Multi-scale predictions of coniferous forest mortality in the northern hemisphere
NASA Astrophysics Data System (ADS)
McDowell, N. G.
2015-12-01
Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.
Modeling the Earth system in the Mission to Planet Earth era
NASA Technical Reports Server (NTRS)
Unninayar, Sushel; Bergman, Kenneth H.
1993-01-01
A broad overview is made of global earth system modeling in the Mission to Planet Earth (MTPE) era for the multidisciplinary audience encompassed by the Global Change Research Program (GCRP). Time scales of global system fluctuation and change are described in Section 2. Section 3 provides a rubric for modeling the global earth system, as presently understood. The ability of models to predict the future state of the global earth system and the extent to which their predictions are reliable are covered in Sections 4 and 5. The 'engineering' use of global system models (and predictions) is covered in Section 6. Section 7 covers aspects of an increasing need for improved transform algorithms and better methods to assimilate this information into global models. Future monitoring and data requirements are detailed in Section 8. Section 9 covers the NASA-initiated concept 'Mission to Planet Earth,' which employs space and ground based measurement systems to provide the scientific basis for understanding global change. Section 10 concludes this review with general remarks concerning the state of global system modeling and observing technology and the need for future research.
Multi-scale predictions of massive conifer mortality due to chronic temperature rise
NASA Astrophysics Data System (ADS)
McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.
2016-03-01
Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
Multi-scale predictions of massive conifer mortality due to chronic temperature rise
McDowell, Nathan G.; Williams, A.P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, Sanna; Pangle, R.; Limousin, J.; Plaut, J.J.; Mackay, D.S.; Ogee, J.; Domec, Jean-Christophe; Allen, Craig D.; Fisher, Rosie A.; Jiang, X.; Muss, J.D.; Breshears, D.D.; Rauscher, Sara A.; Koven, C.
2016-01-01
Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
Global Weather Prediction and High-End Computing at NASA
NASA Technical Reports Server (NTRS)
Lin, Shian-Jiann; Atlas, Robert; Yeh, Kao-San
2003-01-01
We demonstrate current capabilities of the NASA finite-volume General Circulation Model an high-resolution global weather prediction, and discuss its development path in the foreseeable future. This model can be regarded as a prototype of a future NASA Earth modeling system intended to unify development activities cutting across various disciplines within the NASA Earth Science Enterprise.
Projections of Future Summertime Ozone over the U.S.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pfister, G. G.; Walters, Stacy; Lamarque, J. F.
This study uses a regional fully coupled chemistry-transport model to assess changes in surface ozone over the summertime U.S. between present and a 2050 future time period at high spatial resolution (12 km grid spacing) under the SRES A2 climate and RCP8.5 anthropogenic pre-cursor emission scenario. The impact of predicted changes in climate and global background ozone is estimated to increase surface ozone over most of the U.S; the 5th - 95th percentile range for daily 8-hour maximum surface ozone increases from 31-79 ppbV to 30-87 ppbV between the present and future time periods. The analysis of a set ofmore » meteorological drivers suggests that these mostly will add to increasing ozone, but the set of simulations conducted does not allow to separate this effect from that through enhanced global background ozone. Statistically the most robust positive feedbacks are through increased temperature, biogenic emissions and solar radiation. Stringent emission controls can counteract these feedbacks and if considered, we estimate large reductions in surface ozone with the 5th-95th percentile reduced to 27-55 ppbV. A comparison of the high-resolution projections to global model projections shows that even though the global model is biased high in surface ozone compared to the regional model and compared to observations, both the global and the regional model predict similar changes in ozone between the present and future time periods. However, on smaller spatial scales, the regional predictions show more pronounced changes between urban and rural regimes that cannot be resolved at the coarse resolution of global model. In addition, the sign of the changes in overall ozone mixing ratios can be different between the global and the regional predictions in certain regions, such as the Western U.S. This study confirms the key role of emission control strategies in future air quality predictions and demonstrates the need for considering degradation of air quality with future climate change in emission policy making. It also illustrates the need for high resolution modeling when the objective is to address regional and local air quality or establish links to human health and society.« less
Memory underpinnings of future intentions: Would you like to see the sequel?
Stragà, Marta; Del Missier, Fabio; Marcatto, Francesco; Ferrante, Donatella
2017-01-01
In two studies, we investigated the memory underpinnings of future intentions related to past hedonic experiences. Preceding research did not make clear whether the specific memory processes supporting the expression of intentions about the future involve global judgments of the past experience (general affective evaluations formed on-line) or judgments derived from the episodic recollection of the past. Adapting a correlational paradigm previously employed to study future intentions, and applying it to the experience of watching a movie, we comparatively tested the influence of global retrospective evaluations vs. episodic-derived evaluations on future intentions. In Study 1, in which the intentions involved a future experience that was very similar to an overall past one (e.g., seeing the movie sequel), the findings showed that participants relied only on global judgments to form future intentions. In Study 2, in which the global judgment on the past was less diagnostic because the future intentions referred to specific parts of the past experience (e.g., watching a movie centered on a minor character in the previously seen movie), the results indicated that relevant episodic memories provided an essential contribution to the prediction of future intentions. These findings are in agreement with the predictions of the accessibility-diagnosticity framework and they show that global judgments and episodic memories of a past experience contribute differentially to diverse kinds of future intentions.
Memory underpinnings of future intentions: Would you like to see the sequel?
Marcatto, Francesco; Ferrante, Donatella
2017-01-01
In two studies, we investigated the memory underpinnings of future intentions related to past hedonic experiences. Preceding research did not make clear whether the specific memory processes supporting the expression of intentions about the future involve global judgments of the past experience (general affective evaluations formed on-line) or judgments derived from the episodic recollection of the past. Adapting a correlational paradigm previously employed to study future intentions, and applying it to the experience of watching a movie, we comparatively tested the influence of global retrospective evaluations vs. episodic-derived evaluations on future intentions. In Study 1, in which the intentions involved a future experience that was very similar to an overall past one (e.g., seeing the movie sequel), the findings showed that participants relied only on global judgments to form future intentions. In Study 2, in which the global judgment on the past was less diagnostic because the future intentions referred to specific parts of the past experience (e.g., watching a movie centered on a minor character in the previously seen movie), the results indicated that relevant episodic memories provided an essential contribution to the prediction of future intentions. These findings are in agreement with the predictions of the accessibility-diagnosticity framework and they show that global judgments and episodic memories of a past experience contribute differentially to diverse kinds of future intentions. PMID:28448567
Predicting future uncertainty constraints on global warming projections
Shiogama, H.; Stone, D.; Emori, S.; ...
2016-01-11
Projections of global mean temperature changes (ΔT) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by "current knowledge" of the ΔTs uncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of ΔT can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudomore » observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the ΔTs uncertainty in the 2040 s by 2029, and more than 60% of the ΔTs uncertainty in the 2090 s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2°C (3°C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change.« less
Predicting future uncertainty constraints on global warming projections
Shiogama, H.; Stone, D.; Emori, S.; Takahashi, K.; Mori, S.; Maeda, A.; Ishizaki, Y.; Allen, M. R.
2016-01-01
Projections of global mean temperature changes (ΔT) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by “current knowledge” of the ΔTs uncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of ΔT can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudo observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the ΔTs uncertainty in the 2040 s by 2029, and more than 60% of the ΔTs uncertainty in the 2090 s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2 °C (3 °C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change. PMID:26750491
Predicting future uncertainty constraints on global warming projections
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shiogama, H.; Stone, D.; Emori, S.
Projections of global mean temperature changes (ΔT) in the future are associated with intrinsic uncertainties. Much climate policy discourse has been guided by "current knowledge" of the ΔTs uncertainty, ignoring the likely future reductions of the uncertainty, because a mechanism for predicting these reductions is lacking. By using simulations of Global Climate Models from the Coupled Model Intercomparison Project Phase 5 ensemble as pseudo past and future observations, we estimate how fast and in what way the uncertainties of ΔT can decline when the current observation network of surface air temperature is maintained. At least in the world of pseudomore » observations under the Representative Concentration Pathways (RCPs), we can drastically reduce more than 50% of the ΔTs uncertainty in the 2040 s by 2029, and more than 60% of the ΔTs uncertainty in the 2090 s by 2049. Under the highest forcing scenario of RCPs, we can predict the true timing of passing the 2°C (3°C) warming threshold 20 (30) years in advance with errors less than 10 years. These results demonstrate potential for sequential decision-making strategies to take advantage of future progress in understanding of anthropogenic climate change.« less
Gloom and doom? The future of marine capture fisheries
Garcia, Serge M.; Grainger, Richard J. R.
2005-01-01
Predicting global fisheries is a high-order challenge but predictions have been made and updates are needed. Past forecasts, present trends and perspectives of key parameters of the fisheries—including potential harvest, state of stocks, supply and demand, trade, fishing technology and governance—are reviewed in detail, as the basis for new forecasts and forecasting performance assessment. The future of marine capture fisheries will be conditioned by the political, social and economic evolution of the world within which they operate. Consequently, recent global scenarios for the future world are reviewed, with the emphasis on fisheries. The main driving forces (e.g. global economic development, demography, environment, public awareness, information technology, energy, ethics) including aquaculture are described. Outlooks are provided for each aspect of the fishery sector. The conclusion puts these elements in perspective and offers the authors’ personal interpretation of the possible future pathway of fisheries, the uncertainty about it and the still unanswered questions of direct relevance in shaping that future. PMID:15713587
Jarnevich, Catherine S.; Young, Nicholas E; Sheffels, Trevor R.; Carter, Jacoby; Systma, Mark D.; Talbert, Colin
2017-01-01
Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.
NASA Astrophysics Data System (ADS)
Felkner, John Sames
The scale and extent of global land use change is massive, and has potentially powerful effects on the global climate and global atmospheric composition (Turner & Meyer, 1994). Because of this tremendous change and impact, there is an urgent need for quantitative, empirical models of land use change, especially predictive models with an ability to capture the trajectories of change (Agarwal, Green, Grove, Evans, & Schweik, 2000; Lambin et al., 1999). For this research, a spatial statistical predictive model of land use change was created and run in two provinces of Thailand. The model utilized an extensive spatial database, and used a classification tree approach for explanatory model creation and future land use (Breiman, Friedman, Olshen, & Stone, 1984). Eight input variables were used, and the trees were run on a dependent variable of land use change measured from 1979 to 1989 using classified satellite imagery. The derived tree models were used to create probability of change surfaces, and these were then used to create predicted land cover maps for 1999. These predicted 1999 maps were compared with actual 1999 landcover derived from 1999 Landsat 7 imagery. The primary research hypothesis was that an explanatory model using both economic and environmental input variables would better predict future land use change than would either a model using only economic variables or a model using only environmental. Thus, the eight input variables included four economic and four environmental variables. The results indicated a very slight superiority of the full models to predict future agricultural change and future deforestation, but a slight superiority of the economic models to predict future built change. However, the margins of superiority were too small to be statistically significant. The resulting tree structures were used, however, to derive a series of principles or "rules" governing land use change in both provinces. The model was able to predict future land use, given a series of assumptions, with 90 percent overall accuracies. The model can be used in other developing or developed country locations for future land use prediction, determination of future threatened areas, or to derive "rules" or principles driving land use change.
Increase in observed net carbon dioxide uptake by land and oceans during the past 50 years.
Ballantyne, A P; Alden, C B; Miller, J B; Tans, P P; White, J W C
2012-08-02
One of the greatest sources of uncertainty for future climate predictions is the response of the global carbon cycle to climate change. Although approximately one-half of total CO(2) emissions is at present taken up by combined land and ocean carbon reservoirs, models predict a decline in future carbon uptake by these reservoirs, resulting in a positive carbon-climate feedback. Several recent studies suggest that rates of carbon uptake by the land and ocean have remained constant or declined in recent decades. Other work, however, has called into question the reported decline. Here we use global-scale atmospheric CO(2) measurements, CO(2) emission inventories and their full range of uncertainties to calculate changes in global CO(2) sources and sinks during the past 50 years. Our mass balance analysis shows that net global carbon uptake has increased significantly by about 0.05 billion tonnes of carbon per year and that global carbon uptake doubled, from 2.4 ± 0.8 to 5.0 ± 0.9 billion tonnes per year, between 1960 and 2010. Therefore, it is very unlikely that both land and ocean carbon sinks have decreased on a global scale. Since 1959, approximately 350 billion tonnes of carbon have been emitted by humans to the atmosphere, of which about 55 per cent has moved into the land and oceans. Thus, identifying the mechanisms and locations responsible for increasing global carbon uptake remains a critical challenge in constraining the modern global carbon budget and predicting future carbon-climate interactions.
Depletion of heterogeneous source species pools predicts future invasion rates
Andrew M. Liebhold; Eckehard G. Brockerhoff; Mark Kimberley; Jacqueline Beggs
2017-01-01
Predicting how increasing rates of global trade will result in new establishments of potentially damaging invasive species is a question of critical importance to the development of national and international policies aimed at minimizing future invasions. Centuries of historical movement and establishment of invading species may have depleted the supply of species...
Assis, J; Serrão, E A; Claro, B; Perrin, C; Pearson, G A
2014-06-01
The climate-driven dynamics of species ranges is a critical research question in evolutionary ecology. We ask whether present intraspecific diversity is determined by the imprint of past climate. This is an ongoing debate requiring interdisciplinary examination of population genetic pools and persistence patterns across global ranges. Previously, contrasting inferences and predictions have resulted from distinct genomic coverage and/or geographical information. We aim to describe and explain the causes of geographical contrasts in genetic diversity and their consequences for the future baseline of the global genetic pool, by comparing present geographical distribution of genetic diversity and differentiation with predictive species distribution modelling (SDM) during past extremes, present time and future climate scenarios for a brown alga, Fucus vesiculosus. SDM showed that both atmospheric and oceanic variables shape the global distribution of intertidal species, revealing regions of persistence, extinction and expansion during glacial and postglacial periods. These explained the distribution and structure of present genetic diversity, consisting of differentiated genetic pools with maximal diversity in areas of long-term persistence. Most of the present species range comprises postglacial expansion zones and, in contrast to highly dispersive marine organisms, expansions involved only local fronts, leaving distinct genetic pools at rear edges. Besides unravelling a complex phylogeographical history and showing congruence between genetic diversity and persistent distribution zones, supporting the hypothesis of niche conservatism, range shifts and loss of unique genetic diversity at the rear edge were predicted for future climate scenarios, impoverishing the global gene pool. © 2014 John Wiley & Sons Ltd.
Optimal stomatal behaviour around the world
NASA Astrophysics Data System (ADS)
Lin, Yan-Shih; Medlyn, Belinda E.; Duursma, Remko A.; Prentice, I. Colin; Wang, Han; Baig, Sofia; Eamus, Derek; de Dios, Victor Resco; Mitchell, Patrick; Ellsworth, David S.; de Beeck, Maarten Op; Wallin, Göran; Uddling, Johan; Tarvainen, Lasse; Linderson, Maj-Lena; Cernusak, Lucas A.; Nippert, Jesse B.; Ocheltree, Troy W.; Tissue, David T.; Martin-Stpaul, Nicolas K.; Rogers, Alistair; Warren, Jeff M.; de Angelis, Paolo; Hikosaka, Kouki; Han, Qingmin; Onoda, Yusuke; Gimeno, Teresa E.; Barton, Craig V. M.; Bennie, Jonathan; Bonal, Damien; Bosc, Alexandre; Löw, Markus; Macinins-Ng, Cate; Rey, Ana; Rowland, Lucy; Setterfield, Samantha A.; Tausz-Posch, Sabine; Zaragoza-Castells, Joana; Broadmeadow, Mark S. J.; Drake, John E.; Freeman, Michael; Ghannoum, Oula; Hutley, Lindsay B.; Kelly, Jeff W.; Kikuzawa, Kihachiro; Kolari, Pasi; Koyama, Kohei; Limousin, Jean-Marc; Meir, Patrick; Lola da Costa, Antonio C.; Mikkelsen, Teis N.; Salinas, Norma; Sun, Wei; Wingate, Lisa
2015-05-01
Stomatal conductance (gs) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of gs in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of gs that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed gs obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs according to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model and the leaf and wood economics spectrum. We also demonstrate a global relationship with climate. These findings provide a robust theoretical framework for understanding and predicting the behaviour of gs across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.
Dengue: recent past and future threats
Rogers, David J.
2015-01-01
This article explores four key questions about statistical models developed to describe the recent past and future of vector-borne diseases, with special emphasis on dengue: (1) How many variables should be used to make predictions about the future of vector-borne diseases?(2) Is the spatial resolution of a climate dataset an important determinant of model accuracy?(3) Does inclusion of the future distributions of vectors affect predictions of the futures of the diseases they transmit?(4) Which are the key predictor variables involved in determining the distributions of vector-borne diseases in the present and future?Examples are given of dengue models using one, five or 10 meteorological variables and at spatial resolutions of from one-sixth to two degrees. Model accuracy is improved with a greater number of descriptor variables, but is surprisingly unaffected by the spatial resolution of the data. Dengue models with a reduced set of climate variables derived from the HadCM3 global circulation model predictions for the 1980s are improved when risk maps for dengue's two main vectors (Aedes aegypti and Aedes albopictus) are also included as predictor variables; disease and vector models are projected into the future using the global circulation model predictions for the 2020s, 2040s and 2080s. The Garthwaite–Koch corr-max transformation is presented as a novel way of showing the relative contribution of each of the input predictor variables to the map predictions. PMID:25688021
Forest landscape mosaics: Disturbance, restoration, and management at times of global change
Kalev Jogiste; Bengt Gunnar Jonsson; Timo Kuuluvainen; Sylvie Gauthier; W. Keith Moser
2015-01-01
Potential effects of hypothesized anthropogenic climate change are raising concerns about the sustainability of development in terms of both people and the rest of the environment. Land use change at the global scale presents many challenges for the research community. Past land use has a definite effect on future ecosystems, but it is challenging to predict future...
Predicting global change effects on forest biomass and composition in south-central Siberia
Eric Gustafson; Anatoly D. Shvidenko; Brian R. Sturtevant; Robert M. Scheller
2010-01-01
Multiple global changes such as timber harvesting in areas not previously disturbed by cutting and climate change will undoubtedly affect the composition and spatial distribution of boreal forests, which will, in turn, affect the ability of these forests to retain carbon and maintain biodiversity. To predict future states of the boreal forest reliably, it is necessary...
Future hotspots of terrestrial mammal loss
Visconti, Piero; Pressey, Robert L.; Giorgini, Daniele; Maiorano, Luigi; Bakkenes, Michel; Boitani, Luigi; Alkemade, Rob; Falcucci, Alessandra; Chiozza, Federica; Rondinini, Carlo
2011-01-01
Current levels of endangerment and historical trends of species and habitats are the main criteria used to direct conservation efforts globally. Estimates of future declines, which might indicate different priorities than past declines, have been limited by the lack of appropriate data and models. Given that much of conservation is about anticipating and responding to future threats, our inability to look forward at a global scale has been a major constraint on effective action. Here, we assess the geography and extent of projected future changes in suitable habitat for terrestrial mammals within their present ranges. We used a global earth-system model, IMAGE, coupled with fine-scale habitat suitability models and parametrized according to four global scenarios of human development. We identified the most affected countries by 2050 for each scenario, assuming that no additional conservation actions other than those described in the scenarios take place. We found that, with some exceptions, most of the countries with the largest predicted losses of suitable habitat for mammals are in Africa and the Americas. African and North American countries were also predicted to host the most species with large proportional global declines. Most of the countries we identified as future hotspots of terrestrial mammal loss have little or no overlap with the present global conservation priorities, thus confirming the need for forward-looking analyses in conservation priority setting. The expected growth in human populations and consumption in hotspots of future mammal loss mean that local conservation actions such as protected areas might not be sufficient to mitigate losses. Other policies, directed towards the root causes of biodiversity loss, are required, both in Africa and other parts of the world. PMID:21844048
Uden, Daniel R.; Allen, Craig R.; Bishop, Andrew A.; Grosse, Roger; Jorgensen, Christopher F.; LaGrange, Theodore G.; Stutheit, Randy G.; Vrtiska, Mark P.
2015-01-01
In the present period of rapid, worldwide change in climate and landuse (i.e., global change), successful biodiversity conservation warrants proactive management responses, especially for long-distance migratory species. However, the development and implementation of management strategies can be impeded by high levels of uncertainty and low levels of control over potentially impactful future events and their effects. Scenario planning and modeling are useful tools for expanding perspectives and informing decisions under these conditions. We coupled scenario planning and statistical modeling to explain and predict playa wetland inundation (i.e., presence/absence of water) and ponded area (i.e., extent of water) in the Rainwater Basin, an anthropogenically altered landscape that provides critical stopover habitat for migratory waterbirds. Inundation and ponded area models for total wetlands, those embedded in rowcrop fields, and those not embedded in rowcrop fields were trained and tested with wetland ponding data from 2004 and 2006–2009, and then used to make additional predictions under two alternative climate change scenarios for the year 2050, yielding a total of six predictive models and 18 prediction sets. Model performance ranged from moderate to good, with inundation models outperforming ponded area models, and models for non-rowcrop-embedded wetlands outperforming models for total wetlands and rowcrop-embedded wetlands. Model predictions indicate that if the temperature and precipitation changes assumed under our climate change scenarios occur, wetland stopover habitat availability in the Rainwater Basin could decrease in the future. The results of this and similar studies could be aggregated to increase knowledge about the potential spatial and temporal distributions of future stopover habitat along migration corridors, and to develop and prioritize multi-scale management actions aimed at mitigating the detrimental effects of global change on migratory waterbird populations.
An uncertain future for lightning
NASA Astrophysics Data System (ADS)
Murray, Lee T.
2018-03-01
The most commonly used method for representing lightning in global atmospheric models generally predicts lightning increases in a warmer world. A new scheme finds the opposite result, directly challenging the predictive skill of an old stalwart.
Optimal stomatal behaviour around the world
Lin, Yan-Shih; Medlyn, Belinda E.; Duursma, Remko A.; ...
2015-03-02
Stomatal conductance (g s) is a key land-surface attribute as it links transpiration, the dominant component of global land evapotranspiration, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of g s in predictions of global water and carbon cycle changes, a global-scale database and an associated globally applicable model of g s that allow predictions of stomatal behaviour are lacking. Here, we present a database of globally distributed g s obtained in the field for a wide range of plant functional types (PFTs) and biomes. We find that stomatal behaviour differs among PFTs accordingmore » to their marginal carbon cost of water use, as predicted by the theory underpinning the optimal stomatal model 1 and the leaf and wood economics spectrum 2,3. We also demonstrate a global relationship with climate. In conclusion, these findings provide a robust theoretical framework for understanding and predicting the behaviour of g s across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of ecosystem productivity, energy balance and ecohydrological processes in a future changing climate.« less
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.
Importance of vegetation distribution for future carbon balance
NASA Astrophysics Data System (ADS)
Ahlström, A.; Xia, J.; Arneth, A.; Luo, Y.; Smith, B.
2015-12-01
Projections of future terrestrial carbon uptake vary greatly between simulations. Net primary production (NPP), wild fires, vegetation dynamics (including biome shifts) and soil decomposition constitute the main processes governing the response of the terrestrial carbon cycle in a changing climate. While primary production and soil respiration are relatively well studied and implemented in all global ecosystem models used to project the future land sink of CO2, vegetation dynamics are less studied and not always represented in global models. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality and the associated turnover and proven skill in predicting vegetation distribution and succession. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the CMIP5 ensemble under RCP8.5 radiative forcing at year 2085. We exchanged carbon cycle processes between these 13 simulations and investigate the changes predicted by the emulator. This method allowed us to partition the entire ensemble carbon uptake uncertainty into individual processes. We found that NPP, vegetation dynamics (including biome shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33% respectively of uncertainties in modeled global C-uptake. Uncertainty due to vegetation dynamics was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by shifts in vegetation distribution, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.
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.
Mercado, Lina M; Medlyn, Belinda E; Huntingford, Chris; Oliver, Rebecca J; Clark, Douglas B; Sitch, Stephen; Zelazowski, Przemyslaw; Kattge, Jens; Harper, Anna B; Cox, Peter M
2018-06-01
Plant temperature responses vary geographically, reflecting thermally contrasting habitats and long-term species adaptations to their climate of origin. Plants also can acclimate to fast temporal changes in temperature regime to mitigate stress. Although plant photosynthetic responses are known to acclimate to temperature, many global models used to predict future vegetation and climate-carbon interactions do not include this process. We quantify the global and regional impacts of biogeographical variability and thermal acclimation of temperature response of photosynthetic capacity on the terrestrial carbon (C) cycle between 1860 and 2100 within a coupled climate-carbon cycle model, that emulates 22 global climate models. Results indicate that inclusion of biogeographical variation in photosynthetic temperature response is most important for present-day and future C uptake, with increasing importance of thermal acclimation under future warming. Accounting for both effects narrows the range of predictions of the simulated global land C storage in 2100 across climate projections (29% and 43% globally and in the tropics, respectively). Contrary to earlier studies, our results suggest that thermal acclimation of photosynthetic capacity makes tropical and temperate C less vulnerable to warming, but reduces the warming-induced C uptake in the boreal region under elevated CO 2 . © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.
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 ...
Global-local methodologies and their application to nonlinear analysis
NASA Technical Reports Server (NTRS)
Noor, Ahmed K.
1989-01-01
An assessment is made of the potential of different global-local analysis strategies for predicting the nonlinear and postbuckling responses of structures. Two postbuckling problems of composite panels are used as benchmarks and the application of different global-local methodologies to these benchmarks is outlined. The key elements of each of the global-local strategies are discussed and future research areas needed to realize the full potential of global-local methodologies are identified.
Effect of climate change on shoreline shifts at a straight and continuous coast
NASA Astrophysics Data System (ADS)
Rajasree, B. R.; Deo, M. C.; Sheela Nair, L.
2016-12-01
The prediction of the rate of shoreline shifts as well as that of erosion and accretion over future at a given location is traditionally done on the basis of analysis of past wave data. However under the changing climate affected by global warming it is better done considering the projected wave conditions over the future. The same is demonstrated in this work with respect to a stretch of coastline at 'Udupi' along the west coast of India. The shoreline changes in the past are first determined with the help of historic satellite images. A numerical shoreline model is later run on the basis of wave simulations of past 35 years as well as future 35 years. The latter wave conditions are obtained from wind projections corresponding to a high resolution regional climate model run for a moderate pathway of global warming. Alternatively prediction of the changes over future 35 years is also made by using the soft computing tool of artificial neural network (ANN) trained with the help of past satellite images. The results indicate that the area under consideration presently undergoes considerable erosion and this process will accelerate in future. The volume of annual sediment transport will also substantially increase over the future. The alternative computations made with the help of an ANN confirmed the future rising trend of erosion, albeit at smaller rate than the numerically predicted one.
Predictive models of forest dynamics.
Purves, Drew; Pacala, Stephen
2008-06-13
Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.
NASA Technical Reports Server (NTRS)
Noor, Ahmed K.
1986-01-01
An assessment is made of the potential of different global-local analysis strategies for predicting the nonlinear and postbuckling responses of structures. Two postbuckling problems of composite panels are used as benchmarks and the application of different global-local methodologies to these benchmarks is outlined. The key elements of each of the global-local strategies are discussed and future research areas needed to realize the full potential of global-local methodologies are identified.
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
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
Future perspective and healthy lifestyle choices in adulthood.
Tasdemir-Ozdes, Aylin; Strickland-Hughes, Carla M; Bluck, Susan; Ebner, Natalie C
2016-09-01
Regardless of age, making healthy lifestyle choices is prudent. Despite that, individuals of all ages sometimes have difficulty choosing the healthy option. We argue that individuals' view of the future and position in the life span affects their current lifestyle choices. We capture the multidimensionality of future thinking by assessing 3 types of future perspective. Younger and older men and women (N = 127) reported global future time perspective, future health perspective, and perceived importance of future health-related events. They also rated their likelihood of making healthy lifestyle choices. As predicted, older participants indicated greater intention to make healthy choices in their current life than did younger participants. Compared to younger participants, older participants reported shorter global future time perspective and anticipated worse future health but perceived future health-related events as more important. Having a positive view of one's future health and seeing future health-related events as important were related to greater intention to make healthy lifestyle choices, but greater global future time perspective was not directly related to healthy choices. However, follow-up analyses suggested that greater global future time perspective indirectly affected healthy choices via a more positive view of future health. None of these relations were moderated by age. Individuals' perspective on the future is shown to be an important multidimensional construct affecting everyday healthy lifestyle choices for both younger and older adults. Implications for encouraging healthy choices across the adult life span are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Can future land use change be usefully predicted?
NASA Astrophysics Data System (ADS)
Ramankutty, N.; Coomes, O.
2011-12-01
There has been increasing recognition over the last decade that land use and land cover change is an important driver of global environmental change. Consequently, there have been growing efforts to understanding processes of land change from local-to-global scales, and to develop models to predict future changes in the land. However, we believe that such efforts are hampered by limited attention being paid to the critical points of land change. Here, we present a framework for understanding land use change by distinguishing within-regime land-use dynamics from land-use regime shifts. Illustrative historical examples reveal the significance of land-use regime shifts. We further argue that the land-use literature predominantly demonstrates a good understanding (with predictive power) of within-regime dynamics, while understanding of land-use regime shifts is limited to ex post facto explanations with limited predictive capability. The focus of land use change science needs to be redirected toward studying land-use regime shifts if we are to have any hope of making useful future projections. We present a preliminary framework for understanding land-use regime-shifts, using two case studies in Latin America as examples. We finally discuss the implications of our proposal for land change science.
Perspectives on the future of the electric utility industry
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tonn, B.; Schaffhauser, A.
1994-04-01
This report offers perspectives on the future of the electric utility industry. These perspectives will be used in further research to assess the prospects for Integrated Resource Planning (IRP). The perspectives are developed first by examining economic, political and regulatory, societal, technological, and environmental trends that are (1) national and global in scope and (2) directly related to the electric utility industry. Major national and global trends include increasing global economic competition, increasing political and ethnic strife, rapidly changing technologies, and increasing worldwide concern about the environment. Major trends in the utility industry include increasing competition in generation; changing patternsmore » of electricity demand; increasing use of information technology to control power systems; and increasing implementation of environmental controls. Ways in which the national and global trends may directly affect the utility industry are also explored. The trends are used to construct three global and national scenarios- ``business as usual,`` ``technotopia future,`` and ``fortress state`` -and three electric utility scenarios- ``frozen in headlights,`` ``megaelectric,`` and ``discomania.`` The scenarios are designed to be thought provoking descriptions of potential futures, not predictions of the future, although three key variables are identified that will have significant impacts on which future evolves-global climate change, utility technologies, and competition. While emphasis needs to be placed on understanding the electric utility scenarios, the interactions between the two sets of scenarios is also of interest.« less
Climate Change: Past, Present, and Future
NASA Astrophysics Data System (ADS)
Chapman, David S.; Davis, Michael G.
2010-09-01
Questions about global warming concern climate scientists and the general public alike. Specifically, what are the reliable surface temperature reconstructions over the past few centuries? And what are the best predictions of global temperature change the Earth might expect for the next century? Recent publications [National Research Council (NRC), 2006; Intergovernmental Panel on Climate Change (IPCC), 2007] permit these questions to be answered in a single informative illustration by assembling temperature reconstructions of the past thousand years with predictions for the next century. The result, shown in Figure 1, illustrates present and future warming in the context of natural variations in the past [see also Oldfield and Alverson, 2003]. To quote a Chinese proverb, “A picture's meaning can express ten thousand words.” Because it succinctly captures past inferences and future projections of climate, the illustration should be of interest to scientists, educators, policy makers, and the public.
A Global Perspective: NASA's Prediction of Worldwide Energy Resources (POWER) Project
NASA Technical Reports Server (NTRS)
Zhang, Taiping; Stackhouse, Paul W., Jr.; Chandler, William S.; Hoell, James M.; Westberg, David; Whitlock, Charles H.
2007-01-01
The Prediction of the Worldwide Energy Resources (POWER) Project, initiated under the NASA Science Mission Directorate Applied Science Energy Management Program, synthesizes and analyzes data on a global scale that are invaluable to the renewable energy industries, especially to the solar and wind energy sectors. The POWER project derives its data primarily from NASA's World Climate Research Programme (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Version 2.9) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (Version 4). The latest development of the NASA POWER Project and its plans for the future are presented in this paper.
Anantha M. Prasad; Louis R. Iverson; Andy Liaw; Andy Liaw
2006-01-01
We evaluated four statistical models - Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS) - for predictive vegetation mapping under current and future climate scenarios according to the Canadian Climate Centre global circulation model.
Climate, CO2, and demographic impacts on global wildfire emissions
NASA Astrophysics Data System (ADS)
Knorr, W.; Jiang, L.; Arneth, A.
2015-09-01
Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilization of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation. Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation - wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations comprise Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models using two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs), sensitivity tests for the effect of climate and CO2, as well as a sensitivity analysis using two alternative parameterisations of the semi-empirical burned-area model. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load, and faster litter turnover in a warmer climate.
Climate, CO2 and human population impacts on global wildfire emissions
NASA Astrophysics Data System (ADS)
Knorr, W.; Jiang, L.; Arneth, A.
2016-01-01
Wildfires are by far the largest contributor to global biomass burning and constitute a large global source of atmospheric traces gases and aerosols. Such emissions have a considerable impact on air quality and constitute a major health hazard. Biomass burning also influences the radiative balance of the atmosphere and is thus not only of societal, but also of significant scientific interest. There is a common perception that climate change will lead to an increase in emissions as hot and dry weather events that promote wildfire will become more common. However, even though a few studies have found that the inclusion of CO2 fertilisation of photosynthesis and changes in human population patterns will tend to somewhat lower predictions of future wildfire emissions, no such study has included full ensemble ranges of both climate predictions and population projections, including the effect of different degrees of urbanisation.
Here, we present a series of 124 simulations with the LPJ-GUESS-SIMFIRE global dynamic vegetation-wildfire model, including a semi-empirical formulation for the prediction of burned area based on fire weather, fuel continuity and human population density. The simulations use Climate Model Intercomparison Project 5 (CMIP5) climate predictions from eight Earth system models. These were combined with two Representative Concentration Pathways (RCPs) and five scenarios of future human population density based on the series of Shared Socioeconomic Pathways (SSPs) to assess the sensitivity of emissions to the effect of climate, CO2 and humans. In addition, two alternative parameterisations of the semi-empirical burned-area model were applied. Contrary to previous work, we find no clear future trend of global wildfire emissions for the moderate emissions and climate change scenario based on the RCP 4.5. Only historical population change introduces a decline by around 15 % since 1900. Future emissions could either increase for low population growth and fast urbanisation, or continue to decline for high population growth and slow urbanisation. Only for high future climate change (RCP8.5), wildfire emissions start to rise again after ca. 2020 but are unlikely to reach the levels of 1900 by the end of the 21st century. We find that climate warming will generally increase the risk of fire, but that this is only one of several equally important factors driving future levels of wildfire emissions, which include population change, CO2 fertilisation causing woody thickening, increased productivity and fuel load and faster litter turnover in a warmer climate.
Wetter subtropics in a warmer world: Contrasting past and future hydrological cycles
NASA Astrophysics Data System (ADS)
Burls, Natalie J.; Fedorov, Alexey V.
2017-12-01
During the warm Miocene and Pliocene Epochs, vast subtropical regions had enough precipitation to support rich vegetation and fauna. Only with global cooling and the onset of glacial cycles some 3 Mya, toward the end of the Pliocene, did the broad patterns of arid and semiarid subtropical regions become fully developed. However, current projections of future global warming caused by CO2 rise generally suggest the intensification of dry conditions over these subtropical regions, rather than the return to a wetter state. What makes future projections different from these past warm climates? Here, we investigate this question by comparing a typical quadrupling-of-CO2 experiment with a simulation driven by sea-surface temperatures closely resembling available reconstructions for the early Pliocene. Based on these two experiments and a suite of other perturbed climate simulations, we argue that this puzzle is explained by weaker atmospheric circulation in response to the different ocean surface temperature patterns of the Pliocene, specifically reduced meridional and zonal temperature gradients. Thus, our results highlight that accurately predicting the response of the hydrological cycle to global warming requires predicting not only how global mean temperature responds to elevated CO2 forcing (climate sensitivity) but also accurately quantifying how meridional sea-surface temperature patterns will change (structural climate sensitivity).
NASA Astrophysics Data System (ADS)
Exports Science Definition Team
2016-04-01
Ocean ecosystems play a critical role in the Earth's carbon cycle and its quantification on global scales remains one of the greatest challenges in global ocean biogeochemistry. The goal of the EXport Processes in the Ocean from Remote Sensing (EXPORTS) science plan is to develop a predictive understanding of the export and fate of global ocean primary production and its implications for the Earth's carbon cycle in present and future climates. NASA's satellite ocean-color data record has revolutionized our understanding of global marine systems. EXPORTS is designed to advance the utility of NASA ocean color assets to predict how changes in ocean primary production will impact the global carbon cycle. EXPORTS will create a predictive understanding of both the export of organic carbon from the euphotic zone and its fate in the underlying "twilight zone" (depths of 500 m or more) where variable fractions of exported organic carbon are respired back to CO2. Ultimately, it is the sequestration of deep organic carbon transport that defines the impact of ocean biota on atmospheric CO2 levels and hence climate. EXPORTS will generate a new, detailed understanding of ocean carbon transport processes and pathways linking upper ocean phytoplankton processes to the export and fate of organic matter in the underlying twilight zone using a combination of field campaigns, remote sensing and numerical modeling. The overarching objective for EXPORTS is to ensure the success of future satellite missions by establishing mechanistic relationships between remotely sensed signals and carbon cycle processes. Through a process-oriented approach, EXPORTS will foster new insights on ocean carbon cycling that will maximize its societal relevance and be a key component in the U.S. investment to understand Earth as an integrated system.
Eric J. Gustafson
2013-01-01
Researchers and natural resource managers need predictions of how multiple global changes (e.g., climate change, rising levels of air pollutants, exotic invasions) will affect landscape composition and ecosystem function. Ecological predictive models used for this purpose are constructed using either a mechanistic (process-based) or a phenomenological (empirical)...
NASA Technical Reports Server (NTRS)
Lee, Jae K.; Randolph, J. C.; Lulla, Kamlesh P.; Helfert, Michael R.
1993-01-01
Because changes in the Earth's environment have become major global issues, continuous, longterm scientific information is required to assess global problems such as deforestation, desertification, greenhouse effects and climate variations. Global change studies require understanding of interactions of complex processes regulating the Earth system. Space-based Earth observation is an essential element in global change research for documenting changes in Earth environment. It provides synoptic data for conceptual predictive modeling of future environmental change. This paper provides a brief overview of remote sensing technology from the perspective of global change research.
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...
Research highlights of the global modeling and simulation branch for 1986-1987
NASA Technical Reports Server (NTRS)
Baker, Wayman (Editor); Susskind, Joel (Editor); Pfaendtner, James (Editor); Randall, David (Editor); Atlas, Robert (Editor)
1988-01-01
This document provides a summary of the research conducted in the Global Modeling and Simulation Branch and highlights the most significant accomplishments in 1986 to 1987. The Branch has been the focal point for global weather and climate prediction research in the Laboratory for Atmospheres through the retrieval and use of satellite data, the development of global models and data assimilation techniques, the simulation of future observing systems, and the performance of atmospheric diagnostic studies.
The status and challenge of global fire modelling
Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...
2016-06-09
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less
The status and challenge of global fire modelling
NASA Astrophysics Data System (ADS)
Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao
2016-06-01
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.
The status and challenge of global fire modelling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.
Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less
NASA Astrophysics Data System (ADS)
Del Vasto-Terrientes, L.; Kumar, V.; Chao, T.-C.; Valls, A.
2016-03-01
Global change refers to climate changes, but also demographic, technological and economic changes. Predicted water scarcity will be critical in the coastal Mediterranean region, especially for provision to mid-sized and large-sized cities. This paper studies the case of the city of Tarragona, located at the Mediterranean area of north-eastern Spain (Catalonia). Several scenarios have been constructed to evaluate different sectorial water allocation policies to mitigate the water scarcity induced by global change. Future water supply and demand predictions have been made for three time spans. The decision support system presented is based on the outranking model, which constructs a partial pre-order based on pairwise preference relations among all the possible actions. The system analyses a hierarchical structure of criteria, including environmental and economic criteria. We compare several adaptation measures including alternative water sources, inter-basin water transfer and sectorial demand management coming from industry, agriculture and domestic sectors. Results indicate that the most appropriate water allocation strategies depend on the severity of the global change effects.
Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations
NASA Astrophysics Data System (ADS)
Gilligan, J. M.; John, N. J.; van der Linden, M.
2015-12-01
Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).
NASA Astrophysics Data System (ADS)
Ahmadalipour, A.; Beal, B.; Moradkhani, H.
2015-12-01
Changing climate and potential future increases in global temperature are likely to have impacts on drought characteristics and hydrologic cylce. In this study, we analyze changes in temporal and spatial extent of meteorological and hydrological droughts in future, and their trends. Three statistically downscaled datasets from NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), Multivariate Adaptive Constructed Analogs (MACA), and Bias Correction and Spatial Disagregation (BCSD-PSU) each consisting of 10 CMIP5 Global Climate Models (GCM) are utilized for RCP4.5 and RCP8.5 scenarios. Further, Precipitation Runoff Modeling System (PRMS) hydrologic model is used to simulate streamflow from GCM inputs and assess the hydrological drought characteristics. Standard Precipitation Index (SPI) and Streamflow Drought Index (SDI) are the two indexes used to investigate meteorological and hydrological drought, respectively. Study is done for Willamette Basin with a drainage area of 29,700 km2 accommodating more than 3 million inhabitants and 25 dams. We analyze our study for annual time scale as well as three future periods of near future (2010-2039), intermediate future (2040-2069), and far future (2070-2099). Large uncertainty is found from GCM predictions. Results reveal that meteorological drought events are expected to increase in near future. Severe to extreme drought with large areal coverage and several years of occurance is predicted around year 2030 with the likelihood of exceptional drought for both drought types. SPI is usually showing positive trends, while SDI indicates negative trends in most cases.
Predicting climate-induced range shifts: model differences and model reliability.
Joshua J. Lawler; Denis White; Ronald P. Neilson; Andrew R. Blaustein
2006-01-01
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 data set, we investigated the potential implications of alternative modeling approaches for...
River export of triclosan from land to sea: A global modelling approach.
van Wijnen, Jikke; Ragas, Ad M J; Kroeze, Carolien
2018-04-15
Triclosan (TCS) is an antibacterial agent that is added to commonly used personal care products. Emitted to the aquatic environment in large quantities, it poses a potential threat to aquatic organisms. Triclosan enters the aquatic environment mainly through sewage effluent. We developed a global, spatially explicit model, the Global TCS model, to simulate triclosan transport by rivers to coastal areas. With this model we analysed annual, basin-wide triclosan export for the year 2000 and two future scenarios for the year 2050. Our analyses for 2000 indicate that triclosan export to coastal areas in Western Europe, Southeast Asia and the East Coast of the USA is higher than in the rest of the world. For future scenarios, the Global TCS model predicts an increase in river export of triclosan in Southeast Asia and a small decrease in Europe. The number of rivers with an annual average triclosan concentration at the river mouth that exceeds a PNEC of 26.2ng/L is projected to double between 2000 and 2050. This increase is most prominent in Southeast Asia, as a result of fast population growth, increasing urbanisation and increasing numbers of people connected to sewerage systems with poor wastewater treatment. Predicted triclosan loads correspond reasonably well with measured values. However, basin-specific predictions have considerable uncertainty due to lacking knowledge and location-specific data on the processes determining the fate of triclosan in river water, e.g. sorption, degradation and sedimentation. Additional research on the fate of triclosan in river systems is therefore recommended. We developed a global spatially explicit model to simulate triclosan export by rivers to coastal seas. For two future scenarios this Global TCS model projects an increase in river export of triclosan to several seas around the world. Copyright © 2017 Elsevier B.V. All rights reserved.
A first look at global flash drought: long term change and short term predictability
NASA Astrophysics Data System (ADS)
Yuan, Xing; Wang, Linying; Ji, Peng
2017-04-01
"Flash drought" became popular after the unexpected 2012 central USA drought, mainly due to its rapid development, low predictability and devastating impacts on water resources and crop yields. A pilot study by Mo and Lettenmaier (2015) found that flash drought, based on a definition of concurrent heat extreme, soil moisture deficit and evapotranspiration (ET) enhancement at pentad scale, were in decline over USA during recent 100 years. Meanwhile, a recent work indicated that the occurrence of flash drought in China was doubled during the past 30 years, where a severe flash drought in the summer of 2013 ravaged 13 provinces in southern China. As global warming increases the frequency of heat waves and accelerates the hydrological cycle, the flash drought is expected to increase in general, but its trend might also be affected by interannual to decadal climate oscillations. To consolidate the hotspots of flash drought and the effects of climate change on flash drought, a global inventory is being conducted by using multi-source observations (in-situ, satellite and reanalysis), CMIP5 historical simulations and future projections under different forcing scenarios, as well as global land surface hydrological modeling for key variables including surface air temperature, soil moisture and ET. In particular, a global picture of the flash drought distribution, the contribution of naturalized and anthropogenic forcings to global flash drought change, and the risk of global flash drought in the future, will be presented. Besides investigating the long-term change of flash drought, providing reliable early warning is also essential to developing adaptation strategies. While regional drought early warning systems have been emerging in recent decade, forecasting of flash drought is still at an exploratory stage due to limited understanding of flash drought predictability. Here, a set of sub-seasonal to seasonal (S2S) hindcast datasets are being used to assess the short term predictability of flash drought via a perfect model assumption.
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.
Global Education: Connections, Concepts, and Careers. Research in Review 2012-4
ERIC Educational Resources Information Center
Balistreri, Sarah; Di Giacomo, F. Tony; Noisette, Ivanley; Ptak, Thomas
2012-01-01
Following the completion of this century's first decade, educators, policymakers, and researchers are attempting to predict future needs. However, is it possible to know what the education and global landscape will look like at the end of this century? Certainly, in 1900 one could not have comprehended the myriad innovations that would occur by…
Change We Can Fight Over: The Relationship between Arable Land Supply and Substate Conflict
2010-01-01
environmental impact of global warming has spurred a parallel discussion among national security academics and policymakers about the security...consequences of climate change. Roughly speaking, there are two camps in this discussion -one that ominously predicts the potential for global warming to spark...future climate change, but the stark reality is that global warming is already upon us. Thus, policymakers need to know -both now and in the coming
NASA Astrophysics Data System (ADS)
Bamzai, A.
2003-04-01
This talk will highlight science and application activities of the CDEP and RISA programs at NOAA OGP. CDEP, through a set of Applied Research Centers (ARCs), supports NOAA's program of quantitative assessments and predictions of global climate variability and its regional implications on time scales of seasons to centuries. The RISA program consolidates results from ongoing disciplinary process research under an integrative framework. Examples of joint CDEP-RISA activities will be presented. Future directions and programmatic challenges will also be discussed.
Projected shifts in fish species dominance in Wisconsin lakes under climate change.
Hansen, Gretchen J A; Read, Jordan S; Hansen, Jonathan F; Winslow, Luke A
2017-04-01
Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake-specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989-2014) and future (2040-2064 and 2065-2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake-specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33-75% of lakes where recruitment is currently supported and a 27-60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid-century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations. © 2016 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
Early warning model based on correlated networks in global crude oil markets
NASA Astrophysics Data System (ADS)
Yu, Jia-Wei; Xie, Wen-Jie; Jiang, Zhi-Qiang
2018-01-01
Applying network tools on predicting and warning the systemic risks provides a novel avenue to manage risks in financial markets. Here, we construct a series of global crude oil correlated networks based on the historical 57 oil prices covering a period from 1993 to 2012. Two systemic risk indicators are constructed based on the density and modularity of correlated networks. The local maximums of the risk indicators are found to have the ability to predict the trends of oil prices. In our sample periods, the indicator based on the network density sends five signals and the indicator based on the modularity index sends four signals. The four signals sent by both indicators are able to warn the drop of future oil prices and the signal only sent by the network density is followed by a huge rise of oil prices. Our results deepen the application of network measures on building early warning models of systemic risks and can be applied to predict the trends of future prices in financial markets.
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.
Middleton, Beth A.; McKee, Karen
2004-01-01
Plants may offer our best hope of removing greenhouse gases (gases that contribute to global warming) emitted to the atmosphere from the burning of fossil fuels. At the same time, global warming could change environments so that natural plant communities will either need to shift into cooler climate zones, or become extirpated (Prasad and Iverson, 1999; Crumpacker and others, 2001; Davis and Shaw, 2001). It is impossible to know the future, but studies combining field observation of production and modeling can help us make predictions about what may happen to these wetland communities in the future. Widespread wetland types such as baldcypress (Taxodium distichum) swamps in the southeastern portion of the United States could be especially good at carbon sequestration (amount of CO2 stored by forests) from the atmosphere. They have high levels of production and sometimes store undecomposed dead plant material in wet conditions with low oxygen, thus keeping gases stored that would otherwise be released into the atmosphere (fig. 1). To study the ability of baldcypress swamps to store carbon, our project has taken two approaches. The first analysis looked at published data to develop an idea (hypothesis) of how production levels change across a temperature gradient in the baldcypress region (published data study). The second study tested this idea by comparing production levels across a latitudinal range by using swamps in similar field conditions (ongoing carbon storage study). These studies will help us make predictions about the future ability of baldcypress swamps to store carbon in soil and plant biomass, as well as the ability of these forests to shift northward with global warming.
,
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.
Regional analysis of drought and heat impacts on forests: current and future science directions.
Law, Beverly E
2014-12-01
Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
Sustained Satellite Missions for Climate Data Records
NASA Technical Reports Server (NTRS)
Halpern, David
2012-01-01
Satellite CDRs possess the accuracy, longevity, and stability for sustained moni toring of critical variables to enhance understanding of the global integrated Earth system and predict future conditions. center dot Satellite CDRs are a critical element of a global climate observing system. center dot Satellite CDRs are a difficult challenge and require high - level managerial commitment, extensive intellectual capital, and adequate funding.
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.
Regulation of water resources for sustaining global future socioeconomic development
NASA Astrophysics Data System (ADS)
Chen, J.; SHI, H.; Sivakumar, B.
2016-12-01
With population projections indicating continued growth during this century, socio-economic problems (e.g., water, food, and energy shortages) will be most likely to occur, especially if proper planning, development, and management strategies are not adopted. In the present study, firstly, we explore the vital role of dams in promoting economic growth through analyzing the relationship between dams and Gross Domestic Product (GDP) at both global and national scales. Secondly, we analyze the current situation of global water scarcity based on the data representing water resources availability, dam development, and the level of economic development. Third, with comprehensive consideration of population growth as the major driving force, water resources availability as the basic supporting factor, and topography as the important constraint, this study addresses the question of dam development in the future and predicts the locations of future dams around the world.
Recent Advancements in the Global Understanding of what Drives Heatwaves
NASA Astrophysics Data System (ADS)
Perkins-Kirkpatrick, S.
2016-12-01
Heatwaves, defined as prolonged periods of extreme heat, are disastrous events that impact human, natural and industrial systems all over the world. In recent years, the global research effort has greatly increased our understanding on quantifying heatwaves and how they have changed, what drives them, and their future projections. This talk will summarize critical developments made in this field, with particular emphasis on the physical driving mechanisms and the role of internal climate variability. Case studies from various global regions will illustrate both similarities and differences in the physical set-ups of these fascinating events. Future projections of heatwaves and the human contribution behind specific observed heatwave events will be briefly discussed. The talk will conclude by highlighting research priorities such that future investigation is targeted, and closes existing knowledge gaps on what drives heatwaves as effectively as possible. Such developments will ultimately aid in the predictability of heatwaves, thus aiding in reducing their devastating impacts.
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.
Prospects for improved understanding of isotopic reactor antineutrino fluxes
NASA Astrophysics Data System (ADS)
Gebre, Y.; Littlejohn, B. R.; Surukuchi, P. T.
2018-01-01
Predictions of antineutrino fluxes produced by fission isotopes in a nuclear reactor have recently received increased scrutiny due to observed differences in predicted and measured inverse beta decay (IBD) yields, referred to as the "reactor antineutrino flux anomaly." In this paper, global fits are applied to existing IBD yield measurements to produce constraints on antineutrino production by individual plutonium and uranium fission isotopes. We find that fits including measurements from highly
Wintertime urban heat island modified by global climate change over Japan
NASA Astrophysics Data System (ADS)
Hara, M.
2015-12-01
Urban thermal environment change, especially, surface air temperature (SAT) rise in metropolitan areas, is one of the major recent issues in urban areas. The urban thermal environmental change affects not only human health such as heat stroke, but also increasing infectious disease due to spreading out virus vectors habitat and increase of industry and house energy consumption. The SAT rise is mostly caused by global climate change and urban heat island (hereafter UHI) by urbanization. The population in Tokyo metropolitan area is over 30 millions and the Tokyo metropolitan area is one of the biggest megacities in the world. The temperature rise due to urbanization seems comparable to the global climate change in the major megacities. It is important to project how the urbanization and the global climate change affect to the future change of urban thermal environment to plan the adaptation and mitigation policy. To predict future SAT change in urban scale, we should estimate future UHI modified by the global climate change. This study investigates change in UHI intensity (UHII) of major metropolitan areas in Japan by effects of the global climate change. We performed a series of climate simulations. Present climate simulations with and without urban process are conducted for ten seasons using a high-resolution numerical climate model, the Weather Research and Forecasting (WRF) model. Future climate projections with and without urban process are also conducted. The future projections are performed using the pseudo global warming method, assuming 2050s' initial and boundary conditions estimated by a GCM under the RCP scenario. Simulation results indicated that UHII would be enhanced more than 30% in Tokyo during the night due to the global climate change. The enhancement of urban heat island is mostly caused by change of lower atmospheric stability.
Global surface temperatures and the atmospheric electrical circuit
NASA Technical Reports Server (NTRS)
Price, Colin
1993-01-01
To monitor future global temperature trends, it would be extremely useful if parameters nonlinearly related to surface temperature could be found, thereby amplifying any warming signal that may exist. Evidence that global thunderstorm activity is nonlinearly related to diurnal, seasonal and interannual temperature variations is presented. Since global thunderstorm activity is also well correlated with the earth's ionospheric potential, it appears that variations of ionospheric potential, that can be measured at a single location, may be able to supply valuable information regarding global surface temperature fluctuations. The observations presented enable a prediction that a 1 percent increase in global surface temperatures may result in a 20 percent increase in ionospheric potential.
Unravelling the structure of species extinction risk for predictive conservation science.
Lee, Tien Ming; Jetz, Walter
2011-05-07
Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.
Darcy's law predicts widespread forest mortalityunder climate warming
NASA Astrophysics Data System (ADS)
Allen, C. D.; McDowell, N. G.
2015-12-01
Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We used a hydraulic corollary to Darcy's law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy's law indicates today's forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy's corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. There are assumptions and omissions in this theoretical prediction, as well as new evidence supporting its predictions, both of which I will review. Given the robustness of Darcy's law for predictions of vascular plant function, we conclude with high certainty that today's forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.
NASA Technical Reports Server (NTRS)
1985-01-01
An assessment of the status of research using Global Weather Experiment (GWE) data and of the progress in meeting the objectives of the GWE, i.e., better knowledge and understanding of the atmosphere in order to provide more useful weather prediction services. Volume Two consists of a compilation of the papers presented during the workshop. These cover studies that addressed GWE research objectives and utilized GWE information. The titles in Part 2 of this volume include General Circulation Planetary Waves, Interhemispheric, Cross-Equatorial Exchange, Global Aspects of Monsoons, Midlatitude-Tropical Interactions During Monsoons, Stratosphere, Southern Hemisphere, Parameterization, Design of Observations, Oceanography, Future Possibilities, Research Gaps, with an Appendix.
Using Extreme Tropical Precipitation Statistics to Constrain Future Climate States
NASA Astrophysics Data System (ADS)
Igel, M.; Biello, J. A.
2017-12-01
Tropical precipitation is characterized by a rapid growth in mean intensity as the column humidity increases. This behavior is examined in both a cloud resolving model and with high-resolution observations of precipitation and column humidity from CloudSat and AIRS, respectively. The model and the observations exhibit remarkable consistency and suggest a new paradigm for extreme precipitation. We show that the total precipitation can be decomposed into a product of contributions from a mean intensity, a probability of precipitation, and a global PDF of column humidity values. We use the modeling and observational results to suggest simple, analytic forms for each of these functions. The analytic representations are then used to construct a simple expression for the global accumulated precipitation as a function of the parameters of each of the component functions. As the climate warms, extreme precipitation intensity and global precipitation are expected to increase, though at different rates. When these predictions are incorporated into the new analytic expression for total precipitation, predictions for changes due to global warming to the probability of precipitation and the PDF of column humidity can be made. We show that strong constraints can be imposed on the future shape of the PDF of column humidity but that only weak constraints can be set on the probability of precipitation. These are largely imposed by the intensification of extreme precipitation. This result suggests that understanding precisely how extreme precipitation responds to climate warming is critical to predicting other impactful properties of global hydrology. The new framework can also be used to confirm and discount existing theories for shifting precipitation.
Moncrieff, Glenn R; Scheiter, Simon; Bond, William J; Higgins, Steven I
2014-02-01
The dominant vegetation over much of the global land surface is not predetermined by contemporary climate, but also influenced by past environmental conditions. This confounds attempts to predict current and future biome distributions, because even a perfect model would project multiple possible biomes without knowledge of the historical vegetation state. Here we compare the distribution of tree- and grass-dominated biomes across Africa simulated using a dynamic global vegetation model (DGVM). We explicitly evaluate where and under what conditions multiple stable biome states are possible for current and projected future climates. Our simulation results show that multiple stable biomes states are possible for vast areas of tropical and subtropical Africa under current conditions. Widespread loss of the potential for multiple stable biomes states is projected in the 21st Century, driven by increasing atmospheric CO2 . Many sites where currently both tree-dominated and grass-dominated biomes are possible become deterministically tree-dominated. Regions with multiple stable biome states are widespread and require consideration when attempting to predict future vegetation changes. Testing for behaviour characteristic of systems with multiple stable equilibria, such as hysteresis and dependence on historical conditions, and the resulting uncertainty in simulated vegetation, will lead to improved projections of global change impacts. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.
Global Tree Range Shifts Under Forecasts from Two Alternative GCMs Using Two Future Scenarios
NASA Astrophysics Data System (ADS)
Hargrove, W. W.; Kumar, J.; Potter, K. M.; Hoffman, F. M.
2013-12-01
Global shifts in the environmentally suitable ranges of 215 tree species were predicted under forecasts from two GCMs (the Parallel Climate Model (PCM), and the Hadley Model), each under two IPCC future climatic scenarios (A1 and B1), each at two future dates (2050 and 2100). The analysis considers all global land surface at a resolution of 4 km2. A statistical multivariate clustering procedure was used to quantitatively delineate 30 thousand environmentally homogeneous ecoregions across present and 8 potential future global locations at once, using global maps of 17 environmental characteristics describing temperature, precipitation, soils, topography and solar insolation. Presence of each tree species on Forest Inventory Analysis (FIA) plots and in Global Biodiversity Information Facility (GBIF) samples was used to select a subset of suitable ecoregions from the full set of 30 thousand. Once identified, this suitable subset of ecoregions was compared to the known current range of the tree species under present conditions. Predicted present ranges correspond well with current understanding for all but a few of the 215 tree species. The subset of suitable ecoregions for each tree species can then be tracked into the future to determine whether the suitable home range for this species remains the same, moves, grows, shrinks, or disappears under each model/scenario combination. Occurrence and growth performance measurements for various tree species across the U.S. are limited to FIA plots. We present a new, general-purpose empirical imputation method which associates sparse measurements of dependent variables with particular multivariate clustered combinations of the independent variables, and then estimates values for unmeasured clusters, based on directional proximity in multidimensional data space, at both the cluster and map-cell levels of resolution. Using Associative Clustering, we scaled up the FIA point measurements into contonuous maps that show the expected growth and suitability for individual tree species across the continental US. Maps were generated for each tree species showing the Minimum Required Movement (MRM) straight-line distance from each currently suitable location to the geographically nearest "lifeboat" location having suitable conditions in the future. Locations that are the closest "lifeboats" for many MRM propagules originating from wide surrounding areas may constitute high-priority preservation targets as a refugium against climatic change.
Evaluation of coral reef carbonate production models at a global scale
NASA Astrophysics Data System (ADS)
Jones, N. S.; Ridgwell, A.; Hendy, E. J.
2014-09-01
Calcification by coral reef communities is estimated to account for half of all carbonate produced in shallow water environments and more than 25% of the total carbonate buried in marine sediments globally. Production of calcium carbonate by coral reefs is therefore an important component of the global carbon cycle. It is also threatened by future global warming and other global change pressures. Numerical models of reefal carbonate production are essential for understanding how carbonate deposition responds to environmental conditions including future atmospheric CO2 concentrations, but these models must first be evaluated in terms of their skill in recreating present day calcification rates. Here we evaluate four published model descriptions of reef carbonate production in terms of their predictive power, at both local and global scales, by comparing carbonate budget outputs with independent estimates. We also compile available global data on reef calcification to produce an observation-based dataset for the model evaluation. The four calcification models are based on functions sensitive to combinations of light availability, aragonite saturation (Ωa) and temperature and were implemented within a specifically-developed global framework, the Global Reef Accretion Model (GRAM). None of the four models correlated with independent rate estimates of whole reef calcification. The temperature-only based approach was the only model output to significantly correlate with coral-calcification rate observations. The absence of any predictive power for whole reef systems, even when consistent at the scale of individual corals, points to the overriding importance of coral cover estimates in the calculations. Our work highlights the need for an ecosystem modeling approach, accounting for population dynamics in terms of mortality and recruitment and hence coral cover, in estimating global reef carbonate budgets. In addition, validation of reef carbonate budgets is severely hampered by limited and inconsistent methodology in reef-scale observations.
Assessing the ability of plants to respond to climatic change through distribution shifts
Mark W. Schwartz
1996-01-01
Predictions of future global warming suggest northward shifts of up to 800 km in the equilibrium distributions of plant species. Historical data estimating the maximum rate of tree distribution shifts (migration) suggest that most species will not keep pace with future rates of human-induced climatic change. Previous plant migrations have occurred at rates typically...
NASA Astrophysics Data System (ADS)
Vallam, P.; Qin, X. S.
2017-10-01
Anthropogenic-driven climate change would affect the global ecosystem and is becoming a world-wide concern. Numerous studies have been undertaken to determine the future trends of meteorological variables at different scales. Despite these studies, there remains significant uncertainty in the prediction of future climates. To examine the uncertainty arising from using different schemes to downscale the meteorological variables for the future horizons, projections from different statistical downscaling schemes were examined. These schemes included statistical downscaling method (SDSM), change factor incorporated with LARS-WG, and bias corrected disaggregation (BCD) method. Global circulation models (GCMs) based on CMIP3 (HadCM3) and CMIP5 (CanESM2) were utilized to perturb the changes in the future climate. Five study sites (i.e., Alice Springs, Edmonton, Frankfurt, Miami, and Singapore) with diverse climatic conditions were chosen for examining the spatial variability of applying various statistical downscaling schemes. The study results indicated that the regions experiencing heavy precipitation intensities were most likely to demonstrate the divergence between the predictions from various statistical downscaling methods. Also, the variance computed in projecting the weather extremes indicated the uncertainty derived from selection of downscaling tools and climate models. This study could help gain an improved understanding about the features of different downscaling approaches and the overall downscaling uncertainty.
NASA Astrophysics Data System (ADS)
Coakley, Bernard; Edmonds, Henrietta N.; Frey, Karen; Gascard, Jean-Claude; Grebmeier, Jacqueline M.; Kassens, Heidemarie; Thiede, Jörn; Wegner, Carolyn
2007-07-01
A follow-up to the 2nd International Conference on Arctic Research Planning, 19-21 November 2007, Potsdam, Germany The Arctic Ocean is the missing piece for any global model. Records of processes at both long and short timescales will be necessary to predict the future evolution of the Arctic Ocean through what appears to be a period of rapid climate change. Ocean monitoring is impoverished without the long-timescale records available from paleoceanography and the boundary conditions that can be obtained from marine geology and geophysics. The past and the present are the key to our ability to predict the future.
Spatial Pattern of Standing Timber Value across the Brazilian Amazon
Ahmed, Sadia E.; Ewers, Robert M.
2012-01-01
The Amazon is a globally important system, providing a host of ecosystem services from climate regulation to food sources. It is also home to a quarter of all global diversity. Large swathes of forest are removed each year, and many models have attempted to predict the spatial patterns of this forest loss. The spatial patterns of deforestation are determined largely by the patterns of roads that open access to frontier areas and expansion of the road network in the Amazon is largely determined by profit seeking logging activities. Here we present predictions for the spatial distribution of standing value of timber across the Amazon. We show that the patterns of timber value reflect large-scale ecological gradients, determining the spatial distribution of functional traits of trees which are, in turn, correlated with timber values. We expect that understanding the spatial patterns of timber value across the Amazon will aid predictions of logging movements and thus predictions of potential future road developments. These predictions in turn will be of great use in estimating the spatial patterns of deforestation in this globally important biome. PMID:22590520
NASA Astrophysics Data System (ADS)
Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.
2017-12-01
Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.
NASA Astrophysics Data System (ADS)
Li, Y.; Akbariyeh, S.; Gomez Peña, C. A.; Bartlet-Hunt, S.
2016-12-01
Understanding the impacts of future climate change on soil hydrological processes and solute transport is crucial to develop appropriate strategies to minimize adverse impacts of agricultural activities on groundwater quality. The goal of this work is to evaluate the direct effects of climate change on the fate and transport of nitrate beneath a center-pivot irrigated corn field in Nebraska Management Systems Evaluation Area (MSEA) site. Future groundwater recharge rate and actual evapotranspiration rate were predicted based on an inverse modeling approach using climate data generated by Weather Research and Forecasting (WRF) model under the RCP 8.5 scenario, which was downscaled from global CCSM4 model to a resolution of 24 by 24 km2. A groundwater flow model was first calibrated based on historical groundwater table measurement and was then applied to predict future groundwater table in the period 2057-2060. Finally, predicted future groundwater recharge rate, actual evapotranspiration rate, and groundwater level, together with future precipitation data from WRF, were used in a three-dimensional (3D) model, which was validated based on rich historic data set collected from 1993-1996, to predict nitrate concentration in soil and groundwater from the year 2057 to 2060. Future groundwater recharge was found to be decreasing in the study area compared to average groundwater recharge data from the literature. Correspondingly, groundwater elevation was predicted to decrease (1 to 2 ft) over the five years of simulation. Predicted higher transpiration data from climate model resulted in lower infiltration of nitrate concentration in subsurface within the root zone.
Assessing spatiotemporal changes in forest carbon turnover times in observational data and models
NASA Astrophysics Data System (ADS)
Yu, K.; Smith, W. K.; Trugman, A. T.; van Mantgem, P.; Peng, C.; Condit, R.; Anderegg, W.
2017-12-01
Forests influence global carbon and water cycles, biophysical land-atmosphere feedbacks, and atmospheric composition. The capacity of forests to sequester atmospheric CO2 in a changing climate depends not only on the response of carbon uptake (i.e., gross primary productivity) but also on the simultaneous change in carbon residence time. However, changes in carbon residence with climate change are uncertain, impacting the accuracy of predictions of future terrestrial carbon cycle dynamics. Here, we use long-term forest inventory data representative of tropical, temperate, and boreal forests; satellite-based estimates of net primary productivity and vegetation carbon stock; and six models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to investigate spatiotemporal trends in carbon residence time and its relation to climate. Forest inventory and satellite-based estimates of carbon residence time show a pervasive decreasing trend across global forests. In contrast, the CMIP5 models diverge in predicting historical and future trends in carbon residence time. Divergence across CMIP5 models indicate carbon turnover times are not well constrained by observations, which likely contributes to large variability in future carbon cycle projections.
How will SOA change in the future?: SOA IN THE FUTURE
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lin, Guangxing; Penner, Joyce E.; Zhou, Cheng
2016-02-17
Secondary organic aerosol (SOA) plays a significant role in the Earth system by altering its radiative balance. Here we use an Earth system model coupled with an explicit SOA formation module to estimate the response of SOA concentrations to changes in climate, anthropogenic emissions, and human land use in the future. We find that climate change is the major driver for SOA change under the representative concentration pathways for the 8.5 future scenario. Climate change increases isoprene emission rate by 18% with the effect of temperature increases outweighing that of the CO2 inhibition effect. Annual mean global SOA mass ismore » increased by 25% as a result of climate change. However, anthropogenic emissions and land use change decrease SOA. The net effect is that future global SOA burden in 2100 is nearly the same as that of the present day. The SOA concentrations over the Northern Hemisphere are predicted to decline in the future due to the control of sulfur emissions.« less
Development of a Climate Prediction Market
NASA Astrophysics Data System (ADS)
Roulston, M. S.
2017-12-01
Winton, a global investment firm, is planning to establish a prediction market for climate. This prediction market will allow participants to place bets on global climate up to several decades in the future. Winton is pursuing this endeavour as part of its philanthropy that funds scientific research and the communication of scientific ideas. The Winton Climate Prediction Market will be based in the U.K. It will be structured as an online gambling site subject to the regulation of the Gambling Commission. Unlike existing betting sites, the Climate Prediction Market will be subsidized: a central market maker will inject money into the market. This is in contrast to traditional bookmakers or betting exchanges who set odds in their favour or charge commissions to make a profit. The philosophy of a subsidized prediction market is that the party seeking information should fund the market, rather than the participants who provide the information. The initial market will allow bets to be placed on the atmospheric concentration of carbon dioxide and the global mean temperature anomaly. It will thus produce implied forecasts of carbon dioxide concentration as well as global temperatures. If the initial market is successful, additional markets could be added which target other climate variables, such as regional temperatures or sea-level rise. These markets could be sponsored by organizations that are interested in predictions of the specific climate variables. An online platform for the Climate Prediction Market has been developed and has been tested internally at Winton.
Application of wavelet analysis in determining the periodicity of global warming
NASA Astrophysics Data System (ADS)
Feng, Xiao
2018-04-01
In the last two decades of the last century, the global average temperature has risen by 0.48 ° C over 100 years ago. Since then, global warming has become a hot topic. Global warming will have complex and potential impacts on humans and the Earth. However, the negative impacts far outweigh the positive impacts. The most obvious external manifestation of global warming is temperature. Therefore, this study uses wavelet analysis study the characteristics of temperature time series, solve the periodicity of the sequence, find out the trend of temperature change and predict the extent of global warming in the future, so as to take the necessary precautionary measures.
Global precipitation measurement (GPM) preliminary design
NASA Astrophysics Data System (ADS)
Neeck, Steven P.; Kakar, Ramesh K.; Azarbarzin, Ardeshir A.; Hou, Arthur Y.
2008-10-01
The overarching Earth science mission objective of the Global Precipitation Measurement (GPM) mission is to develop a scientific understanding of the Earth system and its response to natural and human-induced changes. This will enable improved prediction of climate, weather, and natural hazards for present and future generations. The specific scientific objectives of GPM are advancing: Precipitation Measurement through combined use of active and passive remote-sensing techniques, Water/Energy Cycle Variability through improved knowledge of the global water/energy cycle and fresh water availability, Climate Prediction through better understanding of surface water fluxes, soil moisture storage, cloud/precipitation microphysics and latent heat release, Weather Prediction through improved numerical weather prediction (NWP) skills from more accurate and frequent measurements of instantaneous rain rates with better error characterizations and improved assimilation methods, Hydrometeorological Prediction through better temporal sampling and spatial coverage of highresolution precipitation measurements and innovative hydro-meteorological modeling. GPM is a joint initiative with the Japan Aerospace Exploration Agency (JAXA) and other international partners and is the backbone of the Committee on Earth Observation Satellites (CEOS) Precipitation Constellation. It will unify and improve global precipitation measurements from a constellation of dedicated and operational active/passive microwave sensors. GPM is completing the Preliminary Design Phase and is advancing towards launch in 2013 and 2014.
NASA Technical Reports Server (NTRS)
1985-01-01
Topics covered include: data systems and quality; analysis and assimilation techniques; impacts on forecasts; tropical forecasts; analysis intercomparisons; improvements in predictability; and heat sources and sinks.
Lunar Global Heat Flow: Predictions and Constraints
NASA Astrophysics Data System (ADS)
Siegler, M.; Williams, J. P.; Paige, D. A.; Feng, J.
2017-12-01
The global thermal state of the Moon provides fundamental information on its bulk composition and interior evolution. The Moon is known to have a highly asymmetric surface composition [e.g. Lawrence et al., 2003] and crustal thickness [Wieczorek et al.,2012], which is suspected to result from interior asymmetries [Wieczorek and Phillips, 2000; Laneuville et al., 2013]. This is likely to cause a highly asymmetric surface heat flux, both past and present. Our understanding the thermal evolution and composition of the bulk moon therefore requires a global picture of the present lunar thermal state, well beyond our two-point Apollo era measurement. As on the on the Earth, heat flow measurements need to be taken in carefully selected locations to truly characterize the state of the planet's interior. Future surface heat flux and seismic observations will be affected by the presence of interior temperature and crustal radiogenic anomalies, so placement of such instruments is critically important for understanding the lunar interior. The unfortunate coincidence that Apollo geophysical measurements lie areas within or directly abutting the highly radiogenic, anomalously thin-crusted Procellarum region highlights the importance of location for in situ geophysical study [e.g. Siegler and Smrekar, 2014]. Here we present the results of new models of global lunar geothermal heat flux. We synthesize data from several recent missions to constrain lunar crustal composition, thickness and density to provide global predictions of the surface heat flux of the Moon. We also discuss implications from new surface heat flux constraints from the LRO Diviner Lunar Radiometer Experiment and Chang'E 2 Microwave Radiometer. We will identify areas with the highest uncertainty to provide insight on the placement of future landed geophysical missions, such as the proposed Lunar Geophysical Network, to better aim our future exploration of the Moon.
Forecasting the global shortage of physicians: an economic- and needs-based approach
Liu, Jenny X; Kinfu, Yohannes; Dal Poz, Mario R
2008-01-01
Abstract Objective Global achievements in health may be limited by critical shortages of health-care workers. To help guide workforce policy, we estimate the future demand for, need for and supply of physicians, by WHO region, to determine where likely shortages will occur by 2015, the target date of the Millennium Development Goals. Methods Using World Bank and WHO data on physicians per capita from 1980 to 2001 for 158 countries, we employ two modelling approaches for estimating the future global requirement for physicians. A needs-based model determines the number of physicians per capita required to achieve 80% coverage of live births by a skilled health-care attendant. In contrast, our economic model identifies the number of physicians per capita that are likely to be demanded, given each country’s economic growth. These estimates are compared to the future supply of physicians projected by extrapolating the historical rate of increase in physicians per capita for each country. Findings By 2015, the global supply of physicians appears to be in balance with projected economic demand. Because our measure of need reflects the minimum level of workforce density required to provide a basic health service that is met in all but the least developed countries, the needs-based estimates predict a global surplus of physicians. However, on a regional basis, both models predict shortages for many countries in the WHO African Region in 2015, with some countries experiencing a needs-based shortage, a demand-based shortage, or both. Conclusion The type of policy intervention needed to alleviate projected shortages, such as increasing health-care training or adopting measures to discourage migration, depends on the type of shortage projected. PMID:18670663
Globalisation and human dignity: the case of the information superhighway.
Hamelink, C J
1996-01-01
In 1994, Vice President Al Gore coined the concept of the Information Superhighway during a speech in Buenos Aires in which he proposed the development of a global information infrastructure. The project envisions the incorporation of all existing communication networks into one system, facilitating the globalization of markets. The internet, a decentralized network of computer networks, is one small-scale, existing model of what the superhighway could be, a public space owned by nobody in which communication takes place largely for noncommercial purposes. The internet currently connects 40 million computer users from at least 90 countries. The alternative model for the superhighway is the privately managed global shopping mall, a global interactive marketplace for information, entertainment, and advertising. The author warns, however, that it is not possible to predict the future social impact of such an information superhighway. Decision makers nonetheless push ahead in development, full of confidence in the merit and infallibility of technology. Since one cannot accurately predict the future, it rational to assume that social consequences may both promote and threaten human dignity. The author explains at which level he believes the superhighway threatens the human rights norms of equality, inviolability, and liberty, and discusses what the World Association for Christian Communication can do.
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.
NASA Astrophysics Data System (ADS)
Wu, Yenan; Zhong, Ping-an; Xu, Bin; Zhu, Feilin; Fu, Jisi
2017-06-01
Using climate models with high performance to predict the future climate changes can increase the reliability of results. In this paper, six kinds of global climate models that selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Path (RCP) 4.5 scenarios were compared to the measured data during baseline period (1960-2000) and evaluate the simulation performance on precipitation. Since the results of single climate models are often biased and highly uncertain, we examine the back propagation (BP) neural network and arithmetic mean method in assembling the precipitation of multi models. The delta method was used to calibrate the result of single model and multimodel ensembles by arithmetic mean method (MME-AM) during the validation period (2001-2010) and the predicting period (2011-2100). We then use the single models and multimodel ensembles to predict the future precipitation process and spatial distribution. The result shows that BNU-ESM model has the highest simulation effect among all the single models. The multimodel assembled by BP neural network (MME-BP) has a good simulation performance on the annual average precipitation process and the deterministic coefficient during the validation period is 0.814. The simulation capability on spatial distribution of precipitation is: calibrated MME-AM > MME-BP > calibrated BNU-ESM. The future precipitation predicted by all models tends to increase as the time period increases. The order of average increase amplitude of each season is: winter > spring > summer > autumn. These findings can provide useful information for decision makers to make climate-related disaster mitigation plans.
Forecasting Western U.S. Snowpack
NASA Astrophysics Data System (ADS)
Kapnick, S. B.; Yang, X.; Vecchi, G. A.; Delworth, T. L.; Gudgel, R.; Malyshev, S.; Milly, C.; Shevliakova, E.; Underwood, S.; Margulis, S. A.
2017-12-01
Cold season mountain snow accumulation in the western United States plays a critical role in regional hydroclimate and water supply. While climate projections provide estimates of future snowpack loss by the end of the century and weather forecasts provide predictions of weather conditions and hazards out to two weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), particularly beyond 6 months. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate our dynamical system's feasibility of seasonal snowpack predictions and quantify the limits of predictive skill more than 2 seasons in advance for snowpack—snow that accumulates on the ground in the mountains. Our ability to predict snowpack is reliant on both temperature and precipitation prediction skill modulating both the amount of frozen precipitation that falls and how much snow accumulates and stays on the ground throughout the season. We will quantify prediction skill and outline areas necessary for the future advancement of seasonal hydroclimate prediction.
NASA Astrophysics Data System (ADS)
Jiang, L.; Luo, Y.; Yan, Y.; Hararuk, O.
2013-12-01
Mitigation of global changes will depend on reliable projection for the future situation. As the major tools to predict future climate, Earth System Models (ESMs) used in Coupled Model Intercomparison Project Phase 5 (CMIP5) for the IPCC Fifth Assessment Report have incorporated carbon cycle components, which account for the important fluxes of carbon between the ocean, atmosphere, and terrestrial biosphere carbon reservoirs; and therefore are expected to provide more detailed and more certain projections. However, ESMs are never perfect; and evaluating the ESMs can help us to identify uncertainties in prediction and give the priorities for model development. In this study, we benchmarked carbon in live vegetation in the terrestrial ecosystems simulated by 19 ESMs models from CMIP5 with an observationally estimated data set of global carbon vegetation pool 'Olson's Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: An Updated Database Using the GLC2000 Land Cover Product' by Gibbs (2006). Our aim is to evaluate the ability of ESMs to reproduce the global vegetation carbon pool at different scales and what are the possible causes for the bias. We found that the performance CMIP5 ESMs is very scale-dependent. While CESM1-BGC, CESM1-CAM5, CESM1-FASTCHEM and CESM1-WACCM, and NorESM1-M and NorESM1-ME (they share the same model structure) have very similar global sums with the observation data but they usually perform poorly at grid cell and biome scale. In contrast, MIROC-ESM and MIROC-ESM-CHEM simulate the best on at grid cell and biome scale but have larger differences in global sums than others. Our results will help improve CMIP5 ESMs for more reliable prediction.
Prediction-Market-Based Quantification of Climate Change Consensus and Uncertainty
NASA Astrophysics Data System (ADS)
Boslough, M.
2012-12-01
Intrade is an online trading exchange that includes climate prediction markets. One such family of contracts can be described as "Global temperature anomaly for 2012 to be greater than x °C or more," where the figure x ranges in increments of .05 from .30 to 1.10 (relative to the 1951-1980 base period), based on data published by NASA GISS. Each market will settle at 10.00 if the published global temperature anomaly for 2012 is equal to or greater than x, and will otherwise settle at 0.00. Similar contracts will be available for 2013. Global warming hypotheses can be cast as probabilistic predictions for future temperatures. The first modern such climate prediction is that of Broecker (1975), whose temperatures are easily separable from his CO2 growth scenario—which he overestimated—by interpolating his table of temperature as a function of CO2 concentration and projecting the current trend into the near future. For the current concentration of 395 ppm, Broecker's equilibrium temperature anomaly prediction relative to pre-industrial is 1.05 °C, or about 0.75 °C relative to the GISS base period. His neglect of lag in response to the changes in radiative forcing was partially compensated by his low sensitivity of 2.4 °C, leading to a slight overestimate. Simple linear extrapolation of the current trend since 1975 yields an estimate of .65 ± .09 °C (net warming of .95 °C) for anthropogenic global warming with a normal distribution of random natural variability. To evaluate an extreme case, we can estimate the prediction Broecker would have made if he had used the Lindzen & Choi (2009) climate sensitivity of 0.5 °C. The net post-industrial warming by 2012 would have been 0.21 °C, for an expected change of -0.09 from the GISS base period. This is the temperature to which the Earth would be expected to revert if the observed warming since the 19th century was merely due to random natural variability that coincidentally mimicked Broecker's anthropogenic change prediction for the past 36 years. Assertions made outside the scientific literature can also be cast into predictions for 2012 temperatures, for example Carter's (2006) argument for a lack of warming since 1998 can be extrapolated to a 2012 value of 0.56 °C (net warming of .86 °C), and Easterbrook's (2010) claim of global cooling can be extrapolated to a 2012 value of .42 °C (net warming of .72 °C). All contracts in the current market ensembles are consistent with net warming from pre-industrial temperatures. They are also capable of distinguishing the level of acceptance of the various global warming hypotheses, even by their respective proponents. Moreover, they can be used as a market-based consensus estimate of future warming and climate variability that is weighted according to level of risk taken on by those providing the estimates, while filtering out the opinions of individuals unwilling to accept any financial risk associated with being wrong.
Remote Sensing and halocene Vegetation: History of Global Change
NASA Technical Reports Server (NTRS)
D'Antoni, Hector L.; Schaebitz, Frank
1995-01-01
Predictions of the future evolution of the earth's atmospheric chemistry and its impact on global circulation patterns are based on Global Climate Models (GCMs) that integrate the complex interactions of the biosphere, atmosphere and the oceans. Most of the available records of climate and environment are short-term records (from decades to a few hundred years) with convolved information of real trends and short-term fluctuations. GCMs must be tested beyond the short-term record of climate and environment to insure that predictions are based on trends and therefore are appropriate to support long term policy making. Unfortunately different parts of the world, weather stations are scattered, records extend over a period of only few years, and there are no systematic climate records for large portions of the globe.
Anticipative management for coral reef ecosystem services in the 21st century.
Rogers, Alice; Harborne, Alastair R; Brown, Christopher J; Bozec, Yves-Marie; Castro, Carolina; Chollett, Iliana; Hock, Karlo; Knowland, Cheryl A; Marshell, Alyssa; Ortiz, Juan C; Razak, Tries; Roff, George; Samper-Villarreal, Jimena; Saunders, Megan I; Wolff, Nicholas H; Mumby, Peter J
2015-02-01
Under projections of global climate change and other stressors, significant changes in the ecology, structure and function of coral reefs are predicted. Current management strategies tend to look to the past to set goals, focusing on halting declines and restoring baseline conditions. Here, we explore a complementary approach to decision making that is based on the anticipation of future changes in ecosystem state, function and services. Reviewing the existing literature and utilizing a scenario planning approach, we explore how the structure of coral reef communities might change in the future in response to global climate change and overfishing. We incorporate uncertainties in our predictions by considering heterogeneity in reef types in relation to structural complexity and primary productivity. We examine 14 ecosystem services provided by reefs, and rate their sensitivity to a range of future scenarios and management options. Our predictions suggest that the efficacy of management is highly dependent on biophysical characteristics and reef state. Reserves are currently widely used and are predicted to remain effective for reefs with high structural complexity. However, when complexity is lost, maximizing service provision requires a broader portfolio of management approaches, including the provision of artificial complexity, coral restoration, fish aggregation devices and herbivore management. Increased use of such management tools will require capacity building and technique refinement and we therefore conclude that diversification of our management toolbox should be considered urgently to prepare for the challenges of managing reefs into the 21st century. © 2014 John Wiley & Sons Ltd.
Multi-nutrient, multi-group model of present and future oceanic phytoplankton communities
NASA Astrophysics Data System (ADS)
Litchman, E.; Klausmeier, C. A.; Miller, J. R.; Schofield, O. M.; Falkowski, P. G.
2006-11-01
Phytoplankton community composition profoundly affects patterns of nutrient cycling and the dynamics of marine food webs; therefore predicting present and future phytoplankton community structure is crucial to understand how ocean ecosystems respond to physical forcing and nutrient limitations. We develop a mechanistic model of phytoplankton communities that includes multiple taxonomic groups (diatoms, coccolithophores and prasinophytes), nutrients (nitrate, ammonium, phosphate, silicate and iron), light, and a generalist zooplankton grazer. Each taxonomic group was parameterized based on an extensive literature survey. We test the model at two contrasting sites in the modern ocean, the North Atlantic (North Atlantic Bloom Experiment, NABE) and subarctic North Pacific (ocean station Papa, OSP). The model successfully predicts general patterns of community composition and succession at both sites: In the North Atlantic, the model predicts a spring diatom bloom, followed by coccolithophore and prasinophyte blooms later in the season. In the North Pacific, the model reproduces the low chlorophyll community dominated by prasinophytes and coccolithophores, with low total biomass variability and high nutrient concentrations throughout the year. Sensitivity analysis revealed that the identity of the most sensitive parameters and the range of acceptable parameters differed between the two sites. We then use the model to predict community reorganization under different global change scenarios: a later onset and extended duration of stratification, with shallower mixed layer depths due to increased greenhouse gas concentrations; increase in deep water nitrogen; decrease in deep water phosphorus and increase or decrease in iron concentration. To estimate uncertainty in our predictions, we used a Monte Carlo sampling of the parameter space where future scenarios were run using parameter combinations that produced acceptable modern day outcomes and the robustness of the predictions was determined. Change in the onset and duration of stratification altered the timing and the magnitude of the spring diatom bloom in the North Atlantic and increased total phytoplankton and zooplankton biomass in the North Pacific. Changes in nutrient concentrations in some cases changed dominance patterns of major groups, as well as total chlorophyll and zooplankton biomass. Based on these scenarios, our model suggests that global environmental change will inevitably alter phytoplankton community structure and potentially impact global biogeochemical cycles.
ScienceCast 151: NASA to Launch Carbon Observatory
2014-06-24
NASA is about to launch a satellite dedicated to the study of the greenhouse gas carbon dioxide. The Orbiting Carbon Observatory (OCO-2) will quantify global CO2 sources and sinks, and help researchers predict the future of climate change.
Dryland photoautotrophic soil surface communities endangered by global change
Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina
2018-01-01
Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth’s terrestrial surface will decrease by about 25–40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.
Dryland photoautotrophic soil surface communities endangered by global change
NASA Astrophysics Data System (ADS)
Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina
2018-03-01
Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth's terrestrial surface will decrease by about 25-40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.
Opening our eyes to Global Health; a philosophy of universal values.
Wass, Val
2015-12-01
Globalization is advancing at a pace. As we strive to introduce 'Global Health' into clinical curricula we risk fundamental misunderstandings unless we clearly define what we aim to achieve. Clinicians must be prepared for a life time of uncertainty, change and challenge. The fluctuating world arena will undoubtedly impact on their future work in ways we cannot predict. Population migration, climate change and shifts in cultural dominance are already at play. Global health risks being translated through the eyes of Western ideology as disease-based curricula focused paternalistically on 'helping' the developing world. We must not lack humility to open eyes to learning within the context of increasingly diverse environments and patient populations. Global health is as 'local' as it is 'international'. It should be viewed, I argue, as a philosophy based on the values and expectations found within ourselves and our communities. Responding to globalization lies not only in knowledge but embraces human rights, justice and, most importantly, self-awareness. Knowledge is more easily translated into curriculum objectives. We risk letting future clinicians and their patients down if we ignore the other universal values.
Climate change and the global malaria recession.
Gething, Peter W; Smith, David L; Patil, Anand P; Tatem, Andrew J; Snow, Robert W; Hay, Simon I
2010-05-20
The current and potential future impact of climate change on malaria is of major public health interest. The proposed effects of rising global temperatures on the future spread and intensification of the disease, and on existing malaria morbidity and mortality rates, substantively influence global health policy. The contemporary spatial limits of Plasmodium falciparum malaria and its endemicity within this range, when compared with comparable historical maps, offer unique insights into the changing global epidemiology of malaria over the last century. It has long been known that the range of malaria has contracted through a century of economic development and disease control. Here, for the first time, we quantify this contraction and the global decreases in malaria endemicity since approximately 1900. We compare the magnitude of these changes to the size of effects on malaria endemicity proposed under future climate scenarios and associated with widely used public health interventions. Our findings have two key and often ignored implications with respect to climate change and malaria. First, widespread claims that rising mean temperatures have already led to increases in worldwide malaria morbidity and mortality are largely at odds with observed decreasing global trends in both its endemicity and geographic extent. Second, the proposed future effects of rising temperatures on endemicity are at least one order of magnitude smaller than changes observed since about 1900 and up to two orders of magnitude smaller than those that can be achieved by the effective scale-up of key control measures. Predictions of an intensification of malaria in a warmer world, based on extrapolated empirical relationships or biological mechanisms, must be set against a context of a century of warming that has seen marked global declines in the disease and a substantial weakening of the global correlation between malaria endemicity and climate.
Contribution of air conditioning adoption to future energy use under global warming.
Davis, Lucas W; Gertler, Paul J
2015-05-12
As household incomes rise around the world and global temperatures go up, the use of air conditioning is poised to increase dramatically. Air conditioning growth is expected to be particularly strong in middle-income countries, but direct empirical evidence is scarce. In this paper we use high-quality microdata from Mexico to describe the relationship between temperature, income, and air conditioning. We describe both how electricity consumption increases with temperature given current levels of air conditioning, and how climate and income drive air conditioning adoption decisions. We then combine these estimates with predicted end-of-century temperature changes to forecast future energy consumption. Under conservative assumptions about household income, our model predicts near-universal saturation of air conditioning in all warm areas within just a few decades. Temperature increases contribute to this surge in adoption, but income growth by itself explains most of the increase. What this will mean for electricity consumption and carbon dioxide emissions depends on the pace of technological change. Continued advances in energy efficiency or the development of new cooling technologies could reduce the energy consumption impacts. Similarly, growth in low-carbon electricity generation could mitigate the increases in carbon dioxide emissions. However, the paper illustrates the enormous potential impacts in this sector, highlighting the importance of future research on adaptation and underscoring the urgent need for global action on climate change.
Contribution of air conditioning adoption to future energy use under global warming
Davis, Lucas W.; Gertler, Paul J.
2015-01-01
As household incomes rise around the world and global temperatures go up, the use of air conditioning is poised to increase dramatically. Air conditioning growth is expected to be particularly strong in middle-income countries, but direct empirical evidence is scarce. In this paper we use high-quality microdata from Mexico to describe the relationship between temperature, income, and air conditioning. We describe both how electricity consumption increases with temperature given current levels of air conditioning, and how climate and income drive air conditioning adoption decisions. We then combine these estimates with predicted end-of-century temperature changes to forecast future energy consumption. Under conservative assumptions about household income, our model predicts near-universal saturation of air conditioning in all warm areas within just a few decades. Temperature increases contribute to this surge in adoption, but income growth by itself explains most of the increase. What this will mean for electricity consumption and carbon dioxide emissions depends on the pace of technological change. Continued advances in energy efficiency or the development of new cooling technologies could reduce the energy consumption impacts. Similarly, growth in low-carbon electricity generation could mitigate the increases in carbon dioxide emissions. However, the paper illustrates the enormous potential impacts in this sector, highlighting the importance of future research on adaptation and underscoring the urgent need for global action on climate change. PMID:25918391
ICPP: Approach for Understanding Complexity of Plasma
NASA Astrophysics Data System (ADS)
Sato, Tetsuya
2000-10-01
In this talk I wish to present an IT system that could promote Science of Complexity. In order to deal with a seemingly `complex' phenomenon, which means `beyond analytical manipulation', computer simulation is a viable powerful tool. However, complexity implies a concept beyond the horizon of reductionism. Therefore, rather than simply solving a complex phenomenon for a given boundary condition, one must establish an intelligent way of attacking mutual evolution of a system and its environment. NIFS-TCSC has been developing a prototype system that consists of supercomputers, virtual reality devices and high-speed network system. Let us explain this by picking up a global atmospheric circulation group, global oceanic circulation group and local weather prediction group. Local weather prediction group predicts the local change of the weather such as the creation of cloud and rain in the near future under the global conditions obtained by the global atmospheric and ocean groups. The global groups run simulations by modifying the local heat source/sink evaluated by the local weather prediction and then obtain the global conditions in the next time step. By repeating such a feedback performance one can predict the mutual evolution of the local system and its environment. Mutual information exchanges among multiple groups are carried out instantaneously by the networked common virtual reality space in which 3-D global and local images of the atmospheric and oceanic circulation and the cloud and rain maps are arbitrarily manipulated by any of the groups and commonly viewed. The present networking system has a great advantage that any simulation groups can freely and arbitrarily change their alignment, so that mutual evolution of any stratum system can become tractable by utilizing this network system.
NASA Astrophysics Data System (ADS)
Tallapragada, V.
2017-12-01
NOAA's Next Generation Global Prediction System (NGGPS) has provided the unique opportunity to develop and implement a non-hydrostatic global model based on Geophysical Fluid Dynamics Laboratory (GFDL) Finite Volume Cubed Sphere (FV3) Dynamic Core at National Centers for Environmental Prediction (NCEP), making a leap-step advancement in seamless prediction capabilities across all spatial and temporal scales. Model development efforts are centralized with unified model development in the NOAA Environmental Modeling System (NEMS) infrastructure based on Earth System Modeling Framework (ESMF). A more sophisticated coupling among various earth system components is being enabled within NEMS following National Unified Operational Prediction Capability (NUOPC) standards. The eventual goal of unifying global and regional models will enable operational global models operating at convective resolving scales. Apart from the advanced non-hydrostatic dynamic core and coupling to various earth system components, advanced physics and data assimilation techniques are essential for improved forecast skill. NGGPS is spearheading ambitious physics and data assimilation strategies, concentrating on creation of a Common Community Physics Package (CCPP) and Joint Effort for Data Assimilation Integration (JEDI). Both initiatives are expected to be community developed, with emphasis on research transitioning to operations (R2O). The unified modeling system is being built to support the needs of both operations and research. Different layers of community partners are also established with specific roles/responsibilities for researchers, core development partners, trusted super-users, and operations. Stakeholders are engaged at all stages to help drive the direction of development, resources allocations and prioritization. This talk presents the current and future plans of unified model development at NCEP for weather, sub-seasonal, and seasonal climate prediction applications with special emphasis on implementation of NCEP FV3 Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) into operations by 2019.
The Global Carbon Cycle: It's a Small World
NASA Astrophysics Data System (ADS)
Ineson, Philip; Milcu, Alexander; Subke, Jens-Arne; Wildman, Dennis; Anderson, Robert; Manning, Peter; Heinemeyer, Andreas
2010-05-01
Predicting future atmospheric concentrations of carbon dioxide (CO2), together with the impacts of these changes on global climate, are some of the most urgent and important challenges facing mankind. Modelling is the only way in which such predictions can be made, leading to the current generation of increasingly complex computer simulations, with associated concerns about embedded assumptions and conflicting model outputs. Alongside analysis of past climates, the GCMs currently represent our only hope of establishing the importance of potential runaway positive feedbacks linking climate change and atmospheric greenhouse gases yet the incorporation of necessary biospheric responses into GCMs markedly increases the uncertainty of predictions. Analysis of the importance of the major components of the global carbon (C) cycle reveals that an understanding of the conditions under which the terrestrial biosphere could switch from an overall carbon (C) sink to a source is critical to our ability to make future climate predictions. Here we present an alternative approach to assessing the short term biotic (plant and soil) sensitivities to elevated temperature and atmospheric CO2 through the use of a purely physical analogue. Centred on the concept of materially-closed systems containing scaled-down ratios of the global C stocks for the atmosphere, vegetation and soil we show that, in these model systems, the terrestrial biosphere is able to buffer a rise of 3oC even when coupled to very strong CO2-temperature positive feedbacks. The system respiratory response appears to be extremely well linked to temperature and is critical in deciding atmospheric concentrations of CO2. Simulated anthropogenic emissions of CO2 into the model systems showed an initial corresponding increase in atmospheric CO2 but, somewhat surprisingly, CO2 concentrations levelled off at ca. 480 p.p.m.v., despite continuing additions of CO2. Experiments were performed in which reversion of atmospheric temperatures, or cessation of CO2 additions, showed rapid and proportionate decreases in atmospheric CO2 concentrations. The results indicate that short term terrestrial feedbacks are not sufficient to induce a CO2-temperature runaway scenario and suggest that predictions of atmospheric CO2 by current GCMs may under-estimate the CO2 fertilisation effect on plants and, hence, over-estimate future atmospheric CO2 increases. Perhaps, more importantly, the experiments show that the impacts of imposed elevated CO2 and temperature increase can be reversed. Whilst clearly representing a simplified version of terrestrial CO2 dynamics, it is proposed that closed system research represents a new form of test-bed for validation of processes represented within digital global CO2 models.
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.
Fodor, Nándor; Challinor, Andrew; Droutsas, Ioannis; Ramirez-Villegas, Julian; Zabel, Florian; Koehler, Ann-Kristin; Foyer, Christine H
2017-11-01
Increasing global CO2 emissions have profound consequences for plant biology, not least because of direct influences on carbon gain. However, much remains uncertain regarding how our major crops will respond to a future high CO2 world. Crop model inter-comparison studies have identified large uncertainties and biases associated with climate change. The need to quantify uncertainty has drawn the fields of plant molecular physiology, crop breeding and biology, and climate change modeling closer together. Comparing data from different models that have been used to assess the potential climate change impacts on soybean and maize production, future yield losses have been predicted for both major crops. When CO2 fertilization effects are taken into account significant yield gains are predicted for soybean, together with a shift in global production from the Southern to the Northern hemisphere. Maize production is also forecast to shift northwards. However, unless plant breeders are able to produce new hybrids with improved traits, the forecasted yield losses for maize will only be mitigated by agro-management adaptations. In addition, the increasing demands of a growing world population will require larger areas of marginal land to be used for maize and soybean production. We summarize the outputs of crop models, together with mitigation options for decreasing the negative impacts of climate on the global maize and soybean production, providing an overview of projected land-use change as a major determining factor for future global crop production. © The Author 2017. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists.
ATLAS trigger operations: Upgrades to ``Xmon'' rate prediction system
NASA Astrophysics Data System (ADS)
Myers, Ava; Aukerman, Andrew; Hong, Tae Min; Atlas Collaboration
2017-01-01
We present ``Xmon,'' a tool to monitor trigger rates in the Control Room of the ATLAS Experiment. We discuss Xmon's recent (1) updates, (2) upgrades, and (3) operations. (1) Xmon was updated to modify the tool written for the three-level trigger architecture in Run-1 (2009-2012) to adapt to the new two-level system for Run-2 (2015-current). The tool takes as input the beam luminosity to make a rate prediction, which is compared with incoming rates to detect anomalies that occur both globally throughout a run and locally within a run. Global offsets are more commonly caught by the predictions based upon past runs, where offline processing allows for function adjustments and fit quality through outlier rejection. (2) Xmon was upgraded to detect local offsets using on-the-fly predictions, which uses a sliding window of in-run rates to make predictions. (3) Xmon operations examples are given. Future work involves further automation of the steps to provide the predictive functions and for alerting shifters.
Scaling the metabolic balance of the oceans.
López-Urrutia, Angel; San Martin, Elena; Harris, Roger P; Irigoien, Xabier
2006-06-06
Oceanic communities are sources or sinks of CO2, depending on the balance between primary production and community respiration. The prediction of how global climate change will modify this metabolic balance of the oceans is limited by the lack of a comprehensive underlying theory. Here, we show that the balance between production and respiration is profoundly affected by environmental temperature. We extend the general metabolic theory of ecology to the production and respiration of oceanic communities and show that ecosystem rates can be reliably scaled from theoretical knowledge of organism physiology and measurement of population abundance. Our theory predicts that the differential temperature-dependence of respiration and photosynthesis at the organism level determines the response of the metabolic balance of the epipelagic ocean to changes in ambient temperature, a prediction that we support with empirical data over the global ocean. Furthermore, our model predicts that there will be a negative feedback of ocean communities to climate warming because they will capture less CO2 with a future increase in ocean temperature. This feedback of marine biota will further aggravate the anthropogenic effects on global warming.
Deconstructing Our Dark Age Future
2009-03-16
existed for centuries . Perhaps the most compelling archetypes, however, were the various anarchist movements of the late Victorian era. In the 30 or so...failed to develop until the late 19th Century . 16 Ibid. Martin van Creveld interprets this differently, stating that because the treaty gave the...to underwrite their observations of global chaos and predictions of a dismal future.8 This paradigm endures because over the past century it has
Global Warming in the 21st Century: An Alternate Scenario
NASA Technical Reports Server (NTRS)
Hansen, James E.
2000-01-01
Evidence on a broad range of time scales, from Proterozoic to the most recent periods, shows that the Earth's climate responds sensitively to global forcings. In the past few decades the Earth's surface has warmed rapidly, apparently in response to increasing anthropogenic greenhouse gases in the atmosphere. The conventional view is that the current global warming rate will continue or accelerate in the 21st century. I will describe an alternate scenario that would slow the rate of global warming and reduce the danger of dramatic climate change. But reliable prediction of future climate change requires improved knowledge of the carbon cycle and global observations that allow interpretation of ongoing climate change.
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.
2004-01-01
international Argo practices. Data appropriate for research applications and for comparison with climate change models are not available for several...global ocean heat and fresh water storage and the detection and attribution of climate change . These presentations can be accessed at http...stresses on ocean ecosystems have serious consequences, and sometimes dramatic ones, such as coral reef bleaching . In the future, the impacts of a
Is Global Warming likely to cause an increased incidence of Malaria?
Nabi, Sa; Qader, Ss
2009-03-01
The rise in the average temperature of earth has been described as global warming which is mainly attributed to the increasing phenomenon of the greenhouse effect. It is believed that global warming can have several harmful effects on human health, both directly and indirectly. Since malaria is greatly influenced by climatic conditions because of its direct relationship with the mosquito population, it is widely assumed that its incidence is likely to increase in a future warmer world.This review article discusses the two contradictory views regarding the association of global warming with an increased incidence of malaria. On one hand, there are many who believe that there is a strong association between the recent increase in malaria incidence and global warming. They predict that as global warming continues, malaria is set to spread in locations where previously it was limited, due to cooler climate. On the other hand, several theories have been put forward which are quite contrary to this prediction. There are multiple other factors which are accountable for the recent upsurge of malaria: for example drug resistance, mosquito control programs, public health facilities, and living standards.
Future change of water vaiables from HadGEM2-AO simulation
NASA Astrophysics Data System (ADS)
Kim, Moon-Hyun; Kang, Hyun-Suk; Lee, Johan; Baek, Hee-Jeong; Cho, Chunho
2013-04-01
Complex global models developed for climate prediction are now applied to the future climate projection in a number of global modeling centers around the world. In climate prediction aspects, an atmosphere-ocean coupled model (one-tier climate system) has been recognized to exhibit useful skill for a global or certain regions (Graham et al., 2005). Wang et al. (2005) demonstrates that an AGCM coupled with an ocean model, simulates realistic SST-rainfall relationships for the Asia during the summer period. Also the transition from two-tier to one-tier approach in climate prediction are mainly caused by recent progresses in development of coupled climate models and enlargement of understanding air-sea interactions obtained from international collaborative efforts such as TOGA (the Tropical Ocean-Global Atmosphere) program (Wang et al., 2009). Meanwhile, water resource including river outflow in association with surface and sub-surface water flow is an important part of the global hydrological cycle, and is affected by climate variability and change through recharge processes (Chen et al., 2002), as well as by human interventions in many locations (Petheram et al., 2001). Also, water is critical resource to the social, economic and environmental aspects, and advances of these core elements requires improved water resource management. Better management and use of water need to abundant real time hydro-meteorological (river and weather) information as well as accurate water resource forecasting (Barrett, 1990). For this reason, many studies have recently carrying out the water resource prediction and estimation using hydrology and climate model. For example, Shiklomanov et al. (2011) predicted that water resource in Russian territory increases about 8-10% during 2010-2020 using the unit hydrograph (UH) model based on hydrologic rainfall-runoff model. Anderson et al. (2000) explained the probabilistic seasonal prediction of drought with a simplified climate model coupled hydrology-atmosphere for water resource planning. Arora et al. (1999) and Oki and Sud (1998) developed a method for routing river flows through GCM grid cells. Accordingly, reliable forecasts are expected to help water managers and users with long lead time decisions, leading to greater water use efficiency and better risk management (Wang, 2012). SO, we analysed hydrological cycle and drought index from precipitation, evaporation, runoff, soil moisture, river outflow, and so on using atmosphere-ocean coupled model which called by HadGEM2-AO. Details and added information by this climate projection system about the future water cycle's change will be presented at the workshop. Acknowledgments: This research has been supported by project NIMR-2013-B-2 of the National Institute of Meteorological Research in Korea Meteorological Administration.
Potential impacts of global warming on water resources in southern California.
Beuhler, M
2003-01-01
Global warming will have a significant impact on water resources within the 20 to 90-year planning period of many water projects. Arid and semi-arid regions such as Southern California are especially vulnerable to anticipated negative impacts of global warming on water resources. Long-range water facility planning must consider global climate change in the recommended mix of new facilities needed to meet future water requirements. The generally accepted impacts of global warming include temperature, rising sea levels, more frequent and severe floods and droughts, and a shift from snowfall to rain. Precipitation changes are more difficult to predict. For Southern California, these impacts will be especially severe on surface water supplies. Additionally, rising sea levels will exacerbate salt-water intrusion into freshwater and impact the quality of surface water supplies. Integrated water resources planning is emerging as a tool to develop water supplies and demand management strategies that are less vulnerable to the impacts of global warming. These tools include water conservation, conjunctive use of surface and groundwater and desalination of brackish water and possibly seawater. Additionally, planning for future water needs should include explicit consideration of the potential range of global warming impacts through techniques such as scenario planning.
McElwain, Jennifer C
2018-04-29
Human carbon use during the next century will lead to atmospheric carbon dioxide concentrations (pCO 2 ) that have been unprecedented for the past 50-100+ million years according to fossil plant-based CO 2 estimates. The paleobotanical record of plants offers key insights into vegetation responses to past global change, including suitable analogs for Earth's climatic future. Past global warming events have resulted in transient poleward migration at rates that are equivalent to the lowest climate velocities required for current taxa to keep pace with climate change. Paleobiome reconstructions suggest that the current tundra biome is the biome most threatened by global warming. The common occurrence of paleoforests at high polar latitudes when pCO 2 was above 500 ppm suggests that the advance of woody shrub and tree taxa into tundra environments may be inevitable. Fossil pollen studies demonstrate the resilience of wet tropical forests to global change up to 700 ppm CO 2 , contrary to modeled predictions of the future. The paleobotanical record also demonstrates a high capacity for functional trait evolution as an additional strategy to migration and maintenance of a species' climate envelope in response to global change.
NASA Astrophysics Data System (ADS)
Land, P. E.; Shutler, J. D.; Bell, T. G.; Yang, M.
2014-11-01
We used coincident Envisat RA2 and AATSR temperature and wind speed data from 2008/2009 to calculate the global net sea-air flux of dimethyl sulfide (DMS), which we estimate to be 19.6 Tg S a-1. Our monthly flux calculations are compared to open ocean eddy correlation measurements of DMS flux from 10 recent cruises, with a root mean square difference of 3.1 μmol m-2 day-1. In a sensitivity analysis, we varied temperature, salinity, surface wind speed, and aqueous DMS concentration, using fixed global changes as well as CMIP5 model output. The range of DMS flux in future climate scenarios is discussed. The CMIP5 model predicts a reduction in surface wind speed and we estimate that this will decrease the global annual sea-air flux of DMS by 22% over 25 years. Concurrent changes in temperature, salinity, and DMS concentration increase the global flux by much smaller amounts. The net effect of all CMIP5 modelled 25 year predictions was a 19% reduction in global DMS flux. 25 year DMS concentration changes had significant regional effects, some positive (Southern Ocean, North Atlantic, Northwest Pacific) and some negative (isolated regions along the Equator and in the Indian Ocean). Using satellite-detected coverage of coccolithophore blooms, our estimate of their contribution to North Atlantic DMS emissions suggests that the coccolithophores contribute only a small percentage of the North Atlantic annual flux estimate, but may be more important in the summertime and in the northeast Atlantic.
Darcy's law predicts widespread forest mortality under climate warming
NASA Astrophysics Data System (ADS)
McDowell, Nathan G.; Allen, Craig D.
2015-07-01
Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We use a hydraulic corollary to Darcy’s law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy’s law indicates today’s forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy’s corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. Given the robustness of Darcy’s law for predictions of vascular plant function, we conclude with high certainty that today’s forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.
Darcy’s law predicts widespread forest mortality under climate warming
McDowell, Nate G.; Allen, Craig D.
2015-01-01
Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We use a hydraulic corollary to Darcy’s law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy’s law indicates today’s forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy’s corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. Given the robustness of Darcy’s law for predictions of vascular plant function, we conclude with high certainty that today’s forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.
Global Oil: Relax, the End Is Not Near
NASA Astrophysics Data System (ADS)
Fisher, W. L.
2004-12-01
Global oil production will peak within the next 25 to 30 years, but peaking will be a function of demand, not supply, as the methane economy comes into full play. Analysts who predict near-term peaking of global oil production generally use some variant of Hubbert's symmetrical life cycle method. The amount of ultimately recoverable oil is assumed to be known and peaking will occur when half that amount is exhausted. In reality, ultimate recovery volumes are not known, but estimated, and estimates vary by a factor of two; production profiles are not necessarily symmetrical. Further assumptions are that the resource base is inelastic, not significantly expandable through technology and new concepts. The historical experience is quite to the contrary. Projections of near-term peaking ignore or discount field reserve growth, the most dynamic element in reserve additions of the past 25 years and one with the future potential equal to that of new field discovery. Future global demand for oil will likely amount to between 1.5 to 2.0 trillion barrels, well within the more realistic estimates of global recovery volumes. The real challenge is not oil, but natural gas where future global demand will likely exceed 25,000 trillion cubic feet. But it too will be met in sufficient volumes to bring us into the hydrogen economy some 50 to 60 years from now.
Jones, Rupert C; Price, David; Chavannes, Niels H; Lee, Amanda J; Hyland, Michael E; Ställberg, Björn; Lisspers, Karin; Sundh, Josefin; van der Molen, Thys; Tsiligianni, Ioanna
2016-01-01
Suitable tools for assessing the severity of chronic obstructive pulmonary disease (COPD) include multi-component indices and the global initiative for chronic obstructive lung disease (GOLD) categories. The aim of this study was to evaluate the dyspnoea, obstruction, smoking, exacerbation (DOSE) and the age, dyspnoea, obstruction (ADO) indices and GOLD categories as measures of current health status and future outcomes in COPD patients. This was an observational cohort study comprising 5,114 primary care COPD patients across three databases from UK, Sweden and Holland. The associations of DOSE and ADO indices with (i) health status using the Clinical COPD Questionnaire (CCQ) and St George’s Respiratory Questionnaire (SGRQ) and COPD Assessment test (CAT) and with (ii) current and future exacerbations, admissions and mortality were assessed in GOLD categories and DOSE and ADO indices. DOSE and ADO indices were significant predictors of future exacerbations: incident rate ratio was 1.52 (95% confidence intervals 1.46–1.57) for DOSE, 1.16 (1.12–1.20) for ADO index and 1.50 (1.33–1.68) and 1.23 (1.10–1.39), respectively, for hospitalisations. Negative binomial regression showed that the DOSE index was a better predictor of future admissions than were its component items. The hazard ratios for mortality were generally higher for ADO index groups than for DOSE index groups. The GOLD categories produced widely differing assessments for future exacerbation risk or for hospitalisation depending on the methods used to calculate them. None of the assessment systems were excellent at predicting future risk in COPD; the DOSE index appears better than the ADO index for predicting many outcomes, but not mortality. The GOLD categories predict future risk inconsistently. The DOSE index and the GOLD categories using exacerbation frequency may be used to identify those at high risk for exacerbations and admissions. PMID:27053297
Jones, Rupert C; Price, David; Chavannes, Niels H; Lee, Amanda J; Hyland, Michael E; Ställberg, Björn; Lisspers, Karin; Sundh, Josefin; van der Molen, Thys; Tsiligianni, Ioanna
2016-04-07
Suitable tools for assessing the severity of chronic obstructive pulmonary disease (COPD) include multi-component indices and the global initiative for chronic obstructive lung disease (GOLD) categories. The aim of this study was to evaluate the dyspnoea, obstruction, smoking, exacerbation (DOSE) and the age, dyspnoea, obstruction (ADO) indices and GOLD categories as measures of current health status and future outcomes in COPD patients. This was an observational cohort study comprising 5,114 primary care COPD patients across three databases from UK, Sweden and Holland. The associations of DOSE and ADO indices with (i) health status using the Clinical COPD Questionnaire (CCQ) and St George's Respiratory Questionnaire (SGRQ) and COPD Assessment test (CAT) and with (ii) current and future exacerbations, admissions and mortality were assessed in GOLD categories and DOSE and ADO indices. DOSE and ADO indices were significant predictors of future exacerbations: incident rate ratio was 1.52 (95% confidence intervals 1.46-1.57) for DOSE, 1.16 (1.12-1.20) for ADO index and 1.50 (1.33-1.68) and 1.23 (1.10-1.39), respectively, for hospitalisations. Negative binomial regression showed that the DOSE index was a better predictor of future admissions than were its component items. The hazard ratios for mortality were generally higher for ADO index groups than for DOSE index groups. The GOLD categories produced widely differing assessments for future exacerbation risk or for hospitalisation depending on the methods used to calculate them. None of the assessment systems were excellent at predicting future risk in COPD; the DOSE index appears better than the ADO index for predicting many outcomes, but not mortality. The GOLD categories predict future risk inconsistently. The DOSE index and the GOLD categories using exacerbation frequency may be used to identify those at high risk for exacerbations and admissions.
Biomes computed from simulated climatologies
DOE Office of Scientific and Technical Information (OSTI.GOV)
Claussen, M.; Esch, M.
1994-01-01
The biome model of Prentice et al. is used to predict global patterns of potential natural plant formations, or biomes, from climatologies simulated by ECHAM, a model used for climate simulations at the Max-Planck-Institut fuer Meteorologie. This study undertaken in order to show the advantage of this biome model in diagnosing the performance of a climate model and assessing effects of past and future climate changes predicted by a climate model. Good overall agreement is found between global patterns of biomes computed from observed and simulated data of present climate. But there are also major discrepancies indicated by a differencemore » in biomes in Australia, in the Kalahari Desert, and in the Middle West of North America. These discrepancies can be traced back to in simulated rainfall as well as summer or winter temperatures. Global patterns of biomes computed from an ice age simulation reveal that North America, Europe, and Siberia should have been covered largely by tundra and taiga, whereas only small differences are for the tropical rain forests. A potential northeast shift of biomes is expected from a simulation with enhanced CO{sub 2} concentration according to the IPCC Scenario A. Little change is seen in the tropical rain forest and the Sahara. Since the biome model used is not capable of predicting chances in vegetation patterns due to a rapid climate change, the latter simulation to be taken as a prediction of chances in conditions favourable for the existence of certain biomes, not as a reduction of a future distribution of biomes. 15 refs., 8 figs., 2 tabs.« less
Predicting ionospheric scintillation: Recent advancements and future challenges
NASA Astrophysics Data System (ADS)
Carter, B. A.; Currie, J. L.; Terkildsen, M.; Bouya, Z.; Parkinson, M. L.
2017-12-01
Society greatly benefits from space-based infrastructure and technology. For example, signals from Global Navigation Satellite Systems (GNSS) are used across a wide range of industrial sectors; including aviation, mining, agriculture and finance. Current trends indicate that the use of these space-based technologies is likely to increase over the coming decades as the global economy becomes more technology-dependent. Space weather represents a key vulnerability to space-based technology, both in terms of the space environment effects on satellite infrastructure and the influence of the ionosphere on the radio signals used for satellite communications. In recent decades, the impact of the ionosphere on GNSS signals has re-ignited research interest into the equatorial ionosphere, particularly towards understanding Equatorial Plasma Bubbles (EPBs). EPBs are a dominant source of nighttime plasma irregularities in the low-latitude ionosphere, which can cause severe scintillation on GNSS signals and subsequent degradation on GNSS product quality. Currently, ionospheric scintillation event forecasts are not being routinely released by any space weather prediction agency around the world, but this is likely to change in the near future. In this contribution, an overview of recent efforts to develop a global ionospheric scintillation prediction capability within Australia will be given. The challenges in understanding user requirements for ionospheric scintillation predictions will be discussed. Next, the use of ground- and space-based datasets for the purpose of near-real time ionospheric scintillation monitoring will be explored. Finally, some modeling that has shown significant promise in transitioning towards an operational ionospheric scintillation forecasting system will be discussed.
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.
Maestre, Fernando T.; Salguero-Gómez, Roberto; Quero, José L.
2012-01-01
Drylands occupy large portions of the Earth, and are a key terrestrial biome from the socio-ecological point of view. In spite of their extent and importance, the impacts of global environmental change on them remain poorly understood. In this introduction, we review some of the main expected impacts of global change in drylands, quantify research efforts on the topic, and highlight how the articles included in this theme issue contribute to fill current gaps in our knowledge. Our literature analyses identify key under-studied areas that need more research (e.g. countries such as Mauritania, Mali, Burkina Faso, Chad and Somalia, and deserts such as the Thar, Kavir and Taklamakan), and indicate that most global change research carried out to date in drylands has been done on a unidisciplinary basis. The contributions included here use a wide array of organisms (from micro-organisms to humans), spatial scales (from local to global) and topics (from plant demography to poverty alleviation) to examine key issues to the socio-ecological impacts of global change in drylands. These papers highlight the complexities and difficulties associated with the prediction of such impacts. They also identify the increased use of long-term experiments and multidisciplinary approaches as priority areas for future dryland research. Major advances in our ability to predict and understand global change impacts on drylands can be achieved by explicitly considering how the responses of individuals, populations and communities will in turn affect ecosystem services. Future research should explore linkages between these responses and their effects on water and climate, as well as the provisioning of services for human development and well-being. PMID:23045705
Maestre, Fernando T; Salguero-Gómez, Roberto; Quero, José L
2012-11-19
Drylands occupy large portions of the Earth, and are a key terrestrial biome from the socio-ecological point of view. In spite of their extent and importance, the impacts of global environmental change on them remain poorly understood. In this introduction, we review some of the main expected impacts of global change in drylands, quantify research efforts on the topic, and highlight how the articles included in this theme issue contribute to fill current gaps in our knowledge. Our literature analyses identify key under-studied areas that need more research (e.g. countries such as Mauritania, Mali, Burkina Faso, Chad and Somalia, and deserts such as the Thar, Kavir and Taklamakan), and indicate that most global change research carried out to date in drylands has been done on a unidisciplinary basis. The contributions included here use a wide array of organisms (from micro-organisms to humans), spatial scales (from local to global) and topics (from plant demography to poverty alleviation) to examine key issues to the socio-ecological impacts of global change in drylands. These papers highlight the complexities and difficulties associated with the prediction of such impacts. They also identify the increased use of long-term experiments and multidisciplinary approaches as priority areas for future dryland research. Major advances in our ability to predict and understand global change impacts on drylands can be achieved by explicitly considering how the responses of individuals, populations and communities will in turn affect ecosystem services. Future research should explore linkages between these responses and their effects on water and climate, as well as the provisioning of services for human development and well-being.
Evaluation of coral reef carbonate production models at a global scale
NASA Astrophysics Data System (ADS)
Jones, N. S.; Ridgwell, A.; Hendy, E. J.
2015-03-01
Calcification by coral reef communities is estimated to account for half of all carbonate produced in shallow water environments and more than 25% of the total carbonate buried in marine sediments globally. Production of calcium carbonate by coral reefs is therefore an important component of the global carbon cycle; it is also threatened by future global warming and other global change pressures. Numerical models of reefal carbonate production are needed for understanding how carbonate deposition responds to environmental conditions including atmospheric CO2 concentrations in the past and into the future. However, before any projections can be made, the basic test is to establish model skill in recreating present-day calcification rates. Here we evaluate four published model descriptions of reef carbonate production in terms of their predictive power, at both local and global scales. We also compile available global data on reef calcification to produce an independent observation-based data set for the model evaluation of carbonate budget outputs. The four calcification models are based on functions sensitive to combinations of light availability, aragonite saturation (Ωa) and temperature and were implemented within a specifically developed global framework, the Global Reef Accretion Model (GRAM). No model was able to reproduce independent rate estimates of whole-reef calcification, and the output from the temperature-only based approach was the only model to significantly correlate with coral-calcification rate observations. The absence of any predictive power for whole reef systems, even when consistent at the scale of individual corals, points to the overriding importance of coral cover estimates in the calculations. Our work highlights the need for an ecosystem modelling approach, accounting for population dynamics in terms of mortality and recruitment and hence calcifier abundance, in estimating global reef carbonate budgets. In addition, validation of reef carbonate budgets is severely hampered by limited and inconsistent methodology in reef-scale observations.
Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.
2017-01-01
Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519
Global Pyrogeography: the Current and Future Distribution of Wildfire
Krawchuk, Meg A.; Moritz, Max A.; Parisien, Marc-André; Van Dorn, Jeff; Hayhoe, Katharine
2009-01-01
Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning. PMID:19352494
NASA Astrophysics Data System (ADS)
Kloster, S.; Mahowald, N. M.; Randerson, J. T.; Lawrence, P. J.
2012-01-01
Landscape fires during the 21st century are expected to change in response to multiple agents of global change. Important controlling factors include climate controls on the length and intensity of the fire season, fuel availability, and fire management, which are already anthropogenically perturbed today and are predicted to change further in the future. An improved understanding of future fires will contribute to an improved ability to project future anthropogenic climate change, as changes in fire activity will in turn impact climate. In the present study we used a coupled-carbon-fire model to investigate how changes in climate, demography, and land use may alter fire emissions. We used climate projections following the SRES A1B scenario from two different climate models (ECHAM5/MPI-OM and CCSM) and changes in population. Land use and harvest rates were prescribed according to the RCP 45 scenario. In response to the combined effect of all these drivers, our model estimated, depending on our choice of climate projection, an increase in future (2075-2099) fire carbon emissions by 17 and 62% compared to present day (1985-2009). The largest increase in fire emissions was predicted for Southern Hemisphere South America for both climate projections. For Northern Hemisphere Africa, a region that contributed significantly to the global total fire carbon emissions, the response varied between a decrease and an increase depending on the climate projection. We disentangled the contribution of the single forcing factors to the overall response by conducting an additional set of simulations in which each factor was individually held constant at pre-industrial levels. The two different projections of future climate change evaluated in this study led to increases in global fire carbon emissions by 22% (CCSM) and 66% (ECHAM5/MPI-OM). The RCP 45 projection of harvest and land use led to a decrease in fire carbon emissions by -5%. The RCP 26 and RCP 60 harvest and landuse projections caused decreases around -20%. Changes in human ignition led to an increase of 20%. When we also included changes in fire management efforts to suppress fires in densely populated areas, global fire carbon emission decreased by -6% in response to changes in population density. We concluded from this study that changes in fire emissions in the future are controlled by multiple interacting factors. Although changes in climate led to an increase in future fire emissions this could be globally counterbalanced by coupled changes in land use, harvest, and demography.
Spread of the Tiger: Global Risk of Invasion by the Mosquito Aedes albopictus
BENEDICT, MARK Q.; LEVINE, REBECCA S.; HAWLEY, WILLIAM A.; LOUNIBOS, L. PHILIP
2008-01-01
Aedes albopictus, commonly known as the Asian tiger mosquito, is currently the most invasive mosquito in the world. It is of medical importance due to its aggressive daytime human-biting behavior and ability to vector many viruses, including dengue, LaCrosse, and West Nile. Invasions into new areas of its potential range are often initiated through the transportation of eggs via the international trade in used tires. We use a genetic algorithm, Genetic Algorithm for Rule Set Production (GARP), to determine the ecological niche of Ae. albopictus and predict a global ecological risk map for the continued spread of the species. We combine this analysis with risk due to importation of tires from infested countries and their proximity to countries that have already been invaded to develop a list of countries most at risk for future introductions and establishments. Methods used here have potential for predicting risks of future invasions of vectors or pathogens. PMID:17417960
NASA Astrophysics Data System (ADS)
Beck, F.; Bárdossy, A.
2013-07-01
Many hydraulic applications like the design of urban sewage systems require projections of future precipitation in high temporal resolution. We developed a method to predict the regional distribution of hourly precipitation sums based on daily mean sea level pressure and temperature data from a Global Circulation Model. It is an indirect downscaling method avoiding uncertain precipitation data from the model. It is based on a fuzzy-logic classification of atmospheric circulation patterns (CPs) that is further subdivided by means of the average daily temperature. The observed empirical distributions at 30 rain gauges to each CP-temperature class are assumed as constant and used for projections of the hourly precipitation sums in the future. The method was applied to the CP-temperature sequence derived from the 20th century run and the scenario A1B run of ECHAM5. According to ECHAM5, the summers in southwest Germany will become progressively drier. Nevertheless, the frequency of the highest hourly precipitation sums will increase. According to the predictions, estival water stress and the risk of extreme hourly precipitation will both increase simultaneously during the next decades.
NASA Astrophysics Data System (ADS)
Lamb, B. K.; Gonzalez Abraham, R.; Avise, J. C.; Chung, S. H.; Salathe, E. P.; Zhang, Y.; Guenther, A. B.; Wiedinmyer, C.; Duhl, T.; Streets, D. G.
2013-05-01
Global change will clearly have a significant impact on the environment. Among the concerns for future air quality in North America, intercontinental transport of pollution has become increasingly important. In this study, we examined the effect of projected changes in Asian emissions and emissions from lightning and wildfires to produce ozone background concentrations within Mexico and the continental US. This provides a basis for developing an understanding of North American background levels and how they may change in the future. Meteorological fields were downscaled from the results of the ECHAM5 global climate model using the Weather Research Forecast (WRF) model. Two nested domains were employed, one covering most of the Northern Hemisphere from eastern Asia to North America using 220 km grid cells (semi-hemispheric domain) and one covering the continental US and northern Mexico using 36 km grid cells. Meteorological results from WRF were used to drive the MEGAN biogenic emissions model, the SMOKE emissions processing tool, and the CMAQ chemical transport model to predict ozone concentrations for current (1995-2004) and future (2045-2054) summertime conditions. The MEGAN model was used to calculate biogenic emissions for all simulations. For the semi-hemispheric domain, year 2000 global emissions of gases (ozone precursors) from anthropogenic (outside of North America), natural, and biomass burning sources from the POET and EDGAR emission inventories were used. The global tabulation for black and organic carbon (BC and OC respectively) was obtained from Bond et al. (2004) For the future decade, the current emissions were projected to the year 2050 following the Intergovernmental Panel for Climate Change (IPCC) A1B emission scenario. Anthropogenic emissions from the US, Canada, and Mexico were omitted so that only global background concentrations, and local biogenic, wildfire, and lightning emissions were treated. In this paper, we focus on background ozone levels in Mexico due to changes in future climate, local biogenic emissions and global emissions.
Enhancing Participation in the U.S. Global Change Research Program
DOE Office of Scientific and Technical Information (OSTI.GOV)
Washington, Warren; Lee, Kai; Arent, Doug
2016-02-29
The US Global Change Research Program (USGCRP) is a collection of 13 Federal entities charged by law to assist the United States and the world to understand, assess, predict, and respond to human-induced and natural processes of global change. As the understanding of global change has evolved over the past decades and as demand for scientific information on global change has increased, the USGCRP has increasingly focused on research that can inform decisions to cope with current climate variability and change, to reduce the magnitude of future changes, and to prepare for changes projected over coming decades. Overall, the currentmore » breadth and depth of research in these agencies is insufficient to meet the country's needs, particularly to support decision makers. This report provides a rationale for evaluating current program membership and capabilities and identifying potential new agencies and departments in the hopes that these changes will enable the program to more effectively inform the public and prepare for the future. It also offers actionable recommendations for adjustments to the methods and procedures that will allow the program to better meet its stated goals.« less
Morita, M
2011-01-01
Global climate change is expected to affect future rainfall patterns. These changes should be taken into account when assessing future flooding risks. This study presents a method for quantifying the increase in flood risk caused by global climate change for use in urban flood risk management. Flood risk in this context is defined as the product of flood damage potential and the probability of its occurrence. The study uses a geographic information system-based flood damage prediction model to calculate the flood damage caused by design storms with different return periods. Estimation of the monetary damages these storms produce and their return periods are precursors to flood risk calculations. The design storms are developed from modified intensity-duration-frequency relationships generated by simulations of global climate change scenarios (e.g. CGCM2A2). The risk assessment method is applied to the Kanda River basin in Tokyo, Japan. The assessment provides insights not only into the flood risk cost increase due to global warming, and the impact that increase may have on flood control infrastructure planning.
Predictive simulation of guide-wave structural health monitoring
NASA Astrophysics Data System (ADS)
Giurgiutiu, Victor
2017-04-01
This paper presents an overview of recent developments on predictive simulation of guided wave structural health monitoring (SHM) with piezoelectric wafer active sensor (PWAS) transducers. The predictive simulation methodology is based on the hybrid global local (HGL) concept which allows fast analytical simulation in the undamaged global field and finite element method (FEM) simulation in the local field around and including the damage. The paper reviews the main results obtained in this area by researchers of the Laboratory for Active Materials and Smart Structures (LAMSS) at the University of South Carolina, USA. After thematic introduction and research motivation, the paper covers four main topics: (i) presentation of the HGL analysis; (ii) analytical simulation in 1D and 2D; (iii) scatter field generation; (iv) HGL examples. The paper ends with summary, discussion, and suggestions for future work.
Lei, Juncheng; Chen, Lian; Li, Hong
2017-08-01
The golden apple snail, Pomacea canaliculata, is one of the world's 100 most notorious invasive alien species. Knowledge about the critical climate variables that limit the global distribution range of the snail, as well as predictions of future species distributions under climate change, is very helpful for management of snail. In this study, the climatically suitable habitats for this kind of snail under current climate conditions were modeled by biomod2 and projected to eight future climate scenarios (2 time periods [2050s, 2080s] × 2 Representative Concentration Pathways [RCPs; RCP2.6, RCP8.5] × 2 atmospheric General Circulation Models [GCMs; Canadian Centre for Climate Modelling and Analysis (CCCMA), Commonwealth Scientific and Industrial Research Organisation (CSIRO)]). The results suggest that the lowest temperature of coldest month is the critical climate variable to restrict the global distribution range of P. canaliculata. It is predicted that the climatically suitable habitats for P. canaliculata will increase by an average of 3.3% in 2050s and 3.8% in 2080s for the RCP2.6 scenario, while they increase by an average of 8.7% in 2050s and 10.3% in 2080s for the RCP8.5 scenario. In general, climate change in the future may promote the global invasion of the invasive species. Therefore, it is necessary to take proactive measures to monitor and preclude the invasion of this species.
The Science-Policy Link: Stakeholder Reactions to the Uncertainties of Future Sea Level Rise
NASA Astrophysics Data System (ADS)
Plag, H.; Bye, B.
2011-12-01
Policy makers and stakeholders in the coastal zone are equally challenged by the risk of an anticipated rise of coastal Local Sea Level (LSL) as a consequence of future global warming. Many low-lying and often densely populated coastal areas are under risk of increased inundation. More than 40% of the global population is living in or near the coastal zone and this fraction is steadily increasing. A rise in LSL will increase the vulnerability of coastal infrastructure and population dramatically, with potentially devastating consequences for the global economy, society, and environment. Policy makers are faced with a trade-off between imposing today the often very high costs of coastal protection and adaptation upon national economies and leaving the costs of potential major disasters to future generations. They are in need of actionable information that provides guidance for the development of coastal zones resilient to future sea level changes. Part of this actionable information comes from risk and vulnerability assessments, which require information on future LSL changes as input. In most cases, a deterministic approach has been applied based on predictions of the plausible range of future LSL trajectories as input. However, there is little consensus in the scientific community on how these trajectories should be determined, and what the boundaries of the plausible range are. Over the last few years, many publications in Science, Nature and other peer-reviewed scientific journals have revealed a broad range of possible futures and significant epistemic uncertainties and gaps concerning LSL changes. Based on the somewhat diffuse science input, policy and decision makers have made rather different choices for mitigation and adaptation in cases such as Venice, The Netherlands, New York City, and the San Francisco Bay area. Replacing the deterministic, prediction-based approach with a statistical one that fully accounts for the uncertainties and epistemic gaps would provide a different kind of science input to policy makers and stakeholders. Like in many other insurance problems (for example, earthquakes), where deterministic predictions are not possible and decisions have to be made on the basis of statistics and probabilities, the statistical approach to coastal resilience would require stakeholders to make decisions on the basis of probabilities instead of predictions. The science input for informed decisions on adaptation would consist of general probabilities of decadal to century scale sea level changes derived from paleo records, including the probabilities for large and rapid rises. Similar to other problems where the appearance of a hazard is associated with a high risk (like a fire in a house), this approach would also require a monitoring and warning system (a "smoke detector") capable of detecting any onset of a rapid sea level rise.
Barnard, Patrick; Maarten van Ormondt,; Erikson, Li H.; Jodi Eshleman,; Hapke, Cheryl J.; Peter Ruggiero,; Peter Adams,; Foxgrover, Amy C.
2014-01-01
The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.
Global elimination of leprosy by 2020: are we on track?
Blok, David J; De Vlas, Sake J; Richardus, Jan Hendrik
2015-10-22
Every year more than 200,000 new leprosy cases are registered globally. This number has been fairly stable over the past 8 years. WHO has set a target to interrupt the transmission of leprosy globally by 2020. The aim of this study is to investigate whether this target, interpreted as global elimination, is feasible given the current control strategy. We focus on the three most important endemic countries, India, Brazil and Indonesia, which together account for more than 80 % of all newly registered leprosy cases. We used the existing individual-based model SIMCOLEP to predict future trends of leprosy incidence given the current control strategy in each country. SIMCOLEP simulates the spread of M. leprae in a population that is structured in households. Current control consists of passive and active case detection, and multidrug therapy (MDT). Predictions of leprosy incidence were made for each country as well as for one high-endemic region within each country: Chhattisgarh (India), Pará State (Brazil) and Madura (Indonesia). Data for model quantification came from: National Leprosy Elimination Program (India), SINAN database (Brazil), and Netherlands Leprosy Relief (Indonesia). Our projections of future leprosy incidence all show a downward trend. In 2020, the country-level leprosy incidence has decreased to 6.2, 6.1 and 3.3 per 100,000 in India, Brazil and Indonesia, respectively, meeting the elimination target of less than 10 per 100,000. However, elimination may not be achieved in time for the high-endemic regions. The leprosy incidence in 2020 is predicted to be 16.2, 21.1 and 19.3 per 100,000 in Chhattisgarh, Pará and Madura, respectively, and the target may only be achieved in another 5 to 10 years. Our predictions show that although country-level elimination is reached by 2020, leprosy is likely to remain a problem in the high-endemic regions (i.e. states, districts and provinces with multimillion populations), which account for most of the cases in a country.
Modeling the Acceleration of Global Surface Temperture
NASA Astrophysics Data System (ADS)
Jones, B.
2017-12-01
A mathematical projection focusing on the changing rate of acceleration of Global Surface Temperatures. Using historical trajectory and informed expert near-term prediction, it is possible to extend this further forward drawing a reference arc of acceleration. Presented here is an example of this technique based on data found in the Summary of Findings of A New Estimate of the Average Earth Surface Land Temperature Spanning 1753 to 2011 and that same team's stated prediction to 2050. With this, we can project a curve showing future acceleration: Decade (midpoint) Change in Global Land Temp Degrees C Known Slope Projected Trend 1755 0.000 1955 0.600 0.0030 2005 1.500 0.0051 2045 3.000 0.0375 2095 5.485 0.0497 2145 8.895 0.0682 2195 13.488 0.0919 Observations: Slopes are getting steeper and doing so faster in an "acceleration of the acceleration" or an "arc of acceleration". This is consistent with the non-linear accelerating feedback loops of global warming. Such projected temperatures threaten human civilization and human life. This `thumbnail' projection is consistent with the other long term predictions based on anthropogenic greenhouse gases. This projection is low when compared to those whose forecasts include greenhouse gases released from thawing permafrost and clathrate hydrates. A reference line: This curve should be considered a point of reference. In the near term and absent significant drawdown of greenhouse gases, my "bet" for this AGU session is that future temperatures will generally be above this reference curve. For example, the decade ending 2020 - more than 1.9C and the decade ending 2030 - more than 2.3C - again measured from the 1750 start point. *Caveat: The long term curve and prediction assumes that mankind does not move quickly away from high cost fossil fuels and does not invent, mobilize and take actions drawing down greenhouse gases. Those seeking a comprehensive action plan are directed to drawdown.org
USDA-ARS?s Scientific Manuscript database
Predictions suggest that current crop production needs to double by 2050 to meet global food and energy demands. Based on theory and experimental studies, overexpression of the photosynthetic enzyme sedoheptulose-1,7-bisphosphatase (SBPase) is expected to enhance C3 crop photosynthesis and yields. H...
Space-time modeling of timber prices
Mo Zhou; Joseph Buongriorno
2006-01-01
A space-time econometric model was developed for pine sawtimber timber prices of 21 geographically contiguous regions in the southern United States. The correlations between prices in neighboring regions helped predict future prices. The impulse response analysis showed that although southern pine sawtimber markets were not globally integrated, local supply and demand...
Predicting Seagrass Occurrence in a Changing Climate Using Random Forests
NASA Astrophysics Data System (ADS)
Aydin, O.; Butler, K. A.
2017-12-01
Seagrasses are marine plants that can quickly sequester vast amounts of carbon (up to 100 times more and 12 times faster than tropical forests). In this work, we present an integrated GIS and machine learning approach to build a data-driven model of seagrass presence-absence. We outline a random forest approach that avoids the prevalence bias in many ecological presence-absence models. One of our goals is to predict global seagrass occurrence from a spatially limited training sample. In addition, we conduct a sensitivity study which investigates the vulnerability of seagrass to changing climate conditions. We integrate multiple data sources including fine-scale seagrass data from MarineCadastre.gov and the recently available globally extensive publicly available Ecological Marine Units (EMU) dataset. These data are used to train a model for seagrass occurrence along the U.S. coast. In situ oceans data are interpolated using Empirical Bayesian Kriging (EBK) to produce globally extensive prediction variables. A neural network is used to estimate probable future values of prediction variables such as ocean temperature to assess the impact of a warming climate on seagrass occurrence. The proposed workflow can be generalized to many presence-absence models.
A model of global citizenship: antecedents and outcomes.
Reysen, Stephen; Katzarska-Miller, Iva
2013-01-01
As the world becomes increasingly interconnected, exposure to global cultures affords individuals opportunities to develop global identities. In two studies, we examine the antecedents and outcomes of identifying with a superordinate identity--global citizen. Global citizenship is defined as awareness, caring, and embracing cultural diversity while promoting social justice and sustainability, coupled with a sense of responsibility to act. Prior theory and research suggest that being aware of one's connection with others in the world (global awareness) and embedded in settings that value global citizenship (normative environment) lead to greater identification with global citizens. Furthermore, theory and research suggest that when global citizen identity is salient, greater identification is related to adherence to the group's content (i.e., prosocial values and behaviors). Results of the present set of studies showed that global awareness (knowledge and interconnectedness with others) and one's normative environment (friends and family support global citizenship) predicted identification with global citizens, and global citizenship predicted prosocial values of intergroup empathy, valuing diversity, social justice, environmental sustainability, intergroup helping, and a felt responsibility to act for the betterment of the world. The relationship between antecedents (normative environment and global awareness) and outcomes (prosocial values) was mediated by identification with global citizens. We discuss the relationship between the present results and other research findings in psychology, the implications of global citizenship for other academic domains, and future avenues of research. Global citizenship highlights the unique effect of taking a global perspective on a multitude of topics relevant to the psychology of everyday actions, environments, and identity.
Predicting climate change impacts on polar bear litter size.
Molnár, Péter K; Derocher, Andrew E; Klanjscek, Tin; Lewis, Mark A
2011-02-08
Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population.
Predicting climate change impacts on polar bear litter size
Molnár, Péter K.; Derocher, Andrew E.; Klanjscek, Tin; Lewis, Mark A.
2011-01-01
Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40–73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55–100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22–67% and 44–100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population. PMID:21304515
Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems
2017-01-01
Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data. PMID:28806754
Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.
Almaraashi, Majid
2017-01-01
Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data.
Is Global Warming likely to cause an increased incidence of Malaria?
Nabi, SA; Qader, SS
2009-01-01
The rise in the average temperature of earth has been described as global warming which is mainly attributed to the increasing phenomenon of the greenhouse effect. It is believed that global warming can have several harmful effects on human health, both directly and indirectly. Since malaria is greatly influenced by climatic conditions because of its direct relationship with the mosquito population, it is widely assumed that its incidence is likely to increase in a future warmer world. This review article discusses the two contradictory views regarding the association of global warming with an increased incidence of malaria. On one hand, there are many who believe that there is a strong association between the recent increase in malaria incidence and global warming. They predict that as global warming continues, malaria is set to spread in locations where previously it was limited, due to cooler climate. On the other hand, several theories have been put forward which are quite contrary to this prediction. There are multiple other factors which are accountable for the recent upsurge of malaria: for example drug resistance, mosquito control programs, public health facilities, and living standards. PMID:21483497
NASA Astrophysics Data System (ADS)
Gilligan, J. M.; Nay, J. J.; van der Linden, M.
2016-12-01
Despite overwhelming scientific evidence and an almost complete consensus among scientists, a large fraction of the American public is not convinced that global warming is anthropogenic. This doubt correlates strongly with political, ideological, and cultural orientation. [1] It has been proposed that people who do not trust climate scientists tend to trust markets, so prediction markets might be able to influence their beliefs about the causes of climate change. [2] We present results from an agent-based simulation of a prediction market in which traders invest based on their beliefs about what drives global temperature change (here, either CO2 concentration or total solar irradiance (TSI), which is a popular hypothesis among many who doubt the dominant role of CO2). At each time step, traders use historical and observed temperatures and projected future forcings (CO2 or TSI) to update Bayesian posterior probability distributions for future temperatures, conditional on their belief about what drives climate change. Traders then bet on future temperatures by trading in climate futures. Trading proceeds by a continuous double auction. Traders are randomly assigned initial beliefs about climate change, and they have some probability of changing their beliefs to match those of the most successful traders in their social network. We simulate two alternate realities in which the global temperature is controlled either by CO2 or by TSI, with stochastic noise. In both cases traders' beliefs converge, with a large majority reaching agreement on the actual cause of climate change. This convergence is robust, but the speed with which consensus emerges depends on characteristics of the traders' psychology and the structure of the market. Our model can serve as a test-bed for studying how beliefs might evolve under different market structures and different modes of decision-making and belief-change. We will report progress on studying alternate models of belief-change. This work was partially supported by National Science Foundation grants EAR-1416964, EAR-1204685, and IIS-1526860. The model code is available at https://github.com/JohnNay/predMarket [1] A Leiserowitz, E Maibach, & C Roser-Renouf, Global Warming's Six Americas (Yale U., 2009). [2] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).
DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kitiashvili, Irina N., E-mail: irina.n.kitiashvili@nasa.gov
Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relativelymore » new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.« less
Climate Information Responding to User Needs (CIRUN)
NASA Astrophysics Data System (ADS)
Busalacchi, A. J.
2009-05-01
For the past several decades many different US agencies have been involved in collecting Earth observations, e.g., NASA, NOAA, DoD, USGS, USDA. More recently, the US has led the international effort to design a Global Earth Observation System of Systems (GEOSS). Yet, there has been little substantive progress at the synthesis and integration of the various research and operational, space-based and in situ, observations. Similarly, access to such a range of observations across the atmosphere, ocean, and land surface remains fragmented. With respect to prediction of the Earth System, the US has not developed a comprehensive strategy. For climate, the US (e.g., NOAA, NASA, DoE) has taken a two-track strategy. At the more immediate time scale, coupled ocean-atmosphere models of the physical climate system have built upon the tradition of daily numerical weather prediction in order to extend the forecast window to seasonal to interannual times scales. At the century time scale, the nascent development of Earth System models, combining components of the physical climate system with biogeochemical cycles, are being used to provide future climate change projections in response to anticipated greenhouse gas forcings. Between these to two approaches to prediction lies a key deficiency of interest to decision makers, especially as it pertains to adaptation, i.e., deterministic prediction of the Earth System at time scales from days to decades with spatial scales from global to regional. One of many obstacles to be overcome is the design of present day observation and prediction products based on user needs. To date, most of such products have evolved from the technology and research "push" rather than the user or stakeholder "pull". In the future as planning proceeds for a national climate service, emphasis must be given to a more coordinated approach in which stakeholders' needs help design future Earth System observational and prediction products, and similarly, such products need to be tailored to provide decision support.
Assessing the impact of a future volcanic eruption on decadal predictions
NASA Astrophysics Data System (ADS)
Illing, Sebastian; Kadow, Christopher; Pohlmann, Holger; Timmreck, Claudia
2018-06-01
The likelihood of a large volcanic eruption in the future provides the largest uncertainty concerning the evolution of the climate system on the timescale of a few years, but also an excellent opportunity to learn about the behavior of the climate system, and our models thereof. So the following question emerges: how predictable is the response of the climate system to future eruptions? By this we mean to what extent will the volcanic perturbation affect decadal climate predictions and how does the pre-eruption climate state influence the impact of the volcanic signal on the predictions? To address these questions, we performed decadal forecasts with the MiKlip prediction system, which is based on the MPI-ESM, in the low-resolution configuration for the initialization years 2012 and 2014, which differ in the Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO) phase. Each forecast contains an artificial Pinatubo-like eruption starting in June of the first prediction year and consists of 10 ensemble members. For the construction of the aerosol radiative forcing, we used the global aerosol model ECHAM5-HAM in a version adapted for volcanic eruptions. We investigate the response of different climate variables, including near-surface air temperature, precipitation, frost days, and sea ice area fraction. Our results show that the average global cooling response over 4 years of about 0.2 K and the precipitation decrease of about 0.025 mm day-1 is relatively robust throughout the different experiments and seemingly independent of the initialization state. However, on a regional scale, we find substantial differences between the initializations. The cooling effect in the North Atlantic and Europe lasts longer and the Arctic sea ice increase is stronger in the simulations initialized in 2014. In contrast, the forecast initialized in 2012 with a negative PDO shows a prolonged cooling in the North Pacific basin.
El-Gabbas, Ahmed; Dormann, Carsten F
2018-02-01
Species distribution modeling (SDM) is an essential method in ecology and conservation. SDMs are often calibrated within one country's borders, typically along a limited environmental gradient with biased and incomplete data, making the quality of these models questionable. In this study, we evaluated how adequate are national presence-only data for calibrating regional SDMs. We trained SDMs for Egyptian bat species at two different scales: only within Egypt and at a species-specific global extent. We used two modeling algorithms: Maxent and elastic net, both under the point-process modeling framework. For each modeling algorithm, we measured the congruence of the predictions of global and regional models for Egypt, assuming that the lower the congruence, the lower the appropriateness of the Egyptian dataset to describe the species' niche. We inspected the effect of incorporating predictions from global models as additional predictor ("prior") to regional models, and quantified the improvement in terms of AUC and the congruence between regional models run with and without priors. Moreover, we analyzed predictive performance improvements after correction for sampling bias at both scales. On average, predictions from global and regional models in Egypt only weakly concur. Collectively, the use of priors did not lead to much improvement: similar AUC and high congruence between regional models calibrated with and without priors. Correction for sampling bias led to higher model performance, whatever prior used, making the use of priors less pronounced. Under biased and incomplete sampling, the use of global bats data did not improve regional model performance. Without enough bias-free regional data, we cannot objectively identify the actual improvement of regional models after incorporating information from the global niche. However, we still believe in great potential for global model predictions to guide future surveys and improve regional sampling in data-poor regions.
NASA Astrophysics Data System (ADS)
Lin, Y. S.; Medlyn, B. E.; Duursma, R.; Prentice, I. C.; Wang, H.
2014-12-01
Stomatal conductance (gs) is a key land surface attribute as it links transpiration, the dominant component of global land evapotranspiration and a key element of the global water cycle, and photosynthesis, the driving force of the global carbon cycle. Despite the pivotal role of gs in predictions of global water and carbon cycles, a global scale database and an associated globally applicable model of gs that allow predictions of stomatal behaviour are lacking. We present a unique database of globally distributed gs obtained in the field for a wide range of plant functional types (PFTs) and biomes. We employed a model of optimal stomatal conductance to assess differences in stomatal behaviour, and estimated the model slope coefficient, g1, which is directly related to the marginal carbon cost of water, for each dataset. We found that g1 varies considerably among PFTs, with evergreen savanna trees having the largest g1 (least conservative water use), followed by C3 grasses and crops, angiosperm trees, gymnosperm trees, and C4 grasses. Amongst angiosperm trees, species with higher wood density had a higher marginal carbon cost of water, as predicted by the theory underpinning the optimal stomatal model. There was an interactive effect between temperature and moisture availability on g1: for wet environments, g1 was largest in high temperature environments, indicated by high mean annual temperature during the period when temperature above 0oC (Tm), but it did not vary with Tm across dry environments. We examine whether these differences in leaf-scale behaviour are reflected in ecosystem-scale differences in water-use efficiency. These findings provide a robust theoretical framework for understanding and predicting the behaviour of stomatal conductance across biomes and across PFTs that can be applied to regional, continental and global-scale modelling of productivity and ecohydrological processes in a future changing climate.
Climate-Induced Range Shifts and Possible Hybridisation Consequences in Insects
Sánchez-Guillén, Rosa Ana; Muñoz, Jesús; Rodríguez-Tapia, Gerardo; Feria Arroyo, T. Patricia; Córdoba-Aguilar, Alex
2013-01-01
Many ectotherms have altered their geographic ranges in response to rising global temperatures. Current range shifts will likely increase the sympatry and hybridisation between recently diverged species. Here we predict future sympatric distributions and risk of hybridisation in seven Mediterranean ischnurid damselfly species (I. elegans, I. fountaineae, I. genei, I. graellsii, I. pumilio, I. saharensis and I. senegalensis). We used a maximum entropy modelling technique to predict future potential distribution under four different Global Circulation Models and a realistic emissions scenario of climate change. We carried out a comprehensive data compilation of reproductive isolation (habitat, temporal, sexual, mechanical and gametic) between the seven studied species. Combining the potential distribution and data of reproductive isolation at different instances (habitat, temporal, sexual, mechanical and gametic), we infer the risk of hybridisation in these insects. Our findings showed that all but I. graellsii will decrease in distributional extent and all species except I. senegalensis are predicted to have northern range shifts. Models of potential distribution predicted an increase of the likely overlapping ranges for 12 species combinations, out of a total of 42 combinations, 10 of which currently overlap. Moreover, the lack of complete reproductive isolation and the patterns of hybridisation detected between closely related ischnurids, could lead to local extinctions of native species if the hybrids or the introgressed colonising species become more successful. PMID:24260411
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.
Sacco, Ralph L
2007-06-01
By the year 2010, it is estimated that 18.1 million people worldwide will die annually because of cardiovascular diseases and stroke. "Global vascular risk" more broadly includes the multiple overlapping disease silos of stroke, myocardial infarction, peripheral arterial disease, and vascular death. Estimation of global vascular risk requires consideration of a variety of variables including demographics, environmental behaviors, and risk factors. Data from multiple studies suggest continuous linear relationships between the physiological vascular risk modulators of blood pressure, lipids, and blood glucose rather than treating these conditions as categorical risk factors. Constellations of risk factors may be more relevant than individual categorical components. Exciting work with novel risk factors may also have predictive value in estimates of global vascular risk. Advances in imaging have led to the measurement of subclinical conditions such as carotid intima-media thickness and subclinical brain conditions such as white matter hyperintensities and silent infarcts. These subclinical measurements may be intermediate stages in the transition from asymptomatic to symptomatic vascular events, appear to be associated with the fundamental vascular risk factors, and represent opportunities to more precisely quantitate disease progression. The expansion of studies in molecular epidemiology and detection of genetic markers underlying vascular risks also promises to extend our precision of global vascular risk estimation. Global vascular risk estimation will require quantitative methods that bundle these multi-dimensional data into more precise estimates of future risk. The power of genetic information coupled with data on demographics, risk-inducing behaviors, vascular risk modulators, biomarkers, and measures of subclinical conditions should provide the most realistic approximation of an individual's future global vascular risk. The ultimate public health benefit, however, will depend on not only identification of global vascular risk but also the realization that we can modify this risk and prove the prediction models wrong.
NASA Technical Reports Server (NTRS)
Bolten, John; Crow, Wade
2012-01-01
The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.
The Prehistory of Antibiotic Resistance.
Perry, Julie; Waglechner, Nicholas; Wright, Gerard
2016-06-01
Antibiotic resistance is a global problem that is reaching crisis levels. The global collection of resistance genes in clinical and environmental samples is the antibiotic "resistome," and is subject to the selective pressure of human activity. The origin of many modern resistance genes in pathogens is likely environmental bacteria, including antibiotic producing organisms that have existed for millennia. Recent work has uncovered resistance in ancient permafrost, isolated caves, and in human specimens preserved for hundreds of years. Together with bioinformatic analyses on modern-day sequences, these studies predict an ancient origin of resistance that long precedes the use of antibiotics in the clinic. Understanding the history of antibiotic resistance is important in predicting its future evolution. Copyright © 2016 Cold Spring Harbor Laboratory Press; all rights reserved.
Future possible crop yield scenarios under multiple SSP and RCP scenarios.
NASA Astrophysics Data System (ADS)
Sakurai, G.; Yokozawa, M.; Nishimori, M.; Okada, M.
2016-12-01
Understanding the effect of future climate change on global crop yields is one of the most important tasks for global food security. Future crop yields would be influenced by climatic factors such as the changes of temperature, precipitation and atmospheric carbon dioxide concentration. On the other hand, the effect of the changes of agricultural technologies such as crop varieties, pesticide and fertilizer input on crop yields have large uncertainty. However, not much is available on the contribution ratio of each factor under the future climate change scenario. We estimated the future global yields of four major crops (maize, soybean, rice and wheat) under three Shared Socio Economic Pathways (SSPs) and four Representative Concentration Pathways (RCPs). For this purpose, firstly, we estimated a parameter of a process based model (PRYSBI2) using a Bayesian method for each 1.125 degree spatial grid. The model parameter is relevant to the agricultural technology (we call "technological parameter" here after). Then, we analyzed the relationship between the values of technological parameter and GDP values. We found that the estimated values of the technological parameter were positively correlated with the GDP. Using the estimated relationship, we predicted future crop yield during 2020 and 2100 under SSP1, SSP2 and SSP3 scenarios and RCP 2.6, 4.5, 6.0 and 8.5. The estimated crop yields were different among SSP scenarios. However, we found that the yield difference attributable to SSPs were smaller than those attributable to CO2 fertilization effects and climate change. Particularly, the estimated effect of the change of atmospheric carbon dioxide concentration on global yields was more than four times larger than that of GDP for C3 crops.
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.
Future battlegrounds for conservation under global change
Lee, Tien Ming; Jetz, Walter
2008-01-01
Global biodiversity is under significant threat from the combined effects of human-induced climate and land-use change. Covering 12% of the Earth's terrestrial surface, protected areas are crucial for conserving biodiversity and supporting ecological processes beneficial to human well-being, but their selection and design are usually uninformed about future global change. Here, we quantify the exposure of the global reserve network to projected climate and land-use change according to the Millennium Ecosystem Assessment and set these threats in relation to the conservation value and capacity of biogeographic and geopolitical regions. We find that geographical patterns of past human impact on the land cover only poorly predict those of forecasted change, thus revealing the inadequacy of existing global conservation prioritization templates. Projected conservation risk, measured as regional levels of land-cover change in relation to area protected, is the greatest at high latitudes (due to climate change) and tropics/subtropics (due to land-use change). Only some high-latitude nations prone to high conservation risk are also of high conservation value, but their high relative wealth may facilitate additional conservation efforts. In contrast, most low-latitude nations tend to be of high conservation value, but they often have limited capacity for conservation which may exacerbate the global biodiversity extinction crisis. While our approach will clearly benefit from improved land-cover projections and a thorough understanding of how species range will shift under climate change, our results provide a first global quantitative demonstration of the urgent need to consider future environmental change in reserve-based conservation planning. They further highlight the pressing need for new reserves in target regions and support a much extended ‘north–south’ transfer of conservation resources that maximizes biodiversity conservation while mitigating global climate change. PMID:18302999
Global estimates of boreal forest carbon stocks and flux
NASA Astrophysics Data System (ADS)
Bradshaw, Corey J. A.; Warkentin, Ian G.
2015-05-01
The boreal ecosystem is an important global reservoir of stored carbon and a haven for diverse biological communities. The natural disturbance dynamics there have historically been driven by fire and insects, with human-mediated disturbances increasing faster than in other biomes globally. Previous research on the total boreal carbon stock and predictions of its future flux reveal high uncertainty in regional patterns. We reviewed and standardised this extensive body of quantitative literature to provide the most up-to-date and comprehensive estimates of the global carbon balance in the boreal forest. We also compiled century-scale predictions of the carbon budget flux. Our review and standardisation confirmed high uncertainty in the available data, but there is evidence that the region's total carbon stock has been underestimated. We found a total carbon store of 367.3 to 1715.8 Pg (1015 g), the mid-point of which (1095 Pg) is between 1.3 and 3.8 times larger than any previous mean estimates. Most boreal carbon resides in its soils and peatlands, although estimates are highly uncertain. We found evidence that the region might become a net carbon source following a reduction in carbon uptake rate from at least the 1980s. Given that the boreal potentially constitutes the largest terrestrial carbon source in the world, in one of the most rapidly warming parts of the globe (Walsh, 2014), how we manage these stocks will be influential on future climate dynamics.
NASA Astrophysics Data System (ADS)
Tommasi, D.; Stock, C. A.
2016-02-01
It is well established that environmental fluctuations affect the productivity of numerous fish stocks. Recent advances in prediction capability of dynamical global forecast systems, such as the state of the art NOAA Geophysical Fluid dynamics Laboratory (GFDL) 2.5-FLOR model, allow for climate predictions of fisheries-relevant variables at temporal scales relevant to the fishery management decision making process. We demonstrate that the GFDL FLOR model produces skillful seasonal SST anomaly predictions over the continental shelf , where most of the global fish yield is generated. The availability of skillful SST projections at this "fishery relevant" scale raises the potential for better constrained estimates of future fish biomass and improved harvest decisions. We assessed the utility of seasonal SST coastal shelf predictions for fisheries management using the case study of Pacific sardine. This fishery was selected because it is one of the few to already incorporate SST into its harvest guideline, and show a robust recruitment-SST relationship. We quantified the effectiveness of management under the status quo harvest guideline (HG) and under alternative HGs including future information at different levels of uncertainty. Usefulness of forecast SST to management was dependent on forecast uncertainty. If the standard deviation of the SST anomaly forecast residuals was less than 0.65, the alternative HG produced higher long-term yield and stock biomass, and reduced the probability of either catch or stock biomass falling below management-set threshold values as compared to the status quo. By contrast, probability of biomass falling to extremely low values increased as compared to the status quo for all alternative HGs except for a perfectly known future SST case. To safeguard against occurrence of such low probability but costly events, a harvest cutoff biomass also has to be implemented into the HG.
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.
Seagrass meadows in a globally changing environment.
Unsworth, Richard K F; van Keulen, Mike; Coles, Rob G
2014-06-30
Seagrass meadows are valuable ecosystem service providers that are now being lost globally at an unprecedented rate, with water quality and other localised stressors putting their future viability in doubt. It is therefore critical that we learn more about the interactions between seagrass meadows and future environmental change in the anthropocene. This needs to be with particular reference to the consequences of poor water quality on ecosystem resilience and the effects of change on trophic interactions within the food web. Understanding and predicting the response of seagrass meadows to future environmental change requires an understanding of the natural long-term drivers of change and how these are currently influenced by anthropogenic stress. Conservation management of coastal and marine ecosystems now and in the future requires increased knowledge of how seagrass meadows respond to environmental change, and how they can be managed to be resilient to these changes. Finding solutions to such issues also requires recognising people as part of the social-ecological system. This special issue aims to further enhance this knowledge by bringing together global expertise across this field. The special issues considers issues such as ecosystem service delivery of seagrass meadows, the drivers of long-term seagrass change and the socio-economic consequences of environmental change to seagrass. Copyright © 2014 Elsevier Ltd. All rights reserved.
Assessment of soil organic carbon stocks under future climate and land cover changes in Europe.
Yigini, Yusuf; Panagos, Panos
2016-07-01
Soil organic carbon plays an important role in the carbon cycling of terrestrial ecosystems, variations in soil organic carbon stocks are very important for the ecosystem. In this study, a geostatistical model was used for predicting current and future soil organic carbon (SOC) stocks in Europe. The first phase of the study predicts current soil organic carbon content by using stepwise multiple linear regression and ordinary kriging and the second phase of the study projects the soil organic carbon to the near future (2050) by using a set of environmental predictors. We demonstrate here an approach to predict present and future soil organic carbon stocks by using climate, land cover, terrain and soil data and their projections. The covariates were selected for their role in the carbon cycle and their availability for the future model. The regression-kriging as a base model is predicting current SOC stocks in Europe by using a set of covariates and dense SOC measurements coming from LUCAS Soil Database. The base model delivers coefficients for each of the covariates to the future model. The overall model produced soil organic carbon maps which reflect the present and the future predictions (2050) based on climate and land cover projections. The data of the present climate conditions (long-term average (1950-2000)) and the future projections for 2050 were obtained from WorldClim data portal. The future climate projections are the recent climate projections mentioned in the Fifth Assessment IPCC report. These projections were extracted from the global climate models (GCMs) for four representative concentration pathways (RCPs). The results suggest an overall increase in SOC stocks by 2050 in Europe (EU26) under all climate and land cover scenarios, but the extent of the increase varies between the climate model and emissions scenarios. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Continental drift and climate change drive instability in insect assemblages
NASA Astrophysics Data System (ADS)
Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk
2015-06-01
Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region—one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale.
Continental drift and climate change drive instability in insect assemblages
Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk
2015-01-01
Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region—one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale. PMID:26081036
Continental drift and climate change drive instability in insect assemblages.
Li, Fengqing; Tierno de Figueroa, José Manuel; Lek, Sovan; Park, Young-Seuk
2015-06-17
Global change has already had observable effects on ecosystems worldwide, and the accelerated rate of global change is predicted in the future. However, the impacts of global change on the stability of biodiversity have not been systematically studied in terms of both large spatial (continental drift) and temporal (from the last inter-glacial period to the next century) scales. Therefore, we analyzed the current geographical distribution pattern of Plecoptera, a thermally sensitive insect group, and evaluated its stability when coping with global change across both space and time throughout the Mediterranean region--one of the first 25 global biodiversity hotspots. Regional biodiversity of Plecoptera reflected the geography in both the historical movements of continents and the current environmental conditions in the western Mediterranean region. The similarity of Plecoptera assemblages between areas in this region indicated that the uplift of new land and continental drift were the primary determinants of the stability of regional biodiversity. Our results revealed that climate change caused the biodiversity of Plecoptera to slowly diminish in the past and will cause remarkably accelerated biodiversity loss in the future. These findings support the theory that climate change has had its greatest impact on biodiversity over a long temporal scale.
High performance equipped mirrors for MTG FCI-TA and IRS-FTO
NASA Astrophysics Data System (ADS)
Kazakov, T.; San Juan, J. L.; Serrano, J.; Moreno, J.; González, D.; Rodríguez, G.; López, D.; Vázquez, E.; Aivar, J.; Motos, A.; Rahmouni, Christophe; Imperiali, Stephan; Fappani, Denis
2017-09-01
The Meteosat Third Generation (MTG) Programme is being realised through the well established and successful Cooperation between EUMETSAT and ESA. It will ensure the future continuity of MSG with the capabilities to enhance nowcasting, global and regional numerical weather prediction, climate and atmospheric chemistry monitoring data from Geostationary Orbit.
Nicholas J. Bouskill; Tana E. Wood; Richard Baran; Zaw Ye; Benjamin P. Bowen; HsiaoChien Lim; Jizhong Zhou; Joy D. Van Nostrand; Peter Nico; Trent R. Northen; Whendee L. Silver; Eoin L. Brodie
2016-01-01
Global climate models predict a future of increased severity of drought in many tropical forests. Soil microbes are central to the balance of these systems as sources or sinks of atmospheric carbon (C), yet how they respond metabolically to drought is not well-understood. We simulated...
Representing climate, disturbance, and vegetation interactions in landscape models
Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg
2015-01-01
The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...
A Multidisciplined Teaching Reform of Biomaterials Course for Undergraduate Students
ERIC Educational Resources Information Center
Li, Xiaoming; Zhao, Feng; Pu, Fang; Liu, Haifeng; Niu, Xufeng; Zhou, Gang; Li, Deyu; Fan, Yubo; Feng, Qingling; Cui, Fu-zhai; Watari, Fumio
2015-01-01
The biomaterials science has advanced in a high speed with global science and technology development during the recent decades, which experts predict to be more obvious in the near future with a more significant position for medicine and health care. Although the three traditional subjects, such as medical science, materials science and biology…
Unlocking the climate riddle in forested ecosystems
Greg C. Liknes; Christopher W. Woodall; Brian F. Walters; Sara A. Goeking
2012-01-01
Climate information is often used as a predictor in ecological studies, where temporal averages are typically based on climate normals (30-year means) or seasonal averages. While ensemble projections of future climate forecast a higher global average annual temperature, they also predict increased climate variability. It remains to be seen whether forest ecosystems...
Chang, Jinfeng; Ciais, Philippe; Viovy, Nicolas; Soussana, Jean-François; Klumpp, Katja; Sultan, Benjamin
2017-12-01
Europe has warmed more than the global average (land and ocean) since pre-industrial times, and is also projected to continue to warm faster than the global average in the twenty-first century. According to the climate models ensemble projections for various climate scenarios, annual mean temperature of Europe for 2071-2100 is predicted to be 1-5.5 °C higher than that for 1971-2000. Climate change and elevated CO 2 concentration are anticipated to affect grassland management and livestock production in Europe. However, there has been little work done to quantify the European-wide response of grassland to future climate change. Here we applied ORCHIDEE-GM v2.2, a grid-based model for managed grassland, over European grassland to estimate the impacts of future global change. Increases in grassland productivity are simulated in response to future global change, which are mainly attributed to the simulated fertilization effect of rising CO 2 . The results show significant phenology shifts, in particular an earlier winter-spring onset of grass growth over Europe. A longer growing season is projected over southern and southeastern Europe. In other regions, summer drought causes an earlier end to the growing season, overall reducing growing season length. Future global change allows an increase of management intensity with higher than current potential annual grass forage yield, grazing capacity and livestock density, and a shift in seasonal grazing capacity. We found a continual grassland soil carbon sink in Mediterranean, Alpine, North eastern, South eastern and Eastern regions under specific warming level (SWL) of 1.5 and 2 °C relative to pre-industrial climate. However, this carbon sink is found to saturate, and gradually turn to a carbon source at warming level reaching 3.5 °C. This study provides a European-wide assessment of the future changes in productivity and phenology of grassland, and their consequences for the management intensity and the carbon balance. The simulated productivity increase in response to future global change enables an intensification of grassland management over Europe. However, the simulated increase in the interannual variability of grassland productivity over some regions may reduce the farmers' ability to take advantage of the increased long-term mean productivity in the face of more frequent, and more severe drops of productivity in the future.
Liang, Jin-Feng; An, Jing; Gao, Jun-Qin; Zhang, Xiao-Ya; Yu, Fei-Hai
2018-01-01
The frequency of soil drying-rewetting cycles is predicted to increase under future global climate change, and arbuscular mycorrhizal fungi (AMF) are symbiotic with most plants. However, it remains unknown how AMF affect plant growth under different frequencies of soil drying-rewetting cycles. We subjected a clonal wetland plant Phragmites australis to three frequencies of drying-rewetting cycles (1, 2, or 4 cycles), two nutrient treatments (with or without), and two AMF treatments (with or without) for 64 days. AMF promoted the growth of P. australis, especially in the 2 cycles of the drying-rewetting treatment. AMF had a significant positive effect on leaf mass and number of ramets in the 2 cycles of the drying-rewetting treatment with nutrient addition. In the 2 cycles of drying-rewetting treatment without nutrient addition, AMF increased leaf area and decreased belowground to aboveground biomass ratio. These results indicate that AMF may assist P. australis in coping with medium frequency of drying-rewetting cycles, and provide theoretical guidance for predicting how wetland plants respond to future global climate change.
NASA Astrophysics Data System (ADS)
Kallepalli, Akhil; Kakani, Nageswara Rao; James, David B.; Richardson, Mark A.
2017-07-01
Coastal regions are highly vulnerable to rising sea levels due to global warming. Previous Intergovernmental Panel on Climate Change (2013) predictions of 26 to 82 cm global sea level rise are now considered conservative. Subsequent investigations predict much higher levels which would displace 10% of the world's population living less than 10 m above sea level. Remote sensing and GIS technologies form the mainstay of models on coastal retreat and inundation to future sea-level rise. This study estimates the varying trends along the Krishna-Godavari (K-G) delta region. The rate of shoreline shift along the 330-km long K-G delta coast was estimated using satellite images between 1977 and 2008. With reference to a selected baseline from along an inland position, end point rate and net shoreline movement were calculated using a GIS-based digital shoreline analysis system. The results indicated a net loss of about 42.1 km2 area during this 31-year period, which is in agreement with previous literature. Considering the nature of landforms and EPR, the future hazard line (or coastline) is predicted for the area; the predication indicates a net erosion of about 57.6 km2 along the K-G delta coast by 2050 AD.
Laurent, Cédric P; Latil, Pierre; Durville, Damien; Rahouadj, Rachid; Geindreau, Christian; Orgéas, Laurent; Ganghoffer, Jean-François
2014-12-01
The use of biodegradable scaffolds seeded with cells in order to regenerate functional tissue-engineered substitutes offers interesting alternative to common medical approaches for ligament repair. Particularly, finite element (FE) method enables the ability to predict and optimise both the macroscopic behaviour of these scaffolds and the local mechanic signals that control the cell activity. In this study, we investigate the ability of a dedicated FE code to predict the geometrical evolution of a new braided and biodegradable polymer scaffold for ligament tissue engineering by comparing scaffold geometries issued from FE simulations and from X-ray tomographic imaging during a tensile test. Moreover, we compare two types of FE simulations the initial geometries of which are issued either from X-ray imaging or from a computed idealised configuration. We report that the dedicated FE simulations from an idealised reference configuration can be reasonably used in the future to predict the global and local mechanical behaviour of the braided scaffold. A valuable and original dialog between the fields of experimental and numerical characterisation of such fibrous media is thus achieved. In the future, this approach should enable to improve accurate characterisation of local and global behaviour of tissue-engineering scaffolds. Copyright © 2014 Elsevier Ltd. All rights reserved.
Water Resource Assessment in KRS Reservoir Using Remote Sensing and GIS Modelling
NASA Astrophysics Data System (ADS)
Manubabu, V. H.; Gouda, K. C.; Bhat, N.; Reddy, A.
2014-12-01
In the recent time the fresh water resource becomes very important because of various reasons like population growth, pollution, over exploitation of the ground water resources etc. As there is no efficient and proper measures for recharging ground water exists and also the climatological impacts on water resources like global warming exacerbating water shortages, growing populations and rising demand for freshwater in agriculture, industry, and energy production. There is a need and challenging task for analyzing the future changes in regional water availability and it is also very much necessary to asses and predict the fresh water present in a lake or reservoir to make better decision making in the optimal usage of surface water. In the present study is intended to provide a practical discussion of methodology that deals with how to asses and predict amount of surface water available in the future using Remote Sensing(RS) data , Geographical Information System(GIS) techniques, and GCM (Global Circulation Model). Basically the study emphasized over one of the biggest reservoir i.e. the Krishna Raja Sagara (KRS) reservoir situated in the state of Karnataka in India. Multispectral satellite images like IRS LISS III and Landsat L8 from different open source web portals like NRSC-Bhuvan and NASA Earth Explorer respectively are used for the present analysis. The multispectral satellite images are used to identify the temporal changes of the water quantity in the reservoir for the period 2000 to 2014. Also the water volume are being calculated using Advances Space born Thermal Emission and Reflection Radiometer (ASTER) Global DEM over the reservoir basin. The hydro meteorological parameters are also studied using multi-source observed data and the empirical water budget models for the reservoir in terms of rainfall, temperature, run off, water inflow and outflow etc. are being developed and analyzed. Statistical analysis are also carried out to quantify the relation between reservoir water volume and the hydrological parameters (Figure 1). A general circulation model (GCM) is used for the prediction of major hydro meteorological parameters like rainfall and using the GCM predictions the water availability in terms of water volume in future are simulated using the empirical water budget model.
The response of tropical rainforests to drought-lessons from recent research and future prospects.
Bonal, Damien; Burban, Benoit; Stahl, Clément; Wagner, Fabien; Hérault, Bruno
We review the recent findings on the influence of drought on tree mortality, growth or ecosystem functioning in tropical rainforests. Drought plays a major role in shaping tropical rainforests and the response mechanisms are highly diverse and complex. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical rainforests on the three continents. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance. Tropical rainforest ecosystems are characterized by high annual rainfall. Nevertheless, rainfall regularly fluctuates during the year and seasonal soil droughts do occur. Over the past decades, a number of extreme droughts have hit tropical rainforests, not only in Amazonia but also in Asia and Africa. The influence of drought events on tree mortality and growth or on ecosystem functioning (carbon and water fluxes) in tropical rainforest ecosystems has been studied intensively, but the response mechanisms are complex. Herein, we review the recent findings related to the response of tropical forest ecosystems to seasonal and extreme droughts and the current knowledge about the future of these ecosystems. This review emphasizes the progress made over recent years and the importance of the studies conducted under extreme drought conditions or in through-fall exclusion experiments in understanding the response of these ecosystems. It also points to the great diversity and complexity of the response of tropical rainforest ecosystems to drought. The numerous gaps identified here require the international scientific community to combine efforts in order to conduct comprehensive studies in tropical forest regions. These results are essential to simulate the future of these ecosystems under diverse climate scenarios and to predict the future of the global earth carbon balance.
NASA Astrophysics Data System (ADS)
Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.
2002-12-01
There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.
Effects of climate change on polar bears.
Wiig, Øystein; Aars, Jon; Born, Erik W
2008-01-01
In this article, we review the effects on polar bears of global warming that have already been observed, and try to evaluate what may happen to the polar bears in the future. Many researchers have predicted a wide range of impacts of climate change on polar bear demography and conditions. A predicted major reduction in sea ice habitat will reduce the availability of ice associated seals, the main prey of polar bears, and a loss and fragmentation of polar bear habitat will ultimately lead to large future reductions in most subpopulations. It is likely that polar bears will be lost from many areas where they are common today and also that the total population will change into a few more distinctly isolated populations.
NASA Astrophysics Data System (ADS)
Tellman, B.; Sullivan, J.; Kettner, A.; Brakenridge, G. R.; Slayback, D. A.; Kuhn, C.; Doyle, C.
2016-12-01
There is an increasing need to understand flood vulnerability as the societal and economic effects of flooding increases. Risk models from insurance companies and flood models from hydrologists must be calibrated based on flood observations in order to make future predictions that can improve planning and help societies reduce future disasters. Specifically, to improve these models both traditional methods of flood prediction from physically based models as well as data-driven techniques, such as machine learning, require spatial flood observation to validate model outputs and quantify uncertainty. A key dataset that is missing for flood model validation is a global historical geo-database of flood event extents. Currently, the most advanced database of historical flood extent is hosted and maintained at the Dartmouth Flood Observatory (DFO) that has catalogued 4320 floods (1985-2015) but has only mapped 5% of these floods. We are addressing this data gap by mapping the inventory of floods in the DFO database to create a first-of- its-kind, comprehensive, global and historical geospatial database of flood events. To do so, we combine water detection algorithms on MODIS and Landsat 5,7 and 8 imagery in Google Earth Engine to map discrete flood events. The created database will be available in the Earth Engine Catalogue for download by country, region, or time period. This dataset can be leveraged for new data-driven hydrologic modeling using machine learning algorithms in Earth Engine's highly parallelized computing environment, and we will show examples for New York and Senegal.
Marx, Uwe; Andersson, Tommy B.; Bahinski, Anthony; Beilmann, Mario; Beken, Sonja; Cassee, Flemming R.; Cirit, Murat; Daneshian, Mardas; Fitzpatrick, Susan; Frey, Olivier; Gaertner, Claudia; Giese, Christoph; Griffith, Linda; Hartung, Thomas; Heringa, Minne B.; Hoeng, Julia; de Jong, Wim H.; Kojima, Hajime; Kuehnl, Jochen; Luch, Andreas; Maschmeyer, Ilka; Sakharov, Dmitry; Sips, Adrienne J. A. M.; Steger-Hartmann, Thomas; Tagle, Danilo A.; Tonevitsky, Alexander; Tralau, Tewes; Tsyb, Sergej; van de Stolpe, Anja; Vandebriel, Rob; Vulto, Paul; Wang, Jufeng; Wiest, Joachim; Rodenburg, Marleen; Roth, Adrian
2017-01-01
Summary The recent advent of microphysiological systems – microfluidic biomimetic devices that aspire to emulate the biology of human tissues, organs and circulation in vitro – is envisaged to enable a global paradigm shift in drug development. An extraordinary US governmental initiative and various dedicated research programs in Europe and Asia have led recently to the first cutting-edge achievements of human single-organ and multi-organ engineering based on microphysiological systems. The expectation is that test systems established on this basis would model various disease stages, and predict toxicity, immunogenicity, ADME profiles and treatment efficacy prior to clinical testing. Consequently, this technology could significantly affect the way drug substances are developed in the future. Furthermore, microphysiological system-based assays may revolutionize our current global programs of prioritization of hazard characterization for any new substances to be used, for example, in agriculture, food, ecosystems or cosmetics, thus, replacing laboratory animal models used currently. Thirty-five experts from academia, industry and regulatory bodies present here the results of an intensive workshop (held in June 2015, Berlin, Germany). They review the status quo of microphysiological systems available today against industry needs, and assess the broad variety of approaches with fit-for-purpose potential in the drug development cycle. Feasible technical solutions to reach the next levels of human biology in vitro are proposed. Furthermore, key organ-on-a-chip case studies, as well as various national and international programs are highlighted. Finally, a roadmap into the future is outlined, to allow for more predictive and regulatory-accepted substance testing on a global scale. PMID:27180100
Climate change impact on soil erosion in the Mandakini River Basin, North India
NASA Astrophysics Data System (ADS)
Khare, Deepak; Mondal, Arun; Kundu, Sananda; Mishra, Prabhash Kumar
2017-09-01
Correct estimation of soil loss at catchment level helps the land and water resources planners to identify priority areas for soil conservation measures. Soil erosion is one of the major hazards affected by the climate change, particularly the increasing intensity of rainfall resulted in increasing erosion, apart from other factors like landuse change. Changes in climate have an adverse effect with increasing rainfall. It has caused increasing concern for modeling the future rainfall and projecting future soil erosion. In the present study, future rainfall has been generated with the downscaling of GCM (Global Circulation Model) data of Mandakini river basin, a hilly catchment in the state of Uttarakhand, India, to obtain future impact on soil erosion within the basin. The USLE is an erosion prediction model designed to predict the long-term average annual soil loss from specific field slopes in specified landuse and management systems (i.e., crops, rangeland, and recreational areas) using remote sensing and GIS technologies. Future soil erosion has shown increasing trend due to increasing rainfall which has been generated from the statistical-based downscaling method.
Understanding climate: A strategy for climate modeling and predictability research, 1985-1995
NASA Technical Reports Server (NTRS)
Thiele, O. (Editor); Schiffer, R. A. (Editor)
1985-01-01
The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.
A global flash flood forecasting system
NASA Astrophysics Data System (ADS)
Baugh, Calum; Pappenberger, Florian; Wetterhall, Fredrik; Hewson, Tim; Zsoter, Ervin
2016-04-01
The sudden and devastating nature of flash flood events means it is imperative to provide early warnings such as those derived from Numerical Weather Prediction (NWP) forecasts. Currently such systems exist on basin, national and continental scales in Europe, North America and Australia but rely on high resolution NWP forecasts or rainfall-radar nowcasting, neither of which have global coverage. To produce global flash flood forecasts this work investigates the possibility of using forecasts from a global NWP system. In particular we: (i) discuss how global NWP can be used for flash flood forecasting and discuss strengths and weaknesses; (ii) demonstrate how a robust evaluation can be performed given the rarity of the event; (iii) highlight the challenges and opportunities in communicating flash flood uncertainty to decision makers; and (iv) explore future developments which would significantly improve global flash flood forecasting. The proposed forecast system uses ensemble surface runoff forecasts from the ECMWF H-TESSEL land surface scheme. A flash flood index is generated using the ERIC (Enhanced Runoff Index based on Climatology) methodology [Raynaud et al., 2014]. This global methodology is applied to a series of flash floods across southern Europe. Results from the system are compared against warnings produced using the higher resolution COSMO-LEPS limited area model. The global system is evaluated by comparing forecasted warning locations against a flash flood database of media reports created in partnership with floodlist.com. To deal with the lack of objectivity in media reports we carefully assess the suitability of different skill scores and apply spatial uncertainty thresholds to the observations. To communicate the uncertainties of the flash flood system output we experiment with a dynamic region-growing algorithm. This automatically clusters regions of similar return period exceedence probabilities, thus presenting the at-risk areas at a spatial resolution appropriate to the NWP system. We then demonstrate how these warning areas could eventually complement existing global systems such as the Global Flood Awareness System (GloFAS), to give warnings of flash floods. This work demonstrates the possibility of creating a global flash flood forecasting system based on forecasts from existing global NWP systems. Future developments, in post-processing for example, will need to address an under-prediction bias, for extreme point rainfall, that is innate to current-generation global models.
Prediction of global ionospheric VTEC maps using an adaptive autoregressive model
NASA Astrophysics Data System (ADS)
Wang, Cheng; Xin, Shaoming; Liu, Xiaolu; Shi, Chuang; Fan, Lei
2018-02-01
In this contribution, an adaptive autoregressive model is proposed and developed to predict global ionospheric vertical total electron content maps (VTEC). Specifically, the spherical harmonic (SH) coefficients are predicted based on the autoregressive model, and the order of the autoregressive model is determined adaptively using the F-test method. To test our method, final CODE and IGS global ionospheric map (GIM) products, as well as altimeter TEC data during low and mid-to-high solar activity period collected by JASON, are used to evaluate the precision of our forecasting products. Results indicate that the predicted products derived from the model proposed in this paper have good consistency with the final GIMs in low solar activity, where the annual mean of the root-mean-square value is approximately 1.5 TECU. However, the performance of predicted vertical TEC in periods of mid-to-high solar activity has less accuracy than that during low solar activity periods, especially in the equatorial ionization anomaly region and the Southern Hemisphere. Additionally, in comparison with forecasting products, the final IGS GIMs have the best consistency with altimeter TEC data. Future work is needed to investigate the performance of forecasting products using the proposed method in an operational environment, rather than using the SH coefficients from the final CODE products, to understand the real-time applicability of the method.
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.
NASA Astrophysics Data System (ADS)
Benedict, Sam; van Oevelen, Peter
2014-05-01
To improve understanding of the various processes at work on spatial and temporal scales from regional to global the Regional Hydroclimate Projects (RHP's) are established as part of the Global Energy and Water Exchanges (GEWEX)Project to link the regional observations and process understanding to the global scale. This is done through exchange of observations, data, modeling, transferability studies etc. In this presentation the series of RHP's that were underway over North and South America, Europe and Asia continuously from the early 1990's up to the present will be examined, the reasons they were established, how they evolved and how they are evolving or are likely to evolve in the future, with an emphasis on where they can and should benefit similar work proposed for the TPE. The results will be presented in the context of the World Climate Research Programme (WCRP) Grand Challenge related to the development of a water strategy that addresses the issue of past and future changes in Water, in general, and the GEWEX science question on global water resource systems, in particular. This material will address issues associated with how changes in land surface and hydrology influence past and future changes in water availability and security, how new observations lead to improvements in water management and how models become better in global and regional climate predictions and projections of precipitation and how these outcomes relate to the TPE Water and Energy Exchanges Studies.
McCreless, Erin E.; Huff, David D.; Croll, Donald A.; Tershy, Bernie R.; Spatz, Dena R.; Holmes, Nick D.; Butchart, Stuart H. M.; Wilcox, Chris
2016-01-01
Invasive mammals on islands pose severe, ongoing threats to global biodiversity. However, the severity of threats from different mammals, and the role of interacting biotic and abiotic factors in driving extinctions, remain poorly understood at a global scale. Here we model global extirpation patterns for island populations of threatened and extinct vertebrates. Extirpations are driven by interacting factors including invasive rats, cats, pigs, mustelids and mongooses, native species taxonomic class and volancy, island size, precipitation and human presence. We show that controlling or eradicating the relevant invasive mammals could prevent 41–75% of predicted future extirpations. The magnitude of benefits varies across species and environments; for example, managing invasive mammals on small, dry islands could halve the extirpation risk for highly threatened birds and mammals, while doing so on large, wet islands may have little benefit. Our results provide quantitative estimates of conservation benefits and, when combined with costs in a return-on-investment framework, can guide efficient conservation strategies. PMID:27535095
Tristan code and its application
NASA Astrophysics Data System (ADS)
Nishikawa, K.-I.
Since TRISTAN: The 3-D Electromagnetic Particle Code was introduced in 1990, it has been used for many applications including the simulations of global solar windmagnetosphere interaction. The most essential ingridients of this code have been published in the ISSS-4 book. In this abstract we describe some of issues and an application of this code for the study of global solar wind-magnetosphere interaction including a substorm study. The basic code (tristan.f) for the global simulation and a local simulation of reconnection with a Harris model (issrec2.f) are available at http:/www.physics.rutger.edu/˜kenichi. For beginners the code (isssrc2.f) with simpler boundary conditions is suitable to start to run simulations. The future of global particle simulations for a global geospace general circulation (GGCM) model with predictive capability (for Space Weather Program) is discussed.
Global Sources and Pathways of Mercury in the Context of Human Health.
Sundseth, Kyrre; Pacyna, Jozef M; Pacyna, Elisabeth G; Pirrone, Nicola; Thorne, Rebecca J
2017-01-22
This paper reviews information from the existing literature and the EU GMOS (Global Mercury Observation System) project to assess the current scientific knowledge on global mercury releases into the atmosphere, on global atmospheric transport and deposition, and on the linkage between environmental contamination and potential impacts on human health. The review concludes that assessment of global sources and pathways of mercury in the context of human health is important for being able to monitor the effects from implementation of the Minamata Convention targets, although new research is needed on the improvement of emission inventory data, the chemical and physical behaviour of mercury in the atmosphere, the improvement of monitoring network data, predictions of future emissions and speciation, and on the subsequent effects on the environment, human health, as well as the economic costs and benefits of reducing these aspects.
NASA Astrophysics Data System (ADS)
Lu, C.; Tian, H.; Yang, J.; Zhang, B.; Xu, R.
2015-12-01
Nitrous oxide (N2O) is among the most important greenhouse gases only next to carbon dioxide (CO2) and methane (CH4) due to its long life time and high radiative forcing (with a global warming potential 265 times as much as CO2 at 100-year time horizon). The Atmospheric concentration of N2O has increased by 20% since pre-industrial era, and this increase plays a significant role in shaping anthropogenic climate change. However, compared to CO2- and CH4-related research, fewer studies have been performed in assessing and predicting the spatiotemporal patterns of N2O emission from natural and agricultural soils. Here we used a coupled biogeochemical model, DLEM, to quantify the historical and future changes in global terrestrial N2O emissions resulting from natural and anthropogenic perturbations including climate variability, atmospheric CO2 concentration, nitrogen deposition, land use and land cover changes, and agricultural land management practices (i.e., synthetic nitrogen fertilizer use, manure application, and irrigation etc.) over the period 1900-2099. We focused on inter-annual variation and long-term trend of terrestrial N2O emission driven by individual and combined environmental changes during historical and future periods. The sensitivity of N2O emission to climate, atmospheric composition, and human activities has been examined at biome-, latitudinal, continental and global scales. Future projections were conducted to identify the hot spots and hot time periods of global N2O emission under two emission scenarios (RCP2.6 and RCP8.5). It provides a modeling perspective for understanding human-induced N2O emission growth and developing potential management strategies to mitigate further atmospheric N2O increase and climate warming.
Current and Future Patterns of Global Marine Mammal Biodiversity
Kaschner, Kristin; Tittensor, Derek P.; Ready, Jonathan; Gerrodette, Tim; Worm, Boris
2011-01-01
Quantifying the spatial distribution of taxa is an important prerequisite for the preservation of biodiversity, and can provide a baseline against which to measure the impacts of climate change. Here we analyse patterns of marine mammal species richness based on predictions of global distributional ranges for 115 species, including all extant pinnipeds and cetaceans. We used an environmental suitability model specifically designed to address the paucity of distributional data for many marine mammal species. We generated richness patterns by overlaying predicted distributions for all species; these were then validated against sightings data from dedicated long-term surveys in the Eastern Tropical Pacific, the Northeast Atlantic and the Southern Ocean. Model outputs correlated well with empirically observed patterns of biodiversity in all three survey regions. Marine mammal richness was predicted to be highest in temperate waters of both hemispheres with distinct hotspots around New Zealand, Japan, Baja California, the Galapagos Islands, the Southeast Pacific, and the Southern Ocean. We then applied our model to explore potential changes in biodiversity under future perturbations of environmental conditions. Forward projections of biodiversity using an intermediate Intergovernmental Panel for Climate Change (IPCC) temperature scenario predicted that projected ocean warming and changes in sea ice cover until 2050 may have moderate effects on the spatial patterns of marine mammal richness. Increases in cetacean richness were predicted above 40° latitude in both hemispheres, while decreases in both pinniped and cetacean richness were expected at lower latitudes. Our results show how species distribution models can be applied to explore broad patterns of marine biodiversity worldwide for taxa for which limited distributional data are available. PMID:21625431
Impacts of climate extremes on gross primary production under global warming
Williams, I. N.; Torn, M. S.; Riley, W. J.; ...
2014-09-24
The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at themore » warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate projections, and the time taken to return to locally optimal climates for GPP following climate extremes increases by more than 25% over many land regions.« less
Impacts of climate extremes on gross primary production under global warming
DOE Office of Scientific and Technical Information (OSTI.GOV)
Williams, I. N.; Torn, M. S.; Riley, W. J.
The impacts of historical droughts and heat-waves on ecosystems are often considered indicative of future global warming impacts, under the assumption that water stress sets in above a fixed high temperature threshold. Historical and future (RCP8.5) Earth system model (ESM) climate projections were analyzed in this study to illustrate changes in the temperatures for onset of water stress under global warming. The ESMs examined here predict sharp declines in gross primary production (GPP) at warm temperature extremes in historical climates, similar to the observed correlations between GPP and temperature during historical heat-waves and droughts. However, soil moisture increases at themore » warm end of the temperature range, and the temperature at which soil moisture declines with temperature shifts to a higher temperature. The temperature for onset of water stress thus increases under global warming and is associated with a shift in the temperature for maximum GPP to warmer temperatures. Despite the shift in this local temperature optimum, the impacts of warm extremes on GPP are approximately invariant when extremes are defined relative to the optimal temperature within each climate period. The GPP sensitivity to these relative temperature extremes therefore remains similar between future and present climates, suggesting that the heat- and drought-induced GPP reductions seen recently can be expected to be similar in the future, and may be underestimates of future impacts given model projections of increased frequency and persistence of heat-waves and droughts. The local temperature optimum can be understood as the temperature at which the combination of water stress and light limitations is minimized, and this concept gives insights into how GPP responds to climate extremes in both historical and future climate periods. Both cold (temperature and light-limited) and warm (water-limited) relative temperature extremes become more persistent in future climate projections, and the time taken to return to locally optimal climates for GPP following climate extremes increases by more than 25% over many land regions.« less
Neogeomorphology, prediction, and the anthropic landscape
NASA Astrophysics Data System (ADS)
Haff, P. K.
The surface of the earth is undergoing profound change due to human impact. By some measures the level of human impact is comparable to the effects of major classical geomorphic processes such as fluvial sediment transport. This change is occurring rapidly, has no geologic precedent, and may represent an irreversible transition to a new and novel landscape with which we have no experience. For these reasons prediction of future landscape evolution will be of increasing importance. The combination of physical and social forces that drive modern landscape change represents the Anthropic Force. Neogeomorphology is the study of the Anthropic Force and its present and likely future effects on the landscape. Unique properties associated with the Anthropic Force include consciousness, intention and design. These properties support the occurrence of nonclassical geomorphic phenomena, such as landscape planning, engineering, and management. The occurrence of short time-scale phenomena induced by anthropic landscape change, the direct effects of this change on society, and the ability to anticipate and intentionally influence the future trajectory of the global landscape underscore the importance of prediction in a neogeomorphic world.
Catastrophic impact of typhoon waves on coral communities in the Ryukyu Islands under global warming
NASA Astrophysics Data System (ADS)
Hongo, Chuki; Kawamata, Hideki; Goto, Kazuhisa
2012-06-01
Typhoon-generated storm waves generally cause mechanical damage to coral communities on present-day reefs, and the magnitude and extent of damage is predicted to increase in the near future as a result of global warming. Therefore, a comprehensive understanding of potential future scenarios of reef ecosystems is of prime interest. This study assesses the current status of coral communities on Ibaruma reef, Ryukyu Islands, on the basis of field observations, engineering and fluid dynamic models, and calculations of wave motion, and predicts the potential effects of a super-extreme typhoon (incident wave height,H = 20 m; wave period, T = 20 s) on the reef. On the present-day reef, massive corals occur in shallow lagoons and tabular corals occur from the reef crest to the reef slope. The observed distribution of corals, which is frequently attacked by moderate (H = 10 m, T = 10 s) and extreme (H = 10 m, T = 15 s) typhoons, is consistent with the predictions of engineering models. Moreover, this study indicates that if a super-extreme typhoon attacks the reef in the near future, massive corals will survive in the shallow lagoons but tabular corals on the reef crest and reef slope will be severely impacted. The findings imply that super-extreme typhoons will cause a loss of species diversity, as the tabular corals are important reef builders and are critical to the maintenance of reef ecosystems. Consequently, reef restoration is a key approach to maintaining reef ecosystems in the wake of super-extreme typhoons.
Hanuschkin, Alexander; Kunkel, Susanne; Helias, Moritz; Morrison, Abigail; Diesmann, Markus
2010-01-01
Traditionally, event-driven simulations have been limited to the very restricted class of neuronal models for which the timing of future spikes can be expressed in closed form. Recently, the class of models that is amenable to event-driven simulation has been extended by the development of techniques to accurately calculate firing times for some integrate-and-fire neuron models that do not enable the prediction of future spikes in closed form. The motivation of this development is the general perception that time-driven simulations are imprecise. Here, we demonstrate that a globally time-driven scheme can calculate firing times that cannot be discriminated from those calculated by an event-driven implementation of the same model; moreover, the time-driven scheme incurs lower computational costs. The key insight is that time-driven methods are based on identifying a threshold crossing in the recent past, which can be implemented by a much simpler algorithm than the techniques for predicting future threshold crossings that are necessary for event-driven approaches. As run time is dominated by the cost of the operations performed at each incoming spike, which includes spike prediction in the case of event-driven simulation and retrospective detection in the case of time-driven simulation, the simple time-driven algorithm outperforms the event-driven approaches. Additionally, our method is generally applicable to all commonly used integrate-and-fire neuronal models; we show that a non-linear model employing a standard adaptive solver can reproduce a reference spike train with a high degree of precision. PMID:21031031
Predicting uncertainty in future marine ice sheet volume using Bayesian statistical methods
NASA Astrophysics Data System (ADS)
Davis, A. D.
2015-12-01
The marine ice instability can trigger rapid retreat of marine ice streams. Recent observations suggest that marine ice systems in West Antarctica have begun retreating. However, unknown ice dynamics, computationally intensive mathematical models, and uncertain parameters in these models make predicting retreat rate and ice volume difficult. In this work, we fuse current observational data with ice stream/shelf models to develop probabilistic predictions of future grounded ice sheet volume. Given observational data (e.g., thickness, surface elevation, and velocity) and a forward model that relates uncertain parameters (e.g., basal friction and basal topography) to these observations, we use a Bayesian framework to define a posterior distribution over the parameters. A stochastic predictive model then propagates uncertainties in these parameters to uncertainty in a particular quantity of interest (QoI)---here, the volume of grounded ice at a specified future time. While the Bayesian approach can in principle characterize the posterior predictive distribution of the QoI, the computational cost of both the forward and predictive models makes this effort prohibitively expensive. To tackle this challenge, we introduce a new Markov chain Monte Carlo method that constructs convergent approximations of the QoI target density in an online fashion, yielding accurate characterizations of future ice sheet volume at significantly reduced computational cost.Our second goal is to attribute uncertainty in these Bayesian predictions to uncertainties in particular parameters. Doing so can help target data collection, for the purpose of constraining the parameters that contribute most strongly to uncertainty in the future volume of grounded ice. For instance, smaller uncertainties in parameters to which the QoI is highly sensitive may account for more variability in the prediction than larger uncertainties in parameters to which the QoI is less sensitive. We use global sensitivity analysis to help answer this question, and make the computation of sensitivity indices computationally tractable using a combination of polynomial chaos and Monte Carlo techniques.
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.
NASA Astrophysics Data System (ADS)
Wang, Guiling
2005-12-01
This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.
Kowler, Eileen; Aitkin, Cordelia D; Ross, Nicholas M; Santos, Elio M; Zhao, Min
2014-05-16
The ability of smooth pursuit eye movements to anticipate the future motion of targets has been known since the pioneering work of Dodge, Travis, and Fox (1930) and Westheimer (1954). This article reviews aspects of anticipatory smooth eye movements, focusing on the roles of the different internal or external cues that initiate anticipatory pursuit.We present new results showing that the anticipatory smooth eye movements evoked by different cues differ substantially, even when the cues are equivalent in the information conveyed about the direction of future target motion. Cues that convey an easily interpretable visualization of the motion path produce faster anticipatory smooth eye movements than the other cues tested, including symbols associated arbitrarily with the path, and the same target motion tested repeatedly over a block of trials. The differences among the cues may be understood within a common predictive framework in which the cues differ in the level of subjective certainty they provide about the future path. Pursuit may be driven by a combined signal in which immediate sensory motion, and the predictions about future motion generated by sets of cues, are weighted according to their respective levels of certainty. Anticipatory smooth eye movements, an overt indicator of expectations and predictions, may not be operating in isolation, but may be part of a global process in which the brain analyzes available cues, formulates predictions, and uses them to control perceptual, motor, and cognitive processes. © 2014 ARVO.
The Missing Middle: Aligning Education and the Knowledge Economy
ERIC Educational Resources Information Center
Carnevale, Anthony P.; Desrochers, Donna M.
2002-01-01
While no one can predict the future, today's economic and demographic realities suggest the opportunities and challenges that will face America in the years to come. The U.S. economy has already undergone dramatic changes in the latter part of the twentieth century. The extension of product and labor markets has expanded global competition, and…
West Antarctic Ice Sheet Initiative. Volume 2: Discipline Reviews
NASA Technical Reports Server (NTRS)
Bindschadler, Robert A. (Editor)
1991-01-01
Seven discipline review papers are presented on the state of the knowledge of West Antarctica and opinions on how that knowledge must be increased to predict the future behavior of this ice sheet and to assess its potential to collapse, rapidly raising the global sea level. These are the goals of the West Antarctic Ice Sheet Initiative (WAIS).
USDA-ARS?s Scientific Manuscript database
In order to determine the likely effect of global warming on agricultural productivity while avoiding experimental artifacts, there is a need to conduct warming research under conditions as representative as possible of future open fields, i.e., temperature free-air controlled enhancement (T-FACE) e...
The Global Observing System in the Assimilation Context
NASA Technical Reports Server (NTRS)
Reinecker, Michele M.; Gelaro, R.; Pawson, S.; Reichle, R.; McCarty, W.
2011-01-01
Weather and climate analyses and predictions all rely on the global observing system. However, the observing system, whether atmosphere, ocean, or land surface, yields a diverse set of incomplete observations of the different components of Earth s environment. Data assimilation systems are essential to synthesize the wide diversity of in situ and remotely sensed observations into four-dimensional state estimates by combining the various observations with model-based estimates. Assimilation, or associated tools and products, are also useful in providing guidance for the evolution of the observing system of the future. This paper provides a brief overview of the global observing system and information gleaned through assimilation tools, and presents some evaluations of observing system gaps and issues.
Precipitation and temperature regime over Cyprus as a result of global climate change
NASA Astrophysics Data System (ADS)
Giannakopoulos, C.; Hadjinicolaou, P.; Kostopoulou, E.; Varotsos, K. V.; Zerefos, C.
2010-02-01
In this study, the impact of global climate change on the temperature and precipitation regime over the island of Cyprus has been investigated. The analysis is based on daily output from a regional climate model (RCM) at a high horizontal resolution (25 km) produced within the framework of the EU-funded ENSEMBLES project. The control run represents the base period 1961-1990 and is used here as reference for comparison with future predictions. Two future periods are studied, 2021-2050 and 2071-2100. For the study area and over the study period, an analysis of the changes associated with the temperature regime and the hydrological cycle, such as mean precipitation and drought duration, is presented. Variations in the mean annual and seasonal rainfall are presented. Changes in the number of hot days/warm nights as well as drought duration are also discussed. These changes should be very important to assess future possible water shortages over the island and to provide a basis for associated impacts on the agricultural sector.
Beekhuijzen, Manon
2017-09-01
Since adoption of the first globally implemented guidelines for developmental and reproductive toxicity (DART) testing for pharmaceuticals, industrial chemicals and agrochemicals, many years passed without major updates. However in recent years, significant changes in these guidelines have been made or are being implemented. These changes have been guided by the ethical drive to reduce, refine and replace (3R) animal testing, as well as the addition of endocrine disruptor relevant endpoints. Recent applied improvements have focused on reduction and refinement. Ongoing scientific and technical innovations will provide the means for replacement of animal testing in the future and will improve predictivity in humans. The aim of this review is to provide an overview of ongoing global DART endeavors in respect to the 3Rs, with an outlook towards future advances in DART testing aspiring to reduce animal testing to a minimum and the supreme ambition towards animal-free hazard and risk assessment. Copyright © 2017 Elsevier Inc. All rights reserved.
Costanza, Robert; Graumlich, Lisa; Steffen, Will; Crumley, Carole; Dearing, John; Hibbard, Kathy; Leemans, Rik; Redman, Charles; Schimel, David
2007-11-01
Understanding the history of how humans have interacted with the rest of nature can help clarify the options for managing our increasingly interconnected global system. Simple, deterministic relationships between environmental stress and social change are inadequate. Extreme drought, for instance, triggered both social collapse and ingenious management of water through irrigation. Human responses to change, in turn, feed into climate and ecological systems, producing a complex web of multidirectional connections in time and space. Integrated records of the co-evolving human-environment system over millennia are needed to provide a basis for a deeper understanding of the present and for forecasting the future. This requires the major task of assembling and integrating regional and global historical, archaeological, and paleoenvironmental records. Humans cannot predict the future. But, if we can adequately understand the past, we can use that understanding to influence our decisions and to create a better, more sustainable and desirable future.
A global scale mechanistic model of photosynthetic capacity (LUNA V1.0)
Ali, Ashehad A.; Xu, Chonggang; Rogers, Alistair; ...
2016-02-12
Although plant photosynthetic capacity as determined by the maximum carboxylation rate (i.e., V c,max25) and the maximum electron transport rate (i.e., J max25) at a reference temperature (generally 25 °C) is known to vary considerably in space and time in response to environmental conditions, it is typically parameterized in Earth system models (ESMs) with tabulated values associated with plant functional types. In this study, we have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA) to predict photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among lightmore » capture, electron transport, carboxylation and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of photosynthetic capacity as it explains ~55 % of the global variation in observed values of V c,max25 and ~65 % of the variation in the observed values of J max25. Model simulations with LUNA under current and future climate conditions demonstrate that modeled values of V c,max25 are most affected in high-latitude regions under future climates. In conclusion, ESMs that relate the values of V c,max25 or J max25 to plant functional types only are likely to substantially overestimate future global photosynthesis.« less
Madronich, S; Shao, M; Wilson, S R; Solomon, K R; Longstreth, J D; Tang, X Y
2015-01-01
UV radiation is an essential driver for the formation of photochemical smog, which includes ground-level ozone and particulate matter (PM). Recent analyses support earlier work showing that poor outdoor air quality is a major environmental hazard as well as quantifying health effects on regional and global scales more accurately. Greater exposure to these pollutants has been linked to increased risks of cardiovascular and respiratory diseases in humans and is associated globally with several million premature deaths per year. Ozone also has adverse effects on yields of crops, leading to loss of billions of US dollars each year. These detrimental effects also may alter biological diversity and affect the function of natural ecosystems. Future air quality will depend mostly on changes in emission of pollutants and their precursors, but changes in UV radiation and climate will contribute as well. Significant reductions in emissions, mainly from the energy and transportation sectors, have already led to improved air quality in many locations. Air quality will continue to improve in those cities/states that can afford controls, and worsen where the regulatory infrastructure is not available. Future changes in UV radiation and climate will alter the rates of formation of ground-level ozone and photochemically-generated particulate matter and must be considered in predictions of air quality. The decrease in UV radiation associated with recovery of stratospheric ozone will, according to recent global atmospheric model simulations, lead to increases in ground-level ozone at most locations. If correct, this will add significantly to future ground-level ozone trends. However, the spatial resolution of these global models is insufficient to inform policy at this time, especially for urban areas. UV radiation affects the atmospheric concentration of hydroxyl radicals, ˙OH, which are responsible for the self-cleaning of the atmosphere. Recent measurements confirm that, on a local scale, ˙OH radicals respond rapidly to changes in UV radiation. However, on large (global) scales, models differ in their predictions by nearly a factor of two, with consequent uncertainties for estimating the atmospheric lifetime and concentrations of key greenhouse gases and air pollutants. Projections of future climate need to consider these uncertainties. No new negative environmental effects of substitutes for ozone depleting substances or their breakdown-products have been identified. However, some substitutes for the ozone depleting substances will continue to contribute to global climate change if concentrations rise above current levels.
Predicting future spatial distribution of SOC across entire France
NASA Astrophysics Data System (ADS)
Meersmans, Jeroen; Van Rompaey, Anton; Quine, Tim; Martin, Manuel; Pagé, Christian; Arrouays, Dominique
2013-04-01
Soil organic carbon (SOC) is widely recognized as a key factor controlling soil quality and as a crucial and active component of the global C-cycle. Hence, there exists a growing interest in monitoring and modeling the spatial and temporal behavior of this pool. So far, a large attempt has been made to map SOC at national scales for current and/or past situations. Despite some coarse predictions, detailed spatial SOC predictions for the future are still lacking. In this study we aim to predict future spatial evolution of SOC driven by climate and land use change for France up to the year 2100. Therefore, we combined 1) an existing model, predicting SOC as a function of soil type, climate, land use and management (Meersmans et al 2012), with 2) eight different IPCC spatial explicit climate change predictions (conducted by CERFACS) and 3) Land use change scenario predictions. We created business-as-usual land use change scenarios by extrapolating observed trends and calibrating logistic regression models, incorporating a large set of physical and socio-economic factors, at the regional level in combination with a multi-objective land allocation (MOLA) procedure. The resultant detailed projections of future SOC evolution across all regions of France, allow us to identify regions that are most likely to be characterized by a significant gain or loss of SOC and the degree to which land use decisions/outcomes control the scale of loss and gain. Therefore, this methodology and resulting maps can be considered as powerful tools to aid decision making concerning appropriate soil management, in order to enlarge SOC storage possibilities and reduce soil related CO2 fluxes.
Research frontiers for improving our understanding of drought‐induced tree and forest mortality
Hartmann, Henrik; Moura, Catarina; Anderegg, William R. L.; Ruehr, Nadine; Salmon, Yann; Allen, Craig D.; Arndt, Stefan K.; Breshears, David D.; Davi, Hendrik; Galbraith, David; Ruthrof, Katinka X.; Wunder, Jan; Adams, Henry D.; Bloemen, Jasper; Cailleret, Maxime; Cobb, Richard; Gessler, Arthur; Grams, Thorsten E. E.; Jansen, Steven; Kautz, Markus; Lloret, Francisco; O’Brien, Michael
2018-01-01
Accumulating evidence highlights increased mortality risks for trees during severe drought, particularly under warmer temperatures and increasing vapour pressure deficit (VPD). Resulting forest die‐off events have severe consequences for ecosystem services, biophysical and biogeochemical land–atmosphere processes. Despite advances in monitoring, modelling and experimental studies of the causes and consequences of tree death from individual tree to ecosystem and global scale, a general mechanistic understanding and realistic predictions of drought mortality under future climate conditions are still lacking. We update a global tree mortality map and present a roadmap to a more holistic understanding of forest mortality across scales. We highlight priority research frontiers that promote: (1) new avenues for research on key tree ecophysiological responses to drought; (2) scaling from the tree/plot level to the ecosystem and region; (3) improvements of mortality risk predictions based on both empirical and mechanistic insights; and (4) a global monitoring network of forest mortality. In light of recent and anticipated large forest die‐off events such a research agenda is timely and needed to achieve scientific understanding for realistic predictions of drought‐induced tree mortality. The implementation of a sustainable network will require support by stakeholders and political authorities at the international level.
Title: Freshwater phytoplankton responses to global warming.
Wagner, Heiko; Fanesi, Andrea; Wilhelm, Christian
2016-09-20
Global warming alters species composition and function of freshwater ecosystems. However, the impact of temperature on primary productivity is not sufficiently understood and water quality models need to be improved in order to assess the quantitative and qualitative changes of aquatic communities. On the basis of experimental data, we demonstrate that the commonly used photosynthetic and water chemistry parameters alone are not sufficient for modeling phytoplankton growth under changing temperature regimes. We present some new aspects of the acclimation process with respect to temperature and how contrasting responses may be explained by a more complete physiological knowledge of the energy flow from photons to new biomass. We further suggest including additional bio-markers/traits for algal growth such as carbon allocation patterns to increase the explanatory power of such models. Although carbon allocation patterns are promising and functional cellular traits for growth prediction under different nutrient and light conditions, their predictive power still waits to be tested with respect to temperature. A great challenge for the near future will be the prediction of primary production efficiencies under the global change scenario using a uniform model for phytoplankton assemblages. Copyright © 2016 Elsevier GmbH. All rights reserved.
NASA Astrophysics Data System (ADS)
Fischer, Dominik; Thomas, Stephanie Margarete; Niemitz, Franziska; Reineking, Björn; Beierkuhnlein, Carl
2011-07-01
During the last decades the disease vector Aedes albopictus ( Ae. albopictus) has rapidly spread around the globe. The spread of this species raises serious public health concerns. Here, we model the present distribution and the future climatic suitability of Europe for this vector in the face of climate change. In order to achieve the most realistic current prediction and future projection, we compare the performance of four different modelling approaches, differentiated by the selection of climate variables (based on expert knowledge vs. statistical criteria) and by the geographical range of presence records (native range vs. global range). First, models of the native and global range were built with MaxEnt and were either based on (1) statistically selected climatic input variables or (2) input variables selected with expert knowledge from the literature. Native models show high model performance (AUC: 0.91-0.94) for the native range, but do not predict the European distribution well (AUC: 0.70-0.72). Models based on the global distribution of the species, however, were able to identify all regions where Ae. albopictus is currently established, including Europe (AUC: 0.89-0.91). In a second step, the modelled bioclimatic envelope of the global range was projected to future climatic conditions in Europe using two emission scenarios implemented in the regional climate model COSMO-CLM for three time periods 2011-2040, 2041-2070, and 2071-2100. For both global-driven models, the results indicate that climatically suitable areas for the establishment of Ae. albopictus will increase in western and central Europe already in 2011-2040 and with a temporal delay in eastern Europe. On the other hand, a decline in climatically suitable areas in southern Europe is pronounced in the Expert knowledge based model. Our projections appear unaffected by non-analogue climate, as this is not detected by Multivariate Environmental Similarity Surface analysis. The generated risk maps can aid in identifying suitable habitats for Ae. albopictus and hence support monitoring and control activities to avoid disease vector establishment.
NASA Astrophysics Data System (ADS)
Levine, N. M.; Galbraith, D.; Christoffersen, B. J.; Imbuzeiro, H. A.; Restrepo-Coupe, N.; Malhi, Y.; Saleska, S. R.; Costa, M. H.; Phillips, O.; Andrade, A.; Moorcroft, P. R.
2011-12-01
The Amazonian rainforests play a vital role in global water, energy and carbon cycling. The sensitivity of this system to natural and anthropogenic disturbances therefore has important implications for the global climate. Some global models have predicted large-scale forest dieback and the savannization of Amazonia over the next century [Meehl et al., 2007]. While several studies have demonstrated the sensitivity of dynamic global vegetation models to changes in temperature, precipitation, and dry season length [e.g. Galbraith et al., 2010; Good et al., 2011], the ability of these models to accurately reproduce ecosystem dynamics of present-day transitional or low biomass tropical forests has not been demonstrated. A model-data intercomparison was conducted with four state-of-the-art terrestrial ecosystem models to evaluate the ability of these models to accurately represent structure, function, and long-term biomass dynamics over a range of Amazonian ecosystems. Each modeling group conducted a series of simulations for 14 sites including mature forest, transitional forest, savannah, and agricultural/pasture sites. All models were run using standard physical parameters and the same initialization procedure. Model results were compared against forest inventory and dendrometer data in addition to flux tower measurements. While the models compared well against field observations for the mature forest sites, significant differences were observed between predicted and measured ecosystem structure and dynamics for the transitional forest and savannah sites. The length of the dry season and soil sand content were good predictors of model performance. In addition, for the big leaf models, model performance was highest for sites dominated by late successional trees and lowest for sites with predominantly early and mid-successional trees. This study provides insight into tropical forest function and sensitivity to environmental conditions that will aid in predictions of the response of the Amazonian rainforest to future anthropogenically induced changes.
Contributions of projected land use to global radiative forcing ascribed to local sources
NASA Astrophysics Data System (ADS)
Ward, D. S.; Mahowald, N. M.; Kloster, S.
2013-12-01
With global demand for food expected to dramatically increase and put additional pressures on natural lands, there is a need to understand the environmental impacts of land use and land cover change (LULCC). Previous studies have shown that the magnitude and even the sign of the radiative forcing (RF) of biogeophysical effects from LULCC depends on the latitude and forest ecology of the disturbed region. Here we ascribe the contributions to the global RF by land-use related anthropogenic activities to their local sources, organized on a grid of 1.9 degrees latitude by 2.5 degrees longitude. We use RF estimates for the year 2100, using five future LULCC projections, computed from simulations with the National Center for Atmospheric Research Community Land Model and Community Atmosphere Models and additional offline analyses. Our definition of the LULCC RF includes changes to terrestrial carbon storage, methane and nitrous oxide emissions, atmospheric chemistry, aerosol emissions, and surface albedo. We ascribe the RF to gridded locations based on LULCC-related emissions of relevant trace gases and aerosols, including emissions from fires. We find that the largest contributions to the global RF in year 2100 from LULCC originate in the tropics for all future scenarios. In fact, LULCC is the largest tropical source of anthropogenic RF. The LULCC RF in the tropics is dominated by emissions of CO2 from deforestation and methane emissions from livestock and soils. Land surface albedo change is rarely the dominant forcing agent in any of the future LULCC projections, at any location. By combining the five future scenarios we find that deforested area at a specific tropical location can be used to predict the contribution to global RF from LULCC at that location (the relationship does not hold as well in the extratropics). This information could support global efforts like REDD (Reducing Emissions from Deforestation and Forest Degradation), that aim to reduce greenhouse gas emissions from land use, by helping to optimize their effectiveness for climate change mitigation.
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.
Model-based redesign of global transcription regulation
Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso
2009-01-01
Synthetic biology aims to the design or redesign of biological systems. In particular, one possible goal could be the rewiring of the transcription regulation network by exchanging the endogenous promoters. To achieve this objective, we have adapted current methods to the inference of a model based on ordinary differential equations that is able to predict the network response after a major change in its topology. Our procedure utilizes microarray data for training. We have experimentally validated our inferred global regulatory model in Escherichia coli by predicting transcriptomic profiles under new perturbations. We have also tested our methodology in silico by providing accurate predictions of the underlying networks from expression data generated with artificial genomes. In addition, we have shown the predictive power of our methodology by obtaining the gene profile in experimental redesigns of the E. coli genome, where rewiring the transcriptional network by means of knockouts of master regulators or by upregulating transcription factors controlled by different promoters. Our approach is compatible with most network inference methods, allowing to explore computationally future genome-wide redesign experiments in synthetic biology. PMID:19188257
Long-Term Temporal Trends of Polychlorinated Biphenyls and Their Controlling Sources in China.
Zhao, Shizhen; Breivik, Knut; Liu, Guorui; Zheng, Minghui; Jones, Kevin C; Sweetman, Andrew J
2017-03-07
Polychlorinated biphenyls (PCBs) are industrial organic contaminants identified as persistent, bioaccumulative, toxic (PBT), and subject to long-range transport (LRT) with global scale significance. This study focuses on a reconstruction and prediction for China of long-term emission trends of intentionally and unintentionally produced (UP) ∑ 7 PCBs (UP-PCBs, from the manufacture of steel, cement and sinter iron) and their re-emissions from secondary sources (e.g., soils and vegetation) using a dynamic fate model (BETR-Global). Contemporary emission estimates combined with predictions from the multimedia fate model suggest that primary sources still dominate, although unintentional sources are predicted to become a main contributor from 2035 for PCB-28. Imported e-waste is predicted to play an increasing role until 2020-2030 on a national scale due to the decline of intentionally produced (IP) emissions. Hypothetical emission scenarios suggest that China could become a potential source to neighboring regions with a net output of ∼0.4 t year -1 by around 2050. However, future emission scenarios and hence model results will be dictated by the efficiency of control measures.
NASA Technical Reports Server (NTRS)
Lawing, P. L.
1981-01-01
Four of the configurations investigated during a proposed NASA-Langley hypersonic research aircraft program were selected for phase-change-paint heat-transfer testing and forebody boundary layer pitot surveys. In anticipation of future hypersonic aircraft, both published and unpublished data and results are reviewed and presented with the purpose of providing a synoptic heat-transfer data base from the research effort. Engineering heat-transfer predictions are compared with experimental data on both a global and a local basis. The global predictions are shown to be sufficient for purposes of configuration development, and even the local predictions can be adequate when interpreted in light of the proper flow field. In that regard, cross flow in the forebody boundary layers was examined for significant heating and aerodynamic effect on the scramjet engines. A design philosophy which evolved from the research airplane effort is used to design a forebody shape that produces thin, uniform, forebody boundary layers on a hypersonic airbreathing missile. Finally, heating/boundary layer phenomena which are not predictable with state-of-the-art knowledge and techniques are shown and discussed.
Thabane, Lehana; Ioannidis, George; Kennedy, Courtney; Papaioannou, Alexandra
2015-01-01
Objectives To compare the predictive accuracy of the frailty index (FI) of deficit accumulation and the phenotypic frailty (PF) model in predicting risks of future falls, fractures and death in women aged ≥55 years. Methods Based on the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort (n = 3,985), we compared the predictive accuracy of the FI and PF in risks of falls, fractures and death using three strategies: (1) investigated the relationship with adverse health outcomes by increasing per one-fifth (i.e., 20%) of the FI and PF; (2) trichotomized the FI based on the overlap in the density distribution of the FI by the three groups (robust, pre-frail and frail) which were defined by the PF; (3) categorized the women according to a predicted probability function of falls during the third year of follow-up predicted by the FI. Logistic regression models were used for falls and death, while survival analyses were conducted for fractures. Results The FI and PF agreed with each other at a good level of consensus (correlation coefficients ≥ 0.56) in all the three strategies. Both the FI and PF approaches predicted adverse health outcomes significantly. The FI quantified the risks of future falls, fractures and death more precisely than the PF. Both the FI and PF discriminated risks of adverse outcomes in multivariable models with acceptable and comparable area under the curve (AUCs) for falls (AUCs ≥ 0.68) and death (AUCs ≥ 0.79), and c-indices for fractures (c-indices ≥ 0.69) respectively. Conclusions The FI is comparable with the PF in predicting risks of adverse health outcomes. These findings may indicate the flexibility in the choice of frailty model for the elderly in the population-based settings. PMID:25764521
Li, Guowei; Thabane, Lehana; Ioannidis, George; Kennedy, Courtney; Papaioannou, Alexandra; Adachi, Jonathan D
2015-01-01
To compare the predictive accuracy of the frailty index (FI) of deficit accumulation and the phenotypic frailty (PF) model in predicting risks of future falls, fractures and death in women aged ≥55 years. Based on the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort (n = 3,985), we compared the predictive accuracy of the FI and PF in risks of falls, fractures and death using three strategies: (1) investigated the relationship with adverse health outcomes by increasing per one-fifth (i.e., 20%) of the FI and PF; (2) trichotomized the FI based on the overlap in the density distribution of the FI by the three groups (robust, pre-frail and frail) which were defined by the PF; (3) categorized the women according to a predicted probability function of falls during the third year of follow-up predicted by the FI. Logistic regression models were used for falls and death, while survival analyses were conducted for fractures. The FI and PF agreed with each other at a good level of consensus (correlation coefficients ≥ 0.56) in all the three strategies. Both the FI and PF approaches predicted adverse health outcomes significantly. The FI quantified the risks of future falls, fractures and death more precisely than the PF. Both the FI and PF discriminated risks of adverse outcomes in multivariable models with acceptable and comparable area under the curve (AUCs) for falls (AUCs ≥ 0.68) and death (AUCs ≥ 0.79), and c-indices for fractures (c-indices ≥ 0.69) respectively. The FI is comparable with the PF in predicting risks of adverse health outcomes. These findings may indicate the flexibility in the choice of frailty model for the elderly in the population-based settings.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Werth, D.; Chen, K. F.
2013-08-22
The ability of water managers to maintain adequate supplies in coming decades depends, in part, on future weather conditions, as climate change has the potential to alter river flows from their current values, possibly rendering them unable to meet demand. Reliable climate projections are therefore critical to predicting the future water supply for the United States. These projections cannot be provided solely by global climate models (GCMs), however, as their resolution is too coarse to resolve the small-scale climate changes that can affect hydrology, and hence water supply, at regional to local scales. A process is needed to ‘downscale’ themore » GCM results to the smaller scales and feed this into a surface hydrology model to help determine the ability of rivers to provide adequate flow to meet future needs. We apply a statistical downscaling to GCM projections of precipitation and temperature through the use of a scaling method. This technique involves the correction of the cumulative distribution functions (CDFs) of the GCM-derived temperature and precipitation results for the 20{sup th} century, and the application of the same correction to 21{sup st} century GCM projections. This is done for three meteorological stations located within the Coosa River basin in northern Georgia, and is used to calculate future river flow statistics for the upper Coosa River. Results are compared to the historical Coosa River flow upstream from Georgia Power Company’s Hammond coal-fired power plant and to flows calculated with the original, unscaled GCM results to determine the impact of potential changes in meteorology on future flows.« less
Global Sources and Pathways of Mercury in the Context of Human Health
Sundseth, Kyrre; Pacyna, Jozef M.; Pacyna, Elisabeth G.; Pirrone, Nicola; Thorne, Rebecca J.
2017-01-01
This paper reviews information from the existing literature and the EU GMOS (Global Mercury Observation System) project to assess the current scientific knowledge on global mercury releases into the atmosphere, on global atmospheric transport and deposition, and on the linkage between environmental contamination and potential impacts on human health. The review concludes that assessment of global sources and pathways of mercury in the context of human health is important for being able to monitor the effects from implementation of the Minamata Convention targets, although new research is needed on the improvement of emission inventory data, the chemical and physical behaviour of mercury in the atmosphere, the improvement of monitoring network data, predictions of future emissions and speciation, and on the subsequent effects on the environment, human health, as well as the economic costs and benefits of reducing these aspects. PMID:28117743
The global diabetes model: user friendly version 3.0.
Brown, J B; Russell, A; Chan, W; Pedula, K; Aickin, M
2000-11-01
The attributes of Release 3.0 of the user friendly version (UFV) of the global diabetes model (GDM) are described and documented in detail. The GDM is a continuous, stochastic microsimulation model of type 2 diabetes. Suitable for predicting the medical futures of both individuals with diabetes and representative diabetic populations, the GDM predicts medical events (complications of diabetes), survival, utilities, and medical care costs. Incidence rate functions for microvascular and macrovascular complications are based on a combination of published studies and analyses of data describing diabetic members of Kaiser Permanente Northwest Region, a non-profit group-model health maintenance organization. Active risk factors include average blood glucose (HbAlc), systolic blood pressure (SBP), low density lipoprotein cholesterol (LDL), high density lipoprotein cholesterol (HDL), triglycerides, smoking status, and use of prophylactic aspirin. Events predicted include diabetic eye disease, diabetic nephropathy, peripheral neuropathy amputation, myocardial infarction, stroke, peripheral artery disease, congestive heart failure, coronary artery surgery, coronary angioplasty, and death.
Structure and Controls of the Global Virtual Water Trade Network
NASA Astrophysics Data System (ADS)
Suweis, S. S.
2011-12-01
Recurrent or ephemeral water shortages are a crucial global challenge, in particular because of their impacts on food production. The global character of this challenge is reflected in the trade among nations of virtual water, i.e. the amount of water used to produce a given commodity. We build, analyze and model the network describing the transfer of virtual water between world nations for staple food products. We find that all the key features of the network are well described by a model, the fitness model, that reproduces both the topological and weighted properties of the global virtual water trade network, by assuming as sole controls each country's gross domestic product and yearly rainfall on agricultural areas. We capture and quantitatively describe the high degree of globalization of water trade and show that a small group of nations play a key role in the connectivity of the network and in the global redistribution of virtual water. Finally, we illustrate examples of prediction of the structure of the network under future political, economic and climatic scenarios, suggesting that the crucial importance of the countries that trade large volumes of water will be strengthened. Our results show the importance of incorporating a network framework in the study of virtual water trades and provide a model to study the structure and resilience of the GVWTN under future scenarios for social, economic and climate change.
Climate Change and Tropical Total Lightning
NASA Technical Reports Server (NTRS)
Albrecht, R.; Petersen, W.; Buechler, D.; Goodman, S.; Blakeslee, R.; Christian, H.
2009-01-01
While global warming is regarded as a fact by many in the scientific community, its future impact remains a challenge to be determined and measured. The International Panel on Climate Change (IPCC) assessment report (IPCC, 2007) shows inconclusive answers on global rainfall trends and general agreement on a future drier climate with increased global warming. The relationship between temperature, humidity and convection is not linear and is strongly dependent on regional scale features, such as topography and land cover. Furthermore, the relationship between convective lightning production (thunderstorms) and temperature is even more complicated, being subjected to the cloud dynamics and microphysics. Total lightning (intracloud and cloud-to-ground) monitoring is a relatively new field of observation. Global and tropical total lightning began to be more extensively measured by satellites in the mid 90s. In this scope, the Lightning Imaging Sensor (LIS) onboard of the Tropical Rainfall Measurement Mission (TRMM) has been operational for over 11 years. Here we address total lightning trends observed by LIS from 1998 to 2008 in different temporal (annual and seasonal) and spatial (large and regional) scales. The observed 11-year trends are then associate to different predicted/hypothesized climate change scenarios.
Study of Regional Downscaled Climate and Air Quality in the United States
NASA Astrophysics Data System (ADS)
Gao, Y.; Fu, J. S.; Drake, J.; Lamarque, J.; Lam, Y.; Huang, K.
2011-12-01
Due to the increasing anthropogenic greenhouse gas emissions, the global and regional climate patterns have significantly changed. Climate change has exerted strong impact on ecosystem, air quality and human life. The global model Community Earth System Model (CESM v1.0) was used to predict future climate and chemistry under projected emission scenarios. Two new emission scenarios, Representative Community Pathways (RCP) 4.5 and RCP 8.5, were used in this study for climate and chemistry simulations. The projected global mean temperature will increase 1.2 and 1.7 degree Celcius for the RCP 4.5 and RCP 8.5 scenarios in 2050s, respectively. In order to take advantage of local detailed topography, land use data and conduct local climate impact on air quality, we downscaled CESM outputs to 4 km by 4 km Eastern US domain using Weather Research and Forecasting (WRF) Model and Community Multi-scale Air Quality modeling system (CMAQ). The evaluations between regional model outputs and global model outputs, regional model outputs and observational data were conducted to verify the downscaled methodology. Future climate change and air quality impact were also examined on a 4 km by 4 km high resolution scale.
Friend, Andrew D; Lucht, Wolfgang; Rademacher, Tim T; Keribin, Rozenn; Betts, Richard; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B; Dankers, Rutger; Falloon, Pete D; Ito, Akihiko; Kahana, Ron; Kleidon, Axel; Lomas, Mark R; Nishina, Kazuya; Ostberg, Sebastian; Pavlick, Ryan; Peylin, Philippe; Schaphoff, Sibyll; Vuichard, Nicolas; Warszawski, Lila; Wiltshire, Andy; Woodward, F Ian
2014-03-04
Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510-758 ppm of CO2), vegetation carbon increases by 52-477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.
Friend, Andrew D.; Lucht, Wolfgang; Rademacher, Tim T.; Keribin, Rozenn; Betts, Richard; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B.; Dankers, Rutger; Falloon, Pete D.; Ito, Akihiko; Kahana, Ron; Kleidon, Axel; Lomas, Mark R.; Nishina, Kazuya; Ostberg, Sebastian; Pavlick, Ryan; Peylin, Philippe; Schaphoff, Sibyll; Vuichard, Nicolas; Warszawski, Lila; Wiltshire, Andy; Woodward, F. Ian
2014-01-01
Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510–758 ppm of CO2), vegetation carbon increases by 52–477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended. PMID:24344265
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
NASA Astrophysics Data System (ADS)
Singer, S. Fred
Long before Ronald Reagan asked voters whether they were better off today than they were 4 years ago, many thoughtful people were asking whether the world as a whole was becoming a better place to live. The Malthusian point of view, restated by the Club of Rome's Limits to Growth, made an enormous impact on the world when it appeared in 1972. Its simplistic message, disguised in computer models, was that exponential growth cannot be maintained forever. Specifically, it predicted imminent exhaustion of food and natural resources and death from evergrowing pollution. Its successor volume, Global 2000, published with the encouragement of the Carter White House in 1980, was more restrained but also predicted general doom. It was responded to by The Resourceful Earth (sponsored by the Heritage Foundation), which views the future as rosy and contradicts Global 2000 on almost every point.
Infrared heater system for warming tropical forest understory plants and soils
Bruce A. Kimball; Aura M. Alonso-Rodríguez; Molly A. Cavaleri; Sasha C. Reed; Grizelle González; Tana E. Wood
2018-01-01
The response of tropical forests to global warming is one of the largest uncertainties in predicting the future carbon balance of Earth. To determine the likely effects of elevated temperatures on tropical forest understory plants and soils, as well as other ecosystems, an infrared (IR) heater system was developed to provide in situ warming for the Tropical Responses...
The U.S. forest sector in 2030: Markets and competitors
James A. Turner; Joseph Buongiorno; Shushuai Zhu; Jeffrey P. Prestemon
2005-01-01
The Global Forest Products Model was used to project international forest sector developments, conditional on the latest RPA Timber Assessment of future domestic changes in the United States. While the United States, Japan, and Europe were predicted to remain major importers of forest products out to 2030, the rapid economic growth of China would make it the world...
Big changes in cold places: the future of wildlife habitat in northwest Alaska
Natasha Vizcarra; Bruce Marcot
2016-01-01
Higher global temperatures are changing ecosystems in the Arctic. They are becoming greener as the climate and land become more hospitable to taller vegetation. Scientists predict that woody vegetation in the Arctic will increase by more than 50 percent, and half of all vegetated areas will shift to types more suited to the higher temperatures and changing physical...
Singer, Peter A; Pellegrino, Edmund D; Siegler, Mark
2001-01-01
A decade ago, we reviewed the field of clinical ethics; assessed its progress in research, education, and ethics committees and consultation; and made predictions about the future of the field. In this article, we revisit clinical ethics to examine our earlier observations, highlight key developments, and discuss remaining challenges for clinical ethics, including the need to develop a global perspective on clinical ethics problems. PMID:11346456
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…
Global megatrends and their implications for environmental assessment practice
DOE Office of Scientific and Technical Information (OSTI.GOV)
Retief, Francois, E-mail: francois.retief@nwu.ac.za; Bond, Alan; Research Unit for Environmental Sciences and Management, North-West University
This paper addresses the future of environmental assessment (EA) practice in light of a rapidly changing world. We apply a literature review-based methodology to firstly identify key global megatrends and then reflect upon the implications for EA practice based on some known challenges. The key megatrends identified are synthesised into six categories: i) demographics, ii) urbanization, iii) technological innovation, iv) power shifts, v) resource scarcity and vi) climate change. We then discuss the implications of these megatrends for EA practice against four known EA challenges namely: dealing with i) complexity and uncertainty, ii) efficiency, iii) significance and iv) communication andmore » participation. Our analysis suggests important implications for EA practice such as: increased difficulties with accuracy of prediction; the need for facilitative adaptation; an increase in the occurrence of unexpected events; higher expectations for procedural efficiency; challenges with information and communication management; dealing with significance judgements; and mitigation amidst resource scarcity and increasing pressures on earth systems. The megatrends underscore the need for continued evolution of EA thinking and practice, especially moving away from seeking a predictable single future or outcome towards the possibility of multiple scenarios with associated adaptability and enhanced system resilience capable of responding to rapid change.« less
NASA Astrophysics Data System (ADS)
Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.
2017-12-01
At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.
Climate change and mosquito-borne disease.
Reiter, P
2001-01-01
Global atmospheric temperatures are presently in a warming phase that began 250--300 years ago. Speculations on the potential impact of continued warming on human health often focus on mosquito-borne diseases. Elementary models suggest that higher global temperatures will enhance their transmission rates and extend their geographic ranges. However, the histories of three such diseases--malaria, yellow fever, and dengue--reveal that climate has rarely been the principal determinant of their prevalence or range; human activities and their impact on local ecology have generally been much more significant. It is therefore inappropriate to use climate-based models to predict future prevalence. PMID:11250812
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.
Hatala, J.A.; Dietze, M.C.; Crabtree, R.L.; Kendall, Katherine C.; Six, D.; Moorcroft, P.R.
2011-01-01
The introduction of nonnative pathogens is altering the scale, magnitude, and persistence of forest disturbance regimes in the western United States. In the high-altitude whitebark pine (Pinus albicaulis) forests of the Greater Yellowstone Ecosystem (GYE), white pine blister rust (Cronartium ribicola) is an introduced fungal pathogen that is now the principal cause of tree mortality in many locations. Although blister rust eradication has failed in the past, there is nonetheless substantial interest in monitoring the disease and its rate of progression in order to predict the future impact of forest disturbances within this critical ecosystem.This study integrates data from five different field-monitoring campaigns from 1968 to 2008 to create a blister rust infection model for sites located throughout the GYE. Our model parameterizes the past rates of blister rust spread in order to project its future impact on high-altitude whitebark pine forests. Because the process of blister rust infection and mortality of individuals occurs over the time frame of many years, the model in this paper operates on a yearly time step and defines a series of whitebark pine infection classes: susceptible, slightly infected, moderately infected, and dead. In our analysis, we evaluate four different infection models that compare local vs. global density dependence on the dynamics of blister rust infection. We compare models in which blister rust infection is: (1) independent of the density of infected trees, (2) locally density-dependent, (3) locally density-dependent with a static global infection rate among all sites, and (4) both locally and globally density-dependent. Model evaluation through the predictive loss criterion for Bayesian analysis supports the model that is both locally and globally density-dependent. Using this best-fit model, we predicted the average residence times for the four stages of blister rust infection in our model, and we found that, on average, whitebark pine trees within the GYE remain susceptible for 6.7 years, take 10.9 years to transition from slightly infected to moderately infected, and take 9.4 years to transition from moderately infected to dead. Using our best-fit model, we project the future levels of blister rust infestation in the GYE at critical sites over the next 20 years.
The future of isoprene emission from leaves, canopies and landscapes.
Sharkey, Thomas D; Monson, Russell K
2014-08-01
Isoprene emission from plants plays a dominant role in atmospheric chemistry. Predicting how isoprene emission may change in the future will help predict changes in atmospheric oxidant, greenhouse gas and secondary organic aerosol concentrations in the future atmosphere. At the leaf-scale, an increase in isoprene emission with increasing temperature is offset by a reduction in isoprene emission rate caused by increased CO₂. At the canopy scale, increased leaf area index in elevated CO₂ can offset the reduction in leaf-scale isoprene emission caused by elevated CO₂. At the landscape scale, a reduction in forest coverage may decrease, while forest fertilization and community composition dynamics are likely to cause an increase in the global isoprene emission rate. Here we review the potential for changes in the isoprene emission rate at all of these scales. When considered together, it is likely that these interacting effects will result in an increase in the emission of the most abundant plant volatile, isoprene, from the biosphere to the atmosphere in the future. © 2014 John Wiley & Sons Ltd.
Prediction of seasonal climate-induced variations in global food production
NASA Astrophysics Data System (ADS)
Iizumi, Toshichika; Sakuma, Hirofumi; Yokozawa, Masayuki; Luo, Jing-Jia; Challinor, Andrew J.; Brown, Molly E.; Sakurai, Gen; Yamagata, Toshio
2013-10-01
Consumers, including the poor in many countries, are increasingly dependent on food imports and are thus exposed to variations in yields, production and export prices in the major food-producing regions of the world. National governments and commercial entities are therefore paying increased attention to the cropping forecasts of important food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We found that moderate-to-marked yield loss over a substantial percentage (26-33%) of the harvested area of these crops is reliably predictable if climatic forecasts are near perfect. However, only rice and wheat production are reliably predictable at three months before the harvest using within-season hindcasts. The reliabilities of estimates varied substantially by crop--rice and wheat yields were the most predictable, followed by soybean and maize. The reasons for variation in the reliability of the estimates included the differences in crop sensitivity to the climate and the technology used by the crop-producing regions. Our findings reveal that the use of seasonal climatic forecasts to predict crop failures will be useful for monitoring global food production and will encourage the adaptation of food systems toclimatic extremes.
Collatz, G James; Berry, Joseph A; Clark, James S
1998-05-01
C 4 photosynthetic physiologies exhibit fundamentally different responses to temperature and atmospheric CO 2 partial pressures (pCO 2 ) compared to the evolutionarily more primitive C 3 type. All else being equal, C 4 plants tend to be favored over C 3 plants in warm humid climates and, conversely, C 3 plants tend to be favored over C 4 plants in cool climates. Empirical observations supported by a photosynthesis model predict the existence of a climatological crossover temperature above which C 4 species have a carbon gain advantage and below which C 3 species are favored. Model calculations and analysis of current plant distribution suggest that this pCO 2 -dependent crossover temperature is approximated by a mean temperature of 22°C for the warmest month at the current pCO 2 (35 Pa). In addition to favorable temperatures, C 4 plants require sufficient precipitation during the warm growing season. C 4 plants which are predominantly graminoids of short stature can be competitively excluded by trees (nearly all C 3 plants) - regardless of the photosynthetic superiority of the C 4 pathway - in regions otherwise favorable for C 4 . To construct global maps of the distribution of C 4 grasses for current, past and future climate scenarios, we make use of climatological data sets which provide estimates of the mean monthly temperature to classify the globe into areas which should favor C 4 photosynthesis during at least 1 month of the year. This area is further screened by excluding areas where precipitation is <25 mm per month during the warm season and by selecting areas classified as grasslands (i.e., excluding areas dominated by woody vegetation) according to a global vegetation map. Using this approach, grasslands of the world are designated as C 3 , C 4 , and mixed under current climate and pCO 2 . Published floristic studies were used to test the accuracy of these predictions in many regions of the world, and agreement with observations was generally good. We then make use of this protocol to examine changes in the global abundance of C 4 grasses in the past and the future using plausible estimates for the climates and pCO 2 . When pCO 2 is lowered to pre-industrial levels, C 4 grasses expanded their range into large areas now classified as C 3 grasslands, especially in North America and Eurasia. During the last glacial maximum (∼18 ka BP) when the climate was cooler and pCO 2 was about 20 Pa, our analysis predicts substantial expansion of C 4 vegetation - particularly in Asia, despite cooler temperatures. Continued use of fossil fuels is expected to result in double the current pCO 2 by sometime in the next century, with some associated climate warming. Our analysis predicts a substantial reduction in the area of C 4 grasses under these conditions. These reductions from the past and into the future are based on greater stimulation of C 3 photosynthetic efficiency by higher pCO 2 than inhibition by higher temperatures. The predictions are testable through large-scale controlled growth studies and analysis of stable isotopes and other data from regions where large changes are predicted to have occurred.
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.
If We Can't Predict Solar Cycle 24, What About Solar Cycle 34?
NASA Technical Reports Server (NTRS)
Pesnell. William Dean
2008-01-01
Predictions of solar activity in Solar Cycle 24 range from 50% larger than SC 23 to the onset of a Grand Minimum. Because low levels of solar activity are associated with global cooling in paleoclimate and isotopic records, anticipating these extremes is required in any longterm extrapolation of climate variability. Climate models often look forward 100 or more years, which would mean 10 solar cycles into the future. Predictions of solar activity are derived from a number of methods, most of which, such as climatology and physics-based models, will be familiar to atmospheric scientists. More than 50 predictions of the maximum amplitude of SC 24 published before solar minimum will be discussed. Descriptions of several methods that result in the extreme predictions and some anticipation of even longer term predictions will be presented.
From local uncertainty to global predictions: Making predictions on fractal basins
2018-01-01
In nonlinear systems long term dynamics is governed by the attractors present in phase space. The presence of a chaotic saddle gives rise to basins of attraction with fractal boundaries and sometimes even to Wada boundaries. These two phenomena involve extreme difficulties in the prediction of the future state of the system. However, we show here that it is possible to make statistical predictions even if we do not have any previous knowledge of the initial conditions or the time series of the system until it reaches its final state. In this work, we develop a general method to make statistical predictions in systems with fractal basins. In particular, we have applied this new method to the Duffing oscillator for a choice of parameters where the system possesses the Wada property. We have computed the statistical properties of the Duffing oscillator for different phase space resolutions, to obtain information about the global dynamics of the system. The key idea is that the fraction of initial conditions that evolve towards each attractor is scale free—which we illustrate numerically. We have also shown numerically how having partial information about the initial conditions of the system does not improve in general the predictions in the Wada regions. PMID:29668687
Food for thought: food systems, livestock futures and animal health.
Wilkinson, Angela
2013-12-01
Global food security, livestock production and animal health are inextricably bound. However, our focus on the future tends to disaggregate food and health into largely separate domains. Indeed, much foresight work is either food systems or health-based with little overlap in terms of predictions or narratives. Work on animal health is no exception. Part of the problem is the fundamental misunderstanding of the role, nature and impact of the modern futures tool kit. Here, I outline three key issues in futures research ranging from methodological confusion over the application of scenarios to the failure to effectively integrate multiple methodologies to the gap between the need for more evidence and power and control over futures processes. At its core, however, a better understanding of the narrative and worldview framing much of the futures work in animal health is required to enhance the value and impact of such exercises.
Marçôa, Raquel; Rodrigues, Daniela Marta; Dias, Margarida; Ladeira, Inês; Vaz, Ana Paula; Lima, Ricardo; Guimarães, Miguel
2018-02-01
Chronic Obstructive Pulmonary Disease (COPD) is a major cause of morbidity and mortality worldwide. The Global Initiative for Chronic Obstructive Lung Disease (GOLD) project has been working to improve awareness, prevention and management of this disease. The aim of this study is to evaluate how COPD patients are reclassified by the 2017 GOLD system (versus GOLD 2011), to calculate the level of agreement between these two classifications in allocation to categories and to compare the performance of each classification to predict future exacerbations. Two-hundred COPD patients (>40 years, post bronchodilator forced expiratory volume in one second/forced vital capacity<0.7) followed in pulmonology consultation were recruited into this prospective multicentric study. Approximately half of the patients classified as GOLD D [2011] changed to GOLD B [2017]. The extent of agreement between GOLD 2011 and GOLD 2017 was moderate (Cohen's Kappa = 0.511; p < 0.001) and the ability to predict exacerbations was similar (69.7% and 67.6%, respectively). GOLD B [2017] exacerbated 17% more than GOLD B [2011] and had a lower percent predicted post bronchodilator forced expiratory volume in one second (FEV1). GOLD B [2017] turned to be the predominant category, more heterogeneous and with a higher risk of exacerbation versus GOLD B [2011]. Physicians should be cautious in assessing the GOLD B [2017] patients. The assessment of patients should always be personalized. More studies are needed to evaluate the impact of the 2017 reclassification in predicting outcomes such as future exacerbations and mortality.
How well do we succeed in modeling the global soil carbon pools?
NASA Astrophysics Data System (ADS)
Viskari, T.; Liski, J.
2017-12-01
Terrestrial carbon pools are a crucial part of the global carbon cycle. Carbon from vegetation is deposited to the soil, which in turn releases carbon dioxide back to the atmosphere through heterotrophic respiration. The resulting soil carbon storage in the largest on land. While there are continuous efforts to improve the modeling of global soil carbon and how this storage is affected by climate change, this research requires still a more reliable baseline on how well the models estimate the current global soil carbon pools. Especially such comparisons are important for identifying the major challenges in the current soil carbon models. Here, we used the Yasso soil carbon model to create a global soil carbon map at a 0.5 degree resolution based on the available climate, land cover and vegetation productivity information. Yasso model describes the soil carbon cycling by pools that represent the breaking down of dead organic matter. We compared the model results to a measurement based projection of global soil carbon pools, and we examined the differences and spatial correlations between the two maps. In our findings, the modelled predictions captured the overall soil carbon distributions within 5 kgCm-2 on 63 % of the land area. The spatial distributions fit each other as well. The average soil carbon is smaller with the Yasso prediction ( 8.5 kg m-2) than with the measurement map ( 10 kg m-2) and there are notable areas, such as Siberia and Southern North America, where there are large differences between the model predictions and measurements. These results not only encourage future development of soil carbon models, but also highlight problem areas to focus and improve upon.
NASA Astrophysics Data System (ADS)
Yang, B.; Lee, D. K.
2016-12-01
Understanding spatial distribution of irrigation requirement is critically important for agricultural water management. However, many studies considering future agricultural water management in Korea assessed irrigation requirement on watershed or administrative district scale, but have not accounted the spatial distribution. Lumped hydrologic model has typically used in Korea for simulating watershed scale irrigation requirement, while distribution hydrologic model can simulate the spatial distribution grid by grid. To overcome this shortcoming, here we applied a grid base global hydrologic model (H08) into local scale to estimate spatial distribution under future irrigation requirement of Korean Peninsula. Korea is one of the world's most densely populated countries, with also high produce and demand of rice which requires higher soil moisture than other crops. Although, most of the precipitation concentrate in particular season and disagree with crop growth season. This precipitation character makes management of agricultural water which is approximately 60% of total water usage critical issue in Korea. Furthermore, under future climate change, the precipitation predicted to be more concentrated and necessary need change of future water management plan. In order to apply global hydrological model into local scale, we selected appropriate major crops under social and local climate condition in Korea to estimate cropping area and yield, and revised the cropping area map more accurately. As a result, future irrigation requirement estimation varies under each projection, however, slightly decreased in most case. The simulation reveals, evapotranspiration increase slightly while effective precipitation also increase to balance the irrigation requirement. This finding suggest practical guideline to decision makers for further agricultural water management plan including future development of water supply plan to resolve water scarcity.
Life-history theory and climate change: resolving population and parental investment paradoxes.
Caudell, Mark; Quinlan, Robert
2016-11-01
Population growth in the next half-century is on pace to raise global carbon emissions by half. Carbon emissions are associated with fertility as a by-product of somatic and parental investment, which is predicted to involve time orientation/preference as a mediating psychological mechanism. Here, we draw upon life-history theory (LHT) to investigate associations between future orientation and fertility, and their impacts on carbon emissions. We argue ' K -strategy' life history (LH) in high-income countries has resulted in parental investment behaviours involving future orientation that, paradoxically, promote unsustainable carbon emissions, thereby lowering the Earth's K or carrying capacity. Increasing the rate of approach towards this capacity are ' r -strategy' LHs in low-income countries that promote population growth. We explore interactions between future orientation and development that might slow the rate of approach towards global K . Examination of 67 000 individuals across 75 countries suggests that future orientation interacts with the relationship between environmental risk and fertility and with development related parental investment, particularly investment in higher education, to slow population growth and mitigate per capita carbon emissions. Results emphasize that LHT will be an important tool in understanding the demographic and consumption patterns that drive anthropogenic climate change.
Extreme Events and Disaster Risk Reduction - a Future Earth KAN initiative
NASA Astrophysics Data System (ADS)
Frank, Dorothea; Reichstein, Markus
2017-04-01
The topic of Extreme Events in the context of global environmental change is both a scientifically challenging and exciting topic, and of very high societal relevance. The Future Earth Cluster initiative E3S organized in 2016 a cross-community/co-design workshop on Extreme Events and Environments from Climate to Society (http://www.e3s-future-earth.eu/index.php/ConferencesEvents/ConferencesAmpEvents). Based on the results, co-design research strategies and established network of the workshop, and previous activities, E3S is thriving to establish the basis for a longer-term research effort under the umbrella of Future Earth. These led to an initiative for a Future Earth Knowledge Action Network on Extreme Events and Disaster Risk Reduction. Example initial key question in this context include: What are meaningful indices to describe and quantify impact-relevant (e.g. climate) extremes? Which system properties yield resistance and resilience to extreme conditions? What are the key interactions between global urbanization processes, extreme events, and social and infrastructure vulnerability and resilience? The long-term goal of this KAN is to contribute to enhancing the resistance, resilience, and adaptive capacity of socio-ecological systems across spatial, temporal and institutional scales, in particular in the light of hazards affected by ongoing environmental change (e.g. climate change, global urbanization and land use/land cover change). This can be achieved by enhanced understanding, prediction, improved and open data and knowledge bases for detection and early warning decision making, and by new insights on natural and societal conditions and governance for resilience and adaptive capacity.
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
Kolanowska, Marta; Kras, Marta; Lipińska, Monika; Mystkowska, Katarzyna; Szlachetko, Dariusz L; Naczk, Aleksandra M
2017-10-05
Current and expected changes in global climate are major threat for biological diversity affecting individuals, communities and ecosystems. However, there is no general trend in the plants response to the climate change. The aim of present study was to evaluate impact of the future climate changes on the distribution of holomycotrophic orchid species using ecological niche modeling approach. Three different scenarios of future climate changes were tested to obtain the most comprehensive insight in the possible habitat loss of 16 holomycotrophic orchids. The extinction of Cephalanthera austiniae was predicted in all analyses. The coverage of suitable niches of Pogoniopsis schenckii will decrease to 1-30% of its current extent. The reduction of at least 50% of climatic niche of Erythrorchis cassythoides and Limodorum abortivum will be observed. In turn, the coverage of suitable niches of Hexalectris spicata, Uleiorchis ulaei and Wullschlaegelia calcarata may be even 16-74 times larger than in the present time. The conducted niche modeling and analysis of the similarity of their climatic tolerance showed instead that the future modification of the coverage of their suitable niches will not be unified and the future climate changes may be not so harmful for holomycotrophic orchids as expected.
Bedrock Erosion Surfaces Record Former East Antarctic Ice Sheet Extent
NASA Astrophysics Data System (ADS)
Paxman, Guy J. G.; Jamieson, Stewart S. R.; Ferraccioli, Fausto; Bentley, Michael J.; Ross, Neil; Armadillo, Egidio; Gasson, Edward G. W.; Leitchenkov, German; DeConto, Robert M.
2018-05-01
East Antarctica hosts large subglacial basins into which the East Antarctic Ice Sheet (EAIS) likely retreated during past warmer climates. However, the extent of retreat remains poorly constrained, making quantifying past and predicted future contributions to global sea level rise from these marine basins challenging. Geomorphological analysis and flexural modeling within the Wilkes Subglacial Basin are used to reconstruct the ice margin during warm intervals of the Oligocene-Miocene. Flat-lying bedrock plateaus are indicative of an ice sheet margin positioned >400-500 km inland of the modern grounding zone for extended periods of the Oligocene-Miocene, equivalent to a 2-m rise in global sea level. Our findings imply that if major EAIS retreat occurs in the future, isostatic rebound will enable the plateau surfaces to act as seeding points for extensive ice rises, thus limiting extensive ice margin retreat of the scale seen during the early EAIS.
Ocean deoxygenation in a warming world.
Keeling, Ralph E; Körtzinger, Arne; Gruber, Nicolas
2010-01-01
Ocean warming and increased stratification of the upper ocean caused by global climate change will likely lead to declines in dissolved O2 in the ocean interior (ocean deoxygenation) with implications for ocean productivity, nutrient cycling, carbon cycling, and marine habitat. Ocean models predict declines of 1 to 7% in the global ocean O2 inventory over the next century, with declines continuing for a thousand years or more into the future. An important consequence may be an expansion in the area and volume of so-called oxygen minimum zones, where O2 levels are too low to support many macrofauna and profound changes in biogeochemical cycling occur. Significant deoxygenation has occurred over the past 50 years in the North Pacific and tropical oceans, suggesting larger changes are looming. The potential for larger O2 declines in the future suggests the need for an improved observing system for tracking ocean 02 changes.
DOE unveils climate model in advance of global test
NASA Astrophysics Data System (ADS)
Popkin, Gabriel
2018-05-01
The world's growing collection of climate models has a high-profile new entry. Last week, after nearly 4 years of work, the U.S. Department of Energy (DOE) released computer code and initial results from an ambitious effort to simulate the Earth system. The new model is tailored to run on future supercomputers and designed to forecast not just how climate will change, but also how those changes might stress energy infrastructure. Results from an upcoming comparison of global models may show how well the new entrant works. But so far it is getting a mixed reception, with some questioning the need for another model and others saying the $80 million effort has yet to improve predictions of the future climate. Even the project's chief scientist, Ruby Leung of the Pacific Northwest National Laboratory in Richland, Washington, acknowledges that the model is not yet a leader.
Range-expanding pests and pathogens in a warming world.
Bebber, Daniel Patrick
2015-01-01
Crop pests and pathogens (CPPs) present a growing threat to food security and ecosystem management. The interactions between plants and their natural enemies are influenced by environmental conditions and thus global warming and climate change could affect CPP ranges and impact. Observations of changing CPP distributions over the twentieth century suggest that growing agricultural production and trade have been most important in disseminating CPPs, but there is some evidence for a latitudinal bias in range shifts that indicates a global warming signal. Species distribution models using climatic variables as drivers suggest that ranges will shift latitudinally in the future. The rapid spread of the Colorado potato beetle across Eurasia illustrates the importance of evolutionary adaptation, host distribution, and migration patterns in affecting the predictions of climate-based species distribution models. Understanding species range shifts in the framework of ecological niche theory may help to direct future research needs.
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.
The MJO-SSW Teleconnection: Interaction Between MJO-Forced Waves and the Midlatitude Jet
NASA Astrophysics Data System (ADS)
Kang, Wanying; Tziperman, Eli
2018-05-01
The Madden-Julian Oscillation (MJO) was shown to affect both present-day sudden stratospheric warming (SSW) events in the Arctic and their future frequency under global warming scenarios, with implications to the Arctic Oscillation and midlatitude extreme weather. This work uses a dry dynamic core model to understand the dependence of SSW frequency on the amplitude and longitudinal range of the MJO, motivated by the prediction that the MJO will strengthen and broaden its longitudinal range in a warmer climate. We focus on the response of the midlatitude jets and the corresponding generated stationary waves, which are shown to dominate the response of SSW events to MJO forcing. Momentum budget analysis of a large ensemble of spinup simulations suggests that the climatological jet response is driven by the MJO-forced meridional eddy momentum transport. The results suggest that the trends in both MJO amplitude and longitudinal range are important for the prediction of the midlatitude jet response and for the prediction of SSWs in a future climate.
Large-scale Modeling of Nitrous Oxide Production: Issues of Representing Spatial Heterogeneity
NASA Astrophysics Data System (ADS)
Morris, C. K.; Knighton, J.
2017-12-01
Nitrous oxide is produced from the biological processes of nitrification and denitrification in terrestrial environments and contributes to the greenhouse effect that warms Earth's climate. Large scale modeling can be used to determine how global rate of nitrous oxide production and consumption will shift under future climates. However, accurate modeling of nitrification and denitrification is made difficult by highly parameterized, nonlinear equations. Here we show that the representation of spatial heterogeneity in inputs, specifically soil moisture, causes inaccuracies in estimating the average nitrous oxide production in soils. We demonstrate that when soil moisture is averaged from a spatially heterogeneous surface, net nitrous oxide production is under predicted. We apply this general result in a test of a widely-used global land surface model, the Community Land Model v4.5. The challenges presented by nonlinear controls on nitrous oxide are highlighted here to provide a wider context to the problem of extraordinary denitrification losses in CLM. We hope that these findings will inform future researchers on the possibilities for model improvement of the global nitrogen cycle.
Terrestrial basking sea turtles are responding to spatio-temporal sea surface temperature patterns.
Van Houtan, Kyle S; Halley, John M; Marks, Wendy
2015-01-01
Naturalists as early as Darwin observed terrestrial basking in green turtles (Chelonia mydas), but the distribution and environmental influences of this behaviour are poorly understood. Here, we examined 6 years of daily basking surveys in Hawaii and compared them with the phenology of local sea surface temperatures (SST). Data and models indicated basking peaks when SST is coolest, and we found this timeline consistent with bone stress markings. Next, we assessed the decadal SST profiles for the 11 global green turtle populations. Basking generally occurs when winter SST falls below 23°C. From 1990 to 2014, the SST for these populations warmed an average 0.04°C yr(-1) (range 0.01-0.09°C yr(-1)); roughly three times the observed global average over this period. Owing to projected future warming at basking sites, we estimated terrestrial basking in green turtles may cease globally by 2100. To predict and manage for future climate change, we encourage a more detailed understanding for how climate influences organismal biology. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Terrestrial basking sea turtles are responding to spatio-temporal sea surface temperature patterns
Van Houtan, Kyle S.; Halley, John M.; Marks, Wendy
2015-01-01
Naturalists as early as Darwin observed terrestrial basking in green turtles (Chelonia mydas), but the distribution and environmental influences of this behaviour are poorly understood. Here, we examined 6 years of daily basking surveys in Hawaii and compared them with the phenology of local sea surface temperatures (SST). Data and models indicated basking peaks when SST is coolest, and we found this timeline consistent with bone stress markings. Next, we assessed the decadal SST profiles for the 11 global green turtle populations. Basking generally occurs when winter SST falls below 23°C. From 1990 to 2014, the SST for these populations warmed an average 0.04°C yr−1 (range 0.01–0.09°C yr−1); roughly three times the observed global average over this period. Owing to projected future warming at basking sites, we estimated terrestrial basking in green turtles may cease globally by 2100. To predict and manage for future climate change, we encourage a more detailed understanding for how climate influences organismal biology. PMID:25589483
A Review of Current Investigations of Urban-Induced Rainfall and Recommendations for the Future
NASA Technical Reports Server (NTRS)
Shepherd, J. Marshall
2004-01-01
Precipitation is a key link in the global water cycle and a proxy for changing climate; therefore proper assessment of the urban environment s impact on precipitation (land use, aerosols, thermal properties) will be increasingly important in ongoing climate diagnostics and prediction, Global Water and Energy Cycle (GWEC) analysis and modeling, weather forecasting, freshwater resource management, urban planning-design and land-atmosphere-ocean interface processes. These facts are particularly critical if current projections for global urban growth are accurate. The goal of this paper is to provide a concise review of recent (1990-present) studies related to how the urban environment affects precipitation. In addition to providing a synopsis of current work, recent findings are placed in context with historical investigations such as METROMEX studies. Both observational and modeling studies of urban-induced rainfall are discussed. Additionally, a discussion of the relative roles of urban dynamic and microphysical (e.g. aerosol) processes is presented. The paper closes with a set of recommendations for what observations and capabilities are needed in the future to advance our understanding of the processes.
Komatsu, Teruhisa; Fukuda, Masahiro; Mikami, Atsuko; Mizuno, Shizuha; Kantachumpoo, Attachai; Tanoue, Hideaki; Kawamiya, Michio
2014-08-30
Global warming effects on seaweed beds are already perceptible. Their geographical distributions greatly depend on water temperatures. To predict future geographical distributions of brown alga, Sargassum horneri, forming large beds in the northwestern Pacific, we referred to future monthly surface water temperatures at about 1.1° of longitude and 0.6° of latitude in February and August in 2050 and 2100 simulated by 12 organizations under an A2 scenario of global warming. The southern limit of S. horneri distribution is expected to keep moving northward such that it may broadly disappear from Honshu Island, the Chinese coast, and Korean Peninsula in 2100, when tropical Sargassum species such as Sargassum tenuifolium may not completely replace S. horneri. Thus, their forests in 2100 do not substitute those of S. horneri in 2000. Fishes using the beds and seaweed rafts consisting of S. horneri in East China Sea suffer these disappearances. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.
NASA Technical Reports Server (NTRS)
Bauer, Frank H.; Dennehy, Neil
2015-01-01
A retrospective consideration of two 15-year old Guidance, Navigation and Control (GN&C) technology 'vision' predictions will be the focus of this paper. A look back analysis and critique of these late 1990s technology roadmaps out-lining the future vision, for two then nascent, but rapidly emerging, GN&C technologies will be performed. Specifically, these two GN&C technologies were: 1) multi-spacecraft formation flying and 2) the spaceborne use and exploitation of global positioning system (GPS) signals to enable formation flying. This paper reprises the promise of formation flying and spaceborne GPS as depicted in the cited 1999 and 1998 papers. It will discuss what happened to cause that promise to be mostly unfulfilled and the reasons why the envisioned formation flying dream has yet to become a reality. The recent technology trends over the past few years will then be identified and a renewed government interest in spacecraft formation flying/cluster flight will be highlighted. The authors will conclude with a reality-tempered perspective, 15 years after the initial technology roadmaps were published, predicting a promising future of spacecraft formation flying technology development over the next decade.
Modified-Fibonacci-Dual-Lucas method for earthquake prediction
NASA Astrophysics Data System (ADS)
Boucouvalas, A. C.; Gkasios, M.; Tselikas, N. T.; Drakatos, G.
2015-06-01
The FDL method makes use of Fibonacci, Dual and Lucas numbers and has shown considerable success in predicting earthquake events locally as well as globally. Predicting the location of the epicenter of an earthquake is one difficult challenge the other being the timing and magnitude. One technique for predicting the onset of earthquakes is the use of cycles, and the discovery of periodicity. Part of this category is the reported FDL method. The basis of the reported FDL method is the creation of FDL future dates based on the onset date of significant earthquakes. The assumption being that each occurred earthquake discontinuity can be thought of as a generating source of FDL time series The connection between past earthquakes and future earthquakes based on FDL numbers has also been reported with sample earthquakes since 1900. Using clustering methods it has been shown that significant earthquakes (<6.5R) can be predicted with very good accuracy window (+-1 day). In this contribution we present an improvement modification to the FDL method, the MFDL method, which performs better than the FDL. We use the FDL numbers to develop possible earthquakes dates but with the important difference that the starting seed date is a trigger planetary aspect prior to the earthquake. Typical planetary aspects are Moon conjunct Sun, Moon opposite Sun, Moon conjunct or opposite North or South Modes. In order to test improvement of the method we used all +8R earthquakes recorded since 1900, (86 earthquakes from USGS data). We have developed the FDL numbers for each of those seeds, and examined the earthquake hit rates (for a window of 3, i.e. +-1 day of target date) and for <6.5R. The successes are counted for each one of the 86 earthquake seeds and we compare the MFDL method with the FDL method. In every case we find improvement when the starting seed date is on the planetary trigger date prior to the earthquake. We observe no improvement only when a planetary trigger coincided with the earthquake date and in this case the FDL method coincides with the MFDL. Based on the MDFL method we present the prediction method capable of predicting global events or localized earthquakes and we will discuss the accuracy of the method in as far as the prediction and location parts of the method. We show example calendar style predictions for global events as well as for the Greek region using planetary alignment seeds.
Projected shifts in fish species dominance in Wisconsin lakes under climate change
Hansen, Gretchen JA; Read, Jordan S.; Hansen, Jonathan F.; Winslow, Luke
2016-01-01
Temperate lakes may contain both coolwater fish species such as walleye (Sander vitreus) and warmwater fish species such as largemouth bass (Micropterus salmoides). Recent declining walleye and increasing largemouth bass populations have raised questions regarding the future trajectories and management actions for these species. We developed a thermodynamic model of water temperatures driven by downscaled climate data and lake-specific characteristics to estimate daily water temperature profiles for 2148 lakes in Wisconsin, US, under contemporary (1989–2014) and future (2040–2064 and 2065–2089) conditions. We correlated contemporary walleye recruitment and largemouth bass relative abundance to modeled water temperature, lake morphometry, and lake productivity, and projected lake-specific changes in each species under future climate conditions. Walleye recruitment success was negatively related and largemouth bass abundance was positively related to water temperature degree days. Both species exhibited a threshold response at the same degree day value, albeit in opposite directions. Degree days were predicted to increase in the future, although the magnitude of increase varied among lakes, time periods, and global circulation models (GCMs). Under future conditions, we predicted a loss of walleye recruitment in 33–75% of lakes where recruitment is currently supported and a 27–60% increase in the number of lakes suitable for high largemouth bass abundance. The percentage of lakes capable of supporting abundant largemouth bass but failed walleye recruitment was predicted to increase from 58% in contemporary conditions to 86% by mid-century and to 91% of lakes by late century, based on median projections across GCMs. Conversely, the percentage of lakes with successful walleye recruitment and low largemouth bass abundance was predicted to decline from 9% of lakes in contemporary conditions to only 1% of lakes in both future periods. Importantly, we identify up to 85 resilient lakes predicted to continue to support natural walleye recruitment. Management resources could target preserving these resilient walleye populations.
Biodiversity response to natural gradients of multiple stressors on continental margins
Sperling, Erik A.; Frieder, Christina A.; Levin, Lisa A.
2016-01-01
Sharp increases in atmospheric CO2 are resulting in ocean warming, acidification and deoxygenation that threaten marine organisms on continental margins and their ecological functions and resulting ecosystem services. The relative influence of these stressors on biodiversity remains unclear, as well as the threshold levels for change and when secondary stressors become important. One strategy to interpret adaptation potential and predict future faunal change is to examine ecological shifts along natural gradients in the modern ocean. Here, we assess the explanatory power of temperature, oxygen and the carbonate system for macrofaunal diversity and evenness along continental upwelling margins using variance partitioning techniques. Oxygen levels have the strongest explanatory capacity for variation in species diversity. Sharp drops in diversity are seen as O2 levels decline through the 0.5–0.15 ml l−1 (approx. 22–6 µM; approx. 21–5 matm) range, and as temperature increases through the 7–10°C range. pCO2 is the best explanatory variable in the Arabian Sea, but explains little of the variance in diversity in the eastern Pacific Ocean. By contrast, very little variation in evenness is explained by these three global change variables. The identification of sharp thresholds in ecological response are used here to predict areas of the seafloor where diversity is most at risk to future marine global change, noting that the existence of clear regional differences cautions against applying global thresholds. PMID:27122565
Characteristic mega-basin water storage behavior using GRACE.
Reager, J T; Famiglietti, James S
2013-06-01
[1] A long-standing challenge for hydrologists has been a lack of observational data on global-scale basin hydrological behavior. With observations from NASA's Gravity Recovery and Climate Experiment (GRACE) mission, hydrologists are now able to study terrestrial water storage for large river basins (>200,000 km 2 ), with monthly time resolution. Here we provide results of a time series model of basin-averaged GRACE terrestrial water storage anomaly and Global Precipitation Climatology Project precipitation for the world's largest basins. We address the short (10 year) length of the GRACE record by adopting a parametric spectral method to calculate frequency-domain transfer functions of storage response to precipitation forcing and then generalize these transfer functions based on large-scale basin characteristics, such as percent forest cover and basin temperature. Among the parameters tested, results show that temperature, soil water-holding capacity, and percent forest cover are important controls on relative storage variability, while basin area and mean terrain slope are less important. The derived empirical relationships were accurate (0.54 ≤ E f ≤ 0.84) in modeling global-scale water storage anomaly time series for the study basins using only precipitation, average basin temperature, and two land-surface variables, offering the potential for synthesis of basin storage time series beyond the GRACE observational period. Such an approach could be applied toward gap filling between current and future GRACE missions and for predicting basin storage given predictions of future precipitation.
An analysis of human-induced land transformations in the San Francisco Bay/Sacramento area
Kirtland, David A.; Gaydos, L.J.; Clarke, Keith; DeCola, Lee; Acevedo, William; Bell, Cindy
1994-01-01
Part of the U.S. Geological Survey's Global Change Research Program involvesstudying the area from the Pacific Ocean to the Sierra foothills to enhance understanding ofthe role that human activities play in global change. The study investigates the ways thathumans transform the land and the effects that changing the landscape may have on regionaland global systems. To accomplish this research, scientists are compiling records ofhistorical transformations in the region's land cover over the last 140 years, developing asimulation model to predict land cover change, and assembling a digital data set to analyzeand describe land transformations. The historical data regarding urban growth focusattention on the significant change the region underwent from 1850 to 1990. Animation isused to visualize a time series of the change in land cover. The historical change is beingused to calibrate a prototype cellular automata model, developed to predict changes in urbanland cover 100 years into the future. Future urban growth scenarios will be developed foranalyzing possible human-induced impacts on land cover at a regional scale. These data aidin documenting and understanding human-induced land transformations from both historical andpredictive perspectives. A descriptive analysis of the region is used to investigate therelationships among data characteristic of the region. These data consist of multilayertopography, climate, vegetation, and population data for a 256-km2 region of centralCalifornia. A variety of multivariate analysis tools are used to integrate the data inraster format from map contours, interpolated climate observations, satellite observations,and population estimates.
Mo isotopes as redox indicators for the Southern Tethys during the PETM
NASA Astrophysics Data System (ADS)
Wouters, H.; Dickson, A.; Porcelli, D.; Hesselbo, S. P.; van den Boorn, S.; Gomez, V. G.; Mutterlose, J.
2014-12-01
As several ocean and climate models predict a decline in dissolved ocean oxygen concentrations associated with future global warming [1], recent research is increasingly focusing on past episodes of low ocean oxygen levels. Trace metals are generally enriched in organic-rich sediments deposited under such low oxygen conditions, and the concentration and isotopic signatures of several of these elements (e.g. Mo, U, Cr) may be applied as proxies to reconstruct the processes involved in these redox changes [2,3]. This project investigates the use of the molybdenum isotope system as a proxy for redox changes during an interval of abrupt environmental change spanning the Paleocene/Eocene boundary (the Paleocene/Eocene Thermal Maximum, PETM, ~56 Ma). The PETM is characterized by global warming and environmental and ecological changes including decreased ocean oxygen levels [4]. Study of the PETM can therefore offer us a valuable insight into how marine ecosystems and biogeochemical cycles may respond to future climate changes, and the predicted decrease of oxygen concentrations in seawater. The molybdenum concentrations and isotope compositions of organic-rich sediments spanning the PETM have been obtained from a Jordan oil shale drill core (OS-28). The obtained δ98/95Mo isotopic ratios range between -0.12‰ and 1.59‰ and coincide with significant fluctuations in trace metal abundances. The data together demonstrate that the global environmental changes associated with the PETM were manifest in the Jordanian basin as significant changes in basin hydrography and dissolved oxygen levels.
Characteristic mega-basin water storage behavior using GRACE
Reager, J T; Famiglietti, James S
2013-01-01
[1] A long-standing challenge for hydrologists has been a lack of observational data on global-scale basin hydrological behavior. With observations from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission, hydrologists are now able to study terrestrial water storage for large river basins (>200,000 km2), with monthly time resolution. Here we provide results of a time series model of basin-averaged GRACE terrestrial water storage anomaly and Global Precipitation Climatology Project precipitation for the world’s largest basins. We address the short (10 year) length of the GRACE record by adopting a parametric spectral method to calculate frequency-domain transfer functions of storage response to precipitation forcing and then generalize these transfer functions based on large-scale basin characteristics, such as percent forest cover and basin temperature. Among the parameters tested, results show that temperature, soil water-holding capacity, and percent forest cover are important controls on relative storage variability, while basin area and mean terrain slope are less important. The derived empirical relationships were accurate (0.54 ≤ Ef ≤ 0.84) in modeling global-scale water storage anomaly time series for the study basins using only precipitation, average basin temperature, and two land-surface variables, offering the potential for synthesis of basin storage time series beyond the GRACE observational period. Such an approach could be applied toward gap filling between current and future GRACE missions and for predicting basin storage given predictions of future precipitation. PMID:24563556
Global reductions in seafloor biomass in response to climate change.
Jones, Daniel O B; Yool, Andrew; Wei, Chih-Lin; Henson, Stephanie A; Ruhl, Henry A; Watson, Reg A; Gehlen, Marion
2014-06-01
Seafloor organisms are vital for healthy marine ecosystems, contributing to elemental cycling, benthic remineralization, and ultimately sequestration of carbon. Deep-sea life is primarily reliant on the export flux of particulate organic carbon from the surface ocean for food, but most ocean biogeochemistry models predict global decreases in export flux resulting from 21st century anthropogenically induced warming. Here we show that decadal-to-century scale changes in carbon export associated with climate change lead to an estimated 5.2% decrease in future (2091-2100) global open ocean benthic biomass under RCP8.5 (reduction of 5.2 Mt C) compared with contemporary conditions (2006-2015). Our projections use multi-model mean export flux estimates from eight fully coupled earth system models, which contributed to the Coupled Model Intercomparison Project Phase 5, that have been forced by high and low representative concentration pathways (RCP8.5 and 4.5, respectively). These export flux estimates are used in conjunction with published empirical relationships to predict changes in benthic biomass. The polar oceans and some upwelling areas may experience increases in benthic biomass, but most other regions show decreases, with up to 38% reductions in parts of the northeast Atlantic. Our analysis projects a future ocean with smaller sized infaunal benthos, potentially reducing energy transfer rates though benthic multicellular food webs. More than 80% of potential deep-water biodiversity hotspots known around the world, including canyons, seamounts, and cold-water coral reefs, are projected to experience negative changes in biomass. These major reductions in biomass may lead to widespread change in benthic ecosystems and the functions and services they provide. © 2013 The Authors Global Change Biology Published by John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Sanyal, S.; Wuebbles, D. J.
2017-12-01
In this study, the focus is on how global changes in climate and emissions will affect the U.S. air quality, especially on fine particulate matter and ozone, projecting their future trends and quantifying key source attribution. We are conducting three primary experiments : (1) historical simulations for period 1994-2013 to establish the credibility of the system and refine process-level understanding of U.S. regional air quality; (2) projections for period 2041-2060 to quantify individual and combined impacts of global climate and emissions changes under multiple scenarios; (3) sensitivity analyses to determine future changes in pollution sources and their relative contributions from anthropogenic and natural emissions, long-range pollutant transport, and climate change effects. Here we will present the result from the first experiment with the global model CESM1.2 (with fully coupled chemistry using CAM-chem5) driven by NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) reanalysis data at 0.9o x 1.25o resolution. We will present the comparison between the results from model simulation with observation data from EPA database. Since there is always a challenge in comparing gridded prediction from model data with point data from the observation databases, because the model simulations calculate the average outcome over a grid for a given set of conditions while the stochastic component (e.g. sub-grid variations) embedded in the observations are not accounted for, we are using extensive statistical measure to do the comparison. We will also determine relative contributions from multiscale (local, regional, global) processes, major source regions (Mexico, Canada, Asia, Africa) and types (natural, anthropogenic) and associated uncertainties (climate decadal oscillations/interannual variations, emissions and model structure errors).
Farrer, Emily C; Ashton, Isabel W; Knape, Jonas; Suding, Katharine N
2014-04-01
Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be added to our toolbox to tease apart complex drivers of global change. © 2013 John Wiley & Sons Ltd.
Mishra, U.; Jastrow, J.D.; Matamala, R.; Hugelius, G.; Koven, C.D.; Harden, Jennifer W.; Ping, S.L.; Michaelson, G.J.; Fan, Z.; Miller, R.M.; McGuire, A.D.; Tarnocai, C.; Kuhry, P.; Riley, W.J.; Schaefer, K.; Schuur, E.A.G.; Jorgenson, M.T.; Hinzman, L.D.
2013-01-01
The vast amount of organic carbon (OC) stored in soils of the northern circumpolar permafrost region is a potentially vulnerable component of the global carbon cycle. However, estimates of the quantity, decomposability, and combustibility of OC contained in permafrost-region soils remain highly uncertain, thereby limiting our ability to predict the release of greenhouse gases due to permafrost thawing. Substantial differences exist between empirical and modeling estimates of the quantity and distribution of permafrost-region soil OC, which contribute to large uncertainties in predictions of carbon–climate feedbacks under future warming. Here, we identify research challenges that constrain current assessments of the distribution and potential decomposability of soil OC stocks in the northern permafrost region and suggest priorities for future empirical and modeling studies to address these challenges.
DeLong, John P; Burger, Oskar; Hamilton, Marcus J
2010-10-05
Influential demographic projections suggest that the global human population will stabilize at about 9-10 billion people by mid-century. These projections rest on two fundamental assumptions. The first is that the energy needed to fuel development and the associated decline in fertility will keep pace with energy demand far into the future. The second is that the demographic transition is irreversible such that once countries start down the path to lower fertility they cannot reverse to higher fertility. Both of these assumptions are problematic and may have an effect on population projections. Here we examine these assumptions explicitly. Specifically, given the theoretical and empirical relation between energy-use and population growth rates, we ask how the availability of energy is likely to affect population growth through 2050. Using a cross-country data set, we show that human population growth rates are negatively related to per-capita energy consumption, with zero growth occurring at ∼13 kW, suggesting that the global human population will stop growing only if individuals have access to this amount of power. Further, we find that current projected future energy supply rates are far below the supply needed to fuel a global demographic transition to zero growth, suggesting that the predicted leveling-off of the global population by mid-century is unlikely to occur, in the absence of a transition to an alternative energy source. Direct consideration of the energetic constraints underlying the demographic transition results in a qualitatively different population projection than produced when the energetic constraints are ignored. We suggest that energetic constraints be incorporated into future population projections.
Questions raised over future of UK research council
NASA Astrophysics Data System (ADS)
Banks, Michael
2010-02-01
Five senior physicists have written to the UK science minister, Lord Drayson, about the "dismal future" for researchers in the country in the wake of a £40m shortfall in the budget of the Science and Technology Facilities Council (STFC). The physicists, who chair the STFC's five advisory panels, have also called for structural reforms to be made to the council. They warn that unless the government takes action to reverse the situation, the UK will be "perceived as an untrustworthy partner in global projects" and predict that a brain drain of the best UK scientists to positions overseas will ensue.
Assis, Jorge; Lucas, Ana Vaz; Bárbara, Ignacio; Serrão, Ester Álvares
2016-02-01
Global climate change is shifting species distributions worldwide. At rear edges (warmer, low latitude range margins), the consequences of small variations in environmental conditions can be magnified, producing large negative effects on species ranges. A major outcome of shifts in distributions that only recently received attention is the potential to reduce the levels of intra-specific diversity and consequently the global evolutionary and adaptive capacity of species to face novel disturbances. This is particularly important for low dispersal marine species, such as kelps, that generally retain high and unique genetic diversity at rear ranges resulting from long-term persistence, while ranges shifts during climatic glacial/interglacial cycles. Using ecological niche modelling, we (1) infer the major environmental forces shaping the distribution of a cold-temperate kelp, Laminaria hyperborea (Gunnerus) Foslie, and we (2) predict the effect of past climate changes in shaping regions of long-term persistence (i.e., climatic refugia), where this species might hypothetically harbour higher genetic diversity given the absence of bottlenecks and local extinctions over the long term. We further (3) assessed the consequences of future climate for the fate of L. hyperborea using different scenarios of greenhouse gas emissions (RCP 2.6 and RCP 8.5). Results show NW Iberia, SW Ireland and W English Channel, Faroe Islands and S Iceland, as regions where L. hyperborea may have persisted during past climate extremes until present day. All predictions for the future showed expansions to northern territories coupled with the significant loss of suitable habitats at low latitude range margins, where long-term persistence was inferred (e.g., NW Iberia). This pattern was particularly evident in the most agressive scenario of climate change (RCP 8.5), likely driving major biodiversity loss, changes in ecosystem functioning and the impoverishment of the global gene pool of L. hyperborea. Because no genetic baseline is currently available for this species, our results may represent a first step in informing conservation and mitigation strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.
King, David A.; Bachelet, Dominique M.; Symstad, Amy J.
2013-01-01
Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.
King, David A; Bachelet, Dominique M; Symstad, Amy J
2013-12-01
Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine-prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.
King, David A; Bachelet, Dominique M; Symstad, Amy J
2013-01-01
Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects. PMID:24455138
Global fish production and climate change
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brander, K.M.
2007-12-11
Current global fisheries production of {approx}160 million tons is rising as a result of increases in aquaculture production. A number of climate-related threats to both capture fisheries and aquaculture are identified, but there is low confidence in predictions of future fisheries production because of uncertainty over future global aquatic net primary production and the transfer of this production through the food chain to human consumption. Recent changes in the distribution and productivity of a number of fish species can be ascribed with high confidence to regional climate variability, such as the El Nino-Southern Oscillation. Future production may increase in somemore » high-latitude regions because of warming and decreased ice cover, but the dynamics in low-latitude regions are giverned by different processes, and production may decline as a result of reduced vertical mixing of the water column and, hence, reduced recycling of nutrients. There are strong interactions between the effects of fishing and the effects of climate because fishing reduces the age, size, and geographic diversity of populations and the biodiversity of marine ecosystems, making both more sensitive to additional stresses such as climate change. Inland fisheries are additionally threatened by changes in precipiation and water management. The frequency and intensity of extreme climate events is likely to have a major impact on future fisheries production in both inland and marine systems. Reducing fishing mortality in the majority of fisheries, which are currently fully exploited or overexploited, is the pricipal feasible means of reducing the impacts of climate change.« less
Global skin colour prediction from DNA.
Walsh, Susan; Chaitanya, Lakshmi; Breslin, Krystal; Muralidharan, Charanya; Bronikowska, Agnieszka; Pospiech, Ewelina; Koller, Julia; Kovatsi, Leda; Wollstein, Andreas; Branicki, Wojciech; Liu, Fan; Kayser, Manfred
2017-07-01
Human skin colour is highly heritable and externally visible with relevance in medical, forensic, and anthropological genetics. Although eye and hair colour can already be predicted with high accuracies from small sets of carefully selected DNA markers, knowledge about the genetic predictability of skin colour is limited. Here, we investigate the skin colour predictive value of 77 single-nucleotide polymorphisms (SNPs) from 37 genetic loci previously associated with human pigmentation using 2025 individuals from 31 global populations. We identified a minimal set of 36 highly informative skin colour predictive SNPs and developed a statistical prediction model capable of skin colour prediction on a global scale. Average cross-validated prediction accuracies expressed as area under the receiver-operating characteristic curve (AUC) ± standard deviation were 0.97 ± 0.02 for Light, 0.83 ± 0.11 for Dark, and 0.96 ± 0.03 for Dark-Black. When using a 5-category, this resulted in 0.74 ± 0.05 for Very Pale, 0.72 ± 0.03 for Pale, 0.73 ± 0.03 for Intermediate, 0.87±0.1 for Dark, and 0.97 ± 0.03 for Dark-Black. A comparative analysis in 194 independent samples from 17 populations demonstrated that our model outperformed a previously proposed 10-SNP-classifier approach with AUCs rising from 0.79 to 0.82 for White, comparable at the intermediate level of 0.63 and 0.62, respectively, and a large increase from 0.64 to 0.92 for Black. Overall, this study demonstrates that the chosen DNA markers and prediction model, particularly the 5-category level; allow skin colour predictions within and between continental regions for the first time, which will serve as a valuable resource for future applications in forensic and anthropologic genetics.
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
Capital death in the world market
NASA Astrophysics Data System (ADS)
Avakian, Adam; Podobnik, Boris; Piskor, Manuela; Stanley, H. Eugene
2014-03-01
We study the gross domestic product (GDP) per capita together with the market capitalization (MCAP) per capita as two indicators of the effect of globalization. We find that g, the GDP per capita, as a function of m, the MCAP per capita, follows a power law with average exponent close to 1/3. In addition, the Zipf ranking approach confirms that the m for countries with initially lower values of m tends to grow more rapidly than for countries with initially larger values of m. If the trends over the past 20 years continue to hold in the future, then the Zipf ranking approach leads to the prediction that in about 50 years, all countries participating in globalization will have comparable values of their MCAP per capita. We call this economic state "capital death," in analogy to the physics state of "heat death" predicted by thermodynamic arguments.
An attempt to estimate the global burden of disease due to fluoride in drinking water.
Fewtrell, Lorna; Smith, Stuart; Kay, Dave; Bartram, Jamie
2006-12-01
A study was conducted to examine the feasibility of estimating the global burden of disease due to fluoride in drinking water. Skeletal fluorosis is a serious and debilitating disease which, with the exception of one area in China, is overwhelmingly due to the presence of elevated fluoride levels in drinking water. The global burden of disease due to fluoride in drinking water was estimated by combining exposure-response curves for dental and skeletal fluorosis (derived from published data) with model-derived predicted drinking water fluoride concentrations and an estimate of the percentage population exposed. There are few data with which to validate the output but given the current uncertainties in the data used, both to form the exposure-response curves and those resulting from the prediction of fluoride concentrations, it is felt that the estimate is unlikely to be precise. However, the exercise has identified a number of data gaps and useful research avenues, especially in relation to determining exposure, which could contribute to future estimates of this problem.
Analysis of continuous GPS measurements from southern Victoria Land, Antarctica
Willis, Michael J.
2007-01-01
Several years of continuous data have been collected at remote bedrock Global Positioning System (GPS) sites in southern Victoria Land, Antarctica. Annual to sub-annual variations are observed in the position time-series. An atmospheric pressure loading (APL) effect is calculated from pressure field anomalies supplied by the European Centre for Medium-Range Weather Forecasts (ECMWF) model loading an elastic Earth model. The predicted APL signal has a moderate correlation with the vertical position time-series at McMurdo, Ross Island (International Global Navigation Satellite System Service (IGS) station MCM4), produced using a global solution. In contrast, a local solution in which MCM4 is the fiducial site generates a vertical time series for a remote site in Victoria Land (Cape Roberts, ROB4) which exhibits a low, inverse correlation with the predicted atmospheric pressure loading signal. If, in the future, known and well modeled geophysical loads can be separated from the time-series, then local hydrological loading, of interest for glaciological and climate applications, can potentially be extracted from the GPS time-series.
Influence versus intent for predictive analytics in situation awareness
NASA Astrophysics Data System (ADS)
Cui, Biru; Yang, Shanchieh J.; Kadar, Ivan
2013-05-01
Predictive analytics in situation awareness requires an element to comprehend and anticipate potential adversary activities that might occur in the future. Most work in high level fusion or predictive analytics utilizes machine learning, pattern mining, Bayesian inference, and decision tree techniques to predict future actions or states. The emergence of social computing in broader contexts has drawn interests in bringing the hypotheses and techniques from social theory to algorithmic and computational settings for predictive analytics. This paper aims at answering the question on how influence and attitude (some interpreted such as intent) of adversarial actors can be formulated and computed algorithmically, as a higher level fusion process to provide predictions of future actions. The challenges in this interdisciplinary endeavor include drawing existing understanding of influence and attitude in both social science and computing fields, as well as the mathematical and computational formulation for the specific context of situation to be analyzed. The study of `influence' has resurfaced in recent years due to the emergence of social networks in the virtualized cyber world. Theoretical analysis and techniques developed in this area are discussed in this paper in the context of predictive analysis. Meanwhile, the notion of intent, or `attitude' using social theory terminologies, is a relatively uncharted area in the computing field. Note that a key objective of predictive analytics is to identify impending/planned attacks so their `impact' and `threat' can be prevented. In this spirit, indirect and direct observables are drawn and derived to infer the influence network and attitude to predict future threats. This work proposes an integrated framework that jointly assesses adversarial actors' influence network and their attitudes as a function of past actions and action outcomes. A preliminary set of algorithms are developed and tested using the Global Terrorism Database (GTD). Our results reveals the benefits to perform joint predictive analytics with both attitude and influence. At the same time, we discover significant challenges in deriving influence and attitude from indirect observables for diverse adversarial behavior. These observations warrant further investigation of optimal use of influence and attitude for predictive analytics, as well as the potential inclusion of other environmental or capability elements for the actors.
NASA Technical Reports Server (NTRS)
Lettenmaier, Dennis P. (Editor); Rind, D. (Editor)
1992-01-01
The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.
Noiseonomics: the relationship between ambient noise levels in the sea and global economic trends.
Frisk, George V
2012-01-01
In recent years, the topic of noise in the sea and its effects on marine mammals has attracted considerable attention from both the scientific community and the general public. Since marine mammals rely heavily on acoustics as a primary means of communicating, navigating, and foraging in the ocean, any change in their acoustic environment may have an impact on their behavior. Specifically, a growing body of literature suggests that low-frequency, ambient noise levels in the open ocean increased approximately 3.3 dB per decade during the period 1950-2007. Here we show that this increase can be attributed primarily to commercial shipping activity, which in turn, can be linked to global economic growth. As a corollary, we conclude that ambient noise levels can be directly related to global economic conditions. We provide experimental evidence supporting this theory and discuss its implications for predicting future noise levels based on global economic trends.
Self-organized global control of carbon emissions
NASA Astrophysics Data System (ADS)
Zhao, Zhenyuan; Fenn, Daniel J.; Hui, Pak Ming; Johnson, Neil F.
2010-09-01
There is much disagreement concerning how best to control global carbon emissions. We explore quantitatively how different control schemes affect the collective emission dynamics of a population of emitting entities. We uncover a complex trade-off which arises between average emissions (affecting the global climate), peak pollution levels (affecting citizens’ everyday health), industrial efficiency (affecting the nation’s economy), frequency of institutional intervention (affecting governmental costs), common information (affecting trading behavior) and market volatility (affecting financial stability). Our findings predict that a self-organized free-market approach at the level of a sector, state, country or continent can provide better control than a top-down regulated scheme in terms of market volatility and monthly pollution peaks. The control of volatility also has important implications for any future derivative carbon emissions market.
NASA Technical Reports Server (NTRS)
Mohnen, V.
1984-01-01
The fundamental processes that control the chemical composition and cycles of the global troposphere and how these processes and properties affect the physical behavior of the atmosphere are examined. The long-term information needs for tropospheric chemistry are: to be able to predict tropospheric responses to perturbations, both natural and anthropogenic, of these cycles, and to provide the information required for the maintenance and effective future management of the atmospheric component of our global life support system. The processes controlling global tropospheric biogeochemical cycles include: the input of trace species into the troposphere, their long-range transport and distribution as affected by the mean wind and vertical venting, their chemical transformations, including gas to particle conversion, leading to the appearance of aerosols or aqueous phase reactions inside cloud droplets, and their removal from the troposphere via wet (precipitation) and dry deposition.
Phylogenetic responses of forest trees to global change.
Senior, John K; Schweitzer, Jennifer A; O'Reilly-Wapstra, Julianne; Chapman, Samantha K; Steane, Dorothy; Langley, Adam; Bailey, Joseph K
2013-01-01
In a rapidly changing biosphere, approaches to understanding the ecology and evolution of forest species will be critical to predict and mitigate the effects of anthropogenic global change on forest ecosystems. Utilizing 26 forest species in a factorial experiment with two levels each of atmospheric CO2 and soil nitrogen, we examined the hypothesis that phylogeny would influence plant performance in response to elevated CO2 and nitrogen fertilization. We found highly idiosyncratic responses at the species level. However, significant, among-genetic lineage responses were present across a molecularly determined phylogeny, indicating that past evolutionary history may have an important role in the response of whole genetic lineages to future global change. These data imply that some genetic lineages will perform well and that others will not, depending upon the environmental context.
Climate change. Accelerating extinction risk from climate change.
Urban, Mark C
2015-05-01
Current predictions of extinction risks from climate change vary widely depending on the specific assumptions and geographic and taxonomic focus of each study. I synthesized published studies in order to estimate a global mean extinction rate and determine which factors contribute the greatest uncertainty to climate change-induced extinction risks. Results suggest that extinction risks will accelerate with future global temperatures, threatening up to one in six species under current policies. Extinction risks were highest in South America, Australia, and New Zealand, and risks did not vary by taxonomic group. Realistic assumptions about extinction debt and dispersal capacity substantially increased extinction risks. We urgently need to adopt strategies that limit further climate change if we are to avoid an acceleration of global extinctions. Copyright © 2015, American Association for the Advancement of Science.
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.
Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel; García de Cortázar-Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry
2016-10-01
The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. © 2016 John Wiley & Sons Ltd.
Sensitivity of the global submarine hydrate inventory to scenarios of future climate change
NASA Astrophysics Data System (ADS)
Hunter, S. J.; Goldobin, D. S.; Haywood, A. M.; Ridgwell, A.; Rees, J. G.
2013-04-01
The global submarine inventory of methane hydrate is thought to be considerable. The stability of marine hydrates is sensitive to changes in temperature and pressure and once destabilised, hydrates release methane into sediments and ocean and potentially into the atmosphere, creating a positive feedback with climate change. Here we present results from a multi-model study investigating how the methane hydrate inventory dynamically responds to different scenarios of future climate and sea level change. The results indicate that a warming-induced reduction is dominant even when assuming rather extreme rates of sea level rise (up to 20 mm yr-1) under moderate warming scenarios (RCP 4.5). Over the next century modelled hydrate dissociation is focussed in the top ˜100m of Arctic and Subarctic sediments beneath <500m water depth. Predicted dissociation rates are particularly sensitive to the modelled vertical hydrate distribution within sediments. Under the worst case business-as-usual scenario (RCP 8.5), upper estimates of resulting global sea-floor methane fluxes could exceed estimates of natural global fluxes by 2100 (>30-50TgCH4yr-1), although subsequent oxidation in the water column could reduce peak atmospheric release rates to 0.75-1.4 Tg CH4 yr-1.
Remote-sensing based approach to forecast habitat quality under climate change scenarios.
Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier
2017-01-01
As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.
Remote-sensing based approach to forecast habitat quality under climate change scenarios
Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier
2017-01-01
As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501
NASA Astrophysics Data System (ADS)
Simpson, I.
2015-12-01
A long standing bias among global climate models (GCMs) is their incorrect representation of the wintertime circulation of the North Atlantic region. Specifically models tend to exhibit a North Atlantic jet (and associated storm track) that is too zonal, extending across central Europe, when it should tilt northward toward Scandinavia. GCM's consistently predict substantial changes in the large scale circulation in this region, consisting of a localized anti-cyclonic circulation, centered over the Mediterranean and accompanied by increased aridity there and increased storminess over Northern Europe.Here, we present preliminary results from experiments that are designed to address the question of what the impact of the climatological circulation biases might be on this predicted future response. Climate change experiments will be compared in two versions of the Community Earth System Model: the first is a free running version of the model, as typically used in climate prediction; the second is a bias corrected version of the model in which a seasonally varying cycle of bias correction tendencies are applied to the wind and temperature fields. These bias correction tendencies are designed to account for deficiencies in the fast parameterized processes, with an aim to push the model toward a more realistic climatology.While these experiments come with the caveat that they assume the bias correction tendencies will remain constant with time, they allow for an initial assessment, through controlled experiments, of the impact that biases in the climatological circulation can have on future predictions in this region. They will also motivate future work that can make use of the bias correction tendencies to understand the underlying physical processes responsible for the incorrect tilt of the jet.
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.
Predicting groundwater recharge for varying land cover and climate conditions - a global meta-study
NASA Astrophysics Data System (ADS)
Mohan, Chinchu; Western, Andrew W.; Wei, Yongping; Saft, Margarita
2018-05-01
Groundwater recharge is one of the important factors determining the groundwater development potential of an area. Even though recharge plays a key role in controlling groundwater system dynamics, much uncertainty remains regarding the relationships between groundwater recharge and its governing factors at a large scale. Therefore, this study aims to identify the most influential factors of groundwater recharge, and to develop an empirical model to estimate diffuse rainfall recharge at a global scale. Recharge estimates reported in the literature from various parts of the world (715 sites) were compiled and used in model building and testing exercises. Unlike conventional recharge estimates from water balance, this study used a multimodel inference approach and information theory to explain the relationship between groundwater recharge and influential factors, and to predict groundwater recharge at 0.5° resolution. The results show that meteorological factors (precipitation and potential evapotranspiration) and vegetation factors (land use and land cover) had the most predictive power for recharge. According to the model, long-term global average annual recharge (1981-2014) was 134 mm yr-1 with a prediction error ranging from -8 to 10 mm yr-1 for 97.2 % of cases. The recharge estimates presented in this study are unique and more reliable than the existing global groundwater recharge estimates because of the extensive validation carried out using both independent local estimates collated from the literature and national statistics from the Food and Agriculture Organization (FAO). In a water-scarce future driven by increased anthropogenic development, the results from this study will aid in making informed decisions about groundwater potential at a large scale.
Artisanal Fisheries Research: A Need for Globalization?
Oliveira Júnior, José Gilmar C; Silva, Luana P S; Malhado, Ana C M; Batista, Vandick S; Fabré, Nidia N; Ladle, Richard J
2016-01-01
Given limited funds for research and widespread degradation of ecosystems, environmental scientists should geographically target their studies where they will be most effective. However, in academic areas such as conservation and natural resource management there is often a mismatch between the geographic foci of research effort/funding and research needs. The former frequently being focused in the developed world while the latter is greater in the biodiverse countries of the Global South. Here, we adopt a bibliometric approach to test this hypothesis using research on artisanal fisheries. Such fisheries occur throughout the world, but are especially prominent in developing countries where they are important for supporting local livelihoods, food security and poverty alleviation. Moreover, most artisanal fisheries in the Global South are unregulated and unmonitored and are in urgent need of science-based management to ensure future sustainability. Our results indicate that, as predicted, global research networks and centres of knowledge production are predominantly located in developed countries, indicating a global mismatch between research needs and capacity.
Artisanal Fisheries Research: A Need for Globalization?
Batista, Vandick S.; Fabré, Nidia N.
2016-01-01
Given limited funds for research and widespread degradation of ecosystems, environmental scientists should geographically target their studies where they will be most effective. However, in academic areas such as conservation and natural resource management there is often a mismatch between the geographic foci of research effort/funding and research needs. The former frequently being focused in the developed world while the latter is greater in the biodiverse countries of the Global South. Here, we adopt a bibliometric approach to test this hypothesis using research on artisanal fisheries. Such fisheries occur throughout the world, but are especially prominent in developing countries where they are important for supporting local livelihoods, food security and poverty alleviation. Moreover, most artisanal fisheries in the Global South are unregulated and unmonitored and are in urgent need of science-based management to ensure future sustainability. Our results indicate that, as predicted, global research networks and centres of knowledge production are predominantly located in developed countries, indicating a global mismatch between research needs and capacity. PMID:26942936
NASA Astrophysics Data System (ADS)
Glotfelty, Timothy; Zhang, Yang
2017-03-01
Following a comprehensive evaluation of the Community Earth System Model modified at the North Carolina State University (CESM-NCSU), Part II describes the projected changes in the future state of the atmosphere under the representative concentration partway scenarios (RCP4.5 and 8.5) by 2100 for the 2050 time frame and examine the impact of climate change on future air quality under both scenarios, and the impact of projected emission changes under the RCP4.5 scenario on future climate through aerosol direct and indirect effects. Both the RCP4.5 and RCP8.5 simulations predict similar changes in air quality by the 2050 period due to declining emissions under both scenarios. The largest differences occur in O3, which decreases by global mean of 1.4 ppb under RCP4.5 but increases by global mean of 2.3 ppb under RCP8.5 due to differences in methane levels, and PM10, which decreases by global mean of 1.2 μg m-3 under RCP4.5 and increases by global mean of 0.2 μg m-3 under RCP8.5 due to differences in dust and sea-salt emissions under both scenarios. Enhancements in cloud formation in the Arctic and Southern Ocean and increases of aerosol optical depth (AOD) in central Africa and South Asia dominate the change in surface radiation in both scenarios, leading to global average dimming of 1.1 W m-2 and 2.0 W m-2 in the RCP4.5 and RCP8.5 scenarios, respectively. Declines in AOD, cloud formation, and cloud optical thickness from reductions of emissions of primary aerosols and aerosol precursors under RCP4.5 result in near surface warming of 0.2 °C from a global average increase of 0.7 W m-2 in surface downwelling solar radiation. This warming leads to a weakening of the Walker Circulation in the tropics, leading to significant changes in cloud and precipitation that mirror a shift in climate towards the negative phase of the El Nino Southern Oscillation.
Linking models and data on vegetation structure
NASA Astrophysics Data System (ADS)
Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.
2010-06-01
For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.
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.
Global Quantitative Modeling of Chromatin Factor Interactions
Zhou, Jian; Troyanskaya, Olga G.
2014-01-01
Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896
NASA Astrophysics Data System (ADS)
Kanemura, Shinya; Kaneta, Kunio; Machida, Naoki; Odori, Shinya; Shindou, Tetsuo
2016-07-01
In the composite Higgs models, originally proposed by Georgi and Kaplan, the Higgs boson is a pseudo Nambu-Goldstone boson (pNGB) of spontaneous breaking of a global symmetry. In the minimal version of such models, global SO(5) symmetry is spontaneously broken to SO(4), and the pNGBs form an isospin doublet field, which corresponds to the Higgs doublet in the Standard Model (SM). Predicted coupling constants of the Higgs boson can in general deviate from the SM predictions, depending on the compositeness parameter. The deviation pattern is determined also by the detail of the matter sector. We comprehensively study how the model can be tested via measuring single and double production processes of the Higgs boson at the LHC and future electron-positron colliders. The possibility to distinguish the matter sector among the minimal composite Higgs models is also discussed. In addition, we point out differences in the cross section of double Higgs boson production from the prediction in other new physics models.
Varela, Sara; Larkin, Daniel J.; Phelps, Nicholas B. D.
2017-01-01
Starry stonewort (Nitellopsis obtusa) is an alga that has emerged as an aquatic invasive species of concern in the United States. Where established, starry stonewort can interfere with recreational uses of water bodies and potentially have ecological impacts. Incipient invasion of starry stonewort in Minnesota provides an opportunity to predict future expansion in order to target early detection and strategic management. We used ecological niche models to identify suitable areas for starry stonewort in Minnesota based on global occurrence records and present-day and future climate conditions. We assessed sensitivity of forecasts to different parameters, using four emission scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6, and RCP 8.5) from five future climate models (i.e., CCSM, GISS, IPSL, MIROC, and MRI). From our niche model analyses, we found that (i) occurrences from the entire range, instead of occurrences restricted to the invaded range, provide more informed models; (ii) default settings in Maxent did not provide the best model; (iii) the model calibration area and its background samples impact model performance; (iv) model projections to future climate conditions should be restricted to analogous environments; and (v) forecasts in future climate conditions should include different future climate models and model calibration areas to better capture uncertainty in forecasts. Under present climate, the most suitable areas for starry stonewort are predicted to be found in central and southeastern Minnesota. In the future, suitable areas for starry stonewort are predicted to shift in geographic range under some future climate models and to shrink under others, with most permutations indicating a net decrease of the species’ suitable range. Our suitability maps can serve to design short-term plans for surveillance and education, while future climate models suggest a plausible reduction of starry stonewort spread in the long-term if the trends in climate warming remain. PMID:28704433
Romero-Alvarez, Daniel; Escobar, Luis E; Varela, Sara; Larkin, Daniel J; Phelps, Nicholas B D
2017-01-01
Starry stonewort (Nitellopsis obtusa) is an alga that has emerged as an aquatic invasive species of concern in the United States. Where established, starry stonewort can interfere with recreational uses of water bodies and potentially have ecological impacts. Incipient invasion of starry stonewort in Minnesota provides an opportunity to predict future expansion in order to target early detection and strategic management. We used ecological niche models to identify suitable areas for starry stonewort in Minnesota based on global occurrence records and present-day and future climate conditions. We assessed sensitivity of forecasts to different parameters, using four emission scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6, and RCP 8.5) from five future climate models (i.e., CCSM, GISS, IPSL, MIROC, and MRI). From our niche model analyses, we found that (i) occurrences from the entire range, instead of occurrences restricted to the invaded range, provide more informed models; (ii) default settings in Maxent did not provide the best model; (iii) the model calibration area and its background samples impact model performance; (iv) model projections to future climate conditions should be restricted to analogous environments; and (v) forecasts in future climate conditions should include different future climate models and model calibration areas to better capture uncertainty in forecasts. Under present climate, the most suitable areas for starry stonewort are predicted to be found in central and southeastern Minnesota. In the future, suitable areas for starry stonewort are predicted to shift in geographic range under some future climate models and to shrink under others, with most permutations indicating a net decrease of the species' suitable range. Our suitability maps can serve to design short-term plans for surveillance and education, while future climate models suggest a plausible reduction of starry stonewort spread in the long-term if the trends in climate warming remain.
I Lacan; Kathleen R. Matthews; K.V. Feldman
2008-01-01
Between-year variation in snowpack (from 20 to 200% of average) and summer rainfall cause large fluctuations in volume of small lakes in the higher elevation (> 3000 m) Sierra Nevada, which are important habitat for the imperiled Sierra Nevada Yellow-legged Frog, Rana sierrae. Climate change (global warming) is predicted to increase these...
Analysis of climate change impact on rainfall pattern of Sambas district, West Kalimantan
NASA Astrophysics Data System (ADS)
Berliana Sipayung, Sinta; Nurlatifah, Amalia; Siswanto, Bambang; Slamet S, Lilik
2018-05-01
Climate change is one of the most important issues being discussed globally. It caused by global warming and indirectly affecting the world climate cycle. This research discussed the effect of climate change on rainfall pattern of Sambas District and predicted the future rainfall pattern due to climate change. CRU and TRMM were used and has been validated using in situ data. This research was used Climate Modelling and Prediction using CCAM (Conformal Cubic Atmospheric Model) which also validated by in situ data (correlation= 0.81). The results show that temperature trends in Sambas regency increased to 0.082°C/yr from 1991-2014 according to CRU data. High temperature trigger changes in rainfall patterns. Rainfall pattern in Sambas District has an equatorial type where the peak occurs when the sun is right on the equator. Rainfall in Sambas reaches the maximum in March and September when the equinox occurs. The CCAM model is used to project rainfall in Sambas District in the future. The model results show that rainfall in Sambas District is projected to increase to 0.018 mm/month until 2055 so the flow rate increase 0.006 m3/month and the water balance increase 0.009 mm/month.
The practice of prediction: What can ecologists learn from applied, ecology-related fields?
Pennekamp, Frank; Adamson, Matthew; Petchey, Owen L; Poggiale, Jean-Christophe; Aguiar, Maira; Kooi, Bob W.; Botkin, Daniel B.; DeAngelis, Donald L.
2017-01-01
The pervasive influence of human induced global environmental change affects biodiversity across the globe, and there is great uncertainty as to how the biosphere will react on short and longer time scales. To adapt to what the future holds and to manage the impacts of global change, scientists need to predict the expected effects with some confidence and communicate these predictions to policy makers. However, recent reviews found that we currently lack a clear understanding of how predictable ecology is, with views seeing it as mostly unpredictable to potentially predictable, at least over short time frames. However, in applied, ecology-related fields predictions are more commonly formulated and reported, as well as evaluated in hindsight, potentially allowing one to define baselines of predictive proficiency in these fields. We searched the literature for representative case studies in these fields and collected information about modeling approaches, target variables of prediction, predictive proficiency achieved, as well as the availability of data to parameterize predictive models. We find that some fields such as epidemiology achieve high predictive proficiency, but even in the more predictive fields proficiency is evaluated in different ways. Both phenomenological and mechanistic approaches are used in most fields, but differences are often small, with no clear superiority of one approach over the other. Data availability is limiting in most fields, with long-term studies being rare and detailed data for parameterizing mechanistic models being in short supply. We suggest that ecologists adopt a more rigorous approach to report and assess predictive proficiency, and embrace the challenges of real world decision making to strengthen the practice of prediction in ecology.
Predicting the Distribution of Commercially Important Invertebrate Stocks under Future Climate
Russell, Bayden D.; Connell, Sean D.; Mellin, Camille; Brook, Barry W.; Burnell, Owen W.; Fordham, Damien A.
2012-01-01
The future management of commercially exploited species is challenging because techniques used to predict the future distribution of stocks under climate change are currently inadequate. We projected the future distribution and abundance of two commercially harvested abalone species (blacklip abalone, Haliotis rubra and greenlip abalone, H. laevigata) inhabiting coastal South Australia, using multiple species distribution models (SDM) and for decadal time slices through to 2100. Projections are based on two contrasting global greenhouse gas emissions scenarios. The SDMs identified August (winter) Sea Surface Temperature (SST) as the best descriptor of abundance and forecast that warming of winter temperatures under both scenarios may be beneficial to both species by allowing increased abundance and expansion into previously uninhabited coasts. This range expansion is unlikely to be realised, however, as projected warming of March SST is projected to exceed temperatures which cause up to 10-fold increases in juvenile mortality. By linking fine-resolution forecasts of sea surface temperature under different climate change scenarios to SDMs and physiological experiments, we provide a practical first approximation of the potential impact of climate-induced change on two species of marine invertebrates in the same fishery. PMID:23251326
Ups and downs of economics and econophysics — Facebook forecast
NASA Astrophysics Data System (ADS)
Gajic, Nenad; Budinski-Petkovic, Ljuba
2013-01-01
What is econophysics and its relationship with economics? What is the state of economics after the global economic crisis, and is there a future for the paradigm of market equilibrium, with imaginary perfect competition and rational agents? Can the next paradigm of economics adopt important assumptions derived from econophysics models: that markets are chaotic systems, striving to extremes as bubbles and crashes show, with psychologically motivated, statistically predictable individual behaviors? Is the future of econophysics, as predicted here, to disappear and become a part of economics? A good test of the current state of econophysics and its methods is the valuation of Facebook immediately after the initial public offering - this forecast indicates that Facebook is highly overvalued, and its IPO valuation of 104 billion dollars is mostly the new financial bubble based on the expectations of unlimited growth, although it’s easy to prove that Facebook is close to the upper limit of its users.
Rising sea levels will reduce extreme temperature variations in tide-dominated reef habitats.
Lowe, Ryan Joseph; Pivan, Xavier; Falter, James; Symonds, Graham; Gruber, Renee
2016-08-01
Temperatures within shallow reefs often differ substantially from those in the surrounding ocean; therefore, predicting future patterns of thermal stresses and bleaching at the scale of reefs depends on accurately predicting reef heat budgets. We present a new framework for quantifying how tidal and solar heating cycles interact with reef morphology to control diurnal temperature extremes within shallow, tidally forced reefs. Using data from northwestern Australia, we construct a heat budget model to investigate how frequency differences between the dominant lunar semidiurnal tide and diurnal solar cycle drive ~15-day modulations in diurnal temperature extremes. The model is extended to show how reefs with tidal amplitudes comparable to their depth, relative to mean sea level, tend to experience the largest temperature extremes globally. As a consequence, we reveal how even a modest sea level rise can substantially reduce temperature extremes within tide-dominated reefs, thereby partially offsetting the local effects of future ocean warming.
Model Projections of Future Fluvial Sediment Delivery to Major Deltas Under Environmental Change
NASA Astrophysics Data System (ADS)
Darby, S. E.; Dunn, F.; Nicholls, R. J.; Cohen, S.; Zarfl, C.
2017-12-01
Deltas are important hot spots for climate change impacts on which over half a billion people live worldwide. Most of the world's deltas are sinking as a result of natural and anthropogenic subsidence and due to eustatic sea level rise. The ability to predict rates of delta aggradation is therefore critical to assessments of the extent to which sedimentation can potentially offset sea level rise, but our ability to make such predictions is severely hindered by a lack of insight into future trends of the fluvial sediment load supplied to their deltas by feeder watersheds. To address this gap we investigate fluvial sediment fluxes under future environmental change for a selection (47) of the world's major river deltas. Specifically, we employed the numerical model WBMsed to project future variations in mean annual fluvial sediment loads under a range of environmental change scenarios that account for changes in climate, socio-economics and dam construction. Our projections indicate a clear decrease (by 34 to 41% on average, depending on the specific scenario) in future fluvial sediment supply to most of the 47 deltas. These reductions in sediment delivery are driven primarily by anthropogenic disturbances, with reservoir construction being the most influential factor globally. Our results indicate the importance of developing new management strategies for reservoir construction and operation.
State of Science: ergonomics and global issues.
Thatcher, Andrew; Waterson, Patrick; Todd, Andrew; Moray, Neville
2018-02-01
In his 1993 IEA keynote address, Neville Moray urged the ergonomics discipline to face up to the global problems facing humanity and consider how ergonomics might help find some of the solutions. In this State of Science article we critically evaluate what the ergonomics discipline has achieved in the last two and a half decades to help create a secure future for humanity. Moray's challenges for ergonomics included deriving a value structure that moves us beyond a Westernised view of worker-organisation-technology fit, taking a multidisciplinary approach which engages with other social and biological sciences, considering the gross cross-cultural factors that determine how different societies function, paying more attention to mindful consumption, and embracing the complexity of our interconnected world. This article takes a socio-historical approach by considering the factors that influence what has been achieved since Moray's keynote address. We conclude with our own set of predictions for the future and priorities for addressing the challenges that we are likely to face. Practitioner Summary: We critically reflect on what has been achieved by the ergonomics profession in addressing the global challenges raised by Moray's 1993 keynote address to the International Ergonomics Association. Apart from healthcare, the response has largely been weak and disorganised. We make suggestions for priority research and practice that is required to facilitate a sustainable future for humanity.
Current and Future Greenhouse Gas Emissions from Global Crop Intensification and Expansion
NASA Astrophysics Data System (ADS)
Carlson, K. M.; Gerber, J. S.; Mueller, N. D.; O'Connell, C.; West, P. C.
2014-12-01
Food systems currently contribute up to one-third of total anthropogenic greenhouse gas emissions, and these emissions are expected to rise as demand for agricultural products increases. Thus, improving the greenhouse gas emissions efficiency of agriculture - the tons or kilocalories of production per ton of CO2 equivalent emissions - will be critical to support a resilient future global system. Here, we model and evaluate global, 2000-era, spatially explicit relationships between a suite of greenhouse gas emissions from various agronomic practices (i.e., fertilizer application, peatland draining, and rice cultivation) and crop yields. Then, we predict potential emissions from future crop production increases achieved through intensification and extensification, including CO2 emissions from croplands replacing non-urban land cover. We find that 2000-era yield-scaled agronomic emissions are highly heterogeneous across crops types, crop management practices, and regions. Rice agriculture produces more total CO2-equivalent emissions than any other crop. Moreover, inundated rice in just a few countries contributes the vast majority of these rice emissions. Crops such as sunflower and cotton have low efficiency on a caloric basis. Our results suggest that intensification tends to be a more efficient pathway to boost greenhouse gas emissions efficiency than expansion. We conclude by discussing potential crop- and region-specific agricultural development pathways that may boost the greenhouse gas emissions efficiency of agriculture.
NASA Astrophysics Data System (ADS)
Spracklen, D. V.; Logan, J. A.; Mickley, L. J.; Park, R. J.; Flannigan, M. D.; Westerling, A. L.
2006-12-01
Increased forest fire activity in the Western United States appears to be driven by increasing spring and summer temperatures. Here we make a first estimate of how climate-driven changes in fire activity will influence summertime organic carbon (OC) concentrations in the Western US. We use output from a general circulation model (GCM) combined with area burned regressions to predict how area burned will change between present day and 2050. Calculated area burned is used to create future emission estimates for the Western U.S. and we use a global chemical transport model (CTM) to predict future changes in OC concentrations. Stepwise linear regression is used to determine the best relationships between observed area burned for 1980- 2004 and variables chosen from temperature, relative humidity, wind speed, rainfall and drought indices from the Candaian Fire Weather Index Model. Best predictors are ecosytem dependent but typically include mean summer temperature and mean drought code. In forest ecosystems of the Western U.S. our regressions explain 50-60% of the variance in annual area burned. Between 2000 and 2050 increases in temperature and reductions in precipitation, as predicted by the GISS GCM, cause mean area burned in the western U.S. to increase by 30-55%. We use the GEOS-Chem CTM to show that these increased emissions result in an increase in summertime western U.S. OC concentrations by 55% over current concentrations. Our results show that the predicted increase in future wild fires will have important consequences for western US air quality and visibility.
Ganapathiraju, Madhavi K; Orii, Naoki
2013-08-30
Advances in biotechnology have created "big-data" situations in molecular and cellular biology. Several sophisticated algorithms have been developed that process big data to generate hundreds of biomedical hypotheses (or predictions). The bottleneck to translating this large number of biological hypotheses is that each of them needs to be studied by experimentation for interpreting its functional significance. Even when the predictions are estimated to be very accurate, from a biologist's perspective, the choice of which of these predictions is to be studied further is made based on factors like availability of reagents and resources and the possibility of formulating some reasonable hypothesis about its biological relevance. When viewed from a global perspective, say from that of a federal funding agency, ideally the choice of which prediction should be studied would be made based on which of them can make the most translational impact. We propose that algorithms be developed to identify which of the computationally generated hypotheses have potential for high translational impact; this way, funding agencies and scientific community can invest resources and drive the research based on a global view of biomedical impact without being deterred by local view of feasibility. In short, data-analytic algorithms analyze big-data and generate hypotheses; in contrast, the proposed inference-analytic algorithms analyze these hypotheses and rank them by predicted biological impact. We demonstrate this through the development of an algorithm to predict biomedical impact of protein-protein interactions (PPIs) which is estimated by the number of future publications that cite the paper which originally reported the PPI. This position paper describes a new computational problem that is relevant in the era of big-data and discusses the challenges that exist in studying this problem, highlighting the need for the scientific community to engage in this line of research. The proposed class of algorithms, namely inference-analytic algorithms, is necessary to ensure that resources are invested in translating those computational outcomes that promise maximum biological impact. Application of this concept to predict biomedical impact of PPIs illustrates not only the concept, but also the challenges in designing these algorithms.
Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions
NASA Astrophysics Data System (ADS)
Van Hooidonk, R. J.
2011-12-01
Future widespread coral bleaching and subsequent mortality has been projected with sea surface temperature (SST) data from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. These model weaknesses likely reduce the skill of coral bleaching predictions, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends and their propagation in predictions. To analyze the relative importance of various types of model errors and biases on coral reef bleaching predictive skill, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from GCMs 20th century simulations to be included in the Intergovernmental Panel on Climate Change (IPCC) 5th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate skill using an objective measure of forecast quality, the Peirce Skill Score (PSS). This methodology will identify frequency bands that are important to predicting coral bleaching and it will highlight deficiencies in these bands in models. The methodology we describe can be used to improve future climate model derived predictions of coral reef bleaching and it can be used to better characterize the errors and uncertainty in predictions.
Importance of vegetation dynamics for future terrestrial carbon cycling
NASA Astrophysics Data System (ADS)
Ahlström, Anders; Xia, Jianyang; Arneth, Almut; Luo, Yiqi; Smith, Benjamin
2015-05-01
Terrestrial ecosystems currently sequester about one third of anthropogenic CO2 emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO2 by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.
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.
Convergence of soil nitrogen isotopes across global climate gradients
Craine, Joseph M.; Elmore, Andrew J.; Wang, Lixin; Augusto, Laurent; Baisden, W. Troy; Brookshire, E. N. J.; Cramer, Michael D.; Hasselquist, Niles J.; Hobbie, Erik A.; Kahmen, Ansgar; Koba, Keisuke; Kranabetter, J. Marty; Mack, Michelle C.; Marin-Spiotta, Erika; Mayor, Jordan R.; McLauchlan, Kendra K.; Michelsen, Anders; Nardoto, Gabriela B.; Oliveira, Rafael S.; Perakis, Steven S.; Peri, Pablo L.; Quesada, Carlos A.; Richter, Andreas; Schipper, Louis A.; Stevenson, Bryan A.; Turner, Benjamin L.; Viani, Ricardo A. G.; Wanek, Wolfgang; Zeller, Bernd
2015-01-01
Quantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing. With limited direct measures of soil N cycling at the global scale, syntheses of the 15 N: 14 N ratio of soil organic matter across climate gradients provide key insights into understanding global patterns of N cycling. In synthesizing data from over 6000 soil samples, we show strong global relationships among soil N isotopes, mean annual temperature (MAT), mean annual precipitation (MAP), and the concentrations of organic carbon and clay in soil. In both hot ecosystems and dry ecosystems, soil organic matter was more enriched in 15 N than in corresponding cold ecosystems or wet ecosystems. Below a MAT of 9.8°C, soil δ15N was invariant with MAT. At the global scale, soil organic C concentrations also declined with increasing MAT and decreasing MAP. After standardizing for variation among mineral soils in soil C and clay concentrations, soil δ15N showed no consistent trends across global climate and latitudinal gradients. Our analyses could place new constraints on interpretations of patterns of ecosystem N cycling and global budgets of gaseous N loss.
Convergence of soil nitrogen isotopes across global climate gradients.
Craine, Joseph M; Elmore, Andrew J; Wang, Lixin; Augusto, Laurent; Baisden, W Troy; Brookshire, E N J; Cramer, Michael D; Hasselquist, Niles J; Hobbie, Erik A; Kahmen, Ansgar; Koba, Keisuke; Kranabetter, J Marty; Mack, Michelle C; Marin-Spiotta, Erika; Mayor, Jordan R; McLauchlan, Kendra K; Michelsen, Anders; Nardoto, Gabriela B; Oliveira, Rafael S; Perakis, Steven S; Peri, Pablo L; Quesada, Carlos A; Richter, Andreas; Schipper, Louis A; Stevenson, Bryan A; Turner, Benjamin L; Viani, Ricardo A G; Wanek, Wolfgang; Zeller, Bernd
2015-02-06
Quantifying global patterns of terrestrial nitrogen (N) cycling is central to predicting future patterns of primary productivity, carbon sequestration, nutrient fluxes to aquatic systems, and climate forcing. With limited direct measures of soil N cycling at the global scale, syntheses of the (15)N:(14)N ratio of soil organic matter across climate gradients provide key insights into understanding global patterns of N cycling. In synthesizing data from over 6000 soil samples, we show strong global relationships among soil N isotopes, mean annual temperature (MAT), mean annual precipitation (MAP), and the concentrations of organic carbon and clay in soil. In both hot ecosystems and dry ecosystems, soil organic matter was more enriched in (15)N than in corresponding cold ecosystems or wet ecosystems. Below a MAT of 9.8°C, soil δ(15)N was invariant with MAT. At the global scale, soil organic C concentrations also declined with increasing MAT and decreasing MAP. After standardizing for variation among mineral soils in soil C and clay concentrations, soil δ(15)N showed no consistent trends across global climate and latitudinal gradients. Our analyses could place new constraints on interpretations of patterns of ecosystem N cycling and global budgets of gaseous N loss.
Jovicić, Dobrica
2012-06-01
Trying to anticipate the future of tourism may be a particularly fraught task. However, this does not mean that trying to predict the future of tourism is not without value. From a business perspective, examining the future enables firms to anticipate new business conditions and develop new strategies. From a destination perspective, reflections on the future enable consideration of how to maintain or improve the qualities of a destination. The paper is focused on an analysis of the impacts of the energy and ecological macro environments on tourism trends in 21st century. Mass international tourism has thrived on the abundant and cheap supply of energy, and this may be about to change as the world moves towards 'Peak Oil'. The resultant scarcity and high price of all energy fuels will produce changes in human activities, specifically in tourism. The basis of the health of the economy is the health of the environment. Therefore issues of global environmental changes are increasingly influencing consideration of trends in tourism. In this looming transitional era tourism needs to make some dramatic changes to harmonize with the new realities of a post-energy world affected additionaly by global warming and other environmental changes.
Social and economic impacts of climate.
Carleton, Tamma A; Hsiang, Solomon M
2016-09-09
For centuries, thinkers have considered whether and how climatic conditions-such as temperature, rainfall, and violent storms-influence the nature of societies and the performance of economies. A multidisciplinary renaissance of quantitative empirical research is illuminating important linkages in the coupled climate-human system. We highlight key methodological innovations and results describing effects of climate on health, economics, conflict, migration, and demographics. Because of persistent "adaptation gaps," current climate conditions continue to play a substantial role in shaping modern society, and future climate changes will likely have additional impact. For example, we compute that temperature depresses current U.S. maize yields by ~48%, warming since 1980 elevated conflict risk in Africa by ~11%, and future warming may slow global economic growth rates by ~0.28 percentage points per year. In general, we estimate that the economic and social burden of current climates tends to be comparable in magnitude to the additional projected impact caused by future anthropogenic climate changes. Overall, findings from this literature point to climate as an important influence on the historical evolution of the global economy, they should inform how we respond to modern climatic conditions, and they can guide how we predict the consequences of future climate changes. Copyright © 2016, American Association for the Advancement of Science.
Earlier Snowmelt Changes the Ratio Between Early and Late Season Forest Productivity
NASA Astrophysics Data System (ADS)
Knowles, J. F.; Molotch, N. P.; Trujillo, E.; Litvak, M. E.
2017-12-01
Future projections of declining snowpack and increasing potential evaporation associated with climate warming are predicted to advance the timing of snowmelt in mountain ecosystems globally. This scenario has direct implications for snowmelt-driven forest productivity, but the net effect of temporally shifting moisture dynamics is unknown with respect to the annual carbon balance. Accordingly, this study uses both satellite- and tower-based observations to document the forest productivity response to snowpack and potential evaporation variability between 1989 and 2012 throughout the southern Rocky Mountain ecoregion, USA. These results show that a combination of low snow accumulation and record high potential evaporation in 2012 resulted in the 34-year minimum ecosystem productivity that could be indicative of future conditions. Moreover, early and late season productivity were significantly and inversely related, suggesting that future shifts toward earlier or reduced snowmelt could increase late-season moisture stress to vegetation and thus restrict productivity despite a longer growing season. This relationship was further subject to modification by summer precipitation, and the controls on the early/late season productivity ratio are explored within the context of ecosystem carbon storage in the future. Any perturbation to the carbon cycle at this scale represents a potential feedback to climate change since snow-covered forests represent an important global carbon sink.
Life-history theory and climate change: resolving population and parental investment paradoxes
Quinlan, Robert
2016-01-01
Population growth in the next half-century is on pace to raise global carbon emissions by half. Carbon emissions are associated with fertility as a by-product of somatic and parental investment, which is predicted to involve time orientation/preference as a mediating psychological mechanism. Here, we draw upon life-history theory (LHT) to investigate associations between future orientation and fertility, and their impacts on carbon emissions. We argue ‘K-strategy’ life history (LH) in high-income countries has resulted in parental investment behaviours involving future orientation that, paradoxically, promote unsustainable carbon emissions, thereby lowering the Earth's K or carrying capacity. Increasing the rate of approach towards this capacity are ‘r-strategy’ LHs in low-income countries that promote population growth. We explore interactions between future orientation and development that might slow the rate of approach towards global K. Examination of 67 000 individuals across 75 countries suggests that future orientation interacts with the relationship between environmental risk and fertility and with development related parental investment, particularly investment in higher education, to slow population growth and mitigate per capita carbon emissions. Results emphasize that LHT will be an important tool in understanding the demographic and consumption patterns that drive anthropogenic climate change. PMID:28018631
Health impacts of an environmental disaster: a polemic
NASA Astrophysics Data System (ADS)
Dorling, Danny; Barford, Anna; Wheeler, Ben
2007-10-01
At this early point in the 21st century a major concern that we face is the future possible effects of people-induced global warming. The predicted effects are severe, but argued by some to be avoidable if we act now. Here we consider the dimensions of another disaster: one for which not only the causes, but also their horrific consequences, are current worldwide. The implicit question is 'why are we more worried about future disasters than those already occurring?' The worldmapper collection of cartograms (where a map is used like a pie-chart to present data) is used here to illustrate the extent of international inequalities in health and living conditions, discussed in relation to other aspects of human lives. Though the shape that we can see the world is in is shocking, we can also envisage a positive future. We compare these current global times to more local past times experienced during the ravaging inequalities of Victorian Britain. We use Britain simply as an example. We end by suggesting a further step the current British Prime Minister could make in his thinking. Doing this we can see the potential for environmental reconstruction, which would result (as it did before) in considerable reductions in infant mortality. Our common future is not already mapped out; it is still to be won.
Structure and controls of the global virtual water trade network
NASA Astrophysics Data System (ADS)
Suweis, S.; Konar, M.; Dalin, C.; Hanasaki, N.; Rinaldo, A.; Rodriguez-Iturbe, I.
2011-05-01
Recurrent or ephemeral water shortages are a crucial global challenge, in particular because of their impacts on food production. The global character of this challenge is reflected in the trade among nations of virtual water, i.e., the amount of water used to produce a given commodity. We build, analyze and model the network describing the transfer of virtual water between world nations for staple food products. We find that all the key features of the network are well described by a model that reproduces both the topological and weighted properties of the global virtual water trade network, by assuming as sole controls each country's gross domestic product and yearly rainfall on agricultural areas. We capture and quantitatively describe the high degree of globalization of water trade and show that a small group of nations play a key role in the connectivity of the network and in the global redistribution of virtual water. Finally, we illustrate examples of prediction of the structure of the network under future political, economic and climatic scenarios, suggesting that the crucial importance of the countries that trade large volumes of water will be strengthened.
Smargiassi, Audrey; Brand, Allan; Fournier, Michel; Tessier, François; Goudreau, Sophie; Rousseau, Jacques; Benjamin, Mario
2012-07-01
Residential wood burning can be a significant wintertime source of ambient fine particles in urban and suburban areas. We developed a statistical model to predict minute (min) levels of particles with median diameter of <1 μm (PM1) from mobile monitoring on evenings of winter weekends at different residential locations in Quebec, Canada, considering wood burning emissions. The 6 s PM1 levels were concurrently measured on 10 preselected routes travelled 3 to 24 times during the winters of 2008-2009 and 2009-2010 by vehicles equipped with a GRIMM or a dataRAM sampler and a Global Positioning System device. Route-specific and global land-use regression (LUR) models were developed using the following spatial and temporal covariates to predict 1-min-averaged PM1 levels: chimney density from property assessment data at sampling locations, PM2.5 "regional background" levels of particles with median diameter of <2.5 μm (PM2.5) and temperature and wind speed at hour of sampling, elevation at sampling locations and day of the week. In the various routes travelled, between 49% and 94% of the variability in PM1 levels was explained by the selected covariates. The effect of chimney density was not negligible in "cottage areas." The R(2) for the global model including all routes was 0.40. This LUR is the first to predict PM1 levels in both space and time with consideration of the effects of wood burning emissions. We show that the influence of chimney density, a proxy for wood burning emissions, varies by regions and that a global model cannot be used to predict PM in regions that were not measured. Future work should consider using both survey data on wood burning intensity and information from numerical air quality forecast models, in LUR models, to improve the generalisation of the prediction of fine particulate levels.
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.
Emergent Hydrological Regimes in Amazonia Determine Vegetation Productivity and Structure.
NASA Astrophysics Data System (ADS)
Ahlström, A.; Canadell, J.; Schurgers, G.; Berry, J. A.; Guan, K.; Jackson, R. B.
2016-12-01
The Amazon rain forest has a disproportionate significance for global CO2 storage and biodiversity. Earth system models (ESMs) that estimate future climate and vegetation show little agreement in simulations in Amazonia. Here we show that evapotranspiration (ET), gross primary productivity (GPP) and above ground biomass in both models and empirical data align on an emergent hydrologically determined relationship that describes a functional relationship with annual precipitation (P). The physical relationship describes the potential for plant productivity and has a breakpoint at 2000 mm annual precipitation, where the system transitions between water and radiation limitation of annual ET. While ESM GPP is generally underestimated due to a low-bias in their internally generated P, their response to annual precipitation generally matches empirical data. It is different for biomass: ESMs show some ability in capturing biomass levels in the energy-limited wet hydrological regime above 2000 mm annual precipitation but they do not fully capture the biomass structure tipping point found in empirical data at the hydrological regime breakpoint that coincide with the forest-savanna transition. This discrepancy is likely due to the relatively simple representation of disturbances, primarily fires, and vegetation dynamics found in ESMs, and implies that ESMs likely overestimate the resilience to a potential future drying of the Amazon. Future elevated CO2 may increase plant water use efficiency and shift GPP upwards, but it will not affect the breakpoint between the regimes or the susceptibility of the forest which are both determined by precipitation and its role in determining the hydrological regime. This analysis reconciles and explains the findings of many studies on the Amazon. Our results suggests that future Amazonian biomass is governed by changes in precipitation, vegetation dynamics and disturbances, none of which are well predicted and represented by ESMs. Improvements of these processes are the most pressing challenges for more accurate future predictions on the fate of the Amazon and the global tropics.
Kapwata, Thandi; Gebreslasie, Michael T; Mathee, Angela; Wright, Caradee Yael
2018-05-10
Climate change has resulted in rising temperature trends which have been associated with changes in temperature extremes globally. Attendees of Conference of the Parties (COP) 21 agreed to strive to limit the rise in global average temperatures to below 2 °C compared to industrial conditions, the target being 1.5 °C. However, current research suggests that the African region will be subjected to more intense heat extremes over a shorter time period, with projections predicting increases of 4⁻6 °C for the period 2071⁻2100, in annual average maximum temperatures for southern Africa. Increased temperatures may exacerbate existing chronic ill health conditions such as cardiovascular disease, respiratory disease, cerebrovascular disease, and diabetes-related conditions. Exposure to extreme temperatures has also been associated with mortality. This study aimed to consider the relationship between temperatures in indoor and outdoor environments in a rural residential setting in a current climate and warmer predicted future climate. Temperature and humidity measurements were collected hourly in 406 homes in summer and spring and at two-hour intervals in 98 homes in winter. Ambient temperature, humidity and windspeed were obtained from the nearest weather station. Regression models were used to identify predictors of indoor apparent temperature (AT) and to estimate future indoor AT using projected ambient temperatures. Ambient temperatures will increase by a mean of 4.6 °C for the period 2088⁻2099. Warming in winter was projected to be greater than warming in summer and spring. The number of days during which indoor AT will be categorized as potentially harmful will increase in the future. Understanding current and future heat-related health effects is key in developing an effective surveillance system. The observations of this study can be used to inform the development and implementation of policies and practices around heat and health especially in rural areas of South Africa.
Kleidon, Axel
2012-03-13
The Earth's chemical composition far from chemical equilibrium is unique in our Solar System, and this uniqueness has been attributed to the presence of widespread life on the planet. Here, I show how this notion can be quantified using non-equilibrium thermodynamics. Generating and maintaining disequilibrium in a thermodynamic variable requires the extraction of power from another thermodynamic gradient, and the second law of thermodynamics imposes fundamental limits on how much power can be extracted. With this approach and associated limits, I show that the ability of abiotic processes to generate geochemical free energy that can be used to transform the surface-atmosphere environment is strongly limited to less than 1 TW. Photosynthetic life generates more than 200 TW by performing photochemistry, thereby substantiating the notion that a geochemical composition far from equilibrium can be a sign for strong biotic activity. Present-day free energy consumption by human activity in the form of industrial activity and human appropriated net primary productivity is of the order of 50 TW and therefore constitutes a considerable term in the free energy budget of the planet. When aiming to predict the future of the planet, we first note that since global changes are closely related to this consumption of free energy, and the demands for free energy by human activity are anticipated to increase substantially in the future, the central question in the context of predicting future global change is then how human free energy demands can increase sustainably without negatively impacting the ability of the Earth system to generate free energy. This question could be evaluated with climate models, and the potential deficiencies in these models to adequately represent the thermodynamics of the Earth system are discussed. Then, I illustrate the implications of this thermodynamic perspective by discussing the forms of renewable energy and planetary engineering that would enhance the overall free energy generation and, thereby 'empower' the future of the planet.
NASA Technical Reports Server (NTRS)
Atlas, Robert
2004-01-01
The lack of adequate observational data continues to be recognized as a major factor limiting both atmospheric research and numerical prediction on a variety of temporal and spatial scales. Since the advent of meteorological satellites in the 1960's, a considerable research effort has been directed toward the design of space-borne meteorological sensors, the development of optimal methods for the utilization of these data, (and an assessment of the influence of existing satellite data and the potential influence of future satellite observations on numerical weather prediction. This has included both Observing System Experiments (OSEs) and Observing System Simulation Experiments (OSSEs). OSEs are conducted to evaluate the impact of specific observations or classes of observations on analyses and forecasts. While OSEs are performed with existing data, OSSEs are conducted to evaluate the potential for future observing systems to improve-NWP, as well as to evaluate trade-offs in observing system design, and to develop and test improved methods for data assimilation. At the conference, results from OSEs to evaluate satellite data sets that have recently become available to the global observing system, such as AIRS and Seawinds, and results from OSSEs to determine the potential impact of space-based lidar winds will be presented.
Quantifying the global contribution of alcohol consumption to cardiomyopathy.
Manthey, Jakob; Imtiaz, Sameer; Neufeld, Maria; Rylett, Margaret; Rehm, Jürgen
2017-05-25
The global impact of alcohol consumption on deaths due to cardiomyopathy (CM) has not been quantified to date, even though CM contains a subcategory for alcoholic CM with an effect of heavy drinking over time as the postulated underlying causal mechanism. In this feasibility study, a model to estimate the alcohol-attributable fraction (AAF) of CM deaths based on alcohol exposure measures is proposed. A two-step model was developed based on aggregate-level data from 95 countries, including the most populous (data from 2013 or last available year). First, the crude mortality rate of alcoholic CM per 1,000,000 adults was predicted using a negative binomial regression based on prevalence of alcohol use disorders (AUD) and adult alcohol per capita consumption (APC) (n = 52 countries). Second, the proportion of alcoholic CM among all CM deaths (i.e., AAF) was predicted using a fractional response probit regression with alcoholic CM crude mortality rate (from Step 1), AUD prevalence, APC per drinker, and Global Burden of Disease region as predictions. Additional models repeated these steps by sex and for the wider Global Burden of Disease study definition of CM. There were strong correlations (>0.9) between the crude mortality rate of alcoholic CM and the AAFs, supporting the modeling strategy. In the first step, the population-weighted mean crude mortality rate was estimated at 8.4 alcoholic CM deaths per 1,000,000 (95% CI: 7.4-9.3). In the second step, the global AAFs were estimated at 6.9% (95% CI: 5.4-8.4%). Sex-specific figures suggested a lower AAF among females (2.9%, 95% CI: 2.3-3.4%) as compared to males (8.9%, 95% CI: 7.0-10.7%). Larger deviations between observed and predicted AAFs were found in Eastern Europe and Central Asia. The model proposed promises to fill the gap to include AAFs for CM into comparative risk assessments in the future. These predictions likely will be underestimates because of the stigma involved in all fully alcohol-attributable conditions and subsequent problems in coding of alcoholic CM deaths.
Kurz, Werner A; Stinson, Graham; Rampley, Gregory J; Dymond, Caren C; Neilson, Eric T
2008-02-05
A large carbon sink in northern land surfaces inferred from global carbon cycle inversion models led to concerns during Kyoto Protocol negotiations that countries might be able to avoid efforts to reduce fossil fuel emissions by claiming large sinks in their managed forests. The greenhouse gas balance of Canada's managed forest is strongly affected by naturally occurring fire with high interannual variability in the area burned and by cyclical insect outbreaks. Taking these stochastic future disturbances into account, we used the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to project that the managed forests of Canada could be a source of between 30 and 245 Mt CO(2)e yr(-1) during the first Kyoto Protocol commitment period (2008-2012). The recent transition from sink to source is the result of large insect outbreaks. The wide range in the predicted greenhouse gas balance (215 Mt CO(2)e yr(-1)) is equivalent to nearly 30% of Canada's emissions in 2005. The increasing impact of natural disturbances, the two major insect outbreaks, and the Kyoto Protocol accounting rules all contributed to Canada's decision not to elect forest management. In Canada, future efforts to influence the carbon balance through forest management could be overwhelmed by natural disturbances. Similar circumstances may arise elsewhere if global change increases natural disturbance rates. Future climate mitigation agreements that do not account for and protect against the impacts of natural disturbances, for example, by accounting for forest management benefits relative to baselines, will fail to encourage changes in forest management aimed at mitigating climate change.
Coupling of pollination services and coffee suitability under climate change.
Imbach, Pablo; Fung, Emily; Hannah, Lee; Navarro-Racines, Carlos E; Roubik, David W; Ricketts, Taylor H; Harvey, Celia A; Donatti, Camila I; Läderach, Peter; Locatelli, Bruno; Roehrdanz, Patrick R
2017-09-26
Climate change will cause geographic range shifts for pollinators and major crops, with global implications for food security and rural livelihoods. However, little is known about the potential for coupled impacts of climate change on pollinators and crops. Coffee production exemplifies this issue, because large losses in areas suitable for coffee production have been projected due to climate change and because coffee production is dependent on bee pollination. We modeled the potential distributions of coffee and coffee pollinators under current and future climates in Latin America to understand whether future coffee-suitable areas will also be suitable for pollinators. Our results suggest that coffee-suitable areas will be reduced 73-88% by 2050 across warming scenarios, a decline 46-76% greater than estimated by global assessments. Mean bee richness will decline 8-18% within future coffee-suitable areas, but all are predicted to contain at least 5 bee species, and 46-59% of future coffee-suitable areas will contain 10 or more species. In our models, coffee suitability and bee richness each increase (i.e., positive coupling) in 10-22% of future coffee-suitable areas. Diminished coffee suitability and bee richness (i.e., negative coupling), however, occur in 34-51% of other areas. Finally, in 31-33% of the future coffee distribution areas, bee richness decreases and coffee suitability increases. Assessing coupled effects of climate change on crop suitability and pollination can help target appropriate management practices, including forest conservation, shade adjustment, crop rotation, or status quo, in different regions.
NASA Astrophysics Data System (ADS)
Weissert, Helmut
2013-04-01
With the beginning of the fossil fuel age in the 19th century mankind has become an important geological agent on a global scale. For the first time in human history action of man has an impact on global biogeochemical cycles. Increasing CO2 concentrations will result in a perturbation of global carbon cycling coupled with climate change. Investigations of past changes in carbon cycling and in climate will improve our predictions of future climate. Increasing atmospheric CO2 concentrations will drive climate into a mode of operation, which may resemble climate conditions in the deep geological past. Pliocene climate will give insight into 400ppm world with higher global sea level than today. Doubling of pre-industrial atmospheric CO2 levels will shift the climate system into a state resembling greenhouse climate in the Early Cenozoic or even in the Cretaceous. Carbon isotope geochemistry serves as tool for tracing the pathway of the carbon cycle through geological time. Globally registered negative C-isotope anomalies in the C-isotope record are interpreted as signatures of rapid addition (103 to a few 104 years) of CO2 to the ocean-atmosphere system. Positive C-isotope excursions following negative spikes record the slow post-perturbation recovery of the biosphere at time scales of 105 to 106 years. Duration of C-cycle perturbations in earth history cannot be directly compared with rapid perturbation characterizing the Anthropocene. However, the investigation of greenhouse pulses in the geological past provides insight into different climate states, it allows to identify tipping points in past climate systems and it offers the opportunity to learn about response reactions of the biosphere to rapid changes in global carbon cycling. Sudden injection of massive amounts of carbon dioxide into the atmosphere is recorded in C-isotope record of the Early Cretaceous. The Aptian carbon cycle perturbation triggered changes in temperature and in global hydrological cycling. Changes in physical and chemical oceanography are reflected in widespread black shale deposition ("Oceanic Anoxic Event 1a"), in carbonate platform drowning and in biocalcification crises. "Days of future passed" (Moody Blues, 1967) reminds us that the past provides essential information needed for decisions to be made in the interest of mankind's future.
Future of endemic flora of biodiversity hotspots in India.
Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi
2014-01-01
India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models.
Future of Endemic Flora of Biodiversity Hotspots in India
Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi
2014-01-01
India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models. PMID:25501852
NASA Astrophysics Data System (ADS)
Bernardes, S.
2016-12-01
Global coupled carbon-climate simulations show considerable variability in outputs for atmospheric and land fields over the 21st century. This variability includes changes in temperature and in the quantity and spatiotemporal distribution of precipitation for large regions on the planet. Studies have considered that reductions in water availability due to decreased precipitation and increased water demand by the atmosphere may negatively affect plant metabolism and reduce carbon uptake. Future increases in carbon dioxide concentrations are expected to affect those interactions and potentially offset reductions in productivity. It is uncertain how plants will adjust their water use efficiency (WUE, plant production per water loss by evapotranspiration) in response to changing environmental conditions. This work investigates predicted changes in WUE in the 21st century by analyzing an ensemble of Earth System Models from the Coupled Model Intercomparison Project 5 (CMIP5), together with flux tower data and products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Two representative concentration pathways were selected to describe possible climate futures (RCP4.5 and RCP8.5). Periods of analysis included 2006-2099 (predicted) and 1850-2005 (reference). Comparisons between modeled, flux and satellite data for IPCC SREX regions were used to address the significant intermodel variability observed for the CMIP5 ensemble (larger variability for RCP8.5, higher intermodel agreement in Southeast Asia, lower intermodel agreement in arid areas). Model skill was evaluated in support of model selection and the spatiotemporal analysis of changes in WUE. Global, regional and latitudinal distributions of departures of projected conditions in relation to historical values are presented for both concentration pathways. Results showed high model sensitivity to different concentration pathways and increase in GPP and WUE for most of the planet (increases consistently higher for RCP8.5). Higher increases in GPP and WUE are predicted to occur over higher latitudes in the northern hemisphere (boreal region), with WUE usually following GPP in changes. Decreases in productivity and WUE occur mostly in the tropics, affecting tropical forests in Central America and in the Amazon.
Nuclear masses far from stability: the interplay of theory and experiment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Haustein, P.E.
1985-01-01
Mass models seek, by a variety of theoretical approaches, to reproduce the measured mass surface and to predict unmeasured masses beyond it. Subsequent measurements of these predicted nuclear masses permit an assessment of the quality of the mass predictions from the various models. Since the last comprehensive revision of the mass predictions (in the mid-to-late 1970's) over 300 new masses have been reported. Global analyses of these data have been performed by several numerical and graphical methods. These have identified both the strengths and weaknesses of the models. In some cases failures in individual models are distinctly apparent when themore » new mass data are plotted as functions of one or more selected physical parameters. Several examples will be given. Future theoretical efforts will also be discussed.« less
NASA Astrophysics Data System (ADS)
Plag, H.-P.
2009-04-01
Local Sea Level (LSL) rise is one of the major anticipated impacts of future global warming. In many low-lying and often subsiding coastal areas, an increase of local sea-surface height is likely to increase the hazards of storm surges and hurricances and to lead to major inundation. Single major disasters due to storm surges and hurricanes hitting densely populated urban areas are estimated to inflict losses in excess of 100 billion. Decision makers face a trade-off between imposing the very high costs of coastal protection, mitigation and adaptation upon today's national economies and leaving the costs of potential major disasters to future generations. Risk and vulnerability assessments in support of informed decisions require as input predictions of the range of future LSL rise with reliable estimates of uncertainties. Secular changes in LSL are the result of a mix of location-dependent factors including ocean temperature and salinity changes, ocean and atmospheric circulation changes, mass exchange of the ocean with terrestrial water storage and the cryosphere, and vertical land motion. Current aleatory uncertainties in observations relevant to past and current LSL changes combined with epistemic uncertainties in some of the forcing functions for LSL changes produce a large range of plausible future LSL trajectories. This large range hampers the development of reasonable mitigation and adaptation strategies in the coastal zone. A detailed analysis of the uncertainties helps to answer the question what and how observations could help to reduce the uncertainties. The analysis shows that the Global Geodetic Observing System (GGOS) provides valuable observations and products towards this goal. Observations of the large ice sheets can improve the constraints on the current mass balance of the cryosphere and support cryosphere model validation. Vertical land motion close to melting ice sheets are highly relevant in the validation of models for the elastic response of the Earth to glacial deloading. Combination of satellite gravity mission with ground-based observations of gravity and vertical land motion in areas with significant mass changes (both in cryosphere, land water storage, and ocean) could help to improve models of the global water and energy cycle, which ultimately improves the understanding of current LSL changes. For LSL projections, local vertical land motion given in a reference frame tied to the center of mass is an important input, which currently contributes significantly to the error budget of LSL predictions. Improvements of the terrestrial reference frame would reduce this error contribution.
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.
Changing climate in Hungary and trends in the annual number of heat stress days
NASA Astrophysics Data System (ADS)
Solymosi, Norbert; Torma, Csaba; Kern, Anikó; Maróti-Agóts, Ákos; Barcza, Zoltán; Könyves, László; Berke, Olaf; Reiczigel, Jenő
2010-07-01
Global climate change can have serious direct effects on animal health and production through heat stress. In Hungary, the number of heat stress days per year (YNHD), i.e., days when the temperature humidity index (THI) is above a specific comfort threshold, has increased in recent years based on observed meteorological data. Between 1973 and 2008, the countrywide average increase in YNHD was 4.1% per year. Climate scenarios based on regional climate models (RCM) were used to predict possible changes in YNHD for the near future (2021-2050) relative to the reference period (1961-1990). This comparison shows that, in Hungary, the 30-year mean of YNHD is expected to increase by between 1 and 27 days, depending on the RCM used. Half of the scenarios investigated in this study predicted that, in large parts of Hungary, YNHD will increase by at least 1 week. However, the increase observed in the past, and that predicted for the near future, is spatially heterogeneous, and areas that currently have large cattle populations are expected to be affected more severely than other regions.
NASA Technical Reports Server (NTRS)
Leprovost, Christian; Mazzega, P.; Vincent, P.
1991-01-01
Ocean tides must be considered in many scientific disciplines: astronomy, oceanography, geodesy, geophysics, meteorology, and space technologies. Progress in each of these disciplines leads to the need for greater knowledge and more precise predictions of the ocean tide contribution. This is particularly true of satellite altimetry. On one side, the present and future satellite altimetry missions provide and will supply new data that will contribute to the improvement of the present ocean tide solutions. On the other side, tidal corrections included in the Geophysical Data Records must be determined with the maximum possible accuracy. The valuable results obtained with satellite altimeter data thus far have not been penalized by the insufficiencies of the present ocean tide predictions included in the geophysical data records (GDR's) because the oceanic processes investigated have shorter wavelengths than the error field of the tidal predictions, so that the residual errors of the tidal corrections are absorbed in the empirical tilt and bias corrections of the satellite orbit. For future applications to large-scale oceanic phenomena, however, it will no longer be possible to ignore these insufficiencies.
Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity.
Swann, Abigail L S; Hoffman, Forrest M; Koven, Charles D; Randerson, James T
2016-09-06
Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.
Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity
Koven, Charles D.; Randerson, James T.
2016-01-01
Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment. PMID:27573831
NASA Astrophysics Data System (ADS)
Bauters, Marijn; Bruneel, Stijn; Demol, Miro; Taveirne, Cys; Van Der Heyden, Dries; Boeckx, Pascal; Kearsley, Elizabeth; Cizungu, Landry; Verbeeck, Hans
2016-04-01
Tropical forests are key actors in the global carbon cycle. Predicting future responses of these forests to global change is challenging, but important for global climate models. However, our current understanding of such responses is limited, due to the complexity of forest ecosystems and the slow dynamics that inherently form these systems. Our understanding of ecosystem ecology and functioning could greatly benefit from experimental setups including strong environmental gradients in the tropics, as found on altitudinal transects. We setup two such transects in both South-America and Africa, focussing on shifts in carbon allocation, forest structure and functional composition. By a cross-continental comparison of both transects, we will gain insight in how different or alike both tropical forests biomes are in their responses, and how universal the observed adaption mechanisms are.
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.
Busch, Susan; Kirillin, Georgiy; Mehner, Thomas
2012-09-01
We used a coupled lake physics and bioenergetics-based foraging model to evaluate how the plasticity in habitat use modifies the seasonal metabolic response of two sympatric cold-water fishes (vendace and Fontane cisco, Coregonus spp.) under a global warming scenario for the year 2100. In different simulations, the vertically migrating species performed either a plastic strategy (behavioral thermoregulation) by shifting their population depth at night to maintain the temperatures occupied at current in-situ observations, or a fixed strategy (no thermoregulation) by keeping their occupied depths at night but facing modified temperatures. The lake physics model predicted higher temperatures above 20 m and lower temperatures below 20 m in response to warming. Using temperature-zooplankton relationships, the density of zooplankton prey was predicted to increase at the surface, but to decrease in hypolimnetic waters. Simulating the fixed strategy, growth was enhanced only for the deeper-living cisco due to the shift in thermal regime at about 20 m. In contrast, simulating the plastic strategy, individual growth of cisco and young vendace was predicted to increase compared to growth currently observed in the lake. Only growth rates of older vendace are reduced under future global warming scenarios irrespective of the behavioral strategy. However, performing behavioral thermoregulation would drive both species into the same depth layers, and hence will erode vertical microhabitat segregation and intensify inter-specific competition between the coexisting coregonids.
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.
Precipitation in the Karakoram-Himalaya: a CMIP5 view
NASA Astrophysics Data System (ADS)
Palazzi, Elisa; von Hardenberg, Jost; Terzago, Silvia; Provenzale, Antonello
2015-07-01
This work analyzes the properties of precipitation in the Hindu-Kush Karakoram Himalaya region as simulated by thirty-two state-of-the-art global climate models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5). We separately consider the Hindu-Kush Karakoram (HKK) in the west and the Himalaya in the east. These two regions are characterized by different precipitation climatologies, which are associated with different circulation patterns. Historical model simulations are compared with the Climate Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) precipitation data in the period 1901-2005. Future precipitation is analyzed for the two representative concentration pathways (RCP) RCP 4.5 and RCP 8.5 scenarios. We find that the multi-model ensemble mean and most individual models exhibit a wet bias with respect to CRU and GPCC observations in both regions and for all seasons. The models differ greatly in the seasonal climatology of precipitation which they reproduce in the HKK. The CMIP5 models predict wetter future conditions in the Himalaya in summer, with a gradual precipitation increase throughout the 21st century. Wetter summer future conditions are also predicted by most models in the RCP 8.5 scenario for the HKK, while on average no significant change can be detected in winter precipitation for both regions. In general, no single model (or group of models) emerges as that providing the best results for all the statistics considered, and the large spread in the behavior of individual models suggests to consider multi-model ensemble means with extreme care.
Influence of internal variability on population exposure to hydroclimatic changes
NASA Astrophysics Data System (ADS)
Mankin, Justin S.; Viviroli, Daniel; Mekonnen, Mesfin M.; Hoekstra, Arjen Y.; Horton, Radley M.; E Smerdon, Jason; Diffenbaugh, Noah S.
2017-04-01
Future freshwater supply, human water demand, and people’s exposure to water stress are subject to multiple sources of uncertainty, including unknown future pathways of fossil fuel and water consumption, and ‘irreducible’ uncertainty arising from internal climate system variability. Such internal variability can conceal forced hydroclimatic changes on multi-decadal timescales and near-continental spatial-scales. Using three projections of population growth, a large ensemble from a single Earth system model, and assuming stationary per capita water consumption, we quantify the likelihoods of future population exposure to increased hydroclimatic deficits, which we define as the average duration and magnitude by which evapotranspiration exceeds precipitation in a basin. We calculate that by 2060, ∽31%-35% of the global population will be exposed to >50% probability of hydroclimatic deficit increases that exceed existing hydrological storage, with up to 9% of people exposed to >90% probability. However, internal variability, which is an irreducible uncertainty in climate model predictions that is under-sampled in water resource projections, creates substantial uncertainty in predicted exposure: ∽86%-91% of people will reside where irreducible uncertainty spans the potential for both increases and decreases in sub-annual water deficits. In one population scenario, changes in exposure to large hydroclimate deficits vary from -3% to +6% of global population, a range arising entirely from internal variability. The uncertainty in risk arising from irreducible uncertainty in the precise pattern of hydroclimatic change, which is typically conflated with other uncertainties in projections, is critical for climate risk management that seeks to optimize adaptations that are robust to the full set of potential real-world outcomes.
Increased wind risk from sting-jet windstorms with climate change
NASA Astrophysics Data System (ADS)
Martínez-Alvarado, Oscar; Gray, Suzanne L.; Hart, Neil C. G.; Clark, Peter A.; Hodges, Kevin; Roberts, Malcolm J.
2018-04-01
Extra-tropical cyclones dominate autumn and winter weather over western Europe. The strongest cyclones, often termed windstorms, have a large socio-economic impact on landfall due to strong surface winds and coastal storm surges. Climate model integrations have predicted a future increase in the frequency of, and potential damage from, European windstorms and yet these integrations cannot properly represent localised jets, such as sting jets, that may significantly enhance damage. Here we present the first prediction of how the climatology of sting-jet-containing cyclones will change in a future warmer climate, considering the North Atlantic and Europe. A proven sting-jet precursor diagnostic is applied to 13 year present-day and future (~2100) climate integrations from the Met Office Unified Model in its Global Atmosphere 3.0 configuration. The present-day climate results are consistent with previously-published results from a reanalysis dataset (with around 32% of cyclones exhibiting the sing-jet precursor), lending credibility to the analysis of the future-climate integration. The proportion of cyclones exhibiting the sting-jet precursor in the future-climate integration increases to 45%. Furthermore, while the proportion of explosively-deepening storms increases only slightly in the future climate, the proportion of those storms with the sting-jet precursor increases by 60%. The European resolved-wind risk associated with explosively-deepening storms containing a sting-jet precursor increases substantially in the future climate; in reality this wind risk is likely to be further enhanced by the release of localised moist instability, unresolved by typical climate models.
How NASA Sees the Earth and Its Climate
NASA Technical Reports Server (NTRS)
BrowndeColstoun, Eric
2012-01-01
NASA Research Addresses Broad Questions: (1) How are global ecosystems changing? (2) What changes are occurring in global land cover and land use and what are their causes? (3) How is the Earth s surface being transformed and how can such information be used to predict future changes? (4) What are the consequences of land cover and land use change for the sustainability of ecosystems and economic productivity? NASA uses the view from above to monitor our changing home. Different satellites help us study the various systems of the Earth. No one system can do it all. NASA tools and science helps us to understand how the planet is changing and what the changes mean for us.
Franchise medicine: how I avoid being a commodity in a global market.
Constantinides, Minas
2010-02-01
As facial plastic surgery becomes more global, pressures for practices to become commoditized will increase. Commoditized practices are those in which price drives the quality of the product. Franchised surgical practices have also recently increased within the United States and abroad. These are always commoditized by their corporate philosophies. There are better ways to create value than to lower price to compete with a neighboring practice. By establishing a Transcendent Relationship of growth, both the surgeon and the patient are more satisfied with their facial plastic surgical experiences. Key tools helpful in predicting future directions for a practice, the Four Compass Points and the Average Best Patient, will be introduced. Thieme Medical Publishers.
Jacobsen, Kathryn H; Aguirre, A Alonso; Bailey, Charles L; Baranova, Ancha V; Crooks, Andrew T; Croitoru, Arie; Delamater, Paul L; Gupta, Jhumka; Kehn-Hall, Kylene; Narayanan, Aarthi; Pierobon, Mariaelena; Rowan, Katherine E; Schwebach, J Reid; Seshaiyer, Padmanabhan; Sklarew, Dann M; Stefanidis, Anthony; Agouris, Peggy
2016-03-01
As the Ebola outbreak in West Africa wanes, it is time for the international scientific community to reflect on how to improve the detection of and coordinated response to future epidemics. Our interdisciplinary team identified key lessons learned from the Ebola outbreak that can be clustered into three areas: environmental conditions related to early warning systems, host characteristics related to public health, and agent issues that can be addressed through the laboratory sciences. In particular, we need to increase zoonotic surveillance activities, implement more effective ecological health interventions, expand prediction modeling, support medical and public health systems in order to improve local and international responses to epidemics, improve risk communication, better understand the role of social media in outbreak awareness and response, produce better diagnostic tools, create better therapeutic medications, and design better vaccines. This list highlights research priorities and policy actions the global community can take now to be better prepared for future emerging infectious disease outbreaks that threaten global public health and security.
Venice: Fifty years after the great flood of November 4, 1966
NASA Astrophysics Data System (ADS)
Rizzoli, P. M.
2017-12-01
Fifty years ago Venice and its lagoon suffered the most devastating flood in their millennial history. The causes of the increasingly recurring floods will be examined, namely the man-induced subsidence in the period 1925-1970 and the storm surges of the Adriatic sea. The engineering solution designed for their protection , named the MOSE system, will be discussed in detail. The MOSE was started in 2003 and is near completion. It consists of four barriers , invisible in normal conditions, which will close the inlets to the lagoon under the prediction of a forthcoming flood. Finally, the perspective of the MOSE capability of protecting the city under scenarios of future global sea level rise will be assessed. This assessment must critically take into account that Venice and its lagoon are confined in the northernmost corner of the semi-enclosed, marginal Mediterranean sea for which the uncertainties of future sea level rise greatly exceed the uncertainties of the global averages.
NASA Astrophysics Data System (ADS)
Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin
2010-09-01
After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.
Lebourgeois, François; Pierrat, Jean-Claude; Perez, Vincent; Piedallu, Christian; Cecchini, Sébastien; Ulrich, Erwin
2010-09-01
After modeling the large-scale climate response patterns of leaf unfolding, leaf coloring and growing season length of evergreen and deciduous French temperate trees, we predicted the effects of eight future climate scenarios on phenological events. We used the ground observations from 103 temperate forests (10 species and 3,708 trees) from the French Renecofor Network and for the period 1997-2006. We applied RandomForest algorithms to predict phenological events from climatic and ecological variables. With the resulting models, we drew maps of phenological events throughout France under present climate and under two climatic change scenarios (A2, B2) and four global circulation models (HadCM3, CGCM2, CSIRO2 and PCM). We compared current observations and predicted values for the periods 2041-2070 and 2071-2100. On average, spring development of oaks precedes that of beech, which precedes that of conifers. Annual cycles in budburst and leaf coloring are highly correlated with January, March-April and October-November weather conditions through temperature, global solar radiation or potential evapotranspiration depending on species. At the end of the twenty-first century, each model predicts earlier budburst (mean: 7 days) and later leaf coloring (mean: 13 days) leading to an average increase in the growing season of about 20 days (for oaks and beech stands). The A2-HadCM3 hypothesis leads to an increase of up to 30 days in many areas. As a consequence of higher predicted warming during autumn than during winter or spring, shifts in leaf coloring dates appear greater than trends in leaf unfolding. At a regional scale, highly differing climatic response patterns were observed.
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.
Global Crop Yields, Climatic Trends and Technology Enhancement
NASA Astrophysics Data System (ADS)
Najafi, E.; Devineni, N.; Khanbilvardi, R.; Kogan, F.
2016-12-01
During the last decades the global agricultural production has soared up and technology enhancement is still making positive contribution to yield growth. However, continuing population, water crisis, deforestation and climate change threaten the global food security. Attempts to predict food availability in the future around the world can be partly understood from the impact of changes to date. A new multilevel model for yield prediction at the country scale using climate covariates and technology trend is presented in this paper. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling and/or clustering to automatically group and reduce estimation uncertainties. El Niño Southern Oscillation (ENSO), Palmer Drought Severity Index (PDSI), Geopotential height (GPH), historical CO2 level and time-trend as a relatively reliable approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2007. Results show that these indicators can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications.
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.
Langer, Martin R.; Weinmann, Anna E.; Lötters, Stefan; Bernhard, Joan M.; Rödder, Dennis
2013-01-01
Species-range expansions are a predicted and realized consequence of global climate change. Climate warming and the poleward widening of the tropical belt have induced range shifts in a variety of marine and terrestrial species. Range expansions may have broad implications on native biota and ecosystem functioning as shifting species may perturb recipient communities. Larger symbiont-bearing foraminifera constitute ubiquitous and prominent components of shallow water ecosystems, and range shifts of these important protists are likely to trigger changes in ecosystem functioning. We have used historical and newly acquired occurrence records to compute current range shifts of Amphistegina spp., a larger symbiont-bearing foraminifera, along the eastern coastline of Africa and compare them to analogous range shifts currently observed in the Mediterranean Sea. The study provides new evidence that amphisteginid foraminifera are rapidly progressing southwestward, closely approaching Port Edward (South Africa) at 31°S. To project future species distributions, we applied a species distribution model (SDM) based on ecological niche constraints of current distribution ranges. Our model indicates that further warming is likely to cause a continued range extension, and predicts dispersal along nearly the entire southeastern coast of Africa. The average rates of amphisteginid range shift were computed between 8 and 2.7 km year−1, and are projected to lead to a total southward range expansion of 267 km, or 2.4° latitude, in the year 2100. Our results corroborate findings from the fossil record that some larger symbiont-bearing foraminifera cope well with rising water temperatures and are beneficiaries of global climate change. PMID:23405081
Langer, Martin R; Weinmann, Anna E; Lötters, Stefan; Bernhard, Joan M; Rödder, Dennis
2013-01-01
Species-range expansions are a predicted and realized consequence of global climate change. Climate warming and the poleward widening of the tropical belt have induced range shifts in a variety of marine and terrestrial species. Range expansions may have broad implications on native biota and ecosystem functioning as shifting species may perturb recipient communities. Larger symbiont-bearing foraminifera constitute ubiquitous and prominent components of shallow water ecosystems, and range shifts of these important protists are likely to trigger changes in ecosystem functioning. We have used historical and newly acquired occurrence records to compute current range shifts of Amphistegina spp., a larger symbiont-bearing foraminifera, along the eastern coastline of Africa and compare them to analogous range shifts currently observed in the Mediterranean Sea. The study provides new evidence that amphisteginid foraminifera are rapidly progressing southwestward, closely approaching Port Edward (South Africa) at 31°S. To project future species distributions, we applied a species distribution model (SDM) based on ecological niche constraints of current distribution ranges. Our model indicates that further warming is likely to cause a continued range extension, and predicts dispersal along nearly the entire southeastern coast of Africa. The average rates of amphisteginid range shift were computed between 8 and 2.7 km year(-1), and are projected to lead to a total southward range expansion of 267 km, or 2.4° latitude, in the year 2100. Our results corroborate findings from the fossil record that some larger symbiont-bearing foraminifera cope well with rising water temperatures and are beneficiaries of global climate change.
Abolafya, Moris; Onmuş, Ortaç; Şekercioğlu, Çağan H.; Bilgin, Raşit
2013-01-01
In this study, we evaluated the potential impact of climate change on the distributions of Turkey’s songbirds in the 21st century by modelling future distributions of 20 resident and nine migratory species under two global climate change scenarios. We combined verified data from an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic variables to estimate species distributions and projections for future time periods. Model predictions for resident and migratory species showed high variability, with some species projected to lose and others projected to gain suitable habitat. Our study helps improve the understanding of the current and potential future distributions of Turkey’s songbirds and their responses to climate change, highlights effective strategies to maximize avian conservation efforts in the study region, and provides a model for using citizen science data for biodiversity research in a large developing country with few professional field biologists. Our results demonstrate that climate change will not affect every species equally in Turkey. Expected range reductions in some breeding species will increase the risk of local extinction, whereas others are likely to expand their ranges. PMID:23844151
Abolafya, Moris; Onmuş, Ortaç; Şekercioğlu, Çağan H; Bilgin, Raşit
2013-01-01
In this study, we evaluated the potential impact of climate change on the distributions of Turkey's songbirds in the 21st century by modelling future distributions of 20 resident and nine migratory species under two global climate change scenarios. We combined verified data from an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic variables to estimate species distributions and projections for future time periods. Model predictions for resident and migratory species showed high variability, with some species projected to lose and others projected to gain suitable habitat. Our study helps improve the understanding of the current and potential future distributions of Turkey's songbirds and their responses to climate change, highlights effective strategies to maximize avian conservation efforts in the study region, and provides a model for using citizen science data for biodiversity research in a large developing country with few professional field biologists. Our results demonstrate that climate change will not affect every species equally in Turkey. Expected range reductions in some breeding species will increase the risk of local extinction, whereas others are likely to expand their ranges.
Paths to future growth in photovoltaics manufacturing
Basore, Paul A.
2016-03-01
The past decade has seen rapid growth in the photovoltaics industry, followed in the past few years by a period of much slower growth. A simple model that is consistent with this historical record can be used to predict the future evolution of the industry. Two key parameters are identified that determine the outcome. One is the annual global investment in manufacturing capacity normalized to the manufacturing capacity for the previous year (capacity-normalized capital investment rate, CapIR, units dollar/W). The other is how much capital investment is required for each watt of annual manufacturing capacity, normalized to the service lifemore » of the assets (capacity-normalized capital demand rate, CapDR, units dollar/W). If these two parameters remain unchanged from the values they have held for the past few years, global manufacturing capacity will peak in the next few years and then decline. However, it only takes a modest improvement in CapIR to ensure future growth in photovoltaics. Here, several approaches are presented that can enable the required improvement in CapIR. If, in addition, there is an accompanying improvement in CapDR, the rate of growth can be substantially accelerated.« less
Coral reef resilience through biodiversity
Rogers, Caroline S.
2013-01-01
Irrefutable evidence of coral reef degradation worldwide and increasing pressure from rising seawater temperatures and ocean acidification associated with climate change have led to a focus on reef resilience and a call to “manage” coral reefs for resilience. Ideally, global action to reduce emission of carbon dioxide and other greenhouse gases will be accompanied by local action. Effective management requires reduction of local stressors, identification of the characteristics of resilient reefs, and design of marine protected area networks that include potentially resilient reefs. Future research is needed on how stressors interact, on how climate change will affect corals, fish, and other reef organisms as well as overall biodiversity, and on basic ecological processes such as connectivity. Not all reef species and reefs will respond similarly to local and global stressors. Because reef-building corals and other organisms have some potential to adapt to environmental changes, coral reefs will likely persist in spite of the unprecedented combination of stressors currently affecting them. The biodiversity of coral reefs is the basis for their remarkable beauty and for the benefits they provide to society. The extraordinary complexity of these ecosystems makes it both more difficult to predict their future and more likely they will have a future.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wehner, Michael; ., Prabhat; Reed, Kevin A.
The four idealized configurations of the U.S. CLIVAR Hurricane Working Group are integrated using the global Community Atmospheric Model version 5.1 at two different horizontal resolutions, approximately 100 and 25 km. The publicly released 0.9° × 1.3° configuration is a poor predictor of the sign of the 0.23° × 0.31° model configuration’s change in the total number of tropical storms in a warmer climate. However, it does predict the sign of the higher-resolution configuration’s change in the number of intense tropical cyclones in a warmer climate. In the 0.23° × 0.31° model configuration, both increased CO 2 concentrations and elevatedmore » sea surface temperature (SST) independently lower the number of weak tropical storms and shorten their average duration. Conversely, increased SST causes more intense tropical cyclones and lengthens their average duration, resulting in a greater number of intense tropical cyclone days globally. Increased SST also increased maximum tropical storm instantaneous precipitation rates across all storm intensities. It was found that while a measure of maximum potential intensity based on climatological mean quantities adequately predicts the 0.23° × 0.31° model’s forced response in its most intense simulated tropical cyclones, a related measure of cyclogenesis potential fails to predict the model’s actual cyclogenesis response to warmer SSTs. These analyses lead to two broader conclusions: 1) Projections of future tropical storm activity obtained by a direct tracking of tropical storms simulated by coarse-resolution climate models must be interpreted with caution. 2) Projections of future tropical cyclogenesis obtained from metrics of model behavior that are based solely on changes in long-term climatological fields and tuned to historical records must also be interpreted with caution.« less
Marras, Stefano; Cucco, Andrea; Antognarelli, Fabio; Azzurro, Ernesto; Milazzo, Marco; Bariche, Michel; Butenschön, Momme; Kay, Susan; Di Bitetto, Massimiliano; Quattrocchi, Giovanni; Sinerchia, Matteo; Domenici, Paolo
2015-01-01
Global increase in sea temperatures has been suggested to facilitate the incoming and spread of tropical invaders. The increasing success of these species may be related to their higher physiological performance compared with indigenous ones. Here, we determined the effect of temperature on the aerobic metabolic scope (MS) of two herbivorous fish species that occupy a similar ecological niche in the Mediterranean Sea: the native salema (Sarpa salpa) and the invasive marbled spinefoot (Siganus rivulatus). Our results demonstrate a large difference in the optimal temperature for aerobic scope between the salema (21.8°C) and the marbled spinefoot (29.1°C), highlighting the importance of temperature in determining the energy availability and, potentially, the distribution patterns of the two species. A modelling approach based on a present-day projection and a future scenario for oceanographic conditions was used to make predictions about the thermal habitat suitability (THS, an index based on the relationship between MS and temperature) of the two species, both at the basin level (the whole Mediterranean Sea) and at the regional level (the Sicilian Channel, a key area for the inflow of invasive species from the Eastern to the Western Mediterranean Sea). For the present-day projection, our basin-scale model shows higher THS of the marbled spinefoot than the salema in the Eastern compared with the Western Mediterranean Sea. However, by 2050, the THS of the marbled spinefoot is predicted to increase throughout the whole Mediterranean Sea, causing its westward expansion. Nevertheless, the regional-scale model suggests that the future thermal conditions of Western Sicily will remain relatively unsuitable for the invasive species and could act as a barrier for its spread westward. We suggest that metabolic scope can be used as a tool to evaluate the potential invasiveness of alien species and the resilience to global warming of native species.
McCluney, Kevin E.; Belnap, Jayne; Collins, Scott L.; González, Angélica L.; Hagen, Elizabeth M.; Holland, J. Nathaniel; Kotler, Burt P.; Maestre, Fernando T.; Smith, Stanley D.; Wolf, Blair O.
2012-01-01
Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems.
Wehner, Michael; ., Prabhat; Reed, Kevin A.; ...
2015-05-12
The four idealized configurations of the U.S. CLIVAR Hurricane Working Group are integrated using the global Community Atmospheric Model version 5.1 at two different horizontal resolutions, approximately 100 and 25 km. The publicly released 0.9° × 1.3° configuration is a poor predictor of the sign of the 0.23° × 0.31° model configuration’s change in the total number of tropical storms in a warmer climate. However, it does predict the sign of the higher-resolution configuration’s change in the number of intense tropical cyclones in a warmer climate. In the 0.23° × 0.31° model configuration, both increased CO 2 concentrations and elevatedmore » sea surface temperature (SST) independently lower the number of weak tropical storms and shorten their average duration. Conversely, increased SST causes more intense tropical cyclones and lengthens their average duration, resulting in a greater number of intense tropical cyclone days globally. Increased SST also increased maximum tropical storm instantaneous precipitation rates across all storm intensities. It was found that while a measure of maximum potential intensity based on climatological mean quantities adequately predicts the 0.23° × 0.31° model’s forced response in its most intense simulated tropical cyclones, a related measure of cyclogenesis potential fails to predict the model’s actual cyclogenesis response to warmer SSTs. These analyses lead to two broader conclusions: 1) Projections of future tropical storm activity obtained by a direct tracking of tropical storms simulated by coarse-resolution climate models must be interpreted with caution. 2) Projections of future tropical cyclogenesis obtained from metrics of model behavior that are based solely on changes in long-term climatological fields and tuned to historical records must also be interpreted with caution.« less
Sishodia, Rajendra P; Shukla, Sanjay; Wani, Suhas P; Graham, Wendy D; Jones, James W
2018-09-01
Simultaneous effects of future climate and irrigation intensification on surface and groundwater systems are not well understood. Efforts are needed to understand the future groundwater availability and associated surface flows under business-as-usual management to formulate policy changes to improve water sustainability. We combine measurements with integrated modeling (MIKE SHE/MIKE11) to evaluate the effects of future climate (2040-2069), with and without irrigation expansion, on water levels and flows in an agricultural watershed in low-storage crystalline aquifer region of south India. Demand and supply management changes, including improved efficiency of irrigation water as well as energy uses, were evaluated. Increased future rainfall (7-43%, from 5 Global Climate Models) with no further expansion of irrigation wells increased the groundwater recharge (10-55%); however, most of the recharge moved out of watershed as increased baseflow (17-154%) with a small increase in net recharge (+0.2mm/year). When increased rainfall was considered with projected increase in irrigation withdrawals, both hydrologic extremes of well drying and flooding were predicted. A 100-year flow event was predicted to be a 5-year event in the future. If irrigation expansion follows the historical trends, earlier and more frequent well drying, a source of farmers' distress in India, was predicted to worsen in the future despite the recharge gains from increased rainfall. Storage and use of excess flows, improved irrigation efficiency with flood to drip conversion in 25% of irrigated area, and reduced energy subsidy (free electricity for 3.5h compared to 7h/day; $1 billion savings) provided sufficient water savings to support future expansion in irrigated areas while mitigating well drying as well as flooding. Reductions in energy subsidy to fund the implementation of economically desirable (high benefit-cost ratio) demand (drip irrigation) and supply (water capture and storage) management was recommended to achieve a sustainable food-water-energy nexus in semi-arid regions. Copyright © 2018 Elsevier B.V. All rights reserved.
Jennings, Simon; Collingridge, Kate
2015-01-01
Existing estimates of fish and consumer biomass in the world's oceans are disparate. This creates uncertainty about the roles of fish and other consumers in biogeochemical cycles and ecosystem processes, the extent of human and environmental impacts and fishery potential. We develop and use a size-based macroecological model to assess the effects of parameter uncertainty on predicted consumer biomass, production and distribution. Resulting uncertainty is large (e.g. median global biomass 4.9 billion tonnes for consumers weighing 1 g to 1000 kg; 50% uncertainty intervals of 2 to 10.4 billion tonnes; 90% uncertainty intervals of 0.3 to 26.1 billion tonnes) and driven primarily by uncertainty in trophic transfer efficiency and its relationship with predator-prey body mass ratios. Even the upper uncertainty intervals for global predictions of consumer biomass demonstrate the remarkable scarcity of marine consumers, with less than one part in 30 million by volume of the global oceans comprising tissue of macroscopic animals. Thus the apparently high densities of marine life seen in surface and coastal waters and frequently visited abundance hotspots will likely give many in society a false impression of the abundance of marine animals. Unexploited baseline biomass predictions from the simple macroecological model were used to calibrate a more complex size- and trait-based model to estimate fisheries yield and impacts. Yields are highly dependent on baseline biomass and fisheries selectivity. Predicted global sustainable fisheries yield increases ≈4 fold when smaller individuals (< 20 cm from species of maximum mass < 1 kg) are targeted in all oceans, but the predicted yields would rarely be accessible in practice and this fishing strategy leads to the collapse of larger species if fishing mortality rates on different size classes cannot be decoupled. Our analyses show that models with minimal parameter demands that are based on a few established ecological principles can support equitable analysis and comparison of diverse ecosystems. The analyses provide insights into the effects of parameter uncertainty on global biomass and production estimates, which have yet to be achieved with complex models, and will therefore help to highlight priorities for future research and data collection. However, the focus on simple model structures and global processes means that non-phytoplankton primary production and several groups, structures and processes of ecological and conservation interest are not represented. Consequently, our simple models become increasingly less useful than more complex alternatives when addressing questions about food web structure and function, biodiversity, resilience and human impacts at smaller scales and for areas closer to coasts.
The Tropical Rainfall Measuring (TRMM) - What Have We Learned and What Does the Future Hold?
NASA Technical Reports Server (NTRS)
Kummerow, C.; Hong, Y.; Olsen, W. S.
2000-01-01
Rainfall is important in the hydrological cycle and to the lives and welfare of humans. In addition to being a life-giving resource, rainfall processes also plays a crucial role in the dynamics of the global atmospheric circulation. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. It varies greatly in space and time. The rain-producing cloud systems may last several hours or days. Their dimensions range from 10 km to several hundred km. This makes it difficult to incorporate rainfall directly large-scale weather and climate models. Until the end of 1997, precipitation in the global tropics was not known to within a factor of two. Regarding "global warming", the various large-scale models differed among themselves in the predicted magnitude of the warming and in the expected regional effects of these temperature and moisture changes. The Tropical Rainfall Measuring Mission (TRMM) satellite has yielded important interim results related to rainfall observations, data assimilation and model forecast skills when rainfall data is assimilated. This talk will summarize where the TRMM science team is with regards to answering some of these important scientific challenges, as well as discuss the future Global Precipitation Mission which will provide 3 hourly rainfall coverage and offers some unique collaborative potential for NOAA and NASA.
In Forests Globally, Large Trees Suffer Most during Drought
NASA Astrophysics Data System (ADS)
Bennett, A. C.; McDowell, N. G.; Allen, C. D.; Anderson-Teixeira, K. J.
2014-12-01
Globally, drought events are increasing in both frequency and intensity. Spatial and temporal variation in water availability is expected to alter the ecophysiology and structure of forests, with consequent feedbacks to climate change. Extensive tree mortality induced by heat and aridity has been documented across a range of latitudes, and several global vegetation models have simulated widespread forest die-off in the future. The impact of drought on forest structure and function will depend on the differential responses of trees of different sizes. Understanding the size-dependence of drought-induced mortality is necessary to predict local and global impacts. Here we show that in forests worldwide, drought has a greater impact on the growth and mortality of large trees compared to smaller trees. This trend holds true for forests ranging from semiarid woodlands to tropical rainforests. This finding contrasts with what would be expected if deep root access to water were the primary determinant of tree drought response. Rather, the greater drought response of larger trees could be driven by greater inherent vulnerability of large trees to hydraulic stress or by canopy position becoming more of a liability under drought, as exposed crowns face higher evaporative demand. These findings imply that future droughts will have a disproportionate effect on large trees, resulting in a larger feedback to climate change than would occur if all tree size classes were equally affected by drought.
Ectomycorrhizal fungi slow soil carbon cycling.
Averill, Colin; Hawkes, Christine V
2016-08-01
Respiration of soil organic carbon is one of the largest fluxes of CO2 on earth. Understanding the processes that regulate soil respiration is critical for predicting future climate. Recent work has suggested that soil carbon respiration may be reduced by competition for nitrogen between symbiotic ectomycorrhizal fungi that associate with plant roots and free-living microbial decomposers, which is consistent with increased soil carbon storage in ectomycorrhizal ecosystems globally. However, experimental tests of the mycorrhizal competition hypothesis are lacking. Here we show that ectomycorrhizal roots and hyphae decrease soil carbon respiration rates by up to 67% under field conditions in two separate field exclusion experiments, and this likely occurs via competition for soil nitrogen, an effect larger than 2 °C soil warming. These findings support mycorrhizal competition for nitrogen as an independent driver of soil carbon balance and demonstrate the need to understand microbial community interactions to predict ecosystem feedbacks to global climate. © 2016 John Wiley & Sons Ltd/CNRS.
Forecast and control of epidemics in a globalized world
Hufnagel, L.; Brockmann, D.; Geisel, T.
2004-01-01
The rapid worldwide spread of severe acute respiratory syndrome demonstrated the potential threat an infectious disease poses in a closely interconnected and interdependent world. Here we introduce a probabilistic model that describes the worldwide spread of infectious diseases and demonstrate that a forecast of the geographical spread of epidemics is indeed possible. This model combines a stochastic local infection dynamics among individuals with stochastic transport in a worldwide network, taking into account national and international civil aviation traffic. Our simulations of the severe acute respiratory syndrome outbreak are in surprisingly good agreement with published case reports. We show that the high degree of predictability is caused by the strong heterogeneity of the network. Our model can be used to predict the worldwide spread of future infectious diseases and to identify endangered regions in advance. The performance of different control strategies is analyzed, and our simulations show that a quick and focused reaction is essential to inhibiting the global spread of epidemics. PMID:15477600
Towards an integrated set of surface meterological observations for climate science and applications
NASA Astrophysics Data System (ADS)
Dunn, Robert; Thorne, Peter
2017-04-01
We cannot predict what is not observed, and we cannot analyse what is not archived. To meet current scientific and societal demands, as well as future requirements for climate services, it is vital that the management and curation of land-based meteorological data holdings is improved. A comprehensive global set of data holdings, of known provenance, integrated across both climate variable and timescale are required to meet the wide range of user needs. Presently, the land-based holdings are highly fractured into global, region and national holdings for different variables and timescales, from a variety of sources, and in a mixture of formats. We present a high level overview, based on broad community input, of the steps that are required to bring about this integration and progress towards such a database. Any long-term, international, program creating such an integrated database will transform the our collective ability to provide societally relevant research, analysis and predictions across the globe.
Modeled climate-induced glacier change in Glacier National Park, 1850-2100
Hall, M.H.P.; Fagre, D.B.
2003-01-01
The glaciers in the Blackfoot-Jackson Glacier Basin of Glacier National Park, Montana, decreased in area from 21.6 square kilometers (km2) in 1850 to 7.4 km2 in 1979. Over this same period global temperatures increased by 0.45??C (?? 0. 15??C). We analyzed the climatic causes and ecological consequences of glacier retreat by creating spatially explicit models of the creation and ablation of glaciers and of the response of vegetation to climate change. We determined the melt rate and spatial distribution of glaciers under two possible future climate scenarios, one based on carbon dioxide-induced global warming and the other on a linear temperature extrapolation. Under the former scenario, all glaciers in the basin will disappear by the year 2030, despite predicted increases in precipitation; under the latter, melting is slower. Using a second model, we analyzed vegetation responses to variations in soil moisture and increasing temperature in a complex alpine landscape and predicted where plant communities are likely to be located as conditions change.
NASA Astrophysics Data System (ADS)
Metcalfe, D. B.; Fisher, R. A.; Wardle, D. A.
2011-03-01
Understanding the impacts of plant community characteristics on soil carbon dioxide efflux (R) is a key prerequisite for accurate prediction of the future carbon balance of terrestrial ecosystems under climate change. In this review, we synthesize relevant information from a wide spectrum of sources to evaluate the current state of knowledge about plant community effects on R, examine how this information is incorporated into global climate models, and highlight priorities for future research. Plant species consistently exhibit cohesive suites of traits, linked to contrasting life history strategies, which exert a variety of impacts on R. As such, we propose that plant community shifts towards dominance by fast growing plants with nutrient rich litter could provide a major, though often neglected, positive feedback to climate change. Within vegetation types, belowground carbon flux will mainly be controlled by photosynthesis, while amongst vegetation types this flux will be more dependent upon the specific characteristics of the plant life form. We also make the case that community composition, rather than diversity, is usually the dominant control on ecosystem processes in natural systems. Individual species impacts on R may be largest where the species accounts for most of the biomass in the ecosystem, has very distinct traits to the rest of the community, or modulates the occurrence of major natural disturbances. We show that climate-vegetation models incorporate a number of pathways whereby plants can affect R, but that simplifications regarding allocation schemes and drivers of litter decomposition may limit model accuracy. This situation could, however, be relatively easily improved with targeted experimental and field studies. Finally, we identify key gaps in knowledge and recommend them as priorities for future work. These include the patterns of photosynthate partitioning amongst belowground components, ecosystem level effects of individual plant traits, and the importance of trophic interactions and species invasions or extinctions for ecosystem processes. A final, overarching challenge is how to link these observations and drivers across spatio-temporal scales to predict regional or global changes in R over long time periods. A more unified approach to understanding R, which integrates information about plant traits and community dynamics, will be essential for better understanding, simulating and predicting feedbacks to R across terrestrial ecosystems and the earth-climate system.
Unbounded boundaries and shifting baselines: Estuaries and coastal seas in a rapidly changing world
NASA Astrophysics Data System (ADS)
Little, S.; Spencer, K. L.; Schuttelaars, H. M.; Millward, G. E.; Elliott, M.
2017-11-01
This Special Issue of Estuarine, Coastal and Shelf Science presents contributions from ECSA 55; an international symposium organised by the Estuarine and Coastal Sciences Association (ECSA) and Elsevier on the broad theme of estuaries and coastal seas in times of intense change. The objectives of the SI are to synthesise, hypothesise and illustrate the impacts of global change on estuaries and coastal seas through learning lessons from the past, discussing the current and forecasting for the future. It is highlighted here that establishing impacts and assigning cause to the many pressures of global change is and will continue to be a formidable challenge in estuaries and coastal seas, due in part to: (1) their complexity and unbounded nature; (2) difficulties distinguishing between human-induced changes and natural variations and; (3) multiple pressures and effects. The contributing authors have explored a number of these issues over a range of disciplines. The complexity and connectivity of estuaries and coastal seas have been investigated through studies of physicochemical and ecological components, whilst the human imprint on the environment has been identified through a series of predictive, contemporary, historical and palaeo approaches. The impact of human activities has been shown to occur over a range of spatial and temporal scales, requiring the development of integrated management approaches. These 30 articles provide an important contribution to our understanding and assessment of the impacts of global change. The authors highlight methods for essential management/mitigation of the consequences of global change and provide a set of directions, ideas and observations for future work. These include the need to consider: (1) the cumulative, synergistic and antagonistic effects of multiple pressures; (2) the importance of unbounded boundaries and connectivity across the aquatic continuum; (3) the value of combining cross-disciplinary palaeo, contemporary and future modelling studies and; (4) the importance of shifting baselines on ecosystem functioning and the future provision of ecosystem services.
Sayegh, Philip; Arentoft, Alyssa; Thaler, Nicholas S.; Dean, Andy C.; Thames, April D.
2014-01-01
The current study examined whether self-rated education quality predicts Wide Range Achievement Test-4th Edition (WRAT-4) Word Reading subtest and neurocognitive performance, and aimed to establish this subtest's construct validity as an educational quality measure. In a community-based adult sample (N = 106), we tested whether education quality both increased the prediction of Word Reading scores beyond demographic variables and predicted global neurocognitive functioning after adjusting for WRAT-4. As expected, race/ethnicity and education predicted WRAT-4 reading performance. Hierarchical regression revealed that when including education quality, the amount of WRAT-4's explained variance increased significantly, with race/ethnicity and both education quality and years as significant predictors. Finally, WRAT-4 scores, but not education quality, predicted neurocognitive performance. Results support WRAT-4 Word Reading as a valid proxy measure for education quality and a key predictor of neurocognitive performance. Future research should examine these findings in larger, more diverse samples to determine their robust nature. PMID:25404004
A predictive framework to understand forest responses to global change.
McMahon, Sean M; Dietze, Michael C; Hersh, Michelle H; Moran, Emily V; Clark, James S
2009-04-01
Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.
Carbon sequestration and its role in the global carbon cycle
McPherson, Brian J.; Sundquist, Eric T.
2009-01-01
For carbon sequestration the issues of monitoring, risk assessment, and verification of carbon content and storage efficacy are perhaps the most uncertain. Yet these issues are also the most critical challenges facing the broader context of carbon sequestration as a means for addressing climate change. In response to these challenges, Carbon Sequestration and Its Role in the Global Carbon Cycle presents current perspectives and research that combine five major areas: • The global carbon cycle and verification and assessment of global carbon sources and sinks • Potential capacity and temporal/spatial scales of terrestrial, oceanic, and geologic carbon storage • Assessing risks and benefits associated with terrestrial, oceanic, and geologic carbon storage • Predicting, monitoring, and verifying effectiveness of different forms of carbon storage • Suggested new CO2 sequestration research and management paradigms for the future. The volume is based on a Chapman Conference and will appeal to the rapidly growing group of scientists and engineers examining methods for deliberate carbon sequestration through storage in plants, soils, the oceans, and geological repositories.
Noiseonomics: The relationship between ambient noise levels in the sea and global economic trends
Frisk, George V.
2012-01-01
In recent years, the topic of noise in the sea and its effects on marine mammals has attracted considerable attention from both the scientific community and the general public. Since marine mammals rely heavily on acoustics as a primary means of communicating, navigating, and foraging in the ocean, any change in their acoustic environment may have an impact on their behavior. Specifically, a growing body of literature suggests that low-frequency, ambient noise levels in the open ocean increased approximately 3.3 dB per decade during the period 1950–2007. Here we show that this increase can be attributed primarily to commercial shipping activity, which in turn, can be linked to global economic growth. As a corollary, we conclude that ambient noise levels can be directly related to global economic conditions. We provide experimental evidence supporting this theory and discuss its implications for predicting future noise levels based on global economic trends. PMID:22666540
Effects of modeled tropical sea surface temperature variability on coral reef bleaching predictions
NASA Astrophysics Data System (ADS)
van Hooidonk, R.; Huber, M.
2012-03-01
Future widespread coral bleaching and subsequent mortality has been projected using sea surface temperature (SST) data derived from global, coupled ocean-atmosphere general circulation models (GCMs). While these models possess fidelity in reproducing many aspects of climate, they vary in their ability to correctly capture such parameters as the tropical ocean seasonal cycle and El Niño Southern Oscillation (ENSO) variability. Such weaknesses most likely reduce the accuracy of predicting coral bleaching, but little attention has been paid to the important issue of understanding potential errors and biases, the interaction of these biases with trends, and their propagation in predictions. To analyze the relative importance of various types of model errors and biases in predicting coral bleaching, various intra- and inter-annual frequency bands of observed SSTs were replaced with those frequencies from 24 GCMs 20th century simulations included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. Subsequent thermal stress was calculated and predictions of bleaching were made. These predictions were compared with observations of coral bleaching in the period 1982-2007 to calculate accuracy using an objective measure of forecast quality, the Peirce skill score (PSS). Major findings are that: (1) predictions are most sensitive to the seasonal cycle and inter-annual variability in the ENSO 24-60 months frequency band and (2) because models tend to understate the seasonal cycle at reef locations, they systematically underestimate future bleaching. The methodology we describe can be used to improve the accuracy of bleaching predictions by characterizing the errors and uncertainties involved in the predictions.
NASA Astrophysics Data System (ADS)
Geiger, Tobias; Levermann, Anders; Frieler, Katja
2015-04-01
Recent years have seen an intense scientific debate of what to expect from future tropical cyclone activity under climate change [1,2]. Besides the projection of cyclones' genesis points and trajectories it is the cyclone's impact on future societies that needs to be quantified. In our present work, where we focus on the Eastern USA, we start out with a comprehensive comparison of a variety of presently available and novel functional relationships that are used to link cyclones' physical properties with their damage caused on the ground. These so-called damage functions make use of high quality data sets consisting of gridded population data, exposed capital at risk, and information on the cyclone's extension and its translational and locally resolved maximum wind speed. Based on a cross-validation ansatz we train a multitude of damage functions on a large variety of data sets in order to evaluate their performance on an equally sized test sample. Although different damage analyses have been conducted in the literature [3,4,5,6], the efforts have so far primarily been focused on determining fit parameters for individual data sets. As our analysis consists of a wide range of damage functions implemented on identical data sets, we can rigorously evaluate which (type of) damage function (for which set of parameters) does best in reproducing damages and should therefore be used for future loss analysis with highest certainty. We find that the benefits of using locally resolved data input tend to be outweighed by the large uncertainties that accompany the data. More coarse and generalized data input therefore captures the diversity of cyclonic features better. Furthermore, our analysis shows that a non-linear relation between wind speed and damage outperforms the linear as well as the exponential relationship discussed in the literature. In a second step, the damage function with the highest predictive quality is implemented to predict potential future cyclone losses for the Eastern USA until the year 2100. The projection is based on downscaling five different GCM model runs for the RCP8.5 scenario, as conducted by Emanuel et al. [7], and accounts for population and GDP changes relying on the newly developed Shared Socioenonomic Pathways (SSPs) [8]. We hereby contribute valuable input to the scientific community as well as the societies at risk. The possibility of extending this work to different regions in order to access the future impact of tropical cyclones on a global scale will also be discussed. References [1] Thomas R. Knutson, John L. McBride, Johnny Chan, Kerry Emanuel, Greg Holland, Chris Landsea, Isaac Held, James P. Kossin, A. K. Srivastava, and Masato Sugi. Tropical cyclones and climate change. Nature Geoscience, 3(3):157-163, 2010. [2] Robert Mendelsohn, Kerry Emanuel, Shun Chonabayashi, and Laura Bakkensen. The impact of climate change on global tropical cyclone damage. Nature Climate Change, 2(3):205-209, 2012. [3] Silvio Schmidt, Claudia Kemfert, and Peter Höppe. The impact of socio-economics and climate change on tropical cyclone losses in the USA. Regional Environmental Change, 10(1):13-26, 2009. [4] William D. Nordhaus. The Economics of Hurricanes and Implications of Global Warming. Climate Change Economics, 01(01):1-20, 2010. [5] Kerry Emanuel. Global Warming Effects on U.S. Hurricane Damage. Weather, Climate, and Society, 3(4):261-268, 2011. [6] Richard J. Murnane and James B. Elsner. Maximum wind speeds and US hurricane losses. Geophysical Research Letters, 39(16):707, 2012. [7] Kerry Emanuel. Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century. Proceedings of the National Academy of Sciences of the United States of America, 110(30):12219-24, 2013. [8] Detlef P. van Vuuren, Keywan Riahi, and Richard Moss. A proposal for a new scenario framework to support research and assessment in different climate research communities. Global Environmental Change, 22(1):21-35, 2012.
Prediction of Seasonal Climate-induced Variations in Global Food Production
NASA Technical Reports Server (NTRS)
Iizumi, Toshichika; Sakuma, Hirofumi; Yokozawa, Masayuki; Luo, Jing-Jia; Challinor, Andrew J.; Brown, Molly E.; Sakurai, Gen; Yamagata, Toshio
2013-01-01
Consumers, including the poor in many countries, are increasingly dependent on food imports and are therefore exposed to variations in yields, production, and export prices in the major food-producing regions of the world. National governments and commercial entities are paying increased attention to the cropping forecasts of major food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We assessed the reliability of hindcasts (i.e., retrospective forecasts for the past) of crop yield loss relative to the previous year for two lead times. Pre-season yield predictions employ climatic forecasts and have lead times of approximately 3 to 5 months for providing information regarding variations in yields for the coming cropping season. Within-season yield predictions use climatic forecasts with lead times of 1 to 3 months. Pre-season predictions can be of value to national governments and commercial concerns, complemented by subsequent updates from within-season predictions. The latter incorporate information on the most recent climatic data for the upcoming period of reproductive growth. In addition to such predictions, hindcasts using observations from satellites were performed to demonstrate the upper limit of the reliability of crop forecasting.
NASA Technical Reports Server (NTRS)
Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon;
2014-01-01
Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.
Low historical nitrogen deposition effect on carbon sequestration in the boreal zone
NASA Astrophysics Data System (ADS)
Fleischer, K.; Wârlind, D.; van der Molen, M. K.; Rebel, K. T.; Arneth, A.; Erisman, J. W.; Wassen, M. J.; Smith, B.; Gough, C. M.; Margolis, H. A.; Cescatti, A.; Montagnani, L.; Arain, A.; Dolman, A. J.
2015-12-01
Nitrogen (N) cycle dynamics and N deposition play an important role in determining the terrestrial biosphere's carbon (C) balance. We assess global and biome-specific N deposition effects on C sequestration rates with the dynamic global vegetation model LPJ-GUESS. Modeled CN interactions are evaluated by comparing predictions of the C and CN version of the model with direct observations of C fluxes from 68 forest FLUXNET sites. N limitation on C uptake reduced overestimation of gross primary productivity for boreal evergreen needleleaf forests from 56% to 18%, presenting the greatest improvement among forest types. Relative N deposition effects on C sequestration (dC/dN) in boreal, temperate, and tropical sites ranged from 17 to 26 kg C kg N-1 when modeled at site scale and were reduced to 12-22 kg C kg N-1 at global scale. We find that 19% of the recent (1990-2007) and 24% of the historical global C sink (1900-2006) was driven by N deposition effects. While boreal forests exhibit highest dC/dN, their N deposition-induced C sink was relatively low and is suspected to stay low in the future as no major changes in N deposition rates are expected in the boreal zone. N deposition induced a greater C sink in temperate and tropical forests, while predicted C fluxes and N-induced C sink response in tropical forests were associated with greatest uncertainties. Future work should be directed at improving the ability of LPJ-GUESS and other process-based ecosystem models to reproduce C cycle dynamics in the tropics, facilitated by more benchmarking data sets. Furthermore, efforts should aim to improve understanding and model representations of N availability (e.g., N fixation and organic N uptake), N limitation, P cycle dynamics, and effects of anthropogenic land use and land cover changes.
Are Plant Species Able to Keep Pace with the Rapidly Changing Climate?
Cunze, Sarah; Heydel, Felix; Tackenberg, Oliver
2013-01-01
Future climate change is predicted to advance faster than the postglacial warming. Migration may therefore become a key driver for future development of biodiversity and ecosystem functioning. For 140 European plant species we computed past range shifts since the last glacial maximum and future range shifts for a variety of Intergovernmental Panel on Climate Change (IPCC) scenarios and global circulation models (GCMs). Range shift rates were estimated by means of species distribution modelling (SDM). With process-based seed dispersal models we estimated species-specific migration rates for 27 dispersal modes addressing dispersal by wind (anemochory) for different wind conditions, as well as dispersal by mammals (dispersal on animal's coat – epizoochory and dispersal by animals after feeding and digestion – endozoochory) considering different animal species. Our process-based modelled migration rates generally exceeded the postglacial range shift rates indicating that the process-based models we used are capable of predicting migration rates that are in accordance with realized past migration. For most of the considered species, the modelled migration rates were considerably lower than the expected future climate change induced range shift rates. This implies that most plant species will not entirely be able to follow future climate-change-induced range shifts due to dispersal limitation. Animals with large day- and home-ranges are highly important for achieving high migration rates for many plant species, whereas anemochory is relevant for only few species. PMID:23894290
Steen, Valerie; Powell, Abby N.
2012-01-01
Wetland-dependent birds are considered to be at particularly high risk for negative climate change effects. Current and future distributions of American Bittern (Botaurus lentiginosus), American Coot (Fulica americana), Black Tern (Chlidonias niger), Pied-billed Grebe (Podilymbus podiceps) and Sora (Porzana carolina), five waterbird species common in the Prairie Pothole Region (PPR), were predicted using species distribution models (SDMs) in combination with climate data that projected a drier future for the PPR. Regional-scale SDMs were created for the U.S. PPR using breeding bird survey occurrence records for 1971-2000 and wetland and climate parameters. For each waterbird species, current distribution and four potential future distributions were predicted: all combinations of two Global Circulation Models and two emissions scenarios. Averaged for all five species, the ensemble range reduction was 64%. However, projected range losses for individual species varied widely with Sora and Black Tern projected to lose close to 100% and American Bittern 29% of their current range. Future distributions were also projected to a hypothetical landscape where wetlands were numerous and constant to highlight areas suitable as conservation reserves under a drier future climate. The ensemble model indicated that northeastern North Dakota and northern Minnesota would be the best areas for conservation reserves within the U.S. PPR under the modeled conditions.
Global Trends and Future Warfare (Strategic Insights. Special Issue, October 2011)
2011-10-01
CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ...cyberspace are constructed .33 In the early 1970s Daniel Bell in The Coming of Post- Industrial Society predicted something like this when he wrote of...ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School,Center on Contemporary Conflict,Monterey,CA,93943 8. PERFORMING ORGANIZATION REPORT
Preparing The U.S. Air Force for Military Operations Other Than War,
1997-01-01
Step 1: Detect and Identify WMD Facilities 70 5.5. Step 2: Neutralize WMD Facilities 71 5.6. Step 3: Conduct BDA Following Attack on...FUTURE It would generally appear that there is no way to predict whether global instability will mushroom . In any case, there is not necessarily a...serious enough problem, then the United States should do some- thing about it. Thus, policymakers often feel compelled by pubic and media pressures to
Ito, Akihiko
2010-07-01
Using a process-based model, I assessed how ecophysiological processes would respond to near-future global changes predicted by coupled atmosphere-ocean climate models. An ecosystem model, Vegetation Integrative SImulator for Trace gases (VISIT), was applied to four sites in East Asia (different types of forest in Takayama, Tomakomai, and Fujiyoshida, Japan, and an Alpine grassland in Qinghai, China) where observational flux data are available for model calibration. The climate models predicted +1-3 degrees C warming and slight change in annual precipitation by 2050 as a result of an increase in atmospheric CO2. Gross primary production (GPP) was estimated to increase substantially at each site because of improved efficiency in the use of water and radiation. Although increased respiration partly offset the GPP increase, the simulation showed that these ecosystems would act as net carbon sinks independent of disturbance-induced uptake for recovery. However, the carbon budget response relied strongly on nitrogen availability, such that photosynthetic down-regulation resulting from leaf nitrogen dilution largely decreased GPP. In relation to long-term monitoring, these results indicate that the impacts of global warming may be more evident in gross fluxes (e.g., photosynthesis and respiration) than in the net CO2 budget, because changes in these fluxes offset each other.
Identifying water price and population criteria for meeting future urban water demand targets
NASA Astrophysics Data System (ADS)
Ashoori, Negin; Dzombak, David A.; Small, Mitchell J.
2017-12-01
Predictive models for urban water demand can help identify the set of factors that must be satisfied in order to meet future targets for water demand. Some of the explanatory variables used in such models, such as service area population and changing temperature and rainfall rates, are outside the immediate control of water planners and managers. Others, such as water pricing and the intensity of voluntary water conservation efforts, are subject to decisions and programs implemented by the water utility. In order to understand this relationship, a multiple regression model fit to 44 years of monthly demand data (1970-2014) for Los Angeles, California was applied to predict possible future demand through 2050 under alternative scenarios for the explanatory variables: population, price, voluntary conservation efforts, and temperature and precipitation outcomes predicted by four global climate models with two CO2 emission scenarios. Future residential water demand in Los Angeles is projected to be largely driven by price and population rather than climate change and conservation. A median projection for the year 2050 indicates that residential water demand in Los Angeles will increase by approximately 36 percent, to a level of 620 million m3 per year. The Monte Carlo simulations of the fitted model for water demand were then used to find the set of conditions in the future for which water demand is predicted to be above or below the Los Angeles Department of Water and Power 2035 goal to reduce residential water demand by 25%. Results indicate that increases in price can not ensure that the 2035 water demand target can be met when population increases. Los Angeles must rely on furthering their conservation initiatives and increasing their use of stormwater capture, recycled water, and expanding their groundwater storage. The forecasting approach developed in this study can be utilized by other cities to understand the future of water demand in water-stressed areas. Improving water demand forecasts will help planners understand and optimize future investments in water supply infrastructure and related programs.
Future generations, environmental ethics, and global environmental change
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tonn, B.E.
1994-12-31
The elements of a methodology to be employed by the global community to investigate the consequences of global environmental change upon future generations and global ecosystems are outlined in this paper. The methodology is comprised of two major components: A possible future worlds model; and a formal, citizen-oriented process to judge whether the possible future worlds potentially inheritable by future generations meet obligational standards. A broad array of descriptors of future worlds can be encompassed within this framework, including survival of ecosystems and other species and satisfaction of human concerns. The methodology expresses fundamental psychological motivations and human myths journey,more » renewal, mother earth, and being-in-nature-and incorporates several viewpoints on obligations to future generations-maintaining options, fairness, humility, and the cause of humanity. The methodology overcomes several severe drawbacks of the economic-based methods most commonly used for global environmental policy analysis.« less
Ozone depletion caused by NO and H2O emissions from hydrazine-fueled rockets
NASA Astrophysics Data System (ADS)
Ross, M. N.; Danilin, M. Y.; Weisenstein, D. K.; Ko, M. K. W.
2004-11-01
Rockets using unsymmetrical dimethyl hydrazine (N(CH3)2NH2) and dinitrogen tetroxide (N2O4) propellants account for about one third of all stratospheric rocket engine emissions, comparable to the solid-fueled rocket emissions. We use plume and global atmosphere models to provide the first estimate of the local and global ozone depletion caused by NO and H2O emissions from the Proton rocket, the largest hydrazine-fueled launcher in use. NO and H2O emission indices are assumed to be 20 and 350 g/kg (propellant), respectively. Predicted maximum ozone loss in the plume of the Proton rocket is 21% at 44 km altitude. Plume ozone loss at 20 km equals 8% just after launch and steadily declines to 2% by model sunset. Predicted steady state global ozone loss from ten Proton launches annually is 1.2 × 10-4%, with nearly all of the loss due to the NO component of the emission. Normalized by stratospheric propellant consumption, the global ozone depletion efficiency of the Proton is approximately 66-90 times less than that of solid-fueled rockets. In situ Proton plume measurements are required to validate assumed emission indices and to assess the role of rocket emissions not considered in these calculations. Such future studies would help to establish a formalism to evaluate the relative ozone depletion caused by different rocket engines using different propellants.
NASA Astrophysics Data System (ADS)
Stuart-Haëntjens, E. J.; De Boeck, H. J.; Lemoine, N. P.; Gough, C. M.; Kröel-Dulay, G.; Mänd, P.; Jentsch, A.; Schmidt, I. K.; Bahn, M.; Lloret, F.; Kreyling, J.; Wohlgemuth, T.; Stampfli, A.; Anderegg, W.; Classen, A. T.; Smith, M. D.
2017-12-01
Extreme drought is increasing globally in frequency and intensity, with uncertain consequences for the resistance and resilience of key ecosystem functions, including primary production. Primary production resistance, the capacity of an ecosystem to withstand change in primary production following extreme climate, and resilience, the degree to which primary production recovers, vary among and within ecosystem types, obscuring global patterns of resistance and resilience to extreme drought. Past syntheses on resistance have focused climatic gradients or individual ecosystem types, without assessing interactions between the two. Theory and many empirical studies suggest that forest production is more resistant but less resilient than grassland production to extreme drought, though some empirical studies reveal that these trends are not universal. Here, we conducted a global meta-analysis of sixty-four grassland and forest sites, finding that primary production resistance to extreme drought is predicted by a common continuum of mean annual precipitation (MAP). However, grasslands and forests exhibit divergent production resilience relationships with MAP. We discuss the likely mechanisms underlying the mixed production resistance and resilience patterns of forests and grasslands, including different plant species turnover times and drought adaptive strategies. These findings demonstrate the primary production responses of forests and grasslands to extreme drought are mixed, with far-reaching implications for Earth System Models, ecosystem management, and future studies of extreme drought resistance and resilience.
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.
Understanding the INTERNET: A guide for materials scientists and engineers
NASA Astrophysics Data System (ADS)
Meltsner, Kenneth J.
1995-04-01
Newspapers and magazines are full of stories about the Internet and the coming "information superhighway." Predictions for the future range from on-line video rentals and 500 channels of cable television to video telephones and global electronic libraries. Unfortunately, "infobahn" metaphors and hyperbole have obscured the fact that the the Internet is useful now and that it connects a significant fraction of the United States and the world. This article describes, without too many metaphors, the current and near-future capabilities of the Internet and provides basic information about access methods, popular services, and planned changes. In addition, the article also offers a brief introduction to "Net" culture and etiquette.
77 FR 35944 - Renewal of the Global Markets Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2012-06-15
... international standards for regulating futures, swaps, options, and derivatives markets, as well as..., competitive, and financially sound futures and options markets. Meetings of the Global Markets Advisory... COMMODITY FUTURES TRADING COMMISSION Renewal of the Global Markets Advisory Committee AGENCY...
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.
Pérez-Garrido, Alfonso; Morales Helguera, Aliuska; Abellán Guillén, Adela; Cordeiro, M Natália D S; Garrido Escudero, Amalio
2009-01-15
This paper reports a QSAR study for predicting the complexation of a large and heterogeneous variety of substances (233 organic compounds) with beta-cyclodextrins (beta-CDs). Several different theoretical molecular descriptors, calculated solely from the molecular structure of the compounds under investigation, and an efficient variable selection procedure, like the Genetic Algorithm, led to models with satisfactory global accuracy and predictivity. But the best-final QSAR model is based on Topological descriptors meanwhile offering a reasonable interpretation. This QSAR model was able to explain ca. 84% of the variance in the experimental activity, and displayed very good internal cross-validation statistics and predictivity on external data. It shows that the driving forces for CD complexation are mainly hydrophobic and steric (van der Waals) interactions. Thus, the results of our study provide a valuable tool for future screening and priority testing of beta-CDs guest molecules.
NASA's future Earth observation plans
NASA Astrophysics Data System (ADS)
Neeck, Steven P.; Paules, Granville E.; McCuistion Ramesh, J. D.
2004-11-01
NASA's Science Mission Directorate, working with its domestic and international partners, provides accurate, objective scientific data and analysis to advance our understanding of Earth system processes. Learning more about these processes will enable improved prediction capability for climate, weather, and natural hazards. Earth interactions occur on a continuum of spatial and temporal scales ranging from short-term weather to long-term climate, and from local and regional to global. Quantitatively describing these changes means precisely measuring from space scores of biological and geophysical parameters globally. New missions that SMD will launch in the coming decade will complement the first series of the Earth Observing System. These next generation systematic measurement missions are being planned to extend or enhance the record of science-quality data necessary for understanding and predicting global change. These missions include the NPOESS Preparatory Project, Ocean Surface Topography Mission, Global Precipitation Measurement, Landsat Data Continuity Mission, and an aerosol polarimetry mission called Glory. New small explorer missions will make first of a kind Earth observations. The Orbiting Carbon Observatory will measure sources and sinks of carbon to help the Nation and the world formulate effective strategies to constrain the amount of this greenhouse gas in the atmosphere. Aquarius will measure ocean surface salinity which is key to ocean circulation in the North Atlantic that produces the current era's mild climate in northern Europe. HYDROS will measure soil moisture globally. Soil moisture is critical to agriculture and to managing fresh water resources. NASA continues to design, develop and launch the Nation's civilian operational environmental satellites, in both polar and geostationary orbits, by agreement with the National Oceanic and Atmospheric Administration (NOAA). NASA plans to develop an advanced atmospheric sounder, GIFTS, for geostationary orbit to facilitate continuous measurements of weather-related phenomena, improve "nowcasting" of extreme weather events, and measure important atmospheric gases. NASA is currently developing with its partners the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and the next-generation geostationary system, GOES-R. Future missions will migrate today's capabilities in low Earth orbit to higher orbits such as L1 and L2 to enable more continuous monitoring of changes in the Earth system with a smaller number of satellites.
Assessing skill of a global bimonthly streamflow ensemble prediction system
NASA Astrophysics Data System (ADS)
van Dijk, A. I.; Peña-Arancibia, J.; Sheffield, J.; Wood, E. F.
2011-12-01
Ideally, a seasonal streamflow forecasting system might be conceived of as a system that ingests skillful climate forecasts from general circulation models and propagates these through thoroughly calibrated hydrological models that are initialised using hydrometric observations. In practice, there are practical problems with each of these aspects. Instead, we analysed whether a comparatively simple hydrological model-based Ensemble Prediction System (EPS) can provide global bimonthly streamflow forecasts with some skill and if so, under what circumstances the greatest skill may be expected. The system tested produces ensemble forecasts for each of six annual bimonthly periods based on the previous 30 years of global daily gridded 1° resolution climate variables and an initialised global hydrological model. To incorporate some of the skill derived from ocean conditions, a post-EPS analog method was used to sample from the ensemble based on El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO) index values observed prior to the forecast. Forecasts skill was assessed through a hind-casting experiment for the period 1979-2008. Potential skill was calculated with reference to a model run with the actual forcing for the forecast period (the 'perfect' model) and was compared to actual forecast skill calculated for each of the six forecast times for an average 411 Australian and 51 pan-tropical catchments. Significant potential skill in bimonthly forecasts was largely limited to northern regions during the snow melt period, seasonally wet tropical regions at the transition of wet to dry season, and the Indonesian region where rainfall is well correlated to ENSO. The actual skill was approximately 34-50% of the potential skill. We attribute this primarily to limitations in the model structure, parameterisation and global forcing data. Use of better climate forecasts and remote sensing observations of initial catchment conditions should help to increase actual skill in future. Future work also could address the potential skill gain from using weather and climate forecasts and from a calibrated and/or alternative hydrological model or model ensemble. The approach and data might be useful as a benchmark for joint seasonal forecasting experiments planned under GEWEX.
Global Futures: The Emerging Scenario.
ERIC Educational Resources Information Center
Seth, Satish C.
1983-01-01
Acknowledging global interdependence, especially in economics, may be the most important step toward resolving international conflicts. Describes seven major global dangers and gives scenarios for exploring likely global futures. As "tools of prescription" these global models are inadequate, but as "tools of analysis" they have…
Convergence of terrestrial plant production across global climate gradients.
Michaletz, Sean T; Cheng, Dongliang; Kerkhoff, Andrew J; Enquist, Brian J
2014-08-07
Variation in terrestrial net primary production (NPP) with climate is thought to originate from a direct influence of temperature and precipitation on plant metabolism. However, variation in NPP may also result from an indirect influence of climate by means of plant age, stand biomass, growing season length and local adaptation. To identify the relative importance of direct and indirect climate effects, we extend metabolic scaling theory to link hypothesized climate influences with NPP, and assess hypothesized relationships using a global compilation of ecosystem woody plant biomass and production data. Notably, age and biomass explained most of the variation in production whereas temperature and precipitation explained almost none, suggesting that climate indirectly (not directly) influences production. Furthermore, our theory shows that variation in NPP is characterized by a common scaling relationship, suggesting that global change models can incorporate the mechanisms governing this relationship to improve predictions of future ecosystem function.
A decade of insights into grassland ecosystem responses to global environmental change
Borer, Elizabeth T.; Grace, James B.; Harpole, W. Stanley; MacDougall, Andrew S.; Seabloom, Eric W.
2017-01-01
Earth’s biodiversity and carbon uptake by plants, or primary productivity, are intricately interlinked, underlie many essential ecosystem processes, and depend on the interplay among environmental factors, many of which are being changed by human activities. While ecological theory generalizes across taxa and environments, most empirical tests of factors controlling diversity and productivity have been observational, single-site experiments, or meta-analyses, limiting our understanding of variation among site-level responses and tests of general mechanisms. A synthesis of results from ten years of a globally distributed, coordinated experiment, the Nutrient Network (NutNet), demonstrates that species diversity promotes ecosystem productivity and stability, and that nutrient supply and herbivory control diversity via changes in composition, including invasions of non-native species and extinction of native species. Distributed experimental networks are a powerful tool for tests and integration of multiple theories and for generating multivariate predictions about the effects of global changes on future ecosystems.
Kuwaiti oil fires—Modeling revisited
NASA Astrophysics Data System (ADS)
Husain, Tahir
Just after the invasion of Kuwait, scientists began predictions on the environmental disaster due to threat by the Iraqi regime to blow out oil wells in the Kuwaiti oil fields. The findings with the speculations ranging from a nuclear winter to super-acid rain and global warming were presented in the World Climate Conference in Geneva in November 1990. Just before the war erupted in the middle of January 1991, a conference in London was called to discuss the potential risks to human life and ecological systems in case of blow out of oil fields. The scientists, using modeling techniques, raised the speculations about the global impact which, however, was discounted at a later stage. This paper presents an overview of the selected models used to assess the local, regional, and global impacts. The paper also highlights the model and data limitations and suggests future research directions to respond more effectively under emergency situations.
A vision for an ultra-high resolution integrated water cycle observation and prediction system
NASA Astrophysics Data System (ADS)
Houser, P. R.
2013-05-01
Society's welfare, progress, and sustainable economic growth—and life itself—depend on the abundance and vigorous cycling and replenishing of water throughout the global environment. The water cycle operates on a continuum of time and space scales and exchanges large amounts of energy as water undergoes phase changes and is moved from one part of the Earth system to another. We must move toward an integrated observation and prediction paradigm that addresses broad local-to-global science and application issues by realizing synergies associated with multiple, coordinated observations and prediction systems. A central challenge of a future water and energy cycle observation strategy is to progress from single variable water-cycle instruments to multivariable integrated instruments in electromagnetic-band families. The microwave range in the electromagnetic spectrum is ideally suited for sensing the state and abundance of water because of water's dielectric properties. Eventually, a dedicated high-resolution water-cycle microwave-based satellite mission may be possible based on large-aperture antenna technology that can harvest the synergy that would be afforded by simultaneous multichannel active and passive microwave measurements. A partial demonstration of these ideas can even be realized with existing microwave satellite observations to support advanced multivariate retrieval methods that can exploit the totality of the microwave spectral information. The simultaneous multichannel active and passive microwave retrieval would allow improved-accuracy retrievals that are not possible with isolated measurements. Furthermore, the simultaneous monitoring of several of the land, atmospheric, oceanic, and cryospheric states brings synergies that will substantially enhance understanding of the global water and energy cycle as a system. The multichannel approach also affords advantages to some constituent retrievals—for instance, simultaneous retrieval of vegetation biomass would improve soil-moisture retrieval by avoiding the need for auxiliary vegetation information. This multivariable water-cycle observation system must be integrated with high-resolution, application relevant prediction systems to optimize their information content and utility is addressing critical water cycle issues. One such vision is a real-time ultra-high resolution locally-moasiced global land modeling and assimilation system, that overlays regional high-fidelity information over a baseline global land prediction system. Such a system would provide the best possible local information for use in applications, while integrating and sharing information globally for diagnosing larger water cycle variability. In a sense, this would constitute a hydrologic telecommunication system, where the best local in-situ gage, Doppler radar, and weather station can be shared internationally, and integrated in a consistent manner with global observation platforms like the multivariable water cycle mission. To realize such a vision, large issues must be addressed, such as international data sharing policy, model-observation integration approaches that maintain local extremes while achieving global consistency, and methods for establishing error estimates and uncertainty.
75 FR 33788 - Renewal of the Global Markets Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2010-06-15
... appropriate international standards for regulating futures and derivatives markets, as well as intermediaries... financially sound futures and options markets. Meetings of the Global Markets Advisory Committee are open to... COMMODITY FUTURES TRADING COMMISSION Renewal of the Global Markets Advisory Committee AGENCY...
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.
Satellite Observations and Chemistry Climate Models - A Meandering Path Towards Better Predictions
NASA Technical Reports Server (NTRS)
Douglass, Anne R.
2011-01-01
Knowledge of the chemical and dynamical processes that control the stratospheric ozone layer has grown rapidly since the 1970s, when ideas that depletion of the ozone layer due to human activity were put forth. The concept of ozone depletion due to anthropogenic chlorine increase is simple; quantification of the effect is much more difficult. The future of stratospheric ozone is complicated because ozone is expected to increase for two reasons: the slow decrease in anthropogenic chlorine due to the Montreal Protocol and its amendments and stratospheric cooling caused by increases in carbon dioxide and other greenhouse gases. Prediction of future ozone levels requires three-dimensional models that represent physical, photochemical and radiative processes, i.e., chemistry climate models (CCMs). While laboratory kinetic and photochemical data are necessary inputs for a CCM, atmospheric measurements are needed both to reveal physical and chemical processes and for comparison with simulations to test the conceptual model that CCMs represent. Global measurements are available from various satellites including but not limited to the LIMS and TOMS instruments on Nimbus 7 (1979 - 1993), and various instruments on the Upper Atmosphere Research Satellite (1991 - 2005), Envisat (2002 - ongoing), Sci-Sat (2003 - ongoing) and Aura (2004 - ongoing). Every successful satellite instrument requires a physical concept for the measurement, knowledge of physical chemical properties of the molecules to be measured, and stellar engineering to design an instrument that will survive launch and operate for years with no opportunity for repair but providing enough information that trend information can be separated from any instrument change. The on-going challenge is to use observations to decrease uncertainty in prediction. This talk will focus on two applications. The first considers transport diagnostics and implications for prediction of the eventual demise of the Antarctic ozone hole. The second focuses on the upper stratosphere, where ozone is predicted to increase both due to chlorine decrease and due to temperature decrease expected as a result of increased concentrations Of CO2 and other greenhouse gases. Both applications show how diagnostics developed from global observations are being used to explain why the ozone response varies among CCM predictions for stratospheric ozone in the 21st century.
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.
Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity
DOE Office of Scientific and Technical Information (OSTI.GOV)
Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.
Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area.more » This area drops to 37% with the use of precipitation minus evapo-transpiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.« less
Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity
Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.; ...
2016-08-29
Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area.more » This area drops to 37% with the use of precipitation minus evapo-transpiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.« less
Potential reduction in terrestrial salamander ranges associated with Marcellus shale development
Brand, Adrianne B,; Wiewel, Amber N. M.; Grant, Evan H. Campbell
2014-01-01
Natural gas production from the Marcellus shale is rapidly increasing in the northeastern United States. Most of the endemic terrestrial salamander species in the region are classified as ‘globally secure’ by the IUCN, primarily because much of their ranges include state- and federally protected lands, which have been presumed to be free from habitat loss. However, the proposed and ongoing development of the Marcellus gas resources may result in significant range restrictions for these and other terrestrial forest salamanders. To begin to address the gaps in our knowledge of the direct impacts of shale gas development, we developed occurrence models for five species of terrestrial plethodontid salamanders found largely within the Marcellus shale play. We predicted future Marcellus shale development under several scenarios. Under scenarios of 10,000, 20,000, and 50,000 new gas wells, we predict 4%, 8%, and 20% forest loss, respectively, within the play. Predictions of habitat loss vary among species, but in general, Plethodon electromorphus and Plethodonwehrlei are predicted to lose the greatest proportion of forested habitat within their ranges if future Marcellus development is based on characteristics of the shale play. If development is based on current well locations,Plethodonrichmondi is predicted to lose the greatest proportion of habitat. Models showed high uncertainty in species’ ranges and emphasize the need for distribution data collected by widespread and repeated, randomized surveys.
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.
Johnson, W B; Lall, R; Bongar, B; Nordlund, M D
1999-01-01
Objective personality assessment instruments offer a comparatively underutilized source of clinical data in attempts to evaluate and predict risk for suicide. In contrast to focal suicide risk measures, global personality inventories may be useful in identification of long-standing styles that predispose persons to eventual suicidal behavior. This article reviews the empirical literature regarding the efficacy of established personality inventories in predicting suicidality. The authors offer several recommendations for future research with these measures and conclude that such objective personality instruments offer only marginal utility as sources of clinical information in comprehensive suicide risk evaluations. Personality inventories may offer greatest utility in long-term assessment of suicide risk.
Predicted extinction of unique genetic diversity in marine forests of Cystoseira spp.
Buonomo, Roberto; Chefaoui, Rosa M; Lacida, Ricardo Bermejo; Engelen, Aschwin H; Serrão, Ester A; Airoldi, Laura
2018-07-01
Climate change is inducing shifts in species ranges across the globe. These can affect the genetic pools of species, including loss of genetic variability and evolutionary potential. In particular, geographically enclosed ecosystems, like the Mediterranean Sea, have a higher risk of suffering species loss and genetic erosion due to barriers to further range shifts and to dispersal. In this study, we address these questions for three habitat-forming seaweed species, Cystoseira tamariscifolia, C. amentacea and C. compressa, throughout their entire ranges in the Atlantic and Mediterranean regions. We aim to 1) describe their population genetic structure and diversity, 2) model the present and predict the future distribution and 3) assess the consequences of predicted future range shifts for their population genetic structure, according to two contrasting future climate change scenarios. A net loss of suitable areas was predicted in both climatic scenarios across the range of distribution of the three species. This loss was particularly severe for C. amentacea in the Mediterranean Sea (less 90% in the most extreme climatic scenario), suggesting that the species could become potentially at extinction risk. For all species, genetic data showed very differentiated populations, indicating low inter-population connectivity, and high and distinct genetic diversity in areas that were predicted to become lost, causing erosion of unique evolutionary lineages. Our results indicated that the Mediterranean Sea is the most threatened region, where future suitable Cystoseira habitats will become more limited. This is likely to have wider ecosystem impacts as there is a lack of species with the same ecological niche and functional role in the Mediterranean. The projected accelerated loss of already fragmented and disturbed populations and the long-term genetic effects highlight the urge for local scale management strategies that sustain the capacity of these habitat-forming species to persist despite climatic impacts while waiting for global emission reductions. Copyright © 2018 Elsevier Ltd. All rights reserved.
The Crossover Time as an Evaluation of Ocean Models Against Persistence
NASA Astrophysics Data System (ADS)
Phillipson, L. M.; Toumi, R.
2018-01-01
A new ocean evaluation metric, the crossover time, is defined as the time it takes for a numerical model to equal the performance of persistence. As an example, the average crossover time calculated using the Lagrangian separation distance (the distance between simulated trajectories and observed drifters) for the global MERCATOR ocean model analysis is found to be about 6 days. Conversely, the model forecast has an average crossover time longer than 6 days, suggesting limited skill in Lagrangian predictability by the current generation of global ocean models. The crossover time of the velocity error is less than 3 days, which is similar to the average decorrelation time of the observed drifters. The crossover time is a useful measure to quantify future ocean model improvements.
Climate-driven basin-scale decadal oscillations of oceanic phytoplankton.
Martinez, Elodie; Antoine, David; D'Ortenzio, Fabrizio; Gentili, Bernard
2009-11-27
Phytoplankton--the microalgae that populate the upper lit layers of the ocean--fuel the oceanic food web and affect oceanic and atmospheric carbon dioxide levels through photosynthetic carbon fixation. Here, we show that multidecadal changes in global phytoplankton abundances are related to basin-scale oscillations of the physical ocean, specifically the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation. This relationship is revealed in approximately 20 years of satellite observations of chlorophyll and sea surface temperature. Interaction between the main pycnocline and the upper ocean seasonal mixed layer is one mechanism behind this correlation. Our findings provide a context for the interpretation of contemporary changes in global phytoplankton and should improve predictions of their future evolution with climate change.
Rising sea levels will reduce extreme temperature variations in tide-dominated reef habitats
Lowe, Ryan Joseph; Pivan, Xavier; Falter, James; Symonds, Graham; Gruber, Renee
2016-01-01
Temperatures within shallow reefs often differ substantially from those in the surrounding ocean; therefore, predicting future patterns of thermal stresses and bleaching at the scale of reefs depends on accurately predicting reef heat budgets. We present a new framework for quantifying how tidal and solar heating cycles interact with reef morphology to control diurnal temperature extremes within shallow, tidally forced reefs. Using data from northwestern Australia, we construct a heat budget model to investigate how frequency differences between the dominant lunar semidiurnal tide and diurnal solar cycle drive ~15-day modulations in diurnal temperature extremes. The model is extended to show how reefs with tidal amplitudes comparable to their depth, relative to mean sea level, tend to experience the largest temperature extremes globally. As a consequence, we reveal how even a modest sea level rise can substantially reduce temperature extremes within tide-dominated reefs, thereby partially offsetting the local effects of future ocean warming. PMID:27540589
Collective behaviour, uncertainty and environmental change.
Bentley, R Alexander; O'Brien, Michael J
2015-11-28
A central aspect of cultural evolutionary theory concerns how human groups respond to environmental change. Although we are painting with a broad brush, it is fair to say that prior to the twenty-first century, adaptation often happened gradually over multiple human generations, through a combination of individual and social learning, cumulative cultural evolution and demographic shifts. The result was a generally resilient and sustainable population. In the twenty-first century, however, considerable change happens within small portions of a human generation, on a vastly larger range of geographical and population scales and involving a greater degree of horizontal learning. As a way of gauging the complexity of societal response to environmental change in a globalized future, we discuss several theoretical tools for understanding how human groups adapt to uncertainty. We use our analysis to estimate the limits of predictability of future societal change, in the belief that knowing when to hedge bets is better than relying on a false sense of predictability. © 2015 The Author(s).
Introduction. Pliocene climate, processes and problems
Haywood, A.M.; Dowsett, H.J.; Valdes, P.J.; Lunt, D.J.; Francis, J.E.; Sellwood, B.W.
2009-01-01
Climate predictions produced by numerical climate models, often referred to as general circulation models (GCMs), suggest that by the end of the twenty-first century global mean annual surface air temperatures will increase by 1.1-6.4??C. Trace gas records from ice cores indicate that atmospheric concentrations of CO2 are already higher than at any time during the last 650000 years. In the next 50 years, atmospheric CO2 concentrations are expected to reach a level not encountered since an epoch of time known as the Pliocene. Uniformitarianism is a key principle of geological science, but can the past also be a guide to the future? To what extent does an examination of the Pliocene geological record enable us to successfully understand and interpret this guide? How reliable are the 'retrodictions' of Pliocene climates produced by GCMs and what does this tell us about the accuracy of model predictions for the future? These questions provide the scientific rationale for this Theme Issue. ?? 2008 The Royal Society.
The Shape of Ecosystem Management to Come: Anticipating Risks and Fostering Resilience
Seidl, Rupert
2014-01-01
Global change is increasingly challenging the sustainable provisioning of ecosystem services to society. Addressing future uncertainty and risk has therefore become a central problem of ecosystem management. With risk management and resilience-based stewardship, two contrasting approaches have been proposed to address this issue. Whereas one is concentrated on anticipating and mitigating risks, the other is focused on fostering the ability to absorb perturbations and maintain desired properties. While they have hitherto been discussed largely separately in the literature, I here propose a unifying framework of anticipating risks and fostering resilience in ecosystem management. Anticipatory action is advocated when the predictability of risk is high and sufficient knowledge to address it is available. Conversely, in situations in which predictability and knowledge are limited, resilience-based measures are paramount. I conclude that, by adopting a purposeful combination of insights from risk and resilience research, we can make ecosystem services provisioning more robust to future uncertainty and change. PMID:25729079
Livestock and food security: vulnerability to population growth and climate change.
Godber, Olivia F; Wall, Richard
2014-10-01
Livestock production is an important contributor to sustainable food security for many nations, particularly in low-income areas and marginal habitats that are unsuitable for crop production. Animal products account for approximately one-third of global human protein consumption. Here, a range of indicators, derived from FAOSTAT and World Bank statistics, are used to model the relative vulnerability of nations at the global scale to predicted climate and population changes, which are likely to impact on their use of grazing livestock for food. Vulnerability analysis has been widely used in global change science to predict impacts on food security and famine. It is a tool that is useful to inform policy decision making and direct the targeting of interventions. The model developed shows that nations within sub-Saharan Africa, particularly in the Sahel region, and some Asian nations are likely to be the most vulnerable. Livestock-based food security is already compromised in many areas on these continents and suffers constraints from current climate in addition to the lack of economic and technical support allowing mitigation of predicted climate change impacts. Governance is shown to be a highly influential factor and, paradoxically, it is suggested that current self-sufficiency may increase future potential vulnerability because trade networks are poorly developed. This may be relieved through freer trade of food products, which is also associated with improved governance. Policy decisions, support and interventions will need to be targeted at the most vulnerable nations, but given the strong influence of governance, to be effective, any implementation will require considerable care in the management of underlying structural reform. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
The Global Ocean Observing System
NASA Technical Reports Server (NTRS)
Kester, Dana
1992-01-01
A Global Ocean Observing System (GOOS) should be established now with international coordination (1) to address issues of global change, (2) to implement operational ENSO forecasts, (3) to provide the data required to apply global ocean circulation models, and (4) to extract the greatest value from the one billion dollar investment over the next ten years in ocean remote sensing by the world's space agencies. The objectives of GOOS will focus on climatic and oceanic predictions, on assessing coastal pollution, and in determining the sustainability of living marine resources and ecosystems. GOOS will be a complete system including satellite observations, in situ observations, numerical modeling of ocean processes, and data exchange and management. A series of practical and economic benefits will be derived from the information generated by GOOS. In addition to the marine science community, these benefits will be realized by the energy industries of the world, and by the world's fisheries. The basic oceanic variables that are required to meet the oceanic and predictability objectives of GOOS include wind velocity over the ocean, sea surface temperature and salinity, oceanic profiles of temperature and salinity, surface current, sea level, the extent and thickness of sea ice, the partial pressure of CO2 in surface waters, and the chlorophyll concentration of surface waters. Ocean circulation models and coupled ocean-atmosphere models can be used to evaluate observing system design, to assimilate diverse data sets from in situ and remotely sensed observations, and ultimately to predict future states of the system. The volume of ocean data will increase enormously over the next decade as new satellite systems are launched and as complementary in situ measuring systems are deployed. These data must be transmitted, quality controlled, exchanged, analyzed, and archived with the best state-of-the-art computational methods.
Allen, Craig D.; Macalady, A.K.; Chenchouni, H.; Bachelet, D.; McDowell, N.; Vennetier, Michel; Kitzberger, T.; Rigling, A.; Breshears, D.D.; Hogg, E.H.(T.); Gonzalez, P.; Fensham, R.; Zhang, Z.; Castro, J.; Demidova, N.; Lim, J.-H.; Allard, G.; Running, S.W.; Semerci, A.; Cobb, N.
2010-01-01
Greenhouse gas emissions have significantly altered global climate, and will continue to do so in the future. Increases in the frequency, duration, and/or severity of drought and heat stress associated with climate change could fundamentally alter the composition, structure, and biogeography of forests in many regions. Of particular concern are potential increases in tree mortality associated with climate-induced physiological stress and interactions with other climate-mediated processes such as insect outbreaks and wildfire. Despite this risk, existing projections of tree mortality are based on models that lack functionally realistic mortality mechanisms, and there has been no attempt to track observations of climate-driven tree mortality globally. Here we present the first global assessment of recent tree mortality attributed to drought and heat stress. Although episodic mortality occurs in the absence of climate change, studies compiled here suggest that at least some of the world's forested ecosystems already may be responding to climate change and raise concern that forests may become increasingly vulnerable to higher background tree mortality rates and die-off in response to future warming and drought, even in environments that are not normally considered water-limited. This further suggests risks to ecosystem services, including the loss of sequestered forest carbon and associated atmospheric feedbacks. Our review also identifies key information gaps and scientific uncertainties that currently hinder our ability to predict tree mortality in response to climate change and emphasizes the need for a globally coordinated observation system. Overall, our review reveals the potential for amplified tree mortality due to drought and heat in forests worldwide.
High resolution global climate modelling; the UPSCALE project, a large simulation campaign
NASA Astrophysics Data System (ADS)
Mizielinski, M. S.; Roberts, M. J.; Vidale, P. L.; Schiemann, R.; Demory, M.-E.; Strachan, J.; Edwards, T.; Stephens, A.; Lawrence, B. N.; Pritchard, M.; Chiu, P.; Iwi, A.; Churchill, J.; del Cano Novales, C.; Kettleborough, J.; Roseblade, W.; Selwood, P.; Foster, M.; Glover, M.; Malcolm, A.
2014-01-01
The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environmental Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the high performance computing center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE dataset. This dataset is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.
High-resolution global climate modelling: the UPSCALE project, a large-simulation campaign
NASA Astrophysics Data System (ADS)
Mizielinski, M. S.; Roberts, M. J.; Vidale, P. L.; Schiemann, R.; Demory, M.-E.; Strachan, J.; Edwards, T.; Stephens, A.; Lawrence, B. N.; Pritchard, M.; Chiu, P.; Iwi, A.; Churchill, J.; del Cano Novales, C.; Kettleborough, J.; Roseblade, W.; Selwood, P.; Foster, M.; Glover, M.; Malcolm, A.
2014-08-01
The UPSCALE (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) project constructed and ran an ensemble of HadGEM3 (Hadley Centre Global Environment Model 3) atmosphere-only global climate simulations over the period 1985-2011, at resolutions of N512 (25 km), N216 (60 km) and N96 (130 km) as used in current global weather forecasting, seasonal prediction and climate modelling respectively. Alongside these present climate simulations a parallel ensemble looking at extremes of future climate was run, using a time-slice methodology to consider conditions at the end of this century. These simulations were primarily performed using a 144 million core hour, single year grant of computing time from PRACE (the Partnership for Advanced Computing in Europe) in 2012, with additional resources supplied by the Natural Environment Research Council (NERC) and the Met Office. Almost 400 terabytes of simulation data were generated on the HERMIT supercomputer at the High Performance Computing Center Stuttgart (HLRS), and transferred to the JASMIN super-data cluster provided by the Science and Technology Facilities Council Centre for Data Archival (STFC CEDA) for analysis and storage. In this paper we describe the implementation of the project, present the technical challenges in terms of optimisation, data output, transfer and storage that such a project involves and include details of the model configuration and the composition of the UPSCALE data set. This data set is available for scientific analysis to allow assessment of the value of model resolution in both present and potential future climate conditions.
Năpăruş, Magdalena; Kuntner, Matjaž
2012-01-01
Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters. We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World), N. livida (Madagascar), N. malabarensis (S-SE Asia), and N. papuana (Australasia). For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range), a large part of Brazil and the Guianas (area of synanthropic spread), and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (sub)tropics. Our model is a customizable GIS tool intended to predict current and future potential distributions of globally distributed terrestrial lineages. Its predictive potential may be tested in foreseeing species distribution shifts due to habitat destruction and global climate change.
Năpăruş, Magdalena; Kuntner, Matjaž
2012-01-01
Background Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters. Methodology/Principal Findings We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World), N. livida (Madagascar), N. malabarensis (S-SE Asia), and N. papuana (Australasia). For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range), a large part of Brazil and the Guianas (area of synanthropic spread), and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (sub)tropics. Conclusions Our model is a customizable GIS tool intended to predict current and future potential distributions of globally distributed terrestrial lineages. Its predictive potential may be tested in foreseeing species distribution shifts due to habitat destruction and global climate change. PMID:22238692
Neale, Patrick J; Thomas, Brian C
2017-01-01
Phytoplankton photosynthesis is often inhibited by ultraviolet (UV) and intense photosynthetically available radiation (PAR), but the effects on ocean productivity have received little consideration aside from polar areas subject to periodic enhanced UV-B due to depletion of stratospheric ozone. A more comprehensive assessment is important for understanding the contribution of phytoplankton production to the global carbon budget, present and future. Here, we consider responses in the temperate and tropical mid-ocean regions typically dominated by picophytoplankton including the prokaryotic lineages, Prochlorococcus and Synechococcus. Spectral models of photosynthetic response for each lineage were constructed using model strains cultured at different growth irradiances and temperatures. In the model, inhibition becomes more severe once exposure exceeds a threshold (E max ) related to repair capacity. Model parameters are presented for Prochlorococcus adding to those previously presented for Synechococcus. The models were applied to estimate midday, water column photosynthesis based on an atmospheric model of spectral radiation, satellite-derived spectral water transparency and temperature. Based on a global survey of inhibitory exposure severity, a full-latitude section of the mid-Pacific and near-equatorial region of the east Pacific were identified as representative regions for prediction of responses over the entire water column. Comparing predictions integrated over the water column including versus excluding inhibition, production was 7-28% lower due to inhibition depending on strain and site conditions. Inhibition was consistently greater for Prochlorococcus compared to two strains of Synechococcus. Considering only the surface mixed layer, production was inhibited 7-73%. On average, including inhibition lowered estimates of midday productivity around 20% for the modeled region of the Pacific with UV accounting for two-thirds of the reduction. In contrast, most other productivity models either ignore inhibition or only include PAR inhibition. Incorporation of E max model responses into an existing spectral model of depth-integrated, daily production will enable efficient global predictions of picophytoplankton productivity including inhibition. © 2016 John Wiley & Sons Ltd.
An experimental test of CSR theory using a globally calibrated ordination method
Li, Yuanzhi
2017-01-01
Can CSR theory, in conjunction with a recently proposed globally calibrated CSR ordination (“StrateFy”), using only three easily measured leaf traits (leaf area, specific leaf area and leaf dry matter content) predict the functional signature of herbaceous vegetation along experimentally manipulated gradients of soil fertility and disturbance? To determine this, we grew 37 herbaceous species in mixture for five years in 24 experimental mesocosms differing in factorial levels of soil resources (stress) and density-independent mortality (disturbance). We measured 16 different functional traits and then ordinated the resulting vegetation within the CSR triangle using StrateFy. We then calculated community-weighted mean (CWM) values of the competitor (CCWM), stress-tolerator (SCWM) and ruderal (RCWM) scores for each mesocosm. We found a significant increase in SCWM from low to high stress mesocosms, and an increase in RCWM from lowly to highly disturbed mesocosms. However, CCWM did not decline significantly as intensity of stress or disturbance increased, as predicted by CSR theory. This last result likely arose because our herbaceous species were relatively poor competitors in global comparisons and thus no strong competitors in our species pool were selectively favoured in low stress and low disturbed mesocosms. Variation in the 13 other traits, not used by StrateFy, largely argeed with the predictions of CSR theory. StrateFy worked surprisingly well in our experimental study except for the C-dimension. Despite loss of some precision, it has great potential applicability in future studies due to its simplicity and generality. PMID:28388622
An experimental test of CSR theory using a globally calibrated ordination method.
Li, Yuanzhi; Shipley, Bill
2017-01-01
Can CSR theory, in conjunction with a recently proposed globally calibrated CSR ordination ("StrateFy"), using only three easily measured leaf traits (leaf area, specific leaf area and leaf dry matter content) predict the functional signature of herbaceous vegetation along experimentally manipulated gradients of soil fertility and disturbance? To determine this, we grew 37 herbaceous species in mixture for five years in 24 experimental mesocosms differing in factorial levels of soil resources (stress) and density-independent mortality (disturbance). We measured 16 different functional traits and then ordinated the resulting vegetation within the CSR triangle using StrateFy. We then calculated community-weighted mean (CWM) values of the competitor (CCWM), stress-tolerator (SCWM) and ruderal (RCWM) scores for each mesocosm. We found a significant increase in SCWM from low to high stress mesocosms, and an increase in RCWM from lowly to highly disturbed mesocosms. However, CCWM did not decline significantly as intensity of stress or disturbance increased, as predicted by CSR theory. This last result likely arose because our herbaceous species were relatively poor competitors in global comparisons and thus no strong competitors in our species pool were selectively favoured in low stress and low disturbed mesocosms. Variation in the 13 other traits, not used by StrateFy, largely argeed with the predictions of CSR theory. StrateFy worked surprisingly well in our experimental study except for the C-dimension. Despite loss of some precision, it has great potential applicability in future studies due to its simplicity and generality.
NASA Astrophysics Data System (ADS)
Gallagher, Sarah; Gleeson, Emily; Tiron, Roxana; McGrath, Ray; Dias, Frédéric
2016-04-01
Ireland has a highly energetic wave and wind climate, and is therefore uniquely placed in terms of its ocean renewable energy resource. The socio-economic importance of the marine resource to Ireland makes it critical to quantify how the wave and wind climate may change in the future due to global climate change. Projected changes in winds, ocean waves and the frequency and severity of extreme weather events should be carefully assessed for long-term marine and coastal planning. We derived an ensemble of future wave climate projections for Ireland using the EC-Earth global climate model and the WAVEWATCH III® wave model, by comparing the future 30-year period 2070-2099 to the period 1980-2009 for the RCP4.5 and the RCP8.5 forcing scenarios. This dataset is currently the highest resolution wave projection dataset available for Ireland. The EC-Earth ensemble predicts decreases in mean (up to 2 % for RCP4.5 and up to 3.5 % for RCP8.5) 10 m wind speeds over the North Atlantic Ocean (5-75° N, 0-80° W) by the end of the century, which will consequently affect swell generation for the Irish wave climate. The WAVEWATCH III® model predicts an overall decrease in annual and seasonal mean significant wave heights around Ireland, with the largest decreases in summer (up to 15 %) and winter (up to 10 %) for RCP8.5. Projected decreases in mean significant wave heights for spring and autumn were found to be small for both forcing scenarios (less than 5 %), with no significant decrease found for RCP4.5 off the west coast in those seasons.
Pérez-Rodríguez, Antón; de la Hera, Iván; Fernández-González, Sofía; Pérez-Tris, Javier
2014-08-01
The importance of parasitism for host populations depends on local parasite richness and prevalence: usually host individuals face higher infection risk in areas where parasites are most diverse, and host dispersal to or from these areas may have fitness consequences. Knowing how parasites are and will be distributed in space and time (in a context of global change) is thus crucial from both an ecological and a biological conservation perspective. Nevertheless, most research articles focus just on elaborating models of parasite distribution instead of parasite diversity. We produced distribution models of the areas where haemosporidian parasites are currently highly diverse (both at community and at within-host levels) and prevalent among Iberian populations of a model passerine host: the blackcap Sylvia atricapilla; and how these areas are expected to vary according to three scenarios of climate change. On the basis of these models, we analysed whether variation among populations in parasite richness or prevalence are expected to remain the same or change in the future, thereby reshuffling the geographic mosaic of host-parasite interactions as we observe it today. Our models predict a rearrangement of areas of high prevalence and richness of parasites in the future, with Haemoproteus and Leucocytozoon parasites (today the most diverse genera in blackcaps) losing areas of high diversity and Plasmodium parasites (the most virulent ones) gaining them. Likewise, the prevalence of multiple infections and parasite infracommunity richness would be reduced. Importantly, differences among populations in the prevalence and richness of parasites are expected to decrease in the future, creating a more homogeneous parasitic landscape. This predicts an altered geographic mosaic of host-parasite relationships, which will modify the interaction arena in which parasite virulence evolves. © 2014 John Wiley & Sons Ltd.
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.
The Contribution of Soils to North America's Current and Future Climate
NASA Astrophysics Data System (ADS)
Mayes, M. A.; Reed, S.; Thornton, P. E.; Lajtha, K.; Bailey, V. L.; Shrestha, G.; Jastrow, J. D.; Torn, M. S.
2015-12-01
This presentation will cover key aspects of the terrestrial soil carbon cycle in North America and the US for the upcoming State of the Carbon Cycle Report (SOCCRII). SOCCRII seeks to summarize how natural processes and human interactions affect the global carbon cycle, how socio-economic trends affect greenhouse gas concentrations in the atmosphere, and how ecosystems are influenced by and respond to greenhouse gas emissions, management decisions, and concomitant climate effects. Here, we will summarize the contemporary understanding of carbon stocks, fluxes, and drivers in the soil ecosystem compartment. We will highlight recent advances in modeling the magnitude of soil carbon stocks and fluxes, as well as the importance of remaining uncertainties in predicting soil carbon cycling and its relationship with climate. Attention will be given to the role of uncertainties in predicting future fluxes from soils, and how those uncertainties vary by region and ecosystem. We will also address how climate feedbacks and management decisions can enhance or minimize future climatic effects based on current understanding and observations, and will highlight select research needs to improve our understanding of the balance of carbon in soils in North America.
Lagerholm, Vendela K; Sandoval-Castellanos, Edson; Vaniscotte, Amélie; Potapova, Olga R; Tomek, Teresa; Bochenski, Zbigniew M; Shepherd, Paul; Barton, Nick; Van Dyck, Marie-Claire; Miller, Rebecca; Höglund, Jacob; Yoccoz, Nigel G; Dalén, Love; Stewart, John R
2017-04-01
Global warming is predicted to cause substantial habitat rearrangements, with the most severe effects expected to occur in high-latitude biomes. However, one major uncertainty is whether species will be able to shift their ranges to keep pace with climate-driven environmental changes. Many recent studies on mammals have shown that past range contractions have been associated with local extinctions rather than survival by habitat tracking. Here, we have used an interdisciplinary approach that combines ancient DNA techniques, coalescent simulations and species distribution modelling, to investigate how two common cold-adapted bird species, willow and rock ptarmigan (Lagopus lagopus and Lagopus muta), respond to long-term climate warming. Contrary to previous findings in mammals, we demonstrate a genetic continuity in Europe over the last 20 millennia. Results from back-casted species distribution models suggest that this continuity may have been facilitated by uninterrupted habitat availability and potentially also the greater dispersal ability of birds. However, our predictions show that in the near future, some isolated regions will have little suitable habitat left, implying a future decrease in local populations at a scale unprecedented since the last glacial maximum. © 2016 John Wiley & Sons Ltd.
Sexual narcissism and the perpetration of sexual aggression.
Widman, Laura; McNulty, James K
2010-08-01
Despite indirect evidence linking narcissism to sexual aggression, studies directly examining this relationship have yielded inconsistent results. Likely contributing to such inconsistencies, prior research has used global measures of narcissism not sensitive to whether the components of narcissism are activated in sexual versus non-sexual domains. The current research avoided such problems by using a measure of sexual narcissism to predict sexual aggression. In a sample of 299 men and women, Study 1 validated the Sexual Narcissism Scale, a new sexuality research instrument with four subscales-Sexual Exploitation, Sexual Entitlement, Low Sexual Empathy, and Sexual Skill. Then, in a sample of 378 men, Study 2 demonstrated that sexual narcissism was associated with reports of the frequency of sexual aggression, three specific types of sexual aggression (unwanted sexual contact, sexual coercion, and attempted/completed rape), and the likelihood of future sexual aggression. Notably, global narcissism was unrelated to all indices of sexual aggression when sexual narcissism was controlled. That sexual narcissism outperformed global assessments of narcissism to account for variance in sexual aggression suggests that future research may benefit by examining whether sexual narcissism and other sexual-situation-specific measurements of personality can similarly provide a more valid test of the association between personality and other sexual behaviors and outcomes (e.g., contraceptive use, infidelity, sexual satisfaction).
Sexual Narcissism and the Perpetration of Sexual Aggression
McNulty, James K.
2014-01-01
Despite indirect evidence linking narcissism to sexual aggression, studies directly examining this relationship have yielded inconsistent results. Likely contributing to such inconsistencies, prior research has used global measures of narcissism not sensitive to whether the components of narcissism are activated in sexual versus non-sexual domains. The current research avoided such problems by using a measure of sexual narcissism to predict sexual aggression. In a sample of 299 men and women, Study 1 validated the Sexual Narcissism Scale, a new sexuality research instrument with four subscales—Sexual Exploitation, Sexual Entitlement, Low Sexual Empathy, and Sexual Skill. Then, in a sample of 378 men, Study 2 demonstrated that sexual narcissism was associated with reports of the frequency of sexual aggression, three specific types of sexual aggression (unwanted sexual contact, sexual coercion, and attempted/completed rape), and the likelihood of future sexual aggression. Notably, global narcissism was unrelated to all indices of sexual aggression when sexual narcissism was controlled. That sexual narcissism outperformed global assessments of narcissism to account for variance in sexual aggression suggests that future research may benefit by examining whether sexual narcissism and other sexual-situation-specific measurements of personality can similarly provide a more valid test of the association between personality and other sexual behaviors and outcomes (e.g., contraceptive use, infidelity, sexual satisfaction). PMID:19130204
Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model
Swain, Eric; Stefanova, Lydia; Smith, Thomas
2014-01-01
Precipitation data from Global Climate Models have been downscaled to smaller regions. Adapting this downscaled precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The downscaled rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.
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.
2010-03-04
Cape Canaveral AFS, Fla. - A United Launch Alliance Delta IV rocket sits poised on its launch pad with the NASA/NOAA Geostationary Operational Environmental Satellite P (GOES P) at Space Launch Complex-37. GOES P will provide NOAA and NASA scientists with data to support weather, solar and space operations, and will enable future science improvements in weather prediction and remote sensing. Additionally, GOES-P will provide data on global climate changes and capability for search and rescue. Photo credit: Carleton Bailie, The Boeing Company
Observing System Simulation Experiment (OSSE) for a future Doppler Wind Lidar satellite in Japan:
NASA Astrophysics Data System (ADS)
Baron, Philippe; Ishii, Shoken; Okamoto, Kozo
2017-04-01
A feasibility study of tropospheric wind measurements by a coherent Doppler lidar aboard a super-low-altitude satellite is being conducted in Japan. We consider a coherent lidar with a laser light source at 2.05 μm whose characteristics correspond to an existing ground-based instrument (power=3.75 W, PRF=30 Hz and pulse width=200 ns). An Observing System Simulation Experiment (OSSE) has been implemented based on the Sensitivity Observing System experiment (SOSE) developed at the Japanese Meteorological-Research-Institute using the Japan Meteorological Agency global Numerical Weather Prediction model. The measurement simulator uses wind, aerosol and cloud 3-d global fields from the OSSE speudo-truth and the aerosol model MASINGAR. In this presentation, we will first discuss the measurement performances. Considering measurement horizontal resolutions of 100 km along the orbit track, we found that below 3 km, the median horizontal wind error is between 0.8-1 m/s for a vertical resolution of 0.5 km, and that near 50% of the data are valid measurements. Decreasing the vertical resolution to 1 km allows us to maintain similar performances up to 8 km almost over most latitudes. Above, the performances significantly fall down but a relatively good percentage of valid measurements (20-40%) are still found near the tropics where cirrus clouds frequently occur. The potential of the instrument to improve weather prediction models will be discussed using the OSSE results obtained for both polar and low inclination orbit satellites. The first results show positive improvements of short-term forecasts (<48 hours), in particular, on the wind speed at 850 hPa and 250 hPa. S. Ishii, K. Okamoto, P. Baron, T. Kubota, Y. Satoh, D. Sakaizawa, T. Ishibashi, T. Y. Tanaka, K. Yamashita, S. Ochiai, K. Gamo, M. Yasui, R. Oki, M. Satoh, and T. Iwasaki, "Measurement performance assessment of future space-borne Doppler wind lidar", SOLA, vol. 12, pp. 55-59, 2016. S. Ishii et al., "Feasibility study for future space-borne coherent Doppler wind lidar, Part 1: Instrumental Overview for Global Wind Profile Observation", submitted to J. Meteor. Soc. Japan, 2016 P. Baron et al., "Feasibility study for future space-borne coherent Doppler wind lidar, Part 2: Measurement simulation algorithms and retrieval error characterization", submitted to J. Meteor. Soc. Japan, 2016.
Zhang, Yibo; Zhang, Yunlin; Shi, Kun; Yao, Xiaolong
2017-06-01
Water is essential for life as it provides drinking water and food for humans and animals. Additionally, the water environment provides habitats for numerous species and plays an important role in hydrological, nutrient, and carbon cycles. Among the existing natural resources on Earth's surface, water is the most extensive as it covers more than 70% of the Earth. To gather a comprehensive understanding of the focus of past, present, and future directions of remote sensing water research, we provide an alternative perspective on water research using moderate resolution imaging spectroradiometer (MODIS) imagery by conducting a comparative quantitative and qualitative analysis of research development, current hotspots, and future directions using a bibliometric analysis. Our study suggests that there has been a rapid growth in the scientific outputs of water research using MODIS imagery over the past 15 years compared to other popular satellites around the world. The analysis indicated that Remote Sensing of Environment was the most active journal, and "remote sensing," "imaging science photographic technology," "environmental sciences ecology," "meteorology atmospheric sciences," and "geology" are the top 5 most popular subject categories. The Chinese Academy of Sciences was the most productive institution with a total of 477 papers, and Hu CM (Chinese) was the most productive author with 76 papers. A keyword analysis indicated that "vegetation index," "evapotranspiration," and "phytoplankton" were the most active research topics throughout the study period. In addition, it is predicted that more attention will be paid to research on climate change and phenology in the future. Based on the keyword analysis and in consideration of current environmental problems, more studies should focus on the following three aspects: (1) develop methods suitable for data assimilation to fully explain climate or phenological phenomena at continental or global scales rather than at local scales; (2) accurately predict the effect of global change and human activities on evapotranspiration and the water cycle; and (3) determine the evolutionary process of the water environment (i.e., water quality, macrophytes, cyanobacteria, etc.), ascertaining its dominant factors and driving mechanisms. By focusing on these three aspects, researchers will be able to provide timely monitoring and evaluation of water quality and its response to global change and human activities.
Bloom, A. Anthony; Exbrayat, Jean-François; van der Velde, Ivar R.; Feng, Liang; Williams, Mathew
2016-01-01
The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence times, and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is, therefore, necessary to better understand its current state and predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates, to our knowledge, of carbon cycle state and process variables at a 1° × 1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r = 0.3). Allocation to structural carbon is highest in the wet tropics (85–88%) in contrast to higher latitudes (73–82%), where allocation shifts toward photosynthetic carbon. Carbon use efficiency is lowest (0.42–0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r = 0.64–0.80) that matches independent trait studies. We show that conventional land cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median = 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which are currently based on globally applied parameters linked to land cover or plant functional types. PMID:26787856
Precipitation Organization in a Warmer Climate
NASA Astrophysics Data System (ADS)
Rickenbach, T. M.; Nieto Ferreira, R.; Nissenbaum, M.
2014-12-01
This study will investigate changes in precipitation organization in a warmer climate using the Weather Research and Forecasting (WRF) model and CMIP-5 ensemble climate simulations. This work builds from an existing four-year NEXRAD radar-based precipitation climatology over the southeastern U.S. that uses a simple two-category framework of precipitation organization based on instantaneous precipitating feature size. The first category - mesoscale precipitation features (MPF) - dominates winter precipitation and is linked to the more predictable large-scale forcing provided by the extratropical cyclones. In contrast, the second category - isolated precipitation - dominates the summer season precipitation in the southern coastal and inland regions but is linked to less predictable mesoscale circulations and to local thermodynamics more crudely represented in climate models. Most climate modeling studies suggest that an accelerated water cycle in a warmer world will lead to an overall increase in precipitation, but few studies have addressed how precipitation organization may change regionally. To address this, WRF will simulate representative wintertime and summertime precipitation events in the Southeast US under the current and future climate. These events will be simulated in an environment resembling the future climate of the 2090s using the pseudo-global warming (PGW) approach based on an ensemble of temperature projections. The working hypothesis is that the higher water vapor content in the future simulation will result in an increase in the number of isolated convective systems, while MPFs will be more intense and longer-lasting. In the context of the seasonal climatology of MPF and isolated precipitation, these results have implications for assessing the predictability of future regional precipitation in the southeastern U.S.
NASA Astrophysics Data System (ADS)
Tomczik, D. W.; Norris, R. D.; Gaskell, D. E.
2014-12-01
A partial analog for future global change is the Paleocene-Eocene Thermal Maximum—a transient episode of warming, acidification, and biogeographic change at ~55.5 Ma. The PETM is known to have triggered extinction in some deep sea biotas, extensive biogeographic range shifts, and the common occurrence of 'excursion biotas'—non-analog occurrences of species that are typically rare in the open ocean before or after the PETM. Here we report on the impact of the PETM on fish production and biodiversity. Our data include the mass accumulation rate of fish teeth and denticles as well as an analysis of tooth morphotypes for three PETM sites: ODP 1220 and 1209 in the Pacific, and ODP 1260 in the equatorial Atlantic. Tooth morphotypes hardly change through the PETM and consist of abundant midwater species (angler fish and flashlight fish) in addition to sharks and epipelagic fish. There is no evidence for a non-analog 'excursion biota' during the PETM, suggesting that fish experienced fewer geographic range shifts than the calcareous and organic-walled plankton where excursion biotas are commonplace. Fish mass accumulation rates are also relatively stable before and after the PETM although all sites show a transient rise in fish production at the onset of the PETM or within the later part of the "PETM Core". These results broadly match published estimates of PETM export production from biogenic barium fluxes. Our findings run counter to "Future Earth" models that use climate forecasts for the next century to predict the impact of global change on fish stocks. These models suggest that future warming and ocean stratification will decrease most tropical and subtropical ocean fish production, accentuate fish production in the boundary currents and generally shift production toward higher latitudes. A resolution of "Future Earth" models and PETM data may reflect the different timescales of observation and stages of ecological response to severe global change.
Lidar Measurements of Atmospheric CO2 From Regional to Global Scales
NASA Technical Reports Server (NTRS)
Lin, Bing; Harrison, F. Wallace; Nehrir, Amin; Browell, Edward; Dobler, Jeremy; Campbell, Joel; Meadows, Byron; Obland, Michael; Ismail, Syed; Kooi, Susan;
2015-01-01
Atmospheric CO2 is a critical forcing for the Earth's climate and the knowledge on its distributions and variations influences predictions of the Earth's future climate. Large uncertainties in the predictions persist due to limited observations. This study uses the airborne Intensity-Modulated Continuous-Wave (IMCW) lidar developed at NASA Langley Research Center to measure regional atmospheric CO2 spatio-temporal variations. Further lidar development and demonstration will provide the capability of global atmospheric CO2 estimations from space, which will significantly advances our knowledge on atmospheric CO2 and reduce the uncertainties in the predictions of future climate. In this presentation, atmospheric CO2 column measurements from airborne flight campaigns and lidar system simulations for space missions will be discussed. A measurement precision of approx.0.3 ppmv for a 10-s average over desert and vegetated surfaces has been achieved. Data analysis also shows that airborne lidar CO2 column measurements over these surfaces agree well with in-situ measurements. Even when thin cirrus clouds present, consistent CO2 column measurements between clear and thin cirrus cloudy skies are obtained. Airborne flight campaigns have demonstrated that precise atmospheric column CO2 values can be measured from current IM-CW lidar systems, which will lead to use this airborne technique in monitoring CO2 sinks and sources in regional and continental scales as proposed by the NASA Atmospheric Carbon and Transport â€" America project. Furthermore, analyses of space CO2 measurements shows that applying the current IM-CW lidar technology and approach to space, the CO2 science goals of space missions will be achieved, and uncertainties in CO2 distributions and variations will be reduced.
Belanger, Christina L.
2012-01-01
Modern climate change has a strong potential to shift earth systems and biological communities into novel states that have no present-day analog, leaving ecologists with no observational basis to predict the likely biotic effects. Fossil records contain long time-series of past environmental changes outside the range of modern observation, which are vital for predicting future ecological responses, and are capable of (a) providing detailed information on rates of ecological change, (b) illuminating the environmental drivers of those changes, and (c) recording the effects of environmental change on individual physiological rates. Outcrops of Early Miocene Newport Member of the Astoria Formation (Oregon) provide one such time series. This record of benthic foraminiferal and molluscan community change from continental shelf depths spans a past interval environmental change (∼20.3-16.7 mya) during which the region warmed 2.1–4.5°C, surface productivity and benthic organic carbon flux increased, and benthic oxygenation decreased, perhaps driven by intensified upwelling as on the modern Oregon coast. The Newport Member record shows that (a) ecological responses to natural environmental change can be abrupt, (b) productivity can be the primary driver of faunal change during global warming, (c) molluscs had a threshold response to productivity change while foraminifera changed gradually, and (d) changes in bivalve body size and growth rates parallel changes in taxonomic composition at the community level, indicating that, either directly or indirectly through some other biological parameter, the physiological tolerances of species do influence community change. Ecological studies in modern and fossil records that consider multiple ecological levels, environmental parameters, and taxonomic groups can provide critical information for predicting future ecological change and evaluating species vulnerability. PMID:22558424
NASA Astrophysics Data System (ADS)
Šolić, Mladen; Krstulović, Nada; Šantić, Danijela; Šestanović, Stefanija; Kušpilić, Grozdan; Bojanić, Natalia; Ordulj, Marin; Jozić, Slaven; Vrdoljak, Ana
2017-09-01
The Mediterranean Sea (including the Adriatic Sea) has been identified as a 'hotspot' for climate change, with the prediction of the increase in water temperature of 2-4 °C over the next few decades. Being mainly oligotrophic, and strongly phosphorus limited, the Adriatic Sea is characterized by the important role of the microbial food web in production and transfer of biomass and energy towards higher trophic levels. We hypothesized that predicted 3 °C temperature rise in the near future might cause an increase of bacterial production and bacterial losses to grazers, which could significantly enlarge the trophic base for metazoans. This empirical study is based on a combined 'space-for-time substitution' analysis (which is performed on 3583 data sets) and on an experimental approach (36 in situ grazing experiments performed at different temperatures). It showed that the predicted 3 °C temperature increase (which is a result of global warming) in the near future could cause a significant increase in bacterial growth at temperatures lower than 16 °C (during the colder winter-spring period, as well as in the deeper layers). The effect of temperature on bacterial growth could be additionally doubled in conditions without phosphorus limitation. Furthermore, a 3 °C increase in temperature could double the grazing on bacteria by heterotrophic nanoflagellate (HNF) and ciliate predators and it could increase the proportion of bacterial production transferred to the metazoan food web by 42%. Therefore, it is expected that global warming may further strengthen the role of the microbial food web in a carbon cycle in the Adriatic Sea.
NASA Astrophysics Data System (ADS)
Tewksbury, J.
2016-12-01
Future Earth has emerged from the more than 30-year history of Global Change Research Programs, including IGBP, DIVERSITAS and IHDP. These programs supported interdisciplinary science in service of societies around the world. Now, their focus on building a greater understanding of changing Earth systems and their couplings with society has passed to Future Earth - with an important addition: Future Earth was also established to focus global change efforts around key societal challenges. The implications for the structure of Future Earth are large. Many challenges within topics, such as the water, energy, food nexus or the future of cities, are manifested within local, national, and regional contexts. How should we organize globally to most effectively confront these multi-scale challenges? The solution proposed in the framing of Future Earth was the formation of regional as well as national committees, as well as the formation of regional centers and offices. Regional Committees serve to both advocate for Future Earth in their regions and to advocate for regional interests in the global Future Earth platform, while regional Centers and offices are built into the Future Earth secretariat to perform a parallel regional implementation function. Implementation has not been easy, and the process has placed regionally-focused projects in an awkward place. Programs such as the Monsoon Asia Integrated Regional Study (MAIRS), the Northern Eurasia Earth Science Partnership Initiative (NEESPI), and the South/Southeast Asia Research Initiative (SARI) represent some of the best global change communities in the world, but by design, their focus is regional. The effective integration of these communities into the Future Earth architecture will be critical, and this integration will require the formation of strong regional committees and regional centers.
NASA Astrophysics Data System (ADS)
Thomas, R. Q.; Zaehle, S.; Templer, P. H.; Goodale, C. L.
2011-12-01
Predictions of climate change depend on accurately modeling the feedbacks among the carbon cycle, nitrogen cycle, and climate system. Several global land surface models have shown that nitrogen limitation determines how land carbon fluxes respond to rising CO2, nitrogen deposition, and climate change, thereby influencing predictions of climate change. However, the magnitude of the carbon-nitrogen-climate feedbacks varies considerably by model, leading to critical and timely questions of why they differ and how they compare to field observations. To address these questions, we initiated a model inter-comparison of spatial patterns and drivers of nitrogen limitation. The experiment assessed the regional consequences of sustained nitrogen additions in a set of 25-year global nitrogen fertilization simulations. The model experiments were designed to cover effects from small changes in nitrogen inputs associated with plausible increases in nitrogen deposition to large changes associated with field-based nitrogen fertilization experiments. The analyses of model simulations included assessing the geographically varying degree of nitrogen limitation on plant and soil carbon cycling and the mechanisms underlying model differences. Here, we present results from two global land-surface models (CLM-CN and O-CN) with differing approaches to modeling carbon-nitrogen interactions. The predictions from each model were compared to a set of globally distributed observational data that includes nitrogen fertilization experiments, 15N tracer studies, small catchment nitrogen input-output studies, and syntheses across nitrogen deposition gradients. Together these datasets test many aspects of carbon-nitrogen coupling and are able to differentiate between the two models. Overall, this study is the first to explicitly benchmark carbon and nitrogen interactions in Earth System Models using a range of observations and is a foundation for future inter-comparisons.
Kuerbis, Alexis; Armeli, Stephen; Muench, Frederick; Morgenstern, Jon
2013-12-01
Despite ample research demonstrating the role of motivation and self-efficacy in predicting drinking in the context of abstinence, little research explicitly explores their role in the context of moderation, and none have utilized daily diary methods. The purpose of this study was to (a) explore the concordance between global self-report and daily diary composite measures of motivation and self-efficacy and (b) compare the ability of each in predicting drinking outcomes in the context of a study of brief AUD treatments focused on controlled drinking. Problem drinkers (N = 89) were assessed, provided feedback about their drinking, and randomly assigned to one of three conditions: two brief AUD treatments or a third group asked to change on their own. Global self-report (GSR) measures were administered at baseline and Week 8 (end of treatment). Daily diary composites (DDC) were created from data collected via an Interactive Voice Recording system during the week prior to baseline and the week prior to Week 8. Findings revealed some concordance between GSR and DDC at both baseline and Week 8, indicating the two methods capture some of the same construct; however, their respective relationships to drinking differed. DDC for both baseline and Week 8 significantly predicted Week 8 drinking outcomes, whereas only change in GSR significantly predicted drinking outcomes. Findings suggest that motivation and self-efficacy are important to moderated drinking, and that both GSR and daily diary methods are useful in understanding mechanisms of change in the context of moderation. Daily diary methods may provide significant advantages. Limitations and arenas for future research are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Predicting the persistence of coastal wetlands to global change stressors
Guntenspergen, G.; McKee, K.; Cahoon, D.; Grace, J.; Megonigal, P.
2006-01-01
Despite progress toward understanding the response of coastal wetlands to increases in relative sea-level rise and an improved understanding of the effect of elevated CO2 on plant species allocation patterns, we are limited in our ability to predict the response of coastal wetlands to the effects associated with global change. Static simulations of the response of coastal wetlands to sea-level rise using LIDAR and GIS lack the biological and physical feedback mechanisms present in such systems. Evidence from current research suggests that biotic processes are likely to have a major influence on marsh vulnerability to future accelerated rates of sea-level rise and the influence of biotic processes likely varies depending on hydrogeomorphic setting and external stressors. We have initiated a new research approach using a series of controlled mesocosm and field experiments, landscape scale studies, a comparative network of brackish coastal wetland monitoring sites and a suite of predictive models that address critical questions regarding the vulnerability of coastal brackish wetland systems to global change. Specifically, this research project evaluates the interaction of sea level rise and elevated CO2 concentrations with flooding, nutrient enrichment and disturbance effects. The study is organized in a hierarchical structure that links mesocosm, field, landscape and biogeographic levels so as to provide important new information that recognizes that coastal wetland systems respond to multiple interacting drivers and feedback effects controlling wetland surface elevation, habitat stability and ecosystem function. We also present a new statistical modelling technique (Structural Equation Modelling) that synthesizes and integrates our environmental and biotic measures in a predictive framework that forecasts ecosystem change and informs managers to consider adaptive shifts in strategies for the sustainable management of coastal wetlands.
NASA Astrophysics Data System (ADS)
Mahmud, A.; Hixson, M.; Hu, J.; Zhao, Z.; Chen, S.-H.; Kleeman, M. J.
2010-11-01
The effect of global climate change on the annual average concentration of fine particulate matter (PM2.5) in California was studied using a climate-air quality modeling system composed of global through regional models. Output from the NCAR/DOE Parallel Climate Model (PCM) generated under the "business as usual" global emissions scenario was downscaled using the Weather Research and Forecasting (WRF) model followed by air quality simulations using the UCD/CIT airshed model. The system represents major atmospheric processes acting on gas and particle phase species including meteorological effects on emissions, advection, dispersion, chemical reaction rates, gas-particle conversion, and dry/wet deposition. The air quality simulations were carried out for the entire state of California with a resolution of 8-km for the years 2000-2006 (present climate with present emissions) and 2047-2053 (future climate with present emissions). Each of these 7-year analysis periods was analyzed using a total of 1008 simulated days to span a climatologically relevant time period with a practical computational burden. The 7-year windows were chosen to properly account for annual variability with the added benefit that the air quality predictions under the present climate could be compared to actual measurements. The climate-air quality modeling system successfully predicted the spatial pattern of present climate PM2.5 concentrations in California but the absolute magnitude of the annual average PM2.5 concentrations were under-predicted by ~4-39% in the major air basins. The majority of this under-prediction was caused by excess ventilation predicted by PCM-WRF that should be present to the same degree in the current and future time periods so that the net bias introduced into the comparison is minimized. Surface temperature, relative humidity (RH), rain rate, and wind speed were predicted to increase in the future climate while the ultra violet (UV) radiation was predicted to decrease in major urban areas in the San Joaquin Valley (SJV) and South Coast Air Basin (SoCAB). These changes lead to a predicted decrease in PM2.5 mass concentrations of ~0.3-0.7 μg m-3 in the southern portion of the SJV and ~0.3-1.1 μg m-3 along coastal regions of California including the heavily populated San Francisco Bay Area and the SoCAB surrounding Los Angeles. Annual average PM2.5 concentrations were predicted to increase at certain locations within the SJV and the Sacramento Valley (SV) due to the effects of climate change, but a corresponding analysis of the annual variability showed that these predictions are not statistically significant (i.e. the choice of a different 7-year period could produce a different outcome for these regions). Overall, virtually no region in California outside of coastal + central Los Angeles, and a small region around the port of Oakland in the San Francisco Bay Area experienced a statistically significant change in annual average PM2.5 concentrations due to the effects of climate change in the present~study. The present study employs the highest spatial resolution (8 km) and the longest analysis windows (7 years) of any climate-air quality analysis conducted for California to date, but the results still have some degree of uncertainty. Most significantly, GCM calculations have inherent uncertainty that is not fully represented in the current study since a single GCM was used as the starting point for all calculations. The PCM results used in the current study predicted greater wintertime increases in air temperature over the Pacific Ocean than over land, further motivating comparison to other GCM results. Ensembles of GCM results are usually employed to build confidence in climate calculations. The current results provide a first data-point for the climate-air quality analysis that simultaneously employ the fine spatial resolution and long time scales needed to capture the behavior of climate-PM2.5 interactions in California. Future downscaling studies should follow up with a full ensemble of GCMs as their starting point, and include aerosol feedback effects on local meteorology.