scholarly journals Predicting the Areas of Suitable Distribution for Zelkova serrata in China under Climate Change

2021 ◽  
Vol 13 (3) ◽  
pp. 1493
Author(s):  
Chunyan Cao ◽  
Jun Tao

Predicting the geographic distribution of a species together with its response to climate change is of great significance for biodiversity conservation and ecosystem sustainable development. Zelkova serrata is an excellent shelterbelt tree species that is used for soil and water conservation due to the fact of its well-developed root system, strong soil fixation, and wind resistance. However, the wild germplasm resources of Z. serrata have been increasingly depleted due to the fact of its weak ability to regenerate naturally and the unprecedented damage humans have caused to the natural habitats. The present work using Maxent aimed to model the current potential distribution of this species as well as in the future, assess how various environmental factors affect species distribution, and identify the shifts in the distribution of this species in various climate change scenarios. Our findings show habitat in provinces in the southern Qinling and Huai river basins have high environmental suitability. Temperature seasonality, annual precipitation, annual mean temperature, and warmest quarter precipitation were the most important factors affecting its distribution. Under a climate change scenario, the appropriate habitat range showed northeastward expansion geographically. The results in the present work can lay the foundation for the cultivation and conservation of Z. serrata.

2021 ◽  
Author(s):  
Christine Moos ◽  
Antoine Guisan ◽  
Christophe F. Randin ◽  
Heike Lischke

Abstract In steep terrain, forests play an important role as natural means of protection against natural hazards, such as rockfall. Due to climate warming, significant changes in the protection service of these forests have to be expected in future. Shifts of current to more drought adapted species may result in temporary or even irreversible losses in the risk reduction provided by these forests. In this study, we assessed how the protective effect against rockfall of a protection forest in the western part of the Valais in the Swiss Alps may change in future, by combining dynamic forest modelling with a quantitative risk analysis. Current and future forest development was modelled with the spatially explicit forest model TreeMig for a moderate (RCP4.5) and an extreme (RCP8.5) climate change scenario. The simulated forest scenarios were compared to ground-truth data from the current forest complex. We quantified the protective effect of the different forest scenarios based on the reduction of rockfall risk for people and infrastructure at the bottom of the slope. Rockfall risk was calculated on the basis of three-dimensional rockfall simulations. The forest simulations predicted a clear decrease in basal area of most of the currently present species in future. The forest turned into a Q. pubescens dominated forest, for both climate scenarios, and mixed with P. sylvestris in RCP4.5. F. sylvatica completely disappeared in RCP8.5. With climate warming, a clear increase in risk is expected for both climate change scenarios. In the long-term (> 100 years), a stabilization of risk, or even a slight decline may be expected due to an increase in biomass of the trees. The results of this study further indicate that regular forest interventions may promote regeneration and thus accelerate the shift in species distribution. Future research should address the long-term effect of different forest management strategies on the protection service of forests under climate change.


Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 525
Author(s):  
Keliang Zhang ◽  
Lanping Sun ◽  
Jun Tao

Analyzing the effects of climate change on forest ecosystems and individual species is of great significance for incorporating management responses to conservation policy development. Euscaphis japonica (Staphyleaceae), a small tree or deciduous shrub, is distributed among the open forests or mountainous valleys of Vietnam, Korea, Japan, and southern China. Meanwhile, it is also used as a medicinal and ornamental plant. Nonetheless, the extents of E. japonica forest have gradually shrunk as a result of deforestation, together with the regional influence of climate change. The present study employed two methods for modeling species distribution, Maxent and Genetic Algorithm for Rule-set Prediction (GARP), to model the potential distribution of this species and the effects of climate change on it. Our results suggest that both models performed favorably, but GARP outperformed Maxent for all performance metrics. The temperate and subtropical regions of eastern China where the species had been recorded was very suitable for E. japonica growth. Temperature and precipitation were two primary environmental factors affecting the distribution of E. japonica. Under climate change scenarios, the range of suitable habitats for E. japonica will expand geographically toward the north. Our findings may be used in several ways such as identifying currently undocumented locations of E. japonica, sites where it may occur in the future, or potential locations where the species could be introduced and so contribute to the conservation and management of this species.


Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1556 ◽  
Author(s):  
Daeeop Lee ◽  
Giha Lee ◽  
Seongwon Kim ◽  
Sungho Jung

In establishing adequate climate change policies regarding water resource development and management, the most essential step is performing a rainfall-runoff analysis. To this end, although several physical models have been developed and tested in many studies, they require a complex grid-based parameterization that uses climate, topography, land-use, and geology data to simulate spatiotemporal runoff. Furthermore, physical rainfall-runoff models also suffer from uncertainty originating from insufficient data quality and quantity, unreliable parameters, and imperfect model structures. As an alternative, this study proposes a rainfall-runoff analysis system for the Kratie station on the Mekong River mainstream using the long short-term memory (LSTM) model, a data-based black-box method. Future runoff variations were simulated by applying a climate change scenario. To assess the applicability of the LSTM model, its result was compared with a runoff analysis using the Soil and Water Assessment Tool (SWAT) model. The following steps (dataset periods in parentheses) were carried out within the SWAT approach: parameter correction (2000–2005), verification (2006–2007), and prediction (2008–2100), while the LSTM model went through the process of training (1980–2005), verification (2006–2007), and prediction (2008–2100). Globally available data were fed into the algorithms, with the exception of the observed discharge and temperature data, which could not be acquired. The bias-corrected Representative Concentration Pathways (RCPs) 4.5 and 8.5 climate change scenarios were used to predict future runoff. When the reproducibility at the Kratie station for the verification period of the two models (2006–2007) was evaluated, the SWAT model showed a Nash–Sutcliffe efficiency (NSE) value of 0.84, while the LSTM model showed a higher accuracy, NSE = 0.99. The trend analysis result of the runoff prediction for the Kratie station over the 2008–2100 period did not show a statistically significant trend for neither scenario nor model. However, both models found that the annual mean flow rate in the RCP 8.5 scenario showed greater variability than in the RCP 4.5 scenario. These findings confirm that the LSTM runoff prediction presents a higher reproducibility than that of the SWAT model in simulating runoff variation according to time-series changes. Therefore, the LSTM model, which derives relatively accurate results with a small amount of data, is an effective approach to large-scale hydrologic modeling when only runoff time-series are available.


Plants ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1015
Author(s):  
Xiaotao Huang ◽  
Li Ma ◽  
Chunbo Chen ◽  
Huakun Zhou ◽  
Buqing Yao ◽  
...  

Sinadoxa corydalifolia is a perennial grass with considerable academic value as a rare species owing to habitat destruction and a narrow distribution. However, its distribution remains unclear. In this study, we predicted the distribution of Sinadoxa corydalifolia in the three-river region (the source of the Yangtze River, Yellow River, and Lancang River) under the context of climate change using the maximum entropy (MaxEnt) model. Under the current climate scenario, the suitable distribution mainly occurred in Yushu County and Nangqian County. The suitable distribution area of Sinadoxa corydalifolia covered 3107 km2, accounting for 0.57% of the three-river region. The mean diurnal air temperature range (Bio2), temperature seasonality (Bio4), and mean air temperature of the driest quarter (Bio9) contributed the most to the distribution model for Sinadoxa corydalifolia, with a cumulative contribution of 81.4%. The highest suitability occurred when air temperature seasonality (Bio4) ranged from 6500 to 6900. The highest suitable mean air temperature of the driest quarter ranged from −5 to 0 °C. The highest suitable mean diurnal temperature (Bio2) ranged from 8.9 to 9.7 °C. In future (2041–2060) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: representative concentration pathway (RCP)26 (6171 km2) > RCP45 (6017 km2) > RCP80 (4238 km2) > RCP60 (2505 km2). In future (2061–2080) scenarios, the suitable distribution areas of Sinadoxa corydalifolia from high to low are as follows: RCP26 (18,299 km2) > RCP60 (11,977 km2) > RCP45 (10,354 km2) > RCP80 (7539 km2). In general, the suitable distribution will increase in the future. The distribution area of Sinadoxa corydalifolia will generally be larger under low CO2 concentrations than under high CO2 concentrations. This study will facilitate the development of appropriate conservation measures for Sinadoxa corydalifolia in the three-river region.


2011 ◽  
Vol 62 (9) ◽  
pp. 1043 ◽  
Author(s):  
Nick Bond ◽  
Jim Thomson ◽  
Paul Reich ◽  
Janet Stein

There are few quantitative predictions for the impacts of climate change on freshwater fish in Australia. We developed species distribution models (SDMs) linking historical fish distributions for 43 species from Victorian streams to a suite of hydro-climatic and catchment predictors, and applied these models to explore predicted range shifts under future climate-change scenarios. Here, we present summary results for the 43 species, together with a more detailed analysis for a subset of species with distinct distributions in relation to temperature and hydrology. Range shifts increased from the lower to upper climate-change scenarios, with most species predicted to undergo some degree of range shift. Changes in total occupancy ranged from –38% to +63% under the lower climate-change scenario to –47% to +182% under the upper climate-change scenario. We do, however, caution that range expansions are more putative than range contractions, because the effects of barriers, limited dispersal and potential life-history factors are likely to exclude some areas from being colonised. As well as potentially informing more mechanistic modelling approaches, quantitative predictions such as these should be seen as representing hypotheses to be tested and discussed, and should be valuable for informing long-term strategies to protect aquatic biota.


2016 ◽  
Vol 02 (03) ◽  
pp. 1650012
Author(s):  
Robert D. Schmidt ◽  
R. Garth Taylor

Aquifers created or sustained by seepage losses from Bureau of Reclamation (Reclamation) Projects extend over vast areas of western states. Yet agricultural water conservation measures such as canal lining top the list of State and Federal policies for mitigating the effect of water shortages brought about by climate change. Cost benefit analysis (CBA) of new Reclamation water conservation infrastructure such as canal lining or piping is too often Project-specific, and detached from basin hydrology. The value of canal seepage as a positive externality is thus ignored in CBA. A basin-wide approach to hydro-economic modeling that accounts for the externalized costs and benefits of both canal seepage and new canal lining conservation insures that incidental aquifer recharge is recognized in CBA of Federally financed irrigation water conservation measures. Integrated hydrologic and partial equilibrium models are employed in the Lower Boise River basin to calculate the foregone benefit to non-project groundwater and drain water irrigation of a hypothetical Boise Project canal lining response to projected climate change water shortages. Basin-wide hydrologic response data is used to compute shifts in non-project groundwater supply functions and drain water supply constraints, and a base-case water supply scenario is compared to six climate change scenarios in which projected water shortages are offset by lining of project canals. The foregone net benefit to non-project groundwater and drain water irrigation resulting from elimination of the canal seepage externality (US$[Formula: see text]4.4–22.6[Formula: see text]million depending on the scenario) outweighs the increase in net benefit to Boise Project irrigation by canal lining (US$[Formula: see text]1.4–19.3[Formula: see text]million). On average, foregone groundwater and drain water irrigation benefit exceeds restored canal irrigation benefit by about 38%. Canal lining conservation is unable to restore total basin-wide irrigation net benefit to the base-case level in any of the climate change scenarios; rather it shifts the foregone benefit of climate change shortages from project canal irrigation to non-project groundwater and drain water irrigation. The canal lining CPA is not a complete accounting of either costs or benefits of canal lining conservation. On the cost side, only the foregone benefits of eliminating the positive canal seepage externality are calculated; construction and maintenance costs of canal lining are omitted. On the benefit side, Arrowrock canal irrigators are assumed to be the sole beneficiary of reduced seepage losses.


2017 ◽  
Vol 19 (3) ◽  
pp. 163 ◽  
Author(s):  
Adjie Pamungkas ◽  
Sarah Bekessy ◽  
Ruth Lane

Reducing community vulnerability to flooding is increasingly important given predicted intensive flood events in many parts of the world. We built a community vulnerability model to explore the effectiveness of a range of proactive and reactive adaptations to reduce community vulnerability to flood. The model consists of floods, victims, housings, responses, savings, expenditure and income sub models. We explore the robustness of adaptations under current conditions and under a range of future climate change scenarios. We present results of this model for a case study of Centini Village in Lamongan Municipality, Indonesia, which is highly vulnerable to the impacts of annual small-scale and infrequent extreme floods.  We compare 11 proactive adaptations using indicators of victims, damage/losses and recovery process to reflect the level of vulnerability. We find that reforestation and flood infrastructure redevelopment are the most effective proactive adaptations for minimising vulnerability to flood under current condition. Under climate change scenario, the floods are predicted to increase 17% on the average and 5% on the maximum measurements. The increasing floods result reforestation is the only effective adaptations in the future under climate change scenario.


Author(s):  
John Saviour Yaw Eleblu ◽  
Eugene Tenkorang Darko ◽  
Eric Yirenkyi Danquah

AbstractClimate smart agriculture (CSA) embodies a blend of innovations, practices, systems, and investment programmes that are used to mitigate against the adverse effects of climate change and variability on agriculture for sustained food production. Food crop production under various climate change scenarios requires the use of improved technologies that are called climate smart agriculture to ensure increased productivity under adverse conditions of increased global temperatures, frequent and more intense storms, floods and drought stresses. This chapter summarizes available information on climate change and climate smart agriculture technologies. It is important to evaluate each climate change scenario and provide technologies that farmers, research scientists, and policy drivers can use to create the desired climate smart agriculture given the array of tools and resources available.


Author(s):  
Carina Almeida ◽  
Paulo Branco ◽  
Pedro Segurado ◽  
Tiago B. Ramos ◽  
Teresa Ferreira ◽  
...  

Abstract This study describes an integrated modelling approach to better understand the trophic status of the Montargil reservoir (southern Portugal) under climate change scenarios. The SWAT and CE-QUAL-W2 models were applied to the basin and reservoir, respectively, for simulating water and nutrient dynamics while considering one climatic scenario and two decadal timelines (2025–2034 and 2055–2064). Model simulations showed that the dissolved oxygen concentration in the reservoir's hypolimnion is expected to decrease by 60% in both decadal timelines, while the chlorophyll-a concentration in the reservoir's epiliminion is expected to increase by 25%. The total phosphorus concentration (TP) is predicted to increase in the water column surface by 63% and in the hypolimion by 90% during the 2030 timeline. These results are even more severe during the 2060 timeline. Under this climate change scenario, the reservoir showed an eutrophic state during 70–80% of both timelines. Even considering measures that involve decreases in 30 to 35% of water use, the eutrophic state is not expected to improve.


2009 ◽  
Vol 1 (1) ◽  
pp. 77-90 ◽  
Author(s):  
Marian Melo ◽  
Milan Lapin ◽  
Ingrid Damborska

Abstract In this paper methods of climate-change scenario projection in Slovakia for the 21st century are outlined. Temperature and precipitation time series of the Hurbanovo Observatory in 1871-2007 (Slovak Hydrometeorological Institute) and data from four global GCMs (GISS 1998, CGCM1, CGCM2, HadCM3) are utilized for the design of climate change scenarios. Selected results of different climate change scenarios (based on different methods) for the region of Slovakia (up to 2100) are presented. The increase in annual mean temperature is about 3°C, though the results are ambiguous in the case of precipitation. These scenarios are required by users in impact studies, mainly from the hydrology, agriculture and forestry sectors.


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