Modeling Climate Change Effects Research Articles

Modeling Climate Change Effects on Genetic Diversity of an Endangered Horse Breed Using Canonical Correlations.

The historical increase in the occurrence of extreme weather events in Spain during the last thirty years makes it a perfect location for the evaluation of climate change. Modeling the effects of climate change on domestic animals' genetic diversity may help to anticipate challenging situations. However, animal populations' short life cycle and patent lack of historical information during extended periods of time drastically compromise the evaluation of climate change effects. Locally adapted breeds' gene pool is the base for their improved resilience and plasticity in response to climate change's extreme climatic conditions. The preservation of these domestic resources offers selection alternatives to breeders who seek such improved adaptability. The Spanish endangered autochthonous Hispano-Arabian horse breed is perfectly adapted to the conditions of the territory where it was created, developed, and widespread worldwide. The possibility to trace genetic diversity in the Hispano-Arabian breed back around seven decades and its global ubiquity make this breed an idoneous reference subject to act as a model for other international populations. Climate change's shaping effects on the genetic diversity of the Hispano-Arabian horse breed's historical population were monitored from 1950 to 2019 and evaluated. Wind speed, gust speed, or barometric pressure have greater repercussions than extreme temperatures on genetic diversity. Extreme climate conditions, rather than average modifications of climate, may push breeders/owners to implement effective strategies in the short to medium term, but the effect will be plausible in the long term due to breed sustainability and enhanced capacity of response to extreme climate events. When extreme climatic conditions occur, breeders opt for mating highly diverse unrelated individuals, avoiding the production of a large number of offspring. People in charge of domestic population conservation act as catalyzers of the regulatory changes occurring during breeds' climate change adaptive process and may identify genes conferring their animals with greater adaptability but still maintaining enhanced performance. This model assists in determining how owners of endangered domestic populations should plan their breeding strategies, seeking the obtention of animals more resilient and adapted to climate-extreme conditions. This efficient alternative is focused on the obtention of increased profitability from this population and in turn ensuring their sustainability.

Modeling climate change effects on transport and fate of pathogens in an urban coastal area of Lake Michigan

Abstract Infrastructure renewal and public health efforts require prediction of climate change effects on the occurrence of pathogens in the Great Lakes' urban coastal waters. This paper presents an investigation that addressed the climate change effects on transport and the fate of bacteria in Milwaukee's urban coastal area. This investigation was part of a study on climate change risks and impacts that included downscaling of climate change data for meteorological stations around Lake Michigan, and implementation of a hydrologic model that predicts tributary flows and bacteria loads. A method to select scenarios appropriate to link watershed and lake transport processes is presented. For the watershed, the sensitivity of bacterial loads with respect to changes in spring-season precipitation and air temperature is critical, while for lake transport, the most important driver is the wind field. Watershed and lake processes are linked by using spring-season watershed loading in the simulation of coastal transport. Scenarios for hydrodynamic modeling were developed by selecting climate projections that yielded high-and-low percentile projected spring-season wind speed. The patterns of bacteria transport showed significant changes under climate change conditions, and the changes in fecal coliform concentration at critical locations were explained by changes in current vector fields.

Non-local modelling of freezing and thawing of unsaturated soils

A large part of the earth’s surface is covered by seasonally or permanently frozen soils. Considering the negative impact of climate change, future development of such regions can be underpinned by mathematical methods for accurate analysis of heat and moisture transport in freezing and thawing soils. Reported in this paper is a novel non-local formulation of water and heat transport in unsaturated soils. The formulation uses bond-based peridynamics (PD) and consists of a set of integral–difference formulations of energy and mass conservation. Specific features of freezing/thawing soils are incorporated by a combination of van Genuthcen and Clausius–Clapeyron relations. Computational results are compared with four sets of laboratory experiments to demonstrate the efficiency of the developed approach. The model can be used to analyse the effect of water flow on heat transfer in soils during thawing of permafrost soils. Further, it can be applied in modelling climate change effects, and can be used for construction of coupled physically justified models of frost heave.

Modeling Climate Change Effects on the Distribution of Oak Forests with Machine Learning

The present study models the effect of climate change on the distribution of Persian oak (Quercus brantii Lindl.) in the Zagros forests, located in the west of Iran. The modeling is conducted under the current and future climatic conditions by fitting the machine learning method of the Bayesian additive regression tree (BART). For the anticipation of the potential habitats for the Persian oak, two general circulation models (GCMs) of CCSM4 and HADGEM2-ES under the representative concentration pathways (RCPs) of 2.6 and 8.5 for 2050 and 2070 are used. The mean temperature (MT) of the wettest quarter (bio8), solar radiation, slope and precipitation of the wettest month (bio13) are respectively reported as the most important variables in the modeling. The results indicate that the suitable habitat of Persian oak will significantly decrease in the future under both climate change scenarios as much as 75.06% by 2070. The proposed study brings insight into the current condition and further projects the future conditions of the local forests for proper management and protection of endangered ecosystems.

Modeling climate change effects on spatial distribution of wild Aegilops L. (Poaceae) toward food security management and biodiversity conservation in Iran.

The demand for food resources is increasing quickly because human populations are growing; therefore, food security may become one of the largest human challenges of this century. Crop wild relatives (CWRs) are the most valuable plant genetic resources (PGR) for the conservation of genetic diversity in crops. However, climate change is an added pressure on biodiversity, particularly on this valuable group of plants. It is predicted that more than 50% of this group may be lost by 2055 as a result of the effects of climate change. Iran ranks high in the world in its conservation priorities for CWRs. This study investigates the impacts of climate change on Aegilops L. as important CWRs. MaxEnt was applied to predict the spatial distribution of seven Aegilops species under different climatic scenarios (RCP 2.6 and RCP 8.5) of 2050 and 2080. According to the findings, all species exhibited reduction or expansion responses under all of the above-mentioned climatic scenarios. However, the range change was negative for some species (i.e., Aegilops columnaris, Aegilops cylindrica, Aegilops speltoides, Aegilops tauschii [in all scenarios of 2050 and 2080], and Aegilops kotschyi [RCP 2.6 2050 and 2080]), and positive for others (i.e., Aegilops crassa, Aegilops triuncialis [in all scenarios of 2050 and 2080], and Aegilops kotschyi [RCP 8.5 2050 and 2080]). The results of this study emphasize the need for conservation plans for the country's genetic resources, including regular monitoring and assessment of ecological and demographic changes. Integr Environ Assess Manag 2022;18:697-708. © 2021 SETAC.

Modeling Climate Change Effects on Rice Yield and Soil Carbon under Variable Water and Nutrient Management

Soil organic carbon (SOC) conservation in agricultural soils is vital for sustainable agricultural production and climate change mitigation. To project changes of SOC and rice yield under different water and carbon management in future climates, based on a two-year (2015 and 2016) field test in Kunshan, China, the Denitrification Decomposition (DNDC) model was modified and validated and the soil moisture module of DNDC was improved to realize the simulation under conditions of water-saving irrigation. Four climate models under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5), which were integrated from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), were ensembled by the Bayesian Model Averaging (BMA) method. The results showed that the modified DNDC model can effectively simulate changes in SOC, dissolved organic carbon (DOC), and rice yield under different irrigation and fertilizer management systems. The normalized root mean squared errors of the SOC and DOC were 3.45–17.59% and 8.79–13.93%, respectively. The model efficiency coefficients of SOC and DOC were close to 1. The climate scenarios had a great impact on rice yield, whereas the impact on SOC was less than that of agricultural management measures on SOC. The average rice yields of all the RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 scenarios in the 2090s decreased by 18.41%, 38.59%, 65.11%, and 65.62%, respectively, compared with those in the 2020s. The long-term effect of irrigation on the SOC content of paddy fields was minimal. The SOC of the paddy fields treated with conventional fertilizer decreased initially and then remained unchanged, while the other treatments increased obviously with time. The rice yields of all the treatments decreased with time. Compared with traditional management, controlled irrigation with straw returning clearly increased the SOC and rice yields of paddy fields. Thus, this water and carbon management system is recommended for paddy fields.

Climate change increases potential plant species richness on Puerto Rican uplands

Modeling climate change effects on species and communities is critical especially in isolated islands. We analyzed the potential effects of climate change on 200 plant species in Puerto Rico under two emission scenarios and in four periods over the twenty-first century. Our approach was based on ensemble bioclimatic modeling using eight modeling algorithms and community richness analysis. Our findings showed that the probabilities of environmental suitability decline for wet climate species and increase for drier and warm climate species in the future periods under both emission scenarios, with stronger effects under the higher emission scenario. Expansion of dry climate species to higher elevations appears to be a prominent response of species to climatic change in the island based on changes in environmental suitability but the actual species redistribution will be influenced by their life histories, potential adaptation, dispersal abilities, species introductions, and species interactions. This potential movement leads to a spatial pattern of species richness at site level that shows a positive relationship with elevation, which becomes stronger in the later periods of the century. The spatial pattern of species richness, if combined with single species projections, can provide critical information for conservation management in the island. Conservation management can support island-wide biological diversity by protecting the wet climate species on the uplands.

Geographical distribution of Stryphnodendron adstringens Mart. Coville (Fabaceae): modeling effects of climate change on past, present and future

The world is passing through abrupt climate changes that are a threat for biodiversity. Stryphnodendron adstringens (Mart.) Coville (Fabaceae) is a tree species endemic to the “Cerrado” biome with a high economic potential. Its exploitation is done in an extractive way, which, coupled with climate changes and other landscape changes, can contribute to its decline. Here, we use ecological niche modeling (ENM) to map its distribution and environmental suitability in the past, present and future climates. The environmental variables were derived from community climate system model, for present, past and future scenarios. The maps showed that the specie had a larger distribution area in the past, during the last glacial maximum, and it decreased mainly in the Amazon rainforest region; today, the species is found mainly in the center of “Cerrado.” For the different climatic scenarios predicted for the future and considering various levels of anthropogenic drivers for climate change, a drastic loss of climatically suitability area of S. adstringens is expected, which may compromise the viability of the species. Our ENMs can then be useful to better establish and delimit conservation actions for this important species in the “Cerrado” region.

Modelling climate change effects on Zagros forests in Iran using individual and ensemble forecasting approaches

It is believed that climate change will cause the extinction of many species in the near future. In this study, we assessed the impact of climate change on the climatic suitability of the Persian oak in Zagros forests in southwest Iran, by simulating their conditions under four climate change scenarios in the 2030s, 2050s, 2070s, and 2080s. Additionally, we evaluated the predictive performance of different modelling algorithms by projecting the geographic distribution of Persian oak, using a block cross-validation technique. According to the results, the Persian oak shows a stronger response to temperature, particularly the maximum temperature of the warmest month, rather than precipitation variables. This indicates that temperature has a powerful control over the geographic distribution of the Persian oak. Based on a comparison of the Persian oak’s current climatic suitability and future projections, regardless of the chosen climatic scenarios, there will be an upward shift in its climatic suitability. However, an upward shift under the pessimistic scenarios was greater than the optimistic ones. The results also indicate that an ensemble of all models had a higher accuracy than single models. Despite the agreement between current climate condition predictions (mean correlation of 0.94), the projection of different algorithms for future periods is highly variable (mean correlation of 0.71). Thus, the ensemble approach was used to reduce the uncertainty of modelling, favouring the consensus of all models for future projection.

Modelling climate change effects on Atlantic salmon: Implications for mitigation in regulated rivers

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.

Modelling climate change effects on benthos: Distributional shifts in the North Sea from 2001 to 2099

In the marine realm, climate change can affect a variety of physico-chemical properties with wide-ranging biological effects, but the knowledge of how climate change affects benthic distributions is limited and mainly restricted to coastal environments. To project the response of benthic species of a shelf sea (North Sea) to the expected climate change, the distributions of 75 marine benthic species were modelled and the spatial changes in distribution were projected for 2099 based on modelled bottom temperature and salinity changes using the IPCC scenario A1B. Mean bottom temperature was projected to increase between 0.15 and 5.4 °C, while mean bottom salinity was projected to moderately increase by 1.7. The spatial changes in species distribution were modelled with Maxent and the direction and extent of these changes were assessed. The results showed a latitudinal northward shift for 64% of the species (maximum 109 km; brittle star Ophiothrix fragilis) and a southward shift for 36% (maximum 101 km; hermit crab Pagurus prideaux and the associated cloak anemone Adamsia carciniopados; 105 km). The relatively low rates of distributional shifts compared to fish or plankton species were probably influenced by the regional topography. The environmental gradients in the central North Sea along the 50 m depth contour might act as a ‘barrier’, possibly resulting in a compression of distribution range and hampering further shifts to the north. For 49 species this resulted in a habitat loss up to 100%, while only 11 species could benefit from the warming in terms of habitat gain. Particularly the benthic communities of the southern North Sea, where the strongest temperature increase was projected, would be strongly affected by the distributional changes, since key species showed northward shifts and high rates of habitat loss, with potential ramifications for the functioning of the ecosystem.

Modeling climate change effects on soil respiration in three different stages of primary succession in deglaciated region on Gongga Mountain, China

Primary succession in deglaciated region is the ideal environment for examining soil respiration (SR). In this study, we measured SR and employed a process-oriented model, Forest-denitrification-decomposition (DNDC), to study responses of SR to climate change in three primary successional stages in deglaciated region on Gongga Mountain, China. Stand types included a hardwood stand (S1), a coniferous and broad-leaved mixed forest stand (S2), and a mature stand of Abies fabri (Mast.) Craib (S3). Four climate scenarios (Baseline, B1, A1B, A2) reported by the Intergovernmental Panel on Climate Change were investigated. According to measured values, there was substantial temporal variation (coefficient of variation ranged from 49.7% in S1 to 61.4% in S3) and spatial variation (annual SR ranged from 2657±944 kg C ha−1 in S1 to 9228±1743 kg C ha−1 in S3) in the data. The modeled results showed that climate change affected the different stages to different extent in this region. Climate change will weaken the carbon sink strength of forest ecosystems in deglaciated region. The results have provided a better understanding on patterns of SR, and provided useful information on the magnitude and the response of SR to climate change in deglaciated region.

Modelling climate change effects in southern Brazil

ABSTRACT Figueiredo, S.A., 2013. Modeling climate change effects in southern Brazil. Along the coast of Rio Grande do Sul state, southern Brazil, differences on coastal configuration are generally accompanied by changes in substrate slope, where steeper gradients characterize coastal projections and gentle gradients the coastal embayments. This study focus on coastal response to climate change effects at two sectors along RS coast: Cassino embayment and Conceicao lighthouse projection. The former has been under very high rates of progradation, on the order of at least 3 m/yr at geological and historical time scales. Whereas Conceicao region has been undergoing rates of recession reaching −3.6 m/yr. In order to forecast coastal response to the effects of climate change at these sites over several time horizons (2030–2070–2100), model simulations using the DRanSTM (Dilating Random Shoreface Translation Model) were performed. Simulation results have demonstrated that Cassino sector is particularly vulnerable...

Modelling climate change effects on a Dutch coastal groundwater system using airborne electromagnetic measurements

Abstract. The forecast of climate change effects on the groundwater system in coastal areas is of key importance for policy makers. The Dutch water system has been deeply studied because of its complex system of low-lying areas, dunes, land won to the sea and dikes, but nowadays large efforts are still being done to find out the best techniques to describe complex fresh-brackish-saline groundwater dynamic systems. In this paper, we describe a methodology consisting of high-resolution airborne electromagnetic (EM) measurements used in a 3-D variable-density transient groundwater model for a coastal area in the Netherlands. We used the airborne EM measurements in combination with borehole-logging data, electrical conductivity cone penetration tests and groundwater samples to create a 3-D fresh-brackish-saline groundwater distribution of the study area. The EM measurements proved to be an improvement compared to older techniques and provided quality input for the model. With the help of the built 3-D variable-density groundwater model, we removed the remaining inaccuracies of the 3-D chloride field and predicted the effects of three climate scenarios on the groundwater and surface water system. Results showed significant changes in the groundwater system, and gave direction for future water policy. Future research should provide more insight in the improvement of data collection for fresh-brackish-saline groundwater systems as it is of high importance to further improve the quality of the model.

Bayesian analysis of climate change effects on observed and projected airborne levels of birch pollen

A Bayesian framework is presented for modeling effects of climate change on pollen indices such as annual birch pollen count, maximum daily birch pollen count, start date of birch pollen season and the date of maximum daily birch pollen count. Annual mean CO2 concentration, mean spring temperature and the corresponding pollen index of prior year were found to be statistically significant accounting for effects of climate change on four pollen indices. Results suggest that annual productions and peak values from 2020 to 2100 under different scenarios will be 1.3–8.0 and 1.1–7.3 times higher respectively than the mean values for 2000, and start and peak dates will occur around two to four weeks earlier. These results have been partly confirmed by the available historical data. As a demonstration, the emission profiles in future years were generated by incorporating the predicted pollen indices into an existing emission model.

Modeling climate change effects on winter ski tourism in Andorra

Mountain regions have been identified as especially vulnerable areas to climate change. Changes in snowfall, glacier retreat and shifts in biodiversity amount and distribution are some examples of the sensitivity of mountain ecosystems. Moreover, in many mountain economies, reliable snow cover plays a key role as an important resource for the winter tourism industry, the main income source and driving force of local development in such regions. This study presents a georeferenced agent-based model to analyze the climate change impacts on the ski industry in Andorra and the effect of snowmaking as future adaptation strategy. The present study is the first attempt to analyze the ski industry in the Pyrenees region and will contribute to a better understanding of the vulnerability of Andorran ski resorts and the suitability of snowmaking as potential adaptation strategy to climate change. This study projects a reduction on the ski season length and the drop of the number of skiers especially in the lowest elevation ski resort of this region. Moreover, this work indicates that snowmaking cannot completely solve the problem of ensuring snow cover at low elevation ski resorts and should be considered as a suitable short-term strategy, but not as a sustainable long-term adaptation strategy. The resulting model can be used as a planning support tool to help local stakeholders understand the vulnerability and potential impacts of climate change and in the decision-making process of designing and developing appropriate sustainable adaptation strategies to future climate variability.

Modeling climate change effects on runoff and soil erosion in southeastern Arizona rangelands and implications for mitigation with conservation practices

Climate change is expected to impact runoff and soil erosion on rangelands in the western United States. This study evaluated the potential impacts of precipitation changes on soil erosion and surface runoff in southeastern Arizona using seven General Circulation Model (GCM) models with three emission scenarios for the 2050s and 2090s. A spatial-temporal downscaling process was used to generate daily precipitation series from GCM outputs for runoff and erosion modeling with the Rangeland Hydrology and Erosion Model (RHEM). Results were compared to 1970 through 1999 conditions. Our results suggested no significant changes in annual precipitation across the region under the three emission scenarios, while projected mean annual runoff and soil loss increased significantly, ranging from 79% to 92% and from 127% to 157%, respectively, relative to 1970 to 1999. At the seasonal scale, though an increase of summer precipitation and a reduction of winter precipitation were projected, both runoff and soil loss increased significantly for both periods. The dramatic increases in runoff and soil loss were attributed to the increase in the frequency and intensity of extreme events in the study area. Predicted soil loss from shrub communities increased more than that predicted for other plant communities under the three emission scenarios. Future increases in runoff and soil erosion may accelerate the transitions of grassland to shrublands or to more eroded states due to the positive vegetation-erosion feedback. Rangeland management policies and practices should consider these changes and adapt to the increased risk of runoff and soil erosion.

Do Interactions of Land Use and Climate Affect Productivity of Waterbirds and Prairie-Pothole Wetlands?

Availability of aquatic invertebrates on migration and breeding areas influences recruitment of ducks and shorebirds. In wetlands of Prairie Pothole Region (PPR), aquatic invertebrate production primarily is driven by interannual fluctuations of water levels in response to wet-dry cycles in climate. However, this understanding comes from studying basins that are minimally impacted by agricultural landscape modifications. In the past 100–150 years, a large proportion of wetlands within the PPR have been altered; often water was drained from smaller to larger wetlands at lower elevations creating consolidated, interconnected basins. Here I present a case study and I hypothesize that large basins receiving inflow from consolidation drainage have reduced water-level fluctuations in response to climate cycles than those in undrained landscapes, resulting in relatively stable wetlands that have lower densities of invertebrate forage for ducks and shorebirds and also less foraging habitat, especially for shorebirds. Furthermore, stable water-levels and interconnected basins may favor introduced or invasive species (e.g., cattail [Typha spp.] or fish) because native communities “evolved” in a dynamic and isolated system. Accordingly, understanding interactions between water-level fluctuations and landscape modifications is a prerequisite step to modeling effects of climate change on wetland hydrology and productivity and concomitant recruitment of waterbirds.

Modelling climate change effects on the spatial distribution of mountain permafrost at three sites in northwest Canada

Spatial models of present-day mountain permafrost probability were perturbed to examine potential climate change impacts. Mean annual air temperature (MAAT) changes were simulated by adjusting elevation in the models, and cloud cover changes were examined by altering the partitioning of direct beam and diffuse radiation within the calculation for potential incoming solar radiation (PISR). The effects of changes in MAAT on equilibrium permafrost distribution proved to be more important than those due to cloud cover. Under a −2 K scenario (approximating Little Ice Age conditions), permafrost expanded into an additional 22–43% of the study areas as zonal boundaries descended by 155–290 m K − 1. Under warming scenarios, permafrost probabilities progressively declined and zonal boundaries rose in elevation. A MAAT change of +5 K, caused two of the areas to become essentially permafrost-free. The absolute values of these predictions were affected up to ±10% when lapse rates were altered by ±1.5 K km − 1 but patterns and trends were maintained. A higher proportion of diffuse radiation (greater cloud cover) produced increases in permafrost extent of only 2–4% while decreases in the diffuse radiation fraction had an equal but opposite effect. Notwithstanding the small change in overall extent, permafrost probabilities on steep south-facing slopes were significantly impacted by the altered partitioning. Combined temperature and PISR partitioning scenarios produced essentially additive results, but the impact of changes in the latter declined as MAAT increased. The modelling illustrated that mountain permafrost in the discontinuous zone is sensitive spatially to long-term climate change and identified those areas where changes may already be underway following recent atmospheric warming.

Modeling Climate Change Effects on Streams and Reservoirs with HSPF

This study deals with the effects of the expected climate change on the hydrology of watersheds and on water resources. HSPF (Hydrological Simulation Program—Fortran) has been used to model streamflow and reservoir volume as realizations of watershed response. Climate change scenarios have been prepared based on trends expected in western Turkey in the first half of the twenty-first century and a hypothetical watershed with different land uses has been simulated. Changes in streamflow due to landuse, soil type and climate change have been examined using flood frequency and low flow analysis. The simulations have revealed quantitatively the difference among the responses of watersheds with no vegetative cover and with forests or pasture to trends in temperature and precipitation. It has also been found that monthly variations are very important in predicting the future response of watersheds. Significant differences have been observed in streamflows and reservoir volumes on a monthly basis between scenarios, soil types and land uses. Though the effects of temperature and precipitation act to counterbalance their effects on a long-term scale, on a monthly basis they can act to reinforce their effects and create drought periods and floods.