Dynamic forest vegetation models for predicting impacts of climate change on forests: An Indian perspective

2018 ◽  
Vol 41 (1) ◽  
pp. 1-12
Author(s):  
Manoj Kumar ◽  
◽  
S.P.S. Rawat ◽  
Hukum Singh ◽  
N.H. Ravindranath ◽  
...  
Keyword(s):  
Climate Change ◽  
Environmental Variables ◽  
Net Primary Productivity ◽  
Climate Change Impacts ◽  
Forest Vegetation ◽  
Elevated Concentration ◽  
Impact Prediction ◽  
Vegetation Models ◽  
Ibis Model ◽  
The Impact

Understanding climate change vulnerability of Indian forests has received wider attention in recent years and a number of assessments with different approaches have emerged over time. These assessments have mostly used climate-sensitive vegetation models to explain the climate change impacts. In these studies, trees constituting a particular forest are often clubbed together into small number of groups having similar functional traits referred as Plant Functional Types (PFTs). Most of the Forest Vegetation Models (FVMs) are still in their developmental stage and there have been attempts at various levels to develop more versatile and precise models. Several developing countries, including India, still lag behind in developing dynamic vegetation models (DVMs), which could be appropriate for the local applications to predict the impact on forests at regional level. This is restrained mainly because of the lack of long-term observations with respect to various interacting biotic, abiotic and climatic (or environmental) variables in a forest ecosystem, like water and nitrogen use efficiency, response to elevated concentration of CO2, nutrient cycling, net primary productivity, etc. The observations on influence of the environmental variables on forest ecosystems are available in discrete form. Existing FVMs integrate observations more appropriately for their place of origin for which they have been developed. Different types of forests in different climatic zones are supposed to respond differently to climatic changes. Hence, it is imperative that models are developed for the specific biogeographic regions in order to predict the influences more accurately. It may not be wise to use existing FVMs in their pristine form for all of the region without considering the regional influences. Various challenges associated with the usage of the generic models of external origin with special reference to Integrated Biosphere Simulator (IBIS) model - being widely used and accepted in Indian policy documents- is presented in this paper. We also discuss on the need for developing a regional FVM for climate change impact studies, so that the impact prediction is more precise and reliable.

scholarly journals Epidemic malaria and warmer temperatures in recent decades in an East African highland

2010 ◽  
Vol 278 (1712) ◽  
pp. 1661-1669 ◽  
Author(s):  
David Alonso ◽  
Menno J. Bouma ◽  
Mercedes Pascual
Keyword(s):  
Climate Change ◽  
East Africa ◽  
Nonlinear Response ◽  
Climate Change Impacts ◽  
Human Model ◽  
Recent Past ◽  
East African ◽  
Highly Nonlinear ◽  
The Impact

Climate change impacts on malaria are typically assessed with scenarios for the long-term future. Here we focus instead on the recent past (1970–2003) to address whether warmer temperatures have already increased the incidence of malaria in a highland region of East Africa. Our analyses rely on a new coupled mosquito–human model of malaria, which we use to compare projected disease levels with and without the observed temperature trend. Predicted malaria cases exhibit a highly nonlinear response to warming, with a significant increase from the 1970s to the 1990s, although typical epidemic sizes are below those observed. These findings suggest that climate change has already played an important role in the exacerbation of malaria in this region. As the observed changes in malaria are even larger than those predicted by our model, other factors previously suggested to explain all of the increase in malaria may be enhancing the impact of climate change.

scholarly journals Producing hydrologic scenarios from raw climate model outputs using an asynchronous modelling framework

2021 ◽  
Author(s):  
Simon Ricard ◽  
Philippe Lucas-Picher ◽  
François Anctil
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Water Discharge ◽  
Climate Change Impacts ◽  
Climate Variables ◽  
Post Processing ◽  
Hydrologic Models ◽  
Simulated Climate ◽  
Meteorological Observations ◽  
The Impact

Abstract. Statistical post-processing of climate model outputs is a common hydroclimatic modelling practice aiming to produce climate scenarios that better fit in-situ observations and to produce reliable stream flows forcing calibrated hydrologic models. Such practice is however criticized for disrupting the physical consistency between simulated climate variables and affecting the trends in climate change signals imbedded within raw climate simulations. It also requires abundant good-quality meteorological observations, which are not available for many regions in the world. A simplified hydroclimatic modelling workflow is proposed to quantify the impact of climate change on water discharge without resorting to meteorological observations, nor for statistical post-processing of climate model outputs, nor for calibrating hydrologic models. By combining asynchronous hydroclimatic modelling, an alternative framework designed to construct hydrologic scenarios without resorting to meteorological observations, and quantile perturbation applied to streamflow observations, the proposed workflow produces sound and plausible hydrologic scenarios considering: (1) they preserve trends and physical consistency between simulated climate variables, (2) are implemented from a modelling cascades despite observation scarcity, and (3) support the participation of end-users in producing and interpreting climate change impacts on water resources. The proposed modelling workflow is implemented over four subcatchments of the Chaudière River, Canada, using 9 North American CORDEX simulations and a pool of lumped conceptual hydrologic models. Forced with raw climate model outputs, hydrologic models are calibrated over the reference period according to a calibration metric designed to function with temporally uncorrelated observed and simulated streamflow values. Perturbation factors are defined by relating each simulated streamflow quantiles over both reference and future periods. Hydrologic scenarios are finally produced by applying perturbation factors to available streamflow observations.

scholarly journals Is Current Research on How Climate Change Impacts Global Food Security Really Objective?

Foods ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2342
Author(s):  
Wangang Liu ◽  
Yiping Chen ◽  
Xinhua He ◽  
Ping Mao ◽  
Hanwen Tian
Keyword(s):  
Climate Change ◽  
Developing Countries ◽  
Food Security ◽  
Field Research ◽  
Climate Change Impacts ◽  
Developed Countries ◽  
Hotspot Analysis ◽  
Global Food Security ◽  
The Impact ◽  
Global Food

Global food insecurity is becoming more severe under the threat of rising global carbon dioxide concentrations, increasing population, and shrinking farmlands and their degeneration. We acquired the ISI Web of Science platform for over 31 years (1988–2018) to review the research on how climate change impacts global food security, and then performed cluster analysis and research hotspot analysis with VosViewer software. We found there were two drawbacks that exist in the current research. Firstly, current field research data were defective because they were collected from various facilities and were hard to integrate. The other drawback is the representativeness of field research site selection as most studies were carried out in developed countries and very few in developing countries. Therefore, more attention should be paid to developing countries, especially some African and Asian countries. At the same time, new modified mathematical models should be utilized to process and integrate the data from various facilities and regions. Finally, we suggested that governments and organizations across the world should be united to wrestle with the impact of climate change on food security.

scholarly journals Evaluation of a Global Vegetation Model using time series of satellite vegetation indices

2011 ◽  
Vol 4 (4) ◽  
pp. 1103-1114 ◽  
Author(s):  
F. Maignan ◽  
F.-M. Bréon ◽  
F. Chevallier ◽  
N. Viovy ◽  
P. Ciais ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Global Scale ◽  
Vegetation Dynamic ◽  
Rate Of Increase ◽  
Vegetation Models ◽  
Global Vegetation ◽  
The Impact

Abstract. Atmospheric CO2 drives most of the greenhouse effect increase. One major uncertainty on the future rate of increase of CO2 in the atmosphere is the impact of the anticipated climate change on the vegetation. Dynamic Global Vegetation Models (DGVM) are used to address this question. ORCHIDEE is such a DGVM that has proven useful for climate change studies. However, there is no objective and methodological way to accurately assess each new available version on the global scale. In this paper, we submit a methodological evaluation of ORCHIDEE by correlating satellite-derived Vegetation Index time series against those of the modeled Fraction of absorbed Photosynthetically Active Radiation (FPAR). A perfect correlation between the two is not expected, however an improvement of the model should lead to an increase of the overall performance. We detail two case studies in which model improvements are demonstrated, using our methodology. In the first one, a new phenology version in ORCHIDEE is shown to bring a significant impact on the simulated annual cycles, in particular for C3 Grasses and C3 Crops. In the second case study, we compare the simulations when using two different weather fields to drive ORCHIDEE. The ERA-Interim forcing leads to a better description of the FPAR interannual anomalies than the simulation forced by a mixed CRU-NCEP dataset. This work shows that long time series of satellite observations, despite their uncertainties, can identify weaknesses in global vegetation models, a necessary first step to improving them.

scholarly journals Spatial Phylogenetics, Biogeographical Patterns and Conservation Implications of the Endemic Flora of Crete (Aegean, Greece) under Climate Change Scenarios

Biology ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 199 ◽  
Author(s):  
Konstantinos Kougioumoutzis ◽  
Ioannis P. Kokkoris ◽  
Maria Panitsa ◽  
Panayiotis Trigas ◽  
Arne Strid ◽  
...  
Keyword(s):  
Climate Change ◽  
Industrial Revolution ◽  
Spatial Configuration ◽  
Climate Change Impacts ◽  
Biodiversity Loss ◽  
Biotic Homogenization ◽  
Climate Change Scenarios ◽  
Conservation Prioritization ◽  
Conservation Implications ◽  
The Impact

Human-induced biodiversity loss has been accelerating since the industrial revolution. The climate change impacts will severely alter the biodiversity and biogeographical patterns at all scales, leading to biotic homogenization. Due to underfunding, a climate smart, conservation-prioritization scheme is needed to optimize species protection. Spatial phylogenetics enable the identification of endemism centers and provide valuable insights regarding the eco-evolutionary and conservation value, as well as the biogeographical origin of a given area. Many studies exist regarding the conservation prioritization of mainland areas, yet none has assessed how climate change might alter the biodiversity and biogeographical patterns of an island biodiversity hotspot. Thus, we conducted a phylogenetically informed, conservation prioritization study dealing with the effects of climate change on Crete’s plant diversity and biogeographical patterns. Using several macroecological analyses, we identified the current and future endemism centers and assessed the impact of climate change on the biogeographical patterns in Crete. The highlands of Cretan mountains have served as both diversity cradles and museums, due to their stable climate and high topographical heterogeneity, providing important ecosystem services. Historical processes seem to have driven diversification and endemic species distribution in Crete. Due to the changing climate and the subsequent biotic homogenization, Crete’s unique bioregionalization, which strongly reminiscent the spatial configuration of the Pliocene/Pleistocene Cretan paleo-islands, will drastically change. The emergence of the ‘Anthropocene’ era calls for the prioritization of biodiversity-rich areas, serving as mixed-endemism centers, with high overlaps among protected areas and climatic refugia.

scholarly journals Severe Drought in Finland: Modeling Effects on Water Resources and Assessing Climate Change Impacts

2019 ◽  
Vol 11 (8) ◽  
pp. 2450 ◽  
Author(s):  
Noora Veijalainen ◽  
Lauri Ahopelto ◽  
Mika Marttunen ◽  
Jaakko Jääskeläinen ◽  
Ritva Britschgi ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Supply ◽  
Impact Analysis ◽  
Climate Change Impacts ◽  
Water Levels ◽  
Severe Drought ◽  
Climate Change Scenarios ◽  
Economic Sectors ◽  
The Impact

Severe droughts cause substantial damage to different socio-economic sectors, and even Finland, which has abundant water resources, is not immune to their impacts. To assess the implications of a severe drought in Finland, we carried out a national scale drought impact analysis. Firstly, we simulated water levels and discharges during the severe drought of 1939–1942 (the reference drought) in present-day Finland with a hydrological model. Secondly, we estimated how climate change would alter droughts. Thirdly, we assessed the impact of drought on key water use sectors, with a focus on hydropower and water supply. The results indicate that the long-lasting reference drought caused the discharges to decrease at most by 80% compared to the average annual minimum discharges. The water levels generally fell to the lowest levels in the largest lakes in Central and South-Eastern Finland. Climate change scenarios project on average a small decrease in the lowest water levels during droughts. Severe drought would have a significant impact on water-related sectors, reducing water supply and hydropower production. In this way drought is a risk multiplier for the water–energy–food security nexus. We suggest that the resilience to droughts could be improved with region-specific drought management plans and by including droughts in existing regional preparedness exercises.

scholarly journals Forest carbon allocation modelling under climate change

2019 ◽  
Vol 39 (12) ◽  
pp. 1937-1960 ◽  
Author(s):  
Katarína Merganičová ◽  
Ján Merganič ◽  
Aleksi Lehtonen ◽  
Giorgio Vacchiano ◽  
Maša Zorana Ostrogović Sever ◽  
...  
Keyword(s):  
Climate Change ◽  
Environmental Conditions ◽  
Carbon Allocation ◽  
Hybrid Approach ◽  
Ecosystem Dynamics ◽  
Nonstructural Carbohydrates ◽  
The Past ◽  
Process Understanding ◽  
Vegetation Models ◽  
The Impact

Abstract Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions.

scholarly journals Climate change impacts on nutrient loads in the Yorkshire Ouse catchment (UK)

2002 ◽  
Vol 6 (2) ◽  
pp. 197-209 ◽  
Author(s):  
F. Bouraoui ◽  
L. Galbiati ◽  
G. Bidoglio
Keyword(s):  
Climate Change ◽  
Assessment Tool ◽  
Swat Model ◽  
Climate Change Impacts ◽  
Climate Change Scenarios ◽  
Baseline Scenario ◽  
Nutrient Loads ◽  
Nitrogen And Phosphorus ◽  
Temperature And Precipitation ◽  
The Impact

Abstract. This study assessed the impact of potential climate change on the nutrient loads to surface and sub-surface waters from agricultural areas and was conducted using the Soil and Water Assessment Tool (SWAT) model. The study focused on a 3500 km2 catchment located in northern England, the Yorkshire Ouse. The SWAT model was calibrated and validated using sets of five years' measurements of nitrate and ortho-phosphorus concentrations and water flow. To increase the reliability of the hydrological model predictions, an uncertainty analysis was conducted by perturbing input parameters using a Monte-Carlo technique. The SWAT model was then run using a baseline scenario corresponding to an actual measured time series of daily temperature and precipitation, and six climate change scenarios. Because of the increase in temperature, all climate scenarios introduced an increase of actual evapotranspiration. Faster crop growth and an increased nutrient uptake resulted, as did an increase of annual losses of total nitrogen and phosphorus, however, with strong seasonal differences. Keywords: SWAT model, climate change, nutrient loads

scholarly journals An assessment of the impact of climate change on the financial performance of South African companies

2015 ◽  
Vol 4 (2) ◽  
pp. 49-62 ◽  
Author(s):  
Mandla Moyo ◽  
Hermina Christina Wingard
Keyword(s):  
Climate Change ◽  
Financial Performance ◽  
South African ◽  
Stock Exchange ◽  
Secondary Analysis ◽  
Climate Change Impacts ◽  
Financial Sustainability ◽  
Johannesburg Stock Exchange ◽  
Historic Data ◽  
The Impact

South African companies face uncertainty about whether they should commit resources to mitigate vulnerabilities and exploit opportunities arising from climate change. There is ambiguity over whether responding to climate change materially affects the financial sustainability of South African companies. The study sought to establish the extent to which responding to climate change impacts financial performance. Secondary analysis of historic data was used to compare the climate-change performance of 70 Johannesburg Stock Exchange listed companies to indicators of their financial performance. The research concluded that there is a positive and statistically significant correlation between climate-change performance and financial performance

scholarly journals The impact of global warming on seasonality of ocean primary production

2013 ◽  
Vol 10 (1) ◽  
pp. 1421-1450 ◽  
Author(s):  
S. Henson ◽  
H. Cole ◽  
C. Beaulieu ◽  
A. Yool
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Nitrate Concentration ◽  
Mixed Layer Depth ◽  
Climate Change Impacts ◽  
The Arctic ◽  
Layer Depth ◽  
Biogeochemical Models ◽  
Ocean Productivity ◽  
The Impact

Abstract. The seasonal cycle (i.e. phenology) of oceanic primary production (PP) is expected to change in response to climate warming. Here, we use output from 6 global biogeochemical models to examine the response in the seasonal amplitude of PP and timing of peak PP to the IPCC AR5 warming scenario. We also investigate whether trends in PP phenology may be more rapidly detectable than trends in PP itself. The seasonal amplitude of PP decreases by an average of 1–2% per year by 2100 in most biomes, with the exception of the Arctic which sees an increase of ~1% per year. This is accompanied by an advance in the timing of peak PP by ~0.5–1 months by 2100 over much of the globe, and particularly pronounced in the Arctic. These changes are driven by an increase in seasonal amplitude of sea surface temperature (where the maxima get hotter faster than the minima) and a decrease in the seasonal amplitude of the mixed layer depth and surface nitrate concentration. Our results indicate a transformation of currently strongly seasonal (bloom forming) regions, typically found at high latitudes, into weakly seasonal (non-bloom) regions, characteristic of contemporary subtropical conditions. On average, 36 yr of data are needed to detect a climate change-driven trend in the seasonal amplitude of PP, compared to 32 yr for mean annual PP. We conclude that analysis of phytoplankton phenology is not necessarily a shortcut to detecting climate change impacts on ocean productivity.

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