scholarly journals Climate change and the complex dynamics of green spruce aphid--spruce plantation interactions

2021 ◽  
Author(s):  
John H. M. Thornley ◽  
Jonathan A Newman
Keyword(s):  
Climate Change ◽  
Mathematical Model ◽  
Complex Dynamics ◽  
Environmental Variable ◽  
Picea Sitchensis ◽  
Climate Variables ◽  
Managed Forests ◽  
Aphid Infestation ◽  
Commercial Yield ◽  
Plantation Yield

Aphids can have a significant impact on the growth and commercial yield of spruce plantations. Here we develop a mechanistic deterministic mathematical model for the dynamics of the green spruce aphid (Elatobium abietum Walker) growing on Sitka spruce (Picea sitchensis (Bong.) Carr.). These grow in a northern British climate in managed plantations, with planting, thinning and a 60-year rotation. Aphid infestation rarely kills the tree but can reduce growth by up to 55%. We used the Edinburgh Forest Model (efm) to simulate spruce tree growth. The aphid sub-model is described in detail in an appendix. The only environmental variable which impacts immediately on aphid dynamics is air temperature which varies diurnally and seasonally. The efm variables that are directly significant for the aphid are leaf area and phloem nitrogen and carbon. Aphid population predictions include dying out, annual, biennual and other complex patterns, including chaos. Predicted impacts on plantation yield of managed forests can be large and variable, as has been observed; they are also much affected by temperature, CO 2 concentration and other climate variables. However increased  CO 2  concentration appears to ameliorate the severity of the effects of increasing temperatures coupled to worsening aphid infestations on plantation yield.

scholarly journals Spatiotemporal climate and vegetation greenness changes and their nexus for Dhidhessa River Basin, Ethiopia

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Gizachew Kabite Wedajo ◽  
Misgana K. Muleta ◽  
Berhan Gessesse ◽  
Sifan A. Koriche
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
River Basin ◽  
Climate Change Adaptation ◽  
Spatial Relationship ◽  
Local Scale ◽  
Climate Variables ◽  
Climatic Zones ◽  
Vegetation Greenness ◽  
Climate Change Adaptation Strategies

Abstract Background Understanding spatiotemporal climate and vegetation changes and their nexus is key for designing climate change adaptation strategies at a local scale. However, such a study is lacking in many basins of Ethiopia. The objectives of this study were (i) to analyze temperature, rainfall and vegetation greenness trends and (ii) determine the spatial relationship of climate variables and vegetation greenness, characterized using Normalized Difference in Vegetation Index (NDVI), for the Dhidhessa River Basin (DRB). Quality checked high spatial resolution satellite datasets were used for the study. Mann–Kendall test and Sen’s slope method were used for the trend analysis. The spatial relationship between climate change and NDVI was analyzed using geographically weighted regression (GWR) technique. Results According to the study, past and future climate trend analysis generally showed wetting and warming for the DRB where the degree of trends varies for the different time and spatial scales. A seasonal shift in rainfall was also observed for the basin. These findings informed that there will be a negative impact on rain-fed agriculture and water availability in the basin. Besides, NDVI trends analysis generally showed greening for most climatic zones for the annual and main rainy season timescales. However, no NDVI trends were observed in all timescales for cool sub-humid, tepid humid and warm humid climatic zones. The increasing NDVI trends could be attributed to agroforestry practices but do not necessarily indicate improved forest coverage for the basin. The change in NDVI was positively correlated to rainfall (r2 = 0.62) and negatively correlated to the minimum (r2 = 0.58) and maximum (r2 = 0.45) temperature. The study revealed a strong interaction between the climate variables and vegetation greenness for the basin that further influences the biophysical processes of the land surface like the hydrologic responses of a basin. Conclusion The study concluded that the trend in climate and vegetation greenness varies spatiotemporally for the DRB. Besides, the climate change and its strong relationship with vegetation greenness observed in this study will further affect the biophysical and environmental processes in the study area; mostly negatively on agricultural and water resource sectors. Thus, this study provides helpful information to device climate change adaptation strategies at a local scale.

scholarly journals Climate Change Patterns of Wild Blueberry Fields in Downeast, Maine over the Past 40 Years

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 594
Author(s):  
Rafa Tasnim ◽  
Francis Drummond ◽  
Yong-Jiang Zhang
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Potential Evapotranspiration ◽  
Growing Season ◽  
Spatial Average ◽  
Climate Variables ◽  
Threshold Values ◽  
The Past ◽  
Wild Blueberry ◽  
Crop Health

Maine, USA is the largest producer of wild blueberries (Vaccinium angustifolium Aiton), an important native North American fruit crop. Blueberry fields are mainly distributed in coastal glacial outwash plains which might not experience the same climate change patterns as the whole region. It is important to analyze the climate change patterns of wild blueberry fields and determine how they affect crop health so fields can be managed more efficiently under climate change. Trends in the maximum (Tmax), minimum (Tmin) and average (Tavg) temperatures, total precipitation (Ptotal), and potential evapotranspiration (PET) were evaluated for 26 wild blueberry fields in Downeast Maine during the growing season (May–September) over the past 40 years. The effects of these climate variables on the Maximum Enhanced Vegetation Index (EVImax) were evaluated using Remote Sensing products and Geographic Information System (GIS) tools. We found differences in the increase in growing season Tmax, Tmin, Tavg, and Ptotal between those fields and the overall spatial average for the region (state of Maine), as well as among the blueberry fields. The maximum, minimum, and average temperatures of the studied 26 wild blueberry fields in Downeast, Maine showed higher rates of increase than those of the entire region during the last 40 years. Fields closer to the coast showed higher rates of warming compared with the fields more distant from the coast. Consequently, PET has been also increasing in wild blueberry fields, with those at higher elevations showing lower increasing rates. Optimum climatic conditions (threshold values) during the growing season were explored based on observed significant quadratic relationships between the climate variables (Tmax and Ptotal), PET, and EVImax for those fields. An optimum Tmax and PET for EVImax at 22.4 °C and 145 mm/month suggest potential negative effects of further warming and increasing PET on crop health and productivity. These climate change patterns and associated physiological relationships, as well as threshold values, could provide important information for the planning and development of optimal management techniques for wild blueberry fields experiencing 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 Evaluation of Climate Change Impacts on Cotton Yield using Cropsyst and Regression Models

2018 ◽  
Vol 8 ◽  
pp. 1433-1451 ◽  
Author(s):  
Pantazis Georgiou ◽  
Panagiota Koukouli
Keyword(s):  
Climate Change ◽  
Regression Models ◽  
General Circulation ◽  
Management Practices ◽  
Potential Evapotranspiration ◽  
Circulation Model ◽  
Planting Date ◽  
Climate Variables ◽  
Cotton Yield ◽  
Cotton Production

The regional as well as the international crop production is expected to be influenced by climate change. This study describes an assessment of simulated potential cotton yield using CropSyst, a cropping systems simulation model, in Northern Greece. CropSyst was used under the General Circulation Model CGCM3.1/T63 of the climate change scenario SRES B1 for time periods of climate change 2020-2050 and 2070-2100 for two planting dates. Additionally, an appraisal of the relationship between climate variables, potential evapotranspiration and cotton yield was done based on regression models. Multiple linear regression models based on climate variables and potential evapotranspiration could be used as a simple tool for the prediction of crop yield changes in response to climate change in the future. The CropSyst simulation under SRES B1, resulted in an increase by 6% for the period 2020-2050 and a decrease by about 15% in cotton yield for 2070-2100. For the earlier planting date a higher increase and a slighter reduction was observed in cotton yield for 2020-2050 and 2070-2100, respectively. The results indicate that alteration of crop management practices, such as changing the planting date could be used as potential adaptation measures to address the impacts of climate change on cotton production.

RAT (Robustness Assessment Test): a straightforward evaluation of hydrological model robustness to a changing climate

2021 ◽  
Author(s):  
Vazken Andréassian ◽  
Léonard Santos ◽  
Torben Sonnenborg ◽  
Alban de Lavenne ◽  
Göran Lindström ◽  
...  
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Hydrological Models ◽  
Climate Variables ◽  
Data Set ◽  
Hydrological Characteristics ◽  
Changing Climate ◽  
Split Sample ◽  
Sample Test ◽  
Model Robustness

<p>Hydrological models are increasingly used under evolving climatic conditions. They should thus be evaluated regarding their temporal transferability (application in different time periods) and extrapolation capacity (application beyond the range of known past conditions). In theory, parameters of hydrological models are independent of climate. In practice, however, many published studies based on the Split-Sample Test (Klemeš, 1986), have shown that model performances decrease systematically when it is used out of its calibration period. The RAT test proposed here aims at evaluating model robustness to a changing climate by assessing potential undesirable dependencies of hydrological model performances to climate variables. The test compares, over a long data period, the annual value of several climate variables (temperature, precipitation and aridity index) and the bias of the model over each year. If a significant relation exists between the climatic variable and the bias, the model is not considered to be robust to climate change on the catchment. The test has been compared to the Generalized Split-Sample Test (Coron et al., 2012) and showed similar results.</p><p>Here, we report on a large scale application of the test for three hydrological models with different level of complexity (GR6J, HYPE, MIKE-SHE) on a data set of 352 catchments in Denmark, France and Sweden. The results show that the test behaves differently given the evaluated variable (be temperature, precipitation or aridity) and the hydrological characteristics of each catchment. They also show that, although of different level of complexity, the robustness of the three models is similar on the overall data set. However, they are not robust on the same catchments and, then, are not sensitive to the same hydrological characteristics. This example highlights the applicability of the RAT test regardless of the model set-up and calibration procedure and its ability to provide a first evaluation of the model robustness to climate change.</p><p> </p><p><strong>References</strong></p><p>Coron, L., V. Andréassian, C. Perrin, J. Lerat, J. Vaze, M. Bourqui, and F. Hendrickx, 2012. Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments, Water Resour. Res., 48, W05552, doi:10.1029/2011WR011721</p><p>Klemeš, V., 1986. Operational testing of hydrological simulation models, Hydrol. Sci. J., 31, 13–24, doi:10.1080/02626668609491024</p><p> </p>

The emergence of Dirofilaria repens in a non-endemic area influenced by climate change: dynamics of transmission using a mathematical model.

Acta Tropica ◽  
2021 ◽  
pp. 106230
Author(s):  
Juan Pablo Gutiérrez-Jara ◽  
Marcela Salazar-Viedma ◽  
Christian R. Gonzélez ◽  
Beatriz Cancino-Faure
Keyword(s):  
Climate Change ◽  
Mathematical Model ◽  
Endemic Area ◽  
Dirofilaria Repens ◽  
Change Dynamics

Vulnerability of megapodes (Megapodiidae, Aves) to climate change and related threats

2018 ◽  
Vol 45 (4) ◽  
pp. 396-406 ◽  
Author(s):  
PAUL M. RADLEY ◽  
ROBERT A. DAVIS ◽  
RENÉ W.R.J. DEKKER ◽  
SHAUN W. MOLLOY ◽  
DAVID BLAKE ◽  
...  
Keyword(s):  
Climate Change ◽  
Gene Flow ◽  
Life Histories ◽  
Population Level ◽  
Genetic Connectivity ◽  
Future Research ◽  
Mean Annual Temperature ◽  
Climate Variables ◽  
Microbial Decomposition ◽  
Anthropogenic Habitat

SUMMARYAspects of species life histories may increase their susceptibility to climate change. Owing to their exclusive reliance on environmental sources of heat for incubation, megapodes may be especially vulnerable. We employed a trait-based vulnerability assessment to weigh their exposure to projected climate variables of increasing temperatures, fluctuating rainfall and sea level rise and their biological sensitivity and capacity to adapt. While all 21 species were predicted to experience at least a 2 °C increase in mean annual temperature, 12 to experience a moderate or greater fluctuation in rainfall and 16 to experience rising seas, the most vulnerable megapodes are intrinsically rare and range restricted. Species that employ microbial decomposition for incubation may have an adaptive advantage over those that do not and may be more resilient to climate change. The moderate microclimate necessary for mound incubation, however, may in some areas be threatened by anthropogenic habitat loss exacerbated by warmer and seasonally drier conditions. As with many avian species, little is known about the capacity of megapodes to adapt to a changing climate. We therefore recommend that future research efforts investigate megapode fecundity, gene flow and genetic connectivity at the population level to better determine their adaptive capacity.

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