Dynamics of harmful dinoflagellates driven by temperature and salinity in a northeastern Mediterranean lagoon

To attempt to determine the effects of temperature and salinity on the dynamics of the dinoflagellate community, a monthly sampling was carried out from October 2008 to March 2009 at eight sampling stations in Ghar El Melh Lagoon (GML; Mediterranean Sea, Northern Tunisia). Dinoflagellates were dominant among plankton, accounting for 73.9 % of the lagoon’s overall plankton community, and were comprised of 25 different species among which 17 were reported in the literature as harmful. While no significant difference was found in the distribution of dinoflagellates among the stations, a strong monthly difference was observed. This temporal variability was due to an increase in the abundance of Prorocentrum micans from December to February, leading to a strong decrease in the Shannon diversity index from station to station. At the onset of P. micans development, dinoflagellate abundances reached 1.26.10⁵ cells l^?1. A redundance analysis indicates that both temperature and salinity have a significant effect on the dynamics of the dinoflagellate community. Using a generalized additive model, both temperature and salinity appear to have significant nonlinear relationships with P. micans abundances. Model predictions indicate that outbreaks of P. micans may occur at a temperature below 22.5 °C and with salinity above 32.5. We discuss our results against a backdrop of climate change which, by affecting temperature and salinity, is likely to have an antagonistic impact on P. micans development and subsequently on the dinoflagellate dynamics in GML.     

Coupling climate and economic models in a cost-benefit framework: A convex optimisation approach

In this paper, we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99, we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model, which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle, which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model.     

A General Equilibrium Assessment of Climate Change Impacts on Swiss Winter Tourism with Adaptation

Winter alpine tourism has been repeatedly identified as one of the economic sectors most at risk from climate change in Switzerland. However, all of the costs that have been estimated so far for the Swiss tourism sector are, to some extent, misleading as they do not, or only partially, incorporate adaptation possibilities and general equilibrium effects. We attempt to fill this gap using a computable general equilibrium model that is specifically designed for the purposes of this research. Our modeling efforts first consist in creating a tourism sector with a part of it being dependent on snow. We also carefully model the snowmaking technology. Using climate change scenarios on future snow cover, we analyze their impacts on the Swiss ski industry. We find welfare effects for the Swiss economy ranging from − 23 to 113 million CHF in 2050. This range arises from the use of various assumptions concerning adaptation possibilities. We also show that geographical substitutions between international ski destinations have large positive effects for Switzerland. From a more general perspective, our results exemplify the risks of estimating the consequences of climate change based only on domestic impacts of climate change with no adaptation being implemented.

     

Changes in Near-Surface Temperature and Sea Level for the Post-SRES CO2-Stabilization Scenarios

Changes in global near-surface temperature and sea level are calculated from 2000 to 2100 for the Post-SRES (Special Report on Emissions Scenarios) scenarios that stabilize the CO₂ concentration early in the 22nd century. Seven stabilization scenarios are examined together with their corresponding SRES marker scenarios – A1, A1/S450, A1/S550, A1/S650, A2, A2/S550, A2/S750, B1, B1/S450, B2, and B2/S550 – where the number following the S indicates the stabilized CO₂ concentration in parts per million by volume (ppmv). The calculations are performed using an energy-balance-climate/upwelling-diffusion-ocean model for three values of the climate sensitivity, ΔT _2x =1.5, 2.5 and 4.5°C. The resulting reductions in global warming and sea-level rise for the stabilization scenarios relative to their corresponding marker scenario increases with ΔT _2x and are greater the lower the stabilized CO₂ concentration. For the S550 stabilization scenarios, the reductions in global warming and sea-level rise in 2100 range from 0.29°C and 3.31 cm for B2/S550 with ΔT _2x =1.5°C, to 1.23°C and 11.81 cm for A2/S550 with ΔT _2x =4.5°C. The percent reductions for the global warming and sea-level rise for each stabilization scenario are almost independent of ΔT _2x and range respectively from about 16% and 12% for the A1/S650 scenario to about 39% and 30% for the A1/S450 scenario. The geographical distributions of near-surface temperature change are constructed using a method to superpose the patterns simulated by our atmospheric general-circulation/mixed-layer-ocean model, individually for doubled CO₂ concentration and decupled SO₄ burden. Results are illustrated for the B2 and B2/S550 scenarios for ΔT _2x =2.5°C. The near-surface temperature changes of the B2/S550 scenario in 2100 are everywhere smaller than those for the B2 scenario, with values ranging from about 0.3°C in the tropics to 0.5°C over Antarctica and 0.7°C in the Arctic. The global results of this study are available on the web at: http://crga.atmos.uiuc.edu/research/post-sres.html. We would be pleased to collaborate with other researchers in using these results in impact and integrated-assessment studies. This revised version was published online in July 2006 with corrections to the Cover Date.     

Predicting climate change effects on surface soil organic carbon of Louisiana,USA

This study aimed to assess the degree of potential temperature and precipitation change as predicted by the HadCM3 (Hadley Centre Coupled Model, version 3) climate model for Louisiana, and to investigate the effects of potential climate change on surface soil organic carbon (SOC) across Louisiana using the Rothamsted Carbon Model (RothC) and GIS techniques at the watershed scale. Climate data sets at a grid cell of 0.5°?×?0.5° for the entire state of Louisiana were collected from the HadCM3 model output for three climate change scenarios: B2, A2, and A1F1, that represent low, higher, and even higher greenhouse gas emissions, respectively. Geo-referenced datasets including USDA-NRCS Soil Geographic Database (STATSGO), USGS Land Cover Dataset (NLCD), and the Louisiana watershed boundary data were gathered for SOC calculation at the watershed scale. A soil carbon turnover model, RothC, was used to simulate monthly changes in SOC from 2001 to 2100 under the projected temperature and precipitation changes. The simulated SOC changes in 253 watersheds from three time periods, 2001–2010, 2041–2050, and 2091–2100, were tested for the influence of the land covers and emissions scenarios using SAS PROC GLIMMIX and PDMIX800 macro to separate Tukey-Kramer (p?p?p?p?相似文献   

Climatic Implications of Revised IPCC Emissions Scenarios, the Kyoto Protocol and Quantification of Uncertainties

In December 1997, the United Nations Framework Convention on Climate Change (FCCC) adopted the Kyoto Protocol. This paper describes a framework that models the climatic implications of this international agreement, using Monte Carlo simulations and the preliminary Intergovernmental Panel on Climate Change emissions scenarios (SRES). Emissions scenarios (including intervention scenarios), climate sensitivity, and terrestrial carbon sink are the key sampled model parameters. This framework gives prior probability distributions to these parameters and, using a simple climate model, posterior distributions of global temperature change are determined for the future. Our exercise showed that the Kyoto Protocol's effectiveness will be mostly dependent upon which SRES world evolves. In some worlds the Protocol decreases the warming considerably but in others it is almost irrelevant. We exemplified this approach with a current FCCC issue, namely “hot air”. This modelling framework provides a probabilistic assessment of climate policies, which can be useful for decision-makers involved in global climate change management. This revised version was published online in July 2006 with corrections to the Cover Date.     

Regional impact analysis of climate change on natural and managed forests in the Federal State of Brandenburg, Germany

A methodology for regional application of forest simulation models has been developed as part of an assessment of possible climate change impacts in the Federal state of Brandenburg (Germany). Here we report on the application of a forest gap model to analyse the impacts of climate change on species composition and productivity of natural and managed forests in Brandenburg using a statistical method for the development of climate scenarios. The forest model was linked to a GIS that includes soil and groundwater table maps, as well as gridded climate data with a resolution of 10 × 10 km and simulated a steady-state species composition which was classified into forest types based on the biomass distribution between species. Different climate scenarios were used to assess the sensitivity of species composition to climate change. The simulated forest distribution patterns for current climate were compared with a map of Potential Natural Vegetation (PNV) of Brandenburg.In order to analyse the possible consequences of climate change on forest management, we used forest inventory data to initialize the model with representative forest stands. Simulation experiments with two different management strategies indicated how forest management could respond to the projected impacts of climate change. The combination of regional analysis of natural forest dynamics under climate change with simulation experiments for managed forests outlines possible trends for the forest resources. The implications of the results are discussed, emphasizing the regional differences in environmental risks and the adaptation potentials of forestry in Brandenburg.     

The potential effects of climate change on the distribution and productivity of Cunninghamia lanceolata in China

Climate changes may have immediate implications for forest productivity and may produce dramatic shifts in tree species distributions in the future. Quantifying these implications is significant for both scientists and managers. Cunninghamia lanceolata is an important coniferous timber species due to its fast growth and wide distribution in China. This paper proposes a methodology aiming at enhancing the distribution and productivity of C. lanceolata against a background of climate change. First, we simulated the potential distributions and establishment probabilities of C. lanceolata based on a species distribution model. Second, a process-based model, the PnET-II model, was calibrated and its parameterization of water balance improved. Finally, the improved PnET-II model was used to simulate the net primary productivity (NPP) of C. lanceolata. The simulated NPP and potential distribution were combined to produce an integrated indicator, the estimated total NPP, which serves to comprehensively characterize the productivity of the forest under climate change. The results of the analysis showed that (1) the distribution of C. lanceolata will increase in central China, but the mean probability of establishment will decrease in the 2050s; (2) the PnET-II model was improved, calibrated, and successfully validated for the simulation of the NPP of C. lanceolata in China; and (3) all scenarios predicted a reduction in total NPP in the 2050s, with a markedly lower reduction under the a2 scenario than under the b2 scenario. The changes in NPP suggested that forest productivity will show a large decrease in southern China and a mild increase in central China. All of these findings could improve our understanding of the impact of climate change on forest ecosystem structure and function and could provide a basis for policy-makers to apply adaptive measures and overcome the unfavorable influences of climate change.     

Response of non-point source pollutant loads to climate change in the Shitoukoumen reservoir catchment

The impacts of climate change on streamflow and non-point source pollutant loads in the Shitoukoumen reservoir catchment are predicted by combining a general circulation model (HadCM3) with the Soil and Water Assessment Tool (SWAT) hydrological model. A statistical downscaling model was used to generate future local scenarios of meteorological variables such as temperature and precipitation. Then, the downscaled meteorological variables were used as input to the SWAT hydrological model calibrated and validated with observations, and the corresponding changes of future streamflow and non-point source pollutant loads in Shitoukoumen reservoir catchment were simulated and analyzed. Results show that daily temperature increases in three future periods (2010–2039, 2040–2069, and 2070–2099) relative to a baseline of 1961–1990, and the rate of increase is 0.63°C per decade. Annual precipitation also shows an apparent increase of 11 mm per decade. The calibration and validation results showed that the SWAT model was able to simulate well the streamflow and non-point source pollutant loads, with a coefficient of determination of 0.7 and a Nash–Sutcliffe efficiency of about 0.7 for both the calibration and validation periods. The future climate change has a significant impact on streamflow and non-point source pollutant loads. The annual streamflow shows a fluctuating upward trend from 2010 to 2099, with an increase rate of 1.1 m³ s⁻¹ per decade, and a significant upward trend in summer, with an increase rate of 1.32 m³ s⁻¹ per decade. The increase in summer contributes the most to the increase of annual load compared with other seasons. The annual NH₄⁺-N load into Shitoukoumen reservoir shows a significant downward trend with a decrease rate of 40.6 t per decade. The annual TP load shows an insignificant increasing trend, and its change rate is 3.77 t per decade. The results of this analysis provide a scientific basis for effective support of decision makers and strategies of adaptation to climate change.     

Potential Impact of Climate Change on Residential Energy Consumption in Dhaka City

This study aimed to assess the impacts of climate change on residential energy consumption in Dhaka city of Bangladesh. The monthly electricity consumption data for the period 2011–2014 and long-term climate variables namely monthly rainfall and temperature records (1961–2010) were used in the study. An ensemble of six global circulation models (GCMs) of coupled model intercomparison project phase 5 (CMIP5) namely, BCCCSM1-1, CanESM2, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, and NorESM1-M under four representative concentration pathway (RCP) scenarios were used to project future changes in rainfall and temperature. The regression models describing the relationship between historical energy consumption and climate variables were developed to project future changes in energy consumptions. The results revealed that daily energy consumption in Dhaka city increases in the range of 6.46–11.97 and 2.37–6.25 MkWh at 95% level of confidence for every increase of temperature by 1 °C and daily average rainfall by 1 mm, respectively. This study concluded that daily total residential energy demand and peak demand in Dhaka city can increase up to 5.9–15.6 and 5.1–16.7%, respectively, by the end of this century under different climate change scenarios.     

Robust Energy Portfolios Under Climate Policy and Socioeconomic Uncertainty

Concerning the stabilization of greenhouse gases, the UNFCCC prescribes measures to anticipate, prevent, or minimize the causes of climate change and mitigate their adverse effects. Such measures should be cost-effective and scientific uncertainty should not be used as a reason for postponing them. However, in the light of uncertainty about climate sensitivity and other underlying parameters, it is difficult to assess the importance of different technologies in achieving robust long-term climate risk mitigation. One example currently debated in this context is biomass energy, which can be used to produce both carbon-neutral energy carriers, e.g., electricity, and at the same time offer a permanent CO₂ sink by capturing carbon from the biomass at the conversion facility and permanently storing it. We use the GGI Scenario Database IIASA [3] as a point of departure for deriving optimal technology portfolios across different socioeconomic scenarios for a range of stabilization targets, focusing, in particular, on new, low-emission scenarios. More precisely, the dynamics underlying technology adoption and operational decisions are analyzed in a real options model, the output of which then informs the portfolio optimization. In this way, we determine the importance of different energy technologies in meeting specific stabilization targets under different circumstances (i.e., under different socioeconomic scenarios), providing valuable insight to policymakers about the incentive mechanisms needed to achieve robust long-term climate risk mitigation.     

Using Temporal Coherence to Determine the Response to Climate Change in Boreal Shield Lakes

Climate change is expected to have important impacts on aquatic ecosystems. On the Boreal Shield, mean annual air temperatures are expected to increase 2 to 4°C over the next 50 years. An important challenge is to predict how changes in climate and climate variability will impact natural systems so that sustainable management policies can be implemented. To predict responses to complex ecosystem changes associated with climate change, we used long-term biotic databases to evaluate how important elements of the biota in Boreal Shield lakes have responded to past fluctuations in climate. Our long-term records span a two decade period where there have been unusually cold years and unusually warm years. We used coherence analyses to test for regionally operating controls on climate, water temperature, pH, and plankton richness and abundance in three regions across Ontario: the Experimental Lakes Area, Sudbury, and Dorset. Inter-annual variation in air temperature was similar among regions, but there was a weak relationship among regions for precipitation. While air temperature was closely related to lake surface temperatures in each of the regions, there were weak relationships between lake surface temperature and richness or abundance of the plankton. However, inter-annual changes in lake chemistry (i.e., pH) were correlated with some biotic variables. In some lakes in Sudbury and Dorset, pH was dependent on extreme events. For example, El Nino related droughts resulted in acidification pulses in some lakes that influenced phytoplankton and zooplankton richness. These results suggest that there can be strong heterogeneity in lake ecosystem responses within and across regions.     

The Impact of Uncertainty in Climate Targets and CO2 Storage Availability on Long-Term Emissions Abatement

A major characteristic of our global interactive climate-energy system is the large uncertainty that exists with respect to both future environmental requirements and the means available for fulfilling these. Potentially, a key technology for leading the transition from the current fossil fuel-dominated energy system to a more sustainable one is carbon dioxide capture and storage. Uncertainties exist, however, concerning the large-scale implementability of this technology, such as related to the regional availability of storage sites for the captured CO₂. We analyze these uncertainties from an integrated assessment perspective by using the bottom-up model TIAM-ECN and by studying a set of scenarios that cover a range of different climate targets and technology futures. Our study consists of two main approaches: (1) a sensitivity analysis through the investigation of a number of scenarios under perfect foresight decision making and (2) a stochastic programming exercise that allows for simultaneously considering a set of potential future states-of-the-world. We find that, if a stringent climate (forcing) target is a possibility, it dominates the solution: if deep CO₂ emission reductions are not started as soon as possible, the target may become unreachable. Attaining a stringent climate target comes in any case at a disproportionally high price, which indicates that adaptation measures or climate damages might be preferable to the high mitigation costs such a target implies.     

Nuclear Versus Coal plus CCS: a Comparison of Two Competitive Base-Load Climate Control Options

In this paper, we analyze the relative importance and mutual behavior of two competing base-load electricity generation options that each are capable of contributing significantly to the abatement of global CO₂ emissions: nuclear energy and coal-based power production complemented with CO₂ capture and storage (CCS). We also investigate how, in scenarios developed with an integrated assessment model that simulates the economics of a climate-constrained world, the prospects for nuclear energy would change if exogenous limitations on the spread of nuclear technology were relaxed. Using the climate change economics model World Induced Technical Change Hybrid, we find that until 2050 the growth rates of nuclear electricity generation capacity would become comparable to historical rates observed during the 1980s. Given that nuclear energy continues to face serious challenges and contention, we inspect how extensive the improvements of coal-based power equipped with CCS technology would need to be if our economic optimization model is to significantly scale down the construction of new nuclear power plants.     

Spatiotemporal analysis of the effect of climate change on vegetation health in the Drakensberg Mountain Region of South Africa

The impact of climate change on mountain ecosystems has been in the spotlight for the past three decades. Climate change is generally considered to be a threat to ecosystem health in mountain regions. Vegetation indices can be used to detect shifts in ecosystem phenology and climate change in mountain regions while satellite imagery can play an important role in this process. However, what has remained problematic is determining the extent to which ecosystem phenology is affected by climate change under increasingly warming conditions. In this paper, we use climate and vegetation indices that were derived from satellite data to investigate the link between ecosystem phenology and climate change in the Namahadi Catchment Area of the Drakensberg Mountain Region of South Africa. The time series for climate indices as well as those for gridded precipitation and temperature data were analyzed in order to determine climate shifts, and concomitant changes in vegetation health were assessed in the resultant epochs using vegetation indices. The results indicate that vegetation indices should only be used to assess trends in climate change under relatively pristine conditions, where human influence is limited. This knowledge is important for designing climate change monitoring strategies that are based on ecosystem phenology and vegetation health.     

The long time scales of the climate–economy feedback and the climatic cost of growth

This paper is based on the perception that the inertia of climate and socio-economic systems are key parameters in the climate change issue. In a first part, it develops and implements a new approach based on a simple integrated model with a particular focus on an innovative transient impact and adaptation modeling. In a second part, a climate–economy feedback is defined and characterized. The following results were found. 1) It has a long characteristic time, which lies between 50 and 100 years depending on the hypotheses; this time scale is long when compared to the system's other time scales, and the feedback cannot act as a natural damping process of climate change. 2) Mitigation has to be anticipated since the feedback of an emission reduction on the economy can be significant only after a 20-year delay and is really efficient only after at least 50 years. 3) Even discounted, production changes due to an action on emissions are significant over more than one century. 4) The methodology of the Intergovernmental Panel on Climate Change (IPCC), which neglects the feedback from impacts to emissions, is acceptable up to 2100, whatever is the level of impacts. This analysis allows also to define a climatic cost of growth as the additional climate change damages due to the additional emissions linked to economic growth.

Effects of Temperature–Climate Patterns on the Production of Some Competitive Species on Grounds of Modelling

Climate change has serious effects on the setting up and the operation of natural ecosystems. Small increase in temperature could cause rise in the amount of some species or potential disappearance of others. During our researches, the dispersion of the species and biomass production of a theoretical ecosystem were examined on the effect of the temperature–climate change. The answers of the ecosystems which are given to the climate change could be described by means of global climate modelling and dynamic vegetation models. The examination of the operation of the ecosystems is only possible in huge centres on supercomputers because of the number and the complexity of the calculation. The number of the calculation could be decreased to the level of a PC by considering the temperature and the reproduction during modelling a theoretical ecosystem, and several important theoretical questions could be answered.     

Adaptation to Climatic Variability and Change: Asian Perspectives on Agriculture and Food Security

The impacts of climate change on potential rice production in Asia are reviewed in the light of the adaptation to climatic variability and change. Collaborative studies carried out by IRRI and US-EPA reported that using process-based crop simulation models increasing temperature may decrease rice potential yield up to 7.4% per degree increment of temperature. When climate scenarios predicted by GCMs were applied it was demonstrated that rice production in Asia may decline by 3.8% under the climates of the next century. Moreover, changes in rainfall pattern and distribution were also found suggesting the possible shift of agricultural lands in the region. The studies however have not taken the impacts of climatic variability into account, which often produce extreme events like that caused by monsoons and El Niño. Shifts in rice-growing areas are likely to be constrained by land-use changes occurring for other developmental reasons, which may force greater cultivation of marginal lands and further deforestation. This should be taken into account and lead to more integrated assessment, especially in developing countries where land-use change is more a top-down policy rather than farmers' decision. A key question is: To what extent will improving the ability of societies to cope with current climatic variability through changing design of agricultural systems and practices help the same societies cope with the likely changes in climate?     

Environmental water demand assessment under climate change conditions

Measures taken to cope with the possible effects of climate change on water resources management are key for the successful adaptation to such change. This work assesses the environmental water demand of the Karkheh river in the reach comprising Karkheh dam to the Hoor-al-Azim wetland, Iran, under climate change during the period 2010–2059. The assessment of the environmental demand applies (1) representative concentration pathways (RCPs) and (2) downscaling methods. The first phase of this work projects temperature and rainfall in the period 2010–2059 under three RCPs and with two downscaling methods. Thus, six climatic scenarios are generated. The results showed that temperature and rainfall average would increase in the range of 1.7–5.2 and 1.9–9.2%, respectively. Subsequently, flows corresponding to the six different climatic scenarios are simulated with the unit hydrographs and component flows from rainfall, evaporation, and stream flow data (IHACRES) rainfall-runoff model and are input to the Karkheh reservoir. The simulation results indicated increases of 0.9–7.7% in the average flow under the six simulation scenarios during the period of analysis. The second phase of this paper’s methodology determines the monthly minimum environmental water demands of the Karkheh river associated with the six simulation scenarios using a hydrological method. The determined environmental demands are compared with historical ones. The results show that the temporal variation of monthly environmental demand would change under climate change conditions. Furthermore, some climatic scenarios project environmental water demand larger than and some of them project less than the baseline one.     

Patterns of Avian Nest Predators and a Brood Parasite Among Restored Riparian Habitats in Agricultural Watersheds

In fragmented edge-dominated landscapes, nest predation and brood parasitism may reduce avian reproductive success and, ultimately, populations of some passerine species. In the fragmented agroecosystem of northwest Mississippi, placement of drop-pipe structures has been used as a restoration technique for abating gully erosion along stream banks. These actions have formed small herbaceous and woody habitat extensions into former agricultural lands. We quantified species relative abundances, species richness, and evenness of avian nest predators and a brood parasite within four categories of constructed habitat resulting from drop-pipe installation. Differences in the abundance of two nest predators, cotton mouse (Peromyscus gossypinus) and blue jay (Cyanocitta cristata), were observed among constructed habitats. However, relative abundances of other predators such as common grackle (Quiscalus quiscula), American crow (Corvus brachyrhynchos), and hispid cotton rat (Sigmodon hispidus), and the obligate brood parasite brown-headed cowbird (Molothrus ater) did not differ among four habitat categories. Although species richness, abundance, and evenness of potential nest predators were generally similar among the constructed habitats, predator species composition varied, suggesting that these habitats supported different predator communities. This difference is important because as each predator species is added to or deleted from the community, variation may occur in the framework of prey search methods, predator strategies, and potentially overall predation pressure. We suggest that land managers using drop-pipes as part of stream restoration projects allow for the development of the constructed habitat with the largest area and greatest vegetative structure.