scholarly journals Climate change and the potential distribution of Xylella fastidiosa in Europe

2018 ◽  
Author(s):  
Martin Godefroid ◽  
Astrid Cruaud ◽  
Jean-Claude Streito ◽  
Jean-Yves Rasplus ◽  
Jean-Pierre Rossi
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Control Strategies ◽  
Integrated Management ◽  
Xylella Fastidiosa ◽  
Agricultural Practices ◽  
Coastal Areas ◽  
Future Climate ◽  
Distribution Models ◽  
Climate Conditions

AbstractThe bacterium Xylella fastidiosa (Xf) is a plant endophyte native to the Americas that causes worldwide concern. Xf has been recently detected in several regions outside its natural range including Europe. In that context, accurate estimates of its response to climate change are required to design cost-efficient and environment-friendly control strategies. In the present study, we collected data documenting the native and invaded ranges of the three main subspecies of Xf: fastidiosa, pauca and multiplex, as well as two strains of Xf subsp. multiplex recently detected in southern France (ST6 and ST7). We fitted bioclimatic species distribution models (SDMs) to forecast their potential geographic range and impact in Europe under current and future climate conditions. According to model predictions, the geographical range of Xf as presently reported in Europe is small compared to the large extent of suitable areas. The European regions most threatened by Xf encompass the Mediterranean coastal areas of Spain, Greece, Italy and France, the Atlantic coastal areas of France, Portugal and Spain as well as the south-western regions of Spain and lowlands in southern Italy. Potential distribution of the different subspecies / strains are contrasted but all are predicted to increase by 2050, which could threaten several of the most economically important wine-, olive- and fruit-producing regions of Europe, warranting the design of control strategies. Bioclimatic models also predict that the subspecies multiplex might represent a threat to most of Europe under current and future climate conditions. These results may serve as a basis for future design of a spatially informed European-scale integrated management strategy, including early detection surveys in plants and insect vectors, quarantine measures as well as agricultural practices.

scholarly journals Endemic Juniperus Montane Species Facing Extinction Risk under Climate Change in Southwest China: Integrative Approach for Conservation Assessment and Prioritization

Biology ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 63
Author(s):  
Mohammed A. Dakhil ◽  
Marwa Waseem A. Halmy ◽  
Walaa A. Hassan ◽  
Ali El-Keblawy ◽  
Kaiwen Pan ◽  
...  
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Extinction Risk ◽  
In Situ Conservation ◽  
Integrative Approach ◽  
Conservation Assessment ◽  
Distribution Models ◽  
Area Of Occupancy ◽  
Annual Range ◽  
The Impact

Climate change is an important driver of biodiversity loss and extinction of endemic montane species. In China, three endemic Juniperus spp. (Juniperuspingii var. pingii, J.tibetica, and J.komarovii) are threatened and subjected to the risk of extinction. This study aimed to predict the potential distribution of these three Juniperus species under climate change and dispersal scenarios, to identify critical drivers explaining their potential distributions, to assess the extinction risk by estimating the loss percentage in their area of occupancy (AOO), and to identify priority areas for their conservation in China. We used ensemble modeling to evaluate the impact of climate change and project AOO. Our results revealed that the projected AOOs followed a similar trend in the three Juniperus species, which predicted an entire loss of their suitable habitats under both climate and dispersal scenarios. Temperature annual range and isothermality were the most critical key variables explaining the potential distribution of these three Juniperus species; they contribute by 16–56.1% and 20.4–38.3%, respectively. Accounting for the use of different thresholds provides a balanced approach for species distribution models’ applications in conservation assessment when the goal is to assess potential climatic suitability in new geographical areas. Therefore, south Sichuan and north Yunnan could be considered important priority conservation areas for in situ conservation and search for unknown populations of these three Juniperus species.

scholarly journals Projections for Mexico’s Tropical Rainforests Considering Ecological Niche and Climate Change

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 119
Author(s):  
Antonio Fidel Santos-Hernández ◽  
Alejandro Ismael Monterroso-Rivas ◽  
Diódoro Granados-Sánchez ◽  
Antonio Villanueva-Morales ◽  
Malinali Santacruz-Carrillo
Keyword(s):  
Climate Change ◽  
Ecological Niche ◽  
Potential Distribution ◽  
Tropical Rainforest ◽  
Statistical Significance ◽  
Climate Change Scenarios ◽  
Climate Conditions ◽  
Tropical Regions ◽  
Temperature And Precipitation ◽  
Ecological Importance

The tropical rainforest is one of the lushest and most important plant communities in Mexico’s tropical regions, yet its potential distribution has not been studied in current and future climate conditions. The aim of this paper was to propose priority areas for conservation based on ecological niche and species distribution modeling of 22 species with the greatest ecological importance at the climax stage. Geographic records were correlated with bioclimatic temperature and precipitation variables using Maxent and Kuenm software for each species. The best Maxent models were chosen based on statistical significance, complexity and predictive power, and current potential distributions were obtained from these models. Future potential distributions were projected with two climate change scenarios: HADGEM2_ES and GFDL_CM3 models and RCP 8.5 W/m2 by 2075–2099. All potential distributions for each scenario were then assembled for further analysis. We found that 14 tropical rainforest species have the potential for distribution in 97.4% of the landscape currently occupied by climax vegetation (0.6% of the country). Both climate change scenarios showed a 3.5% reduction in their potential distribution and possible displacement to higher elevation regions. Areas are proposed for tropical rainforest conservation where suitable bioclimatic conditions are expected to prevail.

Bias correction of extreme values of high resolution climate simulations for risk analysis.

2021 ◽  
Author(s):  
luis Augusto sanabria ◽  
Xuerong Qin ◽  
Jin Li ◽  
Robert Peter Cechet
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Extreme Values ◽  
The Body ◽  
Future Climate ◽  
Return Periods ◽  
Climate Conditions ◽  
Mitigation And Adaptation ◽  
Climate Simulations ◽  
The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

scholarly journals Predicting Current Potential Distribution and the Range Dynamics of Pomacea canaliculata in China under Global Climate Change

Biology ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 110
Author(s):  
Yingxuan Yin ◽  
Qing He ◽  
Xiaowen Pan ◽  
Qiyong Liu ◽  
Yinjuan Wu ◽  
...  
Keyword(s):  
Climate Change ◽  
Native Species ◽  
Potential Distribution ◽  
Global Climate ◽  
Social Economy ◽  
Maximum Temperature ◽  
Pomacea Canaliculata ◽  
Climate Conditions ◽  
Jackknife Test ◽  
Recent Climate

Pomacea canaliculata is one of the 100 worst invasive alien species in the world, which has significant effects and harm to native species, ecological environment, human health, and social economy. Climate change is one of the major causes of species range shifts. With recent climate change, the distribution of P. canaliculata has shifted northward. Understanding the potential distribution under current and future climate conditions will aid in the management of the risk of its invasion and spread. Here, we used species distribution modeling (SDM) methods to predict the potential distribution of P. canaliculata in China, and the jackknife test was used to assess the importance of environmental variables for modeling. Our study found that precipitation of the warmest quarter and maximum temperature in the coldest months played important roles in the distribution of P. canaliculata. With global warming, there will be a trend of expansion and northward movement in the future. This study could provide recommendations for the management and prevention of snail invasion and expansion.

scholarly journals Evaluating catchment response to artificial rainfall from four weather generators for present and future climate

2018 ◽  
Vol 77 (11) ◽  
pp. 2578-2588 ◽  
Author(s):  
Hjalte Jomo Danielsen Sørup ◽  
Steffen Davidsen ◽  
Roland Löwe ◽  
Søren Liedtke Thorndahl ◽  
Morten Borup ◽  
...  
Keyword(s):  
Climate Change ◽  
Future Climate ◽  
Control Measures ◽  
Rainfall Time Series ◽  
Urban Water ◽  
Combined Sewer Overflows ◽  
Climate Conditions ◽  
Artificial Rainfall ◽  
Weather Generators ◽  
Catchment Responses

Abstract The technical lifetime of urban water infrastructure has a duration where climate change has to be considered when alterations to the system are planned. Also, models for urban water management are reaching a very high complexity level with, for example, decentralized stormwater control measures being included. These systems have to be evaluated under as close-to-real conditions as possible. Long term statistics (LTS) modelling with observational data is the most close-to-real solution for present climate conditions, but for future climate conditions artificial rainfall time series from weather generators (WGs) have to be used. In this study, we ran LTS simulations with four different WG products for both present and future conditions on two different catchments. For the present conditions, all WG products result in realistic catchment responses when it comes to the number of full flowing pipes and the number and volume of combined sewer overflows (CSOs). For future conditions, the differences in the WGs representation of the expectations to climate change is evident. Nonetheless, all future results indicate that the catchments will have to handle more events that utilize the full capacity of the drainage systems. Generally, WG products are relevant to use in planning of future changes to sewer systems.

scholarly journals Current and future suitable habitat areas for Nasuella olivacea (Gray, 1865) in Colombia and Ecuador and analysis of its distribution across different land uses

2020 ◽  
Vol 8 ◽  
Author(s):  
Pablo Medrano-Vizcaíno ◽  
Patricia Gutiérrez-Salazar
Keyword(s):  
Climate Change ◽  
Potential Distribution ◽  
Wildlife Conservation ◽  
Distribution Patterns ◽  
Climatic Conditions ◽  
Future Climate ◽  
Future Climate Change ◽  
Suitable Habitat ◽  
Climate Change Scenarios ◽  
Ecological Niche Models

Nasuella olivacea is an endemic mammal from the Andes of Ecuador and Colombia. Due to its rarity, aspects about its natural history, ecology and distribution patterns are not well known, therefore, research is needed to generate knowledge about this carnivore and a first step is studying suitable habitat areas. We performed Ecological Niche Models and applied future climate change scenarios (2.6 and 8.5 RCP) to determine the potential distribution of this mammal in Colombia and Ecuador, with current and future climate change conditions; furthermore, we analysed its distribution along several land covers. We found that N. olivacea is likely to be found in areas where no records have been reported previously; likewise, climate change conditions would increase suitable distribution areas. Concerning land cover, 73.4% of N. olivacea potential distribution was located outside Protected Areas (PA), 46.1% in Forests and 40.3% in Agricultural Lands. These findings highlight the need to further research understudied species, furthering our understanding about distribution trends and responses to changing climatic conditions, as well as informig future PA designing. These are essential tools for supporting wildlife conservation plans, being applicable for rare species whose biology and ecology remain unknown.

Trading space for time: Assessment of tree habitat shifts under climate change using bioclimatic envelopes

2021 ◽  
Author(s):  
Katharina Enigl ◽  
Matthias Schlögl ◽  
Christoph Matulla
Keyword(s):  
Climate Change ◽  
Tree Species ◽  
Ips Typographus ◽  
Future Climate ◽  
Forest Damage ◽  
Climate Conditions ◽  
North East ◽  
Bioclimatic Variables ◽  
The Future ◽  
Forest District

<p>Climate change constitutes a main driver of altering population dynamics of spruce bark beetles (<em>Ips typographus</em>) all over Europe. Their swarming activity as well as development rate are strongly dependent on temperature and the availability of brood trees. Especially over the last years, the latter has substantially increased due to major drought events which led to a widespread weakening of spruce stands. Since both higher temperatures and longer drought periods are to be expected in Central Europe in the decades ahead, foresters face the challenges of maintaining sustainable forest management and safeguarding future yields. One approach used to foster decision support in silviculture relies on the identification of possible alternative tree species suitable for adapting to expected future climate conditions in threatened regions. </p><p>In this study, we focus on the forest district of Horn, a region in Austria‘s north east that is beneficially influenced by the mesoclimate of the Pannonian basin. This fertile yet dry area has been severely affected by mass propagations of <em>Ips typographus</em> due to extensive droughts since 2017, and consequently has suffered from substantial forest damage in recent years. The urgent need for action was realized and has expedited the search for more robust alternative species to ensure sustainable silviculture in the area.</p><p>The determination of suitable tree species is based on the identification of regions whose climatic conditions in the recent past are similar to those that are to be expected in the forest district of Horn in the future. To characterize these conditions, we consider 19 bioclimatic variables that are derived from monthly temperature and rainfall values. Using downscaled CMIP6 projections with a spatial resolution of 2.5 minutes, we determine future conditions in Horn throughout the 21st century. By employing 20-year periods from 2021 to 2100 for the scenarios SSP1-26, SSP2-45, SSP3-70 and SSP5-85,  and comparing them to worldwide past climate conditions, we obtain corresponding bioclimatic regions for four future time slices until the end of the century. The Euclidian distance is applied as measure of similarity, effectively yielding similarity maps on a continuous scale. In order to account for the spatial variability within the forest district, this procedure is performed for the colder northwest and the warmer southeast of the area, individually seeking similar bioclimatic regions for each of these two subregions. Results point to Eastern Europe as well as the Po Valley in northern Italy as areas exhibiting the highest similarity to the future climate in this North-Eastern part of Austria.</p>

scholarly journals Simulated Biomass, Climate Change Impacts, and Nitrogen Management to Achieve Switchgrass Biofuel Production at Diverse Sites in U.S.

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 503 ◽  
Author(s):  
Sumin Kim ◽  
Sojung Kim ◽  
Jaepil Cho ◽  
Seonggyu Park ◽  
Fernando Xavier Jarrín Perez ◽  
...  
Keyword(s):  
Climate Change ◽  
Panicum Virgatum ◽  
Warm Season ◽  
Field Trials ◽  
N Fertilization ◽  
N Fertilizer ◽  
Future Climate ◽  
Biofuel Production ◽  
Climate Conditions ◽  
Functional Relationships

Switchgrass (Panicum virgatum L.) is a C4, warm season, perennial native grass that has been strongly recommended as an ideal biofuel feedstock. Accurate forecasting of switchgrass yield across a geographically diverse region and under future climate conditions is essential for determining realistic future ethanol production from switchgrass. This study compiled a switchgrass database through reviewing the existing literature from field trials across the U.S. Using observed switchgrass data, a process-based model (ALMANAC) was developed. The ALMANAC simulation results showed that crop management had more effect on yield than location. The ALMANAC model consists of functional relationships that provide a better understanding of interactions among plant physiological processes and environmental factors (water, soil, climate, and nutrients) giving realistic predictions in different climate conditions. This model was used to quantify the impacts of climate change on switchgrass yields. Simulated lowland switchgrass would have more yield increases between Illinois and Ohio in future (2021–2050) under both Representative Concentration Pathway (RCP) 4.5 and 8.5 pathways with low N fertilizer inputs than high N fertilizer inputs. There was no significant effect of climate variability on upland simulated yields, which means that N fertilization is a key factor in controlling upland switchgrass yields under future climate conditions.

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