scholarly journals Predicting Present and Future Suitable Climate Spaces (Potential Distributions) for an Armillaria Root Disease Pathogen (Armillaria solidipes) and Its Host, Douglas-fir (Pseudotsuga menziesii), Under Changing Climates

2021 ◽  
Vol 4 ◽  
Author(s):  
Mee-Sook Kim ◽  
John W. Hanna ◽  
Jane E. Stewart ◽  
Marcus V. Warwell ◽  
Geral I. McDonald ◽  
...  

Climate change and associated disturbances are expected to exacerbate forest root diseases because of altered distributions of existing and emerging forest pathogens and predisposition of trees due to climatic maladaptation and other disturbances. Predictions of suitable climate space (potential geographic distribution) for forest pathogens and host trees under contemporary and future climate scenarios will guide the selection of appropriate management practices by forest managers to minimize adverse impacts of forest disease within forest ecosystems. A native pathogen (Armillaria solidipes) that causes Armillaria root disease of conifers in North America is used to demonstrate bioclimatic models (maps) that predict suitable climate space for both pathogen and a primary host (Pseudotsuga menziesii, Douglas-fir) under contemporary and future climate scenarios. Armillaria root disease caused by A. solidipes is a primary cause of lost productivity and reduced carbon sequestration in coniferous forests of North America, and its impact is expected to increase under climate change due to tree maladaptation. Contemporary prediction models of suitable climate space were produced using Maximum Entropy algorithms that integrate climatic data with 382 georeferenced occurrence locations for DNA sequence-confirmed A. solidipes. A similar approach was used for visually identified P. menziesii from 11,826 georeferenced locations to predict its climatic requirements. From the contemporary models, data were extrapolated through future climate scenarios to forecast changes in geographic areas where native A. solidipes and P. menziesii will be climatically adapted. Armillaria root disease is expected to increase in geographic areas where predictions suggest A. solidipes is well adapted and P. menziesii is maladapted within its current range. By predicting areas at risk for Armillaria root disease, forest managers can deploy suitable strategies to reduce damage from the disease.

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.


2016 ◽  
Vol 283 (1831) ◽  
pp. 20160442 ◽  
Author(s):  
Emma F. Camp ◽  
David J. Smith ◽  
Chris Evenhuis ◽  
Ian Enochs ◽  
Derek Manzello ◽  
...  

Corals are acclimatized to populate dynamic habitats that neighbour coral reefs. Habitats such as seagrass beds exhibit broad diel changes in temperature and pH that routinely expose corals to conditions predicted for reefs over the next 50–100 years. However, whether such acclimatization effectively enhances physiological tolerance to, and hence provides refuge against, future climate scenarios remains unknown. Also, whether corals living in low-variance habitats can tolerate present-day high-variance conditions remains untested. We experimentally examined how pH and temperature predicted for the year 2100 affects the growth and physiology of two dominant Caribbean corals ( Acropora palmata and Porites astreoides ) native to habitats with intrinsically low (outer-reef terrace, LV) and/or high (neighbouring seagrass, HV) environmental variance. Under present-day temperature and pH, growth and metabolic rates (calcification, respiration and photosynthesis) were unchanged for HV versus LV populations. Superimposing future climate scenarios onto the HV and LV conditions did not result in any enhanced tolerance to colonies native to HV. Calcification rates were always lower for elevated temperature and/or reduced pH. Together, these results suggest that seagrass habitats may not serve as refugia against climate change if the magnitude of future temperature and pH changes is equivalent to neighbouring reef habitats.


Climate ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 165
Author(s):  
Prem B. Parajuli ◽  
Avay Risal

This study evaluated changes in climatic variable impacts on hydrology and water quality in Big Sunflower River Watershed (BSRW), Mississippi. Site-specific future time-series precipitation, temperature, and solar radiation data were generated using a stochastic weather generator LARS-WG model. For the generation of climate scenarios, Representative Concentration Pathways (RCPs), 4.5 and 8.5 of Global Circulation Models (GCMs): Hadley Center Global Environmental Model (HadGEM) and EC-EARTH, for three (2021–2040, 2041–2060 and 2061–2080) future climate periods. Analysis of future climate data based on six ground weather stations located within BSRW showed that the minimum temperature ranged from 11.9 °C to 15.9 °C and the maximum temperature ranged from 23.2 °C to 28.3 °C. Similarly, the average daily rainfall ranged from 3.6 mm to 4.3 mm. Analysis of changes in monthly average maximum/minimum temperature showed that January had the maximum increment and July/August had a minimum increment in monthly average temperature. Similarly, maximum increase in monthly average rainfall was observed during May and maximum decrease was observed during September. The average monthly streamflow, sediment, TN, and TP loads under different climate scenarios varied significantly. The change in average TN and TP loads due to climate change were observed to be very high compared to the change in streamflow and sediment load. The monthly average nutrient load under two different RCP scenarios varied greatly from as low as 63% to as high as 184%, compared to the current monthly nutrient load. The change in hydrology and water quality was mainly attributed to changes in surface temperature, precipitation, and stream flow. This study can be useful in the development and implementation of climate change smart management of agricultural watersheds.


2021 ◽  
Vol 43 ◽  
pp. e56026
Author(s):  
Gabriela Leite Neves ◽  
Jorim Sousa das Virgens Filho ◽  
Maysa de Lima Leite ◽  
Frederico Fabio Mauad

Water is an essential natural resource that is being impacted by climate change. Thus, knowledge of future water availability conditions around the globe becomes necessary. Based on that, this study aimed to simulate future climate scenarios and evaluate the impact on water balance in southern Brazil. Daily data of rainfall and air temperature (maximum and minimum) were used. The meteorological data were collected in 28 locations over 30 years (1980-2009). For the data simulation, we used the climate data stochastic generator PGECLIMA_R. It was considered two scenarios of the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and a scenario with the historical data trend. The water balance estimates were performed for the current data and the simulated data, through the methodology of Thornthwaite and Mather (1955). The moisture indexes were spatialized by the kriging method. These indexes were chosen as the parameters to represent the water conditions in different situations. The region assessed presented a high variability in water availability among locations; however, it did not present high water deficiency values, even with climate change. Overall, it was observed a reduction of moisture index in most sites and in all scenarios assessed, especially in the northern region when compared to the other regions. The second scenario of the IPCC (the worst situation) promoting higher reductions and dry conditions for the 2099 year. The impacts of climate change on water availability, identified in this study, can affect the general society, therefore, they must be considered in the planning and management of water resources, especially in the regional context


2019 ◽  
Vol 111 ◽  
pp. 06006 ◽  
Author(s):  
Matteo Bilardo ◽  
Maria Ferrara ◽  
Enrico Fabrizio

In Europe, the second recast of EPBD promotes long-term strategies to accelerate the path to nZEBs, fostering the cost-optimized building design already suggested in the EPBD first recast. Since the nZEB design is a complex optimization problem that is subjected to uncertainty in its boundary conditions (climate, technologies, market, ...), it is necessary to guarantee the resilience of the NZEB optimal design to possible variations of future scenarios, especially as regards the climate change. This work applies the new EdeSSOpt methodology (Energy Demand and Supply Simultaneous Optimization) developed by the Authors aiming at investigating the variation of the cost-optimized multi-family building design in different Italian future climate scenarios, therefore considering parameters related to the building envelope, energy systems and renewable energy sources. The method is implemented into the TRNSYS® (energy model), GenOpt (optimizer) and WeatherShift® (future climate scenario generator) tools. The resulting cost-optimal solutions in future scenarios are related to a lower global cost and a decreased total primary energy consumption. Beyond the future trends of such performance indexes, the fact that most of technical solutions associated with the optimal solutions have not changed with the studied climate scenarios, indicates a certain resilience of the optimal design variables facing climate change.


Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 286
Author(s):  
Bangshuai Han ◽  
Shawn G. Benner ◽  
Alejandro N. Flores

:In intensively managed watersheds, water scarcity is a product of interactions between complex biophysical processes and human activities. Understanding how intensively managed watersheds respond to climate change requires modeling these coupled processes. One challenge in assessing the response of these watersheds to climate change lies in adequately capturing the trends and variability of future climates. Here we combine a stochastic weather generator together with future projections of climate change to efficiently create a large ensemble of daily weather for three climate scenarios, reflecting recent past and two future climate scenarios. With a previously developed model that captures rainfall-runoff processes and the redistribution of water according to declared water rights, we use these large ensembles to evaluate how future climate change may impact satisfied and unsatisfied irrigation throughout the study area, the Treasure Valley in Southwest Idaho, USA. The numerical experiments quantify the changing rate of allocated and unsatisfied irrigation amount and reveal that the projected temperature increase more significantly influences allocated and unsatisfied irrigation amounts than precipitation changes. The scenarios identify spatially distinct regions in the study area that are at greater risk of the occurrence of unsatisfied irrigation. This study demonstrates how combining stochastic weather generators and future climate projections can support efforts to assess future risks of negative water resource outcomes. It also allows identification of regions in the study area that may be less suitable for irrigated agriculture in future decades, potentially benefiting planners and managers.


Diversity ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 54 ◽  
Author(s):  
Christopher Ellis

This paper provides an overview of bioclimatic models applied to lichen species, supporting their potential use in this context as indicators of climate change risk. First, it provides a brief summary of climate change risk, pointing to the relevance of lichens as a topic area. Second, it reviews the past use of lichen bioclimatic models, applied for a range of purposes with respect to baseline climate, and the application of data sources, statistical methods, model extents and resolution and choice of predictor variables. Third, it explores additional challenges to the use of lichen bioclimatic models, including: 1. The assumption of climatically controlled lichen distributions, 2. The projection to climate change scenarios, and 3. The issue of nonanalogue climates and model transferability. Fourth, the paper provides a reminder that bioclimatic models estimate change in the extent or range of a species suitable climate space, and that an outcome will be determined by vulnerability responses, including potential for migration, adaptation, and acclimation, within the context of landscape habitat quality. The degree of exposure to climate change, estimated using bioclimatic models, can help to inform an understanding of whether vulnerability responses are sufficient for species resilience. Fifth, the paper draws conclusions based on its overview, highlighting the relevance of bioclimatic models to conservation, support received from observational data, and pointing the way towards mechanistic approaches that align with field-scale climate change experiments.


2015 ◽  
Vol 61 (4) ◽  
pp. 669-689 ◽  
Author(s):  
Pamela D. Noyes ◽  
Sean C. Lema

Abstract Global climate change is impacting organisms, biological communities and ecosystems around the world. While most research has focused on characterizing how the climate is changing, including modeling future climatic conditions and predicting the impacts of these conditions on biodiversity, it is also the case that climate change is altering the environmental impacts of chemical pollution. Future climate conditions are expected to influence both the worldwide distribution of chemicals and the toxicological consequences of chemical exposures to organisms. Many of the environmental changes associated with a warming global climate (e.g., increased average – and possibly extreme – temperatures; intense periods of drier and wetter conditions; reduced ocean pH; altered salinity dynamics in estuaries) have the potential to enhance organism susceptibility to chemical toxicity. Additionally, chemical exposures themselves may impair the ability of organisms to cope with the changing environmental conditions of the shifting climate. Such reciprocity in the interactions between climate change and chemicals illustrates the complexity inherent in predicting the toxicological consequences of chemical exposures under future climate scenarios. Here, we summarize what is currently known about the potential reciprocal effects of climate change and chemical toxicity on wildlife, and depict current approaches and ongoing challenges for incorporating climate effects into chemical testing and assessment. Given the rapid pace of new man-made chemistries, the development of accurate and rapid methods to evaluate multiple chemical and non-chemical stressors in an ecologically relevant context will be critical to understanding toxic and endocrine-disrupting effects of chemical pollutants under future climate scenarios.


2014 ◽  
Vol 94 (2) ◽  
pp. 213-222 ◽  
Author(s):  
Qi Jing ◽  
Gilles Bélanger ◽  
Budong Qian ◽  
Vern Baron

Jing, Q., Bélanger, G., Qian, B. and Baron, V. 2014. Timothy yield and nutritive value with a three-harvest system under the projected future climate in Canada. Can. J. Plant Sci. 94: 213–222. Timothy (Phleum pratense L.) is harvested twice annually in Canada but with projected climate change, an additional harvest may be possible. Our objective was to evaluate the impact on timothy dry matter (DM) yield and key nutritive value attributes of shifting from a two- to a three-harvest system under projected future climate conditions at 10 sites across Canada. Future climate scenarios were generated with a stochastic weather generator (AAFC-WG) using two global climate models under the forcing of two Intergovernmental Panel on Climate Change emission scenarios and, then, used by the CATIMO (Canadian Timothy Model) grass model to simulate DM yield and key nutritive value attributes. Under future climate scenarios (2040–2069), the additional harvest and the resulting three-harvest system are expected to increase annual DM yield (+0.46 to +2.47 Mg DM ha−1) compared with a two-harvest system across Canada but the yield increment will on average be greater in eastern Canada (1.88 Mg DM ha−1) and Agassiz (2.02 Mg DM ha−1) than in the prairie provinces of Canada (0.84 Mg DM ha−1). The DM yield of the first harvest in a three-harvest system is expected to be less than in the two-harvest system, while that of the second harvest would be greater. Decreases in average neutral detergent fibre (NDF) concentration (−19 g kg−1 DM) and digestibility (dNDF, −5 g kg−1 NDF) are also expected with the three-harvest system under future conditions. Our results indicate that timothy will take advantage of projected climate change, through taking a third harvest, thereby increasing annual DM production.


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