scholarly journals Predicted Future Benefits for an Endemic Rodent in the Irano-Turanian Region

Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Suzanna Meeussen ◽  
Anouschka Hof
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Species Distribution Modelling ◽  
Geographic Range ◽  
Future Climate ◽  
Future Climate Change ◽  
Distribution Ranges ◽  
Bioclimatic Variables ◽  
Suitable Area ◽  
The Impact

Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.

Predictions of future grazing season length for European dairy, beef and sheep farms based on regression with bioclimatic variables

2015 ◽  
Vol 154 (5) ◽  
pp. 765-781 ◽  
Author(s):  
P. PHELAN ◽  
E. R. MORGAN ◽  
H. ROSE ◽  
J. GRANT ◽  
P. O'KIELY
Keyword(s):  
Climate Change ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Season Length ◽  
The West ◽  
Grazing Season ◽  
North East ◽  
Bioclimatic Variables ◽  
The Impact

SUMMARYGrazing season length (GSL) on grassland farms with ruminant production systems can influence farm economics, livestock disease transmission, environmental impact, milk and meat quality, and consumer choice. Bioclimatic variables are biologically meaningful climate variables that may enable predictions of the impact of future climate change on GSL on European farms. The present study investigated the spatial relationship between current GSL (months) measured by EUROSTAT on dairy, beef and sheep farms in 706, 774 and 878 regions, respectively, and bioclimatic variables. A stepwise multiple regression model revealed a highly significant association between observed GSL and bioclimatic variables across Europe. Mean GSL was positively associated with the mean temperature of the coldest quarter and isothermality, and negatively associated with precipitation in the wettest month. Extrapolating these relationships to future climate change scenarios, most European countries were predicted to have a net increase in GSL with the increase being largest (up to 2·5 months) in the north-east of Europe. However, there were also predictions of increased variability between regions and decreases in GSL of up to 1·5 months in some areas such as the west of France, the south-west of Norway and the west coast of Britain. The study quantified and mapped the potential impact of climate change on GSL for dairy, beef and sheep farms across Europe.

scholarly journals Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Arable Land ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Scenarios ◽  
The Impact

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.

Selection of models to describe the temperature-dependent development of Neoleucinodes elegantalis (Lepidoptera: Crambidae) and its application to predict the species voltinism under future climate conditions

2021 ◽  
pp. 1-9
Author(s):  
Hevellyn Talissa dos Santos ◽  
Cesar Augusto Marchioro
Keyword(s):  
Climate Change ◽  
Linear Model ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Dependent ◽  
Dependent Development ◽  
Degree Day ◽  
Non Linear ◽  
The Impact

Abstract The small tomato borer, Neoleucinodes elegantalis (Guenée, 1854) is a multivoltine pest of tomato and other cultivated solanaceous plants. The knowledge on how N. elegantalis respond to temperature may help in the development of pest management strategies, and in the understanding of the effects of climate change on its voltinism. In this context, this study aimed to select models to describe the temperature-dependent development rate of N. elegantalis and apply the best models to evaluate the impacts of climate change on pest voltinism. Voltinism was estimated with the best fit non-linear model and the degree-day approach using future climate change scenarios representing intermediary and high greenhouse gas emission rates. Two out of the six models assessed showed a good fit to the observed data and accurately estimated the thermal thresholds of N. elegantalis. The degree-day and the non-linear model estimated more generations in the warmer regions and fewer generations in the colder areas, but differences of up to 41% between models were recorded mainly in the warmer regions. In general, both models predicted an increase in the voltinism of N. elegantalis in most of the study area, and this increase was more pronounced in the scenarios with high emission of greenhouse gases. The mathematical model (74.8%) and the location (9.8%) were the factors that mostly contributed to the observed variation in pest voltinism. Our findings highlight the impact of climate change on the voltinism of N. elegantalis and indicate that an increase in its population growth is expected in most regions of the study area.

scholarly journals An Assessment of Recent and Future Temperature Change over the Sichuan Basin, China, Using CMIP5 Climate Models

2017 ◽  
Vol 30 (17) ◽  
pp. 6701-6722 ◽  
Author(s):  
Daniel Bannister ◽  
Michael Herzog ◽  
Hans-F. Graf ◽  
J. Scott Hosking ◽  
C. Alan Short
Keyword(s):  
Climate Change ◽  
Sichuan Basin ◽  
Climate Models ◽  
Distribution Functions ◽  
Future Climate ◽  
First Century ◽  
Future Climate Change ◽  
Change Scenario ◽  
The Sichuan Basin ◽  
Twenty First Century

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.

scholarly journals An evaluation of the effect of future climate on runoff in the Dongjiang River basin, South China

2015 ◽  
Vol 368 ◽  
pp. 257-262
Author(s):  
K. Lin ◽  
W. Zhai ◽  
S. Huang ◽  
Z. Liu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
South China ◽  
Annual Runoff ◽  
Future Climate ◽  
Weather Data ◽  
Future Climate Change ◽  
Dongjiang River ◽  
The Future ◽  
The Impact

Abstract. The impact of future climate change on the runoff for the Dongjiang River basin, South China, has been investigated with the Soil and Water Assessment Tool (SWAT). First, the SWAT model was applied in the three sub-basins of the Dongjiang River basin, and calibrated for the period of 1970–1975, and validated for the period of 1976–1985. Then the hydrological response under climate change and land use scenario in the next 40 years (2011–2050) was studied. The future weather data was generated by using the weather generators of SWAT, based on the trend of the observed data series (1966–2005). The results showed that under the future climate change and LUCC scenario, the annual runoff of the three sub-basins all decreased. Its impacts on annual runoff were –6.87%, –6.54%, and –18.16% for the Shuntian, Lantang, and Yuecheng sub-basins respectively, compared with the baseline period 1966–2005. The results of this study could be a reference for regional water resources management since Dongjiang River provides crucial water supplies to Guangdong Province and the District of Hong Kong in China.

scholarly journals Evaluating the impact of future climate change on irrigated maize production in Kansas

2017 ◽  
Vol 17 ◽  
pp. 139-154 ◽  
Author(s):  
A. Araya ◽  
I. Kisekka ◽  
X. Lin ◽  
P.V. Vara Prasad ◽  
P.H. Gowda ◽  
...  
Keyword(s):  
Climate Change ◽  
Future Climate ◽  
Future Climate Change ◽  
Maize Production ◽  
The Impact

scholarly journals Past temperature reconstructions from deep ice cores: relevance for future climate change

2006 ◽  
Vol 2 (2) ◽  
pp. 145-165 ◽  
Author(s):  
V. Masson-Delmotte ◽  
G. Dreyfus ◽  
P. Braconnot ◽  
S. Johnsen ◽  
J. Jouzel ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
Climate Models ◽  
Ice Core ◽  
Ice Cores ◽  
Future Climate ◽  
Future Climate Change ◽  
Interglacial Period ◽  
Temperature Reconstructions

Abstract. Ice cores provide unique archives of past climate and environmental changes based only on physical processes. Quantitative temperature reconstructions are essential for the comparison between ice core records and climate models. We give an overview of the methods that have been developed to reconstruct past local temperatures from deep ice cores and highlight several points that are relevant for future climate change. We first analyse the long term fluctuations of temperature as depicted in the long Antarctic record from EPICA Dome C. The long term imprint of obliquity changes in the EPICA Dome C record is highlighted and compared to simulations conducted with the ECBILT-CLIO intermediate complexity climate model. We discuss the comparison between the current interglacial period and the long interglacial corresponding to marine isotopic stage 11, ~400 kyr BP. Previous studies had focused on the role of precession and the thresholds required to induce glacial inceptions. We suggest that, due to the low eccentricity configuration of MIS 11 and the Holocene, the effect of precession on the incoming solar radiation is damped and that changes in obliquity must be taken into account. The EPICA Dome C alignment of terminations I and VI published in 2004 corresponds to a phasing of the obliquity signals. A conjunction of low obliquity and minimum northern hemisphere summer insolation is not found in the next tens of thousand years, supporting the idea of an unusually long interglacial ahead. As a second point relevant for future climate change, we discuss the magnitude and rate of change of past temperatures reconstructed from Greenland (NorthGRIP) and Antarctic (Dome C) ice cores. Past episodes of temperatures above the present-day values by up to 5°C are recorded at both locations during the penultimate interglacial period. The rate of polar warming simulated by coupled climate models forced by a CO2 increase of 1% per year is compared to ice-core-based temperature reconstructions. In Antarctica, the CO2-induced warming lies clearly beyond the natural rhythm of temperature fluctuations. In Greenland, the CO2-induced warming is as fast or faster than the most rapid temperature shifts of the last ice age. The magnitude of polar temperature change in response to a quadrupling of atmospheric CO2 is comparable to the magnitude of the polar temperature change from the Last Glacial Maximum to present-day. When forced by prescribed changes in ice sheet reconstructions and CO2 changes, climate models systematically underestimate the glacial-interglacial polar temperature change.

A multiproxy reconstruction of vegetation dynamics in the Eastern Alps (Switzerland): combining paleoecological and paleogenetic approaches.

2021 ◽  
Author(s):  
Laura Dziomber ◽  
Lisa Gurtner ◽  
Maria Leunda ◽  
Christoph Schwörer
Keyword(s):  
Climate Change ◽  
Ancient Dna ◽  
Vegetation Dynamics ◽  
Population Decline ◽  
Future Climate ◽  
Ice Age ◽  
Future Climate Change ◽  
The Holocene ◽  
Plant Remains ◽  
The Impact

<p>Current and future climate change is a serious threat to biodiversity and ecosystem stability. With a rapid increase of global temperatures by 1.5°C since the pre-industrial period and a projected warming of 1.5-4°C by the end of this century, plant species are forced to either adapt to these changes, shift their distribution range to higher elevation, or face population decline and extinction. Today, there is an urgent need to better understand the responses of mountain vegetation to climate change in order to predict the consequences of the human-driven global change currently occurring during the Anthropocene and maintain species diversity and ecosystem services. However, most predictions are based on short-term experiments. There is, in general, an insufficient use of longer time scales in conservation biology to understand long-term processes. Palaeoecological data are a great source of information to infer past species responses to changing environmental factors, such as climate or anthropogenic disturbances.</p><p>The last climate change of a similar magnitude and rate as projected for this century was the transition between the last Ice Age and the Holocene interglacial (ca. 11,700 years ago). By analyzing subfossil plant remains such as plant macrofossils, charcoal and pollen from natural archives, we can study past responses to climate change. However, until recently it was not possible to reconstruct changes at the population level. With the development of new methods to extract ancient DNA (aDNA) from plant remains and next generation DNA-sequencing techniques, we can now infer past population dynamics by analyzing the genetic variation through time. Ancient DNA might also be able to reveal if species could adapt to climatic changes by identifying intraspecific variation of specific genes related to climatic adaptations.</p><p>We are currently investigating a palaeoecological archive from a high-altitude mountain lake, Lai da Vons (1991 m a.s.l), situated in Eastern Switzerland. We are presenting preliminary macrofossil, pollen and charcoal results to reconstruct local to regional vegetation and fire dynamics with high chronological precision and resolution. In a next step, we will use novel molecular methods, in order to track adaptive and neutral genetic diversity through the Holocene by analyzing aDNA from subfossil conifer needles. The overarching goal of this large-scale, multiproxy study is to better understand past vegetation dynamics and the impact of future climate change on plants at multiple scales; from the genetic to the community level.</p><p> </p>

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