future climates, unplanned fire incidence and area burned increased in the mesic landscape, but decreased in the arid landscape in accordance with predictions based on these limiting factors. Area burned by large fires (greater than the 95th percentile of historical, unplanned fire size) increased with future climates in the mesic landscape. Simulated prescribed burning was more effective in reducing unplanned fire activity in the mesic landscape. However, the inhibitory effects of prescribed burning are predicted to be outweighed by climate change in the mesic landscape, whereas in the arid landscape prescribed burning reinforced a predicted decline in fire under climate change. The potentially contrasting direction of future changes to fire will have fundamentally different consequences for biodiversity in these contrasting ecosystems, and these will need to be accommodated through contrasting, innovative management solutions. © 2012 Blackwell Publishing Ltd.
Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts
NASA Astrophysics Data System (ADS)
Alcaraz-Segura, Domingo; Lomba, Angela; Sousa-Silva, Rita; Nieto-Lugilde, Diego; Alves, Paulo; Georges, Damien; Vicente, Joana R.; Honrado, João P.
2017-05-01
In a world facing rapid environmental changes, anticipating their impacts on biodiversity is of utmost relevance. Remotely-sensed Ecosystem Functional Attributes (EFAs) are promising predictors for Species Distribution Models (SDMs) by offering an early and integrative response of vegetation performance to environmental drivers. Species of high conservation concern would benefit the most from a better ability to anticipate changes in habitat suitability. Here we illustrate how yearly projections from SDMs based on EFAs could reveal short-term changes in potential habitat suitability, anticipating mid-term shifts predicted by climate-change-scenario models. We fitted two sets of SDMs for 41 plant species of conservation concern in the Iberian Peninsula: one calibrated with climate variables for baseline conditions and projected under two climate-change-scenarios (future conditions); and the other calibrated with EFAs for 2001 and projected annually from 2001 to 2013. Range shifts predicted by climate-based models for future conditions were compared to the 2001-2013 trends from EFAs-based models. Projections of EFAs-based models estimated changes (mostly contractions) in habitat suitability that anticipated, for the majority (up to 64%) of species, the mid-term shifts projected by traditional climate-change-scenario forecasting, and showed greater agreement with the business-as-usual scenario than with the sustainable-development one. This study shows how satellite-derived EFAs can be used as meaningful essential biodiversity variables in SDMs to provide early-warnings of range shifts and predictions of short-term fluctuations in suitable conditions for multiple species.
Prestoration: Using species in restoration that will persist now and into the future
Butterfield, B.J.; Copeland, Stella; Munson, Seth M.; Roybal, C.M.; Wood, Troy E.
2017-01-01
Climate change presents new challenges for selecting species for restoration. If migration fails to keep pace with climate change, as models predict, the most suitable sources for restoration may not occur locally at all. To address this issue we propose a strategy of “prestoration”: utilizing species in restoration for which a site represents suitable habitat now and into the future. Using the Colorado Plateau, USA as a case study, we assess the ability of grass species currently used regionally in restoration to persist into the future using projections of ecological niche models (or climate envelope models) across a suite of climate change scenarios. We then present a technique for identifying new species that best compensate for future losses of suitable habitat by current target species. We found that the current suite of species, selected by a group of experts, is predicted to perform reasonably well in the short-term, but that losses of prestorable habitat by mid-century would approach 40%. Using an algorithm to identify additional species, we found that fewer than ten species could compensate for nearly all of the losses incurred by the current target species. This case study highlights the utility of integrating ecological niche modeling and future climate forecasts to predict the utility of species in restoring under climate change across a wide range of spatial and temporal scales.
Book Review: Regional Hydrological Response to Climate Change
NASA Technical Reports Server (NTRS)
Koster, Randal
1998-01-01
The book being reviewed, Regional Hydrological Response to Climate Change, addresses the effects of global climate change, particularly global warming induced by greenhouse gas emissions, on hydrological budgets at the regional scale. As noted in its preface, the book consists of peer-reviewed papers delivered at scientific meetings held by the International Geographical Union Working Group on Regional Hydrological Response to Climate Change and Global Warming, supplemented with some additional chapters that round out coverage of the topic. The editors hope that this book will serve as "not only a record of current achievements, but also a stimulus to further hydrological research as the detail and spatial resolution of Global Climate Models improves". The reviewer found the background material on regional climatology to be valuable and the methodologies presented to be of interest. The value of the book is significantly diminished, however by the dated nature of some of the material and by large uncertainties in the predictions of regional precipitation change. The book would have been improved by a much more extensive documentation of the uncertainty associated with each step of the prediction process.
NASA Astrophysics Data System (ADS)
Davis, A. D.; Heimbach, P.; Marzouk, Y.
2017-12-01
We develop a Bayesian inverse modeling framework for predicting future ice sheet volume with associated formal uncertainty estimates. Marine ice sheets are drained by fast-flowing ice streams, which we simulate using a flowline model. Flowline models depend on geometric parameters (e.g., basal topography), parameterized physical processes (e.g., calving laws and basal sliding), and climate parameters (e.g., surface mass balance), most of which are unknown or uncertain. Given observations of ice surface velocity and thickness, we define a Bayesian posterior distribution over static parameters, such as basal topography. We also define a parameterized distribution over variable parameters, such as future surface mass balance, which we assume are not informed by the data. Hyperparameters are used to represent climate change scenarios, and sampling their distributions mimics internal variation. For example, a warming climate corresponds to increasing mean surface mass balance but an individual sample may have periods of increasing or decreasing surface mass balance. We characterize the predictive distribution of ice volume by evaluating the flowline model given samples from the posterior distribution and the distribution over variable parameters. Finally, we determine the effect of climate change on future ice sheet volume by investigating how changing the hyperparameters affects the predictive distribution. We use state-of-the-art Bayesian computation to address computational feasibility. Characterizing the posterior distribution (using Markov chain Monte Carlo), sampling the full range of variable parameters and evaluating the predictive model is prohibitively expensive. Furthermore, the required resolution of the inferred basal topography may be very high, which is often challenging for sampling methods. Instead, we leverage regularity in the predictive distribution to build a computationally cheaper surrogate over the low dimensional quantity of interest (future ice sheet volume). Continual surrogate refinement guarantees asymptotic sampling from the predictive distribution. Directly characterizing the predictive distribution in this way allows us to assess the ice sheet's sensitivity to climate variability and change.
NASA Astrophysics Data System (ADS)
Rani Nayak, Dali; Gottschalk, Pia; Evans, Chris; Smith, Pete; Smith, Jo
2010-05-01
Within Wales soils hold between 400-500 MtC, over half of this carbon is stored in organic and organo-mineral soil which cover less than 20% of the land area of Wales. It has been predicted that climate change will increasingly have an impact on the C stock of soils in Wales. Higher temperatures will increase the rate of decomposition of organic matter, leading to increased C losses. However increased net primary production (NPP), leading to increased inputs of organic matter, may offset this. Land use plays a major role in determining the level of soil C and the direction of change in status (soil as a source or sink). We present here an assessment of the effect of land use change and climate change on the upland soil carbon stock of Wales in 3 different catchments i.e. Migneint, Plynlimon and Pontbren using a process-based model of soil carbon and nitrogen dynamics, ECOSSE. The uncertainties introduced in the simulations by using only the data available at national scale are determined. The ECOSSE model (1,2) has been developed to simulate greenhouse gas emissions from both organic and mineral soils. ECOSSE was derived from RothC (3) and SUNDIAL (4,5) and predicts the impacts of changes in land use and climate on emissions and soil carbon stock. Simulated changes in soil C are dependent on the type of land use change, the soil type where the land use change is occurring, and the C content of soil under the initial and final land uses. At Migneint and Plynlimon, the major part of the losses occurs due to the conversion of semi-natural land to grassland. Reducing the land use change from semi-natural to grassland is the main measure needed to mitigate losses of soil C. At Pontbren, the model predicts a net gain in soil C with the predicted land use change, so there is no need to mitigate. Simulations of future changes in soil C to 2050 showed very small changes in soil C due to climate compared to changes due to land use change. At the selected catchments, changes in soil C due to the impacts of land use change were predicted to be up to 1000 times greater than the changes predicted due to climate change. This is encouraging, as it illustrates the great potential for C losses due to climate change to be mitigated by changing land use. 1. Smith P, et al 2007. SEERAD Report. ISBN 978 0 7559 1498 2. 166pp. 2. Smith JU, et al 2009. RERAD Report. In press. 3. Coleman K & Jenkinson DS 1996. In: Evaluation of Soil Organic Matter Models Using Existing, Long-Term Datasets, NATO ASI Series I, Vol.38 (eds Powlson DS, Smith P, Smith JU), pp. 237-246. Springer-Verlag, Heidelberg, Germany. 4. Bradbury NJ, et al 1993. Journal of Agricultural Science, Cambridge 121, 363-379. 5. Smith JU, et al 1996. Agronomy Journal 88, 38-42.
Updating Known Distribution Models for Forecasting Climate Change Impact on Endangered Species
Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo
2013-01-01
To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only. PMID:23840330
Updating known distribution models for forecasting climate change impact on endangered species.
Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo
2013-01-01
To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only.
NASA Astrophysics Data System (ADS)
Concepción Ramos, Maria
2017-04-01
This aim of the research was to analyse the effect of rainfall distribution and intensity on soil erosion in vines cultivated in the Mediterranean under the projected climate change scenario. The simulations were done at plot scale using the WEPP model. Climatic data for the period 1996-2014 were obtained from a meteorological station located 6km far from the plot. Soil characteristics such as texture, organic matter content, water retention capacity and infiltration were analysed. Runoff and soil losses were measured at four locations within the plot during 4 years and used to calibrate and validate the model. According to evidences recorded in the area, changes of rainfall intensities of 10 and 20% were considered for different rainfall distributions. The simulations were extended to the predicted changes for 2030, 2050 and 2070 based on the HadGEM2-CC under the Representative Concentration Pathways (RCPs) 8.5 scenario. WEPP model provided a suitable prediction of the seasonal runoff and erosion as simulated relatively well the runoff and erosion of the most important events although some deficiencies were found for those events that produced low runoff. The simulation confirmed the contribution of the extreme events to annual erosion rates in 70%, on average. The model responded to changes in precipitation predicted under a climate change scenario with a decrease of runoff and erosion, and with higher erosion rates for an increase in rainfall intensity. A 10% increase may imply erosion rates up to 22% greater for the scenario 2030, and despite the predicted decrease in precipitation for the scenario 2050, soil losses may be up to 40% greater than at present for some rainfall distributions and intensity rainfall increases of 20%. These findings show the need of considering rainfall intensity as one of the main driven factors when soil erosion rates under climate change are predicted. Keywords: extreme events, rainfall distribution, runoff, soil losses, wines, WEPP.
Thomassen, Henri A.; Fuller, Trevon; Asefi-Najafabady, Salvi; Shiplacoff, Julia A. G.; Mulembakani, Prime M.; Blumberg, Seth; Johnston, Sara C.; Kisalu, Neville K.; Kinkela, Timothée L.; Fair, Joseph N.; Wolfe, Nathan D.; Shongo, Robert L.; LeBreton, Matthew; Meyer, Hermann; Wright, Linda L.; Muyembe, Jean-Jacques; Buermann, Wolfgang; Okitolonda, Emile; Hensley, Lisa E.; Lloyd-Smith, James O.; Smith, Thomas B.; Rimoin, Anne W.
2013-01-01
Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts. PMID:23935820
Orwin, Kate H; Stevenson, Bryan A; Smaill, Simeon J; Kirschbaum, Miko U F; Dickie, Ian A; Clothier, Brent E; Garrett, Loretta G; van der Weerden, Tony J; Beare, Michael H; Curtin, Denis; de Klein, Cecile A M; Dodd, Michael B; Gentile, Roberta; Hedley, Carolyn; Mullan, Brett; Shepherd, Mark; Wakelin, Steven A; Bell, Nigel; Bowatte, Saman; Davis, Murray R; Dominati, Estelle; O'Callaghan, Maureen; Parfitt, Roger L; Thomas, Steve M
2015-08-01
Future human well-being under climate change depends on the ongoing delivery of food, fibre and wood from the land-based primary sector. The ability to deliver these provisioning services depends on soil-based ecosystem services (e.g. carbon, nutrient and water cycling and storage), yet we lack an in-depth understanding of the likely response of soil-based ecosystem services to climate change. We review the current knowledge on this topic for temperate ecosystems, focusing on mechanisms that are likely to underpin differences in climate change responses between four primary sector systems: cropping, intensive grazing, extensive grazing and plantation forestry. We then illustrate how our findings can be applied to assess service delivery under climate change in a specific region, using New Zealand as an example system. Differences in the climate change responses of carbon and nutrient-related services between systems will largely be driven by whether they are reliant on externally added or internally cycled nutrients, the extent to which plant communities could influence responses, and variation in vulnerability to erosion. The ability of soils to regulate water under climate change will mostly be driven by changes in rainfall, but can be influenced by different primary sector systems' vulnerability to soil water repellency and differences in evapotranspiration rates. These changes in regulating services resulted in different potentials for increased biomass production across systems, with intensively managed systems being the most likely to benefit from climate change. Quantitative prediction of net effects of climate change on soil ecosystem services remains a challenge, in part due to knowledge gaps, but also due to the complex interactions between different aspects of climate change. Despite this challenge, it is critical to gain the information required to make such predictions as robust as possible given the fundamental role of soils in supporting human well-being. © 2015 John Wiley & Sons Ltd.
DOE Contribution to the 2015 US CLIVAR Project Office Budget
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeWeaver, Eric; Patterson, Michael
The primary goal of the US Climate Variability and Predictability (CLIVAR) Project Office is to enable science community planning and implementation of research to understand and predict climate variability and change on intraseasonal-to-centennial timescales, through observations and modeling with emphasis on the role of the ocean and its interaction with other elements of the Earth system, and to serve the climate community and society through the coordination and facilitation of research on outstanding climate questions.
NASA Astrophysics Data System (ADS)
Lucas, S. E.
2017-12-01
The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). In 2017, the CVP Program had a call for proposals focused on observing and understanding processes affecting the propagation of intraseasonal oscillations in the Maritime Continent region. This poster will present the recently funded CVP projects, the expected scientific outcomes, the geographic areas of their work in the Maritime Continent region, and the collaborations with the Office of Naval Research, Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and other partners.
Malaria ecology and climate change
NASA Astrophysics Data System (ADS)
McCord, G. C.
2016-05-01
Understanding the costs that climate change will exact on society is crucial to devising an appropriate policy response. One of the channels through while climate change will affect human society is through vector-borne diseases whose epidemiology is conditioned by ambient ecology. This paper introduces the literature on malaria, its cost on society, and the consequences of climate change to the physics community in hopes of inspiring synergistic research in the area of climate change and health. It then demonstrates the use of one ecological indicator of malaria suitability to provide an order-of-magnitude assessment of how climate change might affect the malaria burden. The average of Global Circulation Model end-of-century predictions implies a 47% average increase in the basic reproduction number of the disease in today's malarious areas, significantly complicating malaria elimination efforts.
Direct and indirect effects of climate change on amphibian populations
Blaustein, Andrew R.; Walls, Susan C.; Bancroft, Betsy A.; Lawler, Joshua J.; Searle, Catherine L.; Gervasi, Stephanie S.
2010-01-01
As part of an overall decline in biodiversity, populations of many organisms are declining and species are being lost at unprecedented rates around the world. This includes many populations and species of amphibians. Although numerous factors are affecting amphibian populations, we show potential direct and indirect effects of climate change on amphibians at the individual, population and community level. Shifts in amphibian ranges are predicted. Changes in climate may affect survival, growth, reproduction and dispersal capabilities. Moreover, climate change can alter amphibian habitats including vegetation, soil, and hydrology. Climate change can influence food availability, predator-prey relationships and competitive interactions which can alter community structure. Climate change can also alter pathogen-host dynamics and greatly influence how diseases are manifested. Changes in climate can interact with other stressors such as UV-B radiation and contaminants. The interactions among all these factors are complex and are probably driving some amphibian population declines and extinctions.
Briner, Simon; Elkin, Ché; Huber, Robert
2013-11-15
Provisioning of ecosystem services (ES) in mountainous regions is predicted to be influenced by i) the direct biophysical impacts of climate change, ii) climate mediated land use change, and iii) socioeconomic driven changes in land use. The relative importance and the spatial distribution of these factors on forest and agricultural derived ES, however, is unclear, making the implementation of ES management schemes difficult. Using an integrated economic-ecological modeling framework, we evaluated the impact of these driving forces on the provision of forest and agricultural ES in a mountain region of southern Switzerland. Results imply that forest ES will be strongly influenced by the direct impact of climate change, but that changes in land use will have a comparatively small impact. The simulation of direct impacts of climate change affects forest ES at all elevations, while land use changes can only be found at high elevations. In contrast, changes to agricultural ES were found to be primarily due to shifts in economic conditions that alter land use and land management. The direct influence of climate change on agriculture is only predicted to be substantial at high elevations, while socioeconomic driven shifts in land use are projected to affect agricultural ES at all elevations. Our simulation results suggest that policy schemes designed to mitigate the negative impact of climate change on forests should focus on suitable adaptive management plans, accelerating adaptation processes for currently forested areas. To maintain provision of agricultural ES policy needs to focus on economic conditions rather than on supporting adaptation to new climate. Copyright © 2013 Elsevier Ltd. All rights reserved.
Forecasting the viability of sea turtle eggs in a warming world.
Pike, David A
2014-01-01
Animals living in tropical regions may be at increased risk from climate change because current temperatures at these locations already approach critical physiological thresholds. Relatively small temperature increases could cause animals to exceed these thresholds more often, resulting in substantial fitness costs or even death. Oviparous species could be especially vulnerable because the maximum thermal tolerances of incubating embryos is often lower than adult counterparts, and in many species mothers abandon the eggs after oviposition, rendering them immobile and thus unable to avoid extreme temperatures. As a consequence, the effects of climate change might become evident earlier and be more devastating for hatchling production in the tropics. Loggerhead sea turtles (Caretta caretta) have the widest nesting range of any living reptile, spanning temperate to tropical latitudes in both hemispheres. Currently, loggerhead sea turtle populations in the tropics produce nearly 30% fewer hatchlings per nest than temperate populations. Strong correlations between empirical hatching success and habitat quality allowed global predictions of the spatiotemporal impacts of climate change on this fitness trait. Under climate change, many sea turtle populations nesting in tropical environments are predicted to experience severe reductions in hatchling production, whereas hatching success in many temperate populations could remain unchanged or even increase with rising temperatures. Some populations could show very complex responses to climate change, with higher relative hatchling production as temperatures begin to increase, followed by declines as critical physiological thresholds are exceeded more frequently. Predicting when, where, and how climate change could impact the reproductive output of local populations is crucial for anticipating how a warming world will influence population size, growth, and stability.
NASA Astrophysics Data System (ADS)
Zhu, Jie; Sun, Ge; Li, Wenhong; Zhang, Yu; Miao, Guofang; Noormets, Asko; McNulty, Steve G.; King, John S.; Kumar, Mukesh; Wang, Xuan
2017-12-01
The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, groundwater recharge, and wildlife habitat. However, these wetland ecosystems are dependent on local climate and hydrology, and are therefore at risk due to climate and land use change. This study develops site-specific empirical hydrologic models for five forested wetlands with different characteristics by analyzing long-term observed meteorological and hydrological data. These wetlands represent typical cypress ponds/swamps, Carolina bays, pine flatwoods, drained pocosins, and natural bottomland hardwood ecosystems. The validated empirical models are then applied at each wetland to predict future water table changes using climate projections from 20 general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 5 (CMIP5) under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. We show that combined future changes in precipitation and potential evapotranspiration would significantly alter wetland hydrology including groundwater dynamics by the end of the 21st century. Compared to the historical period, all five wetlands are predicted to become drier over time. The mean water table depth is predicted to drop by 4 to 22 cm in response to the decrease in water availability (i.e., precipitation minus potential evapotranspiration) by the year 2100. Among the five examined wetlands, the depressional wetland in hot and humid Florida appears to be most vulnerable to future climate change. This study provides quantitative information on the potential magnitude of wetland hydrological response to future climate change in typical forested wetlands in the southeastern US.