scholarly journals Weather variation affects the dispersal of grasshoppers beyond their elevational ranges

2020 ◽  
Vol 10 (24) ◽  
pp. 14411-14422
Author(s):  
Andrew J. Prinster ◽  
Julian Resasco ◽  
Cesar R. Nufio
Keyword(s):  
Weather Variation

scholarly journals Characteristics of Climate Change and Extreme Weather from 1951 to 2011 in China

2018 ◽  
Vol 15 (11) ◽  
pp. 2540 ◽  
Author(s):  
Chunli Zhao ◽  
Jianguo Chen ◽  
Peng Du ◽  
Hongyong Yuan
Keyword(s):  
Climate Change ◽  
Spatial Scale ◽  
Spatial Scales ◽  
Seasonal Fluctuation ◽  
Extreme Weather ◽  
Temperature And Precipitation ◽  
Weather Variation ◽  
Variation Characteristics ◽  
Established Fact ◽  
Temporal And Spatial

It has been demonstrated that climate change is an established fact. A good comprehension of climate and extreme weather variation characteristics on a temporal and a spatial scale is important for adaptation and response. In this work, the characteristics of temperature, precipitation, and extreme weather distribution and variation is summarized for a period of 60 years and the seasonal fluctuation of temperature and precipitation is also analyzed. The results illustrate the reduction in daily and annual temperature divergence on both temporal and spatial scales. However, the gaps remain relatively significant. Furthermore, the disparity in daily and annual precipitation are found to be increasing on both temporal and spatial scales. The findings indicate that climate change, to a certain extent, narrowed the temperature gap while widening the precipitation gap on temporal and spatial scales in China.

Evaluating the effect of climate variation on the cost efficiency of a crop permit policy in Southern Sweden

2013 ◽  
Vol 4 (2) ◽  
pp. 110-117
Author(s):  
Dennis Collentine ◽  
Holger Johnsson
Keyword(s):  
Cost Efficiency ◽  
Agricultural Sector ◽  
Policy Design ◽  
Correlation Coefficients ◽  
Nitrogen Loads ◽  
Weather Variation ◽  
The Baltic ◽  
The Individual ◽  
The Cost ◽  
The Impact

Current international agreements call for a significant reduction of nitrogen loads to the Baltic Sea. New measures to reduce nitrogen loads from the agricultural sector and an increased focus on cost efficiency will be needed to meet reduction targets. For policy design and evaluation it is important to understand the impact of weather on the efficiency of abatement measures. One new proposed policy is the use of crop permits based on weather normalized average leaching. This paper describes the use of the Spearman method to determine the efficiency of this policy with annual weather variation. The conclusion is that the values of the Spearman correlation coefficients in the study indicate that using average leaching for the individual crops on specific soil types for calculating crop permit requirements is an efficient policy. The Spearman method is demonstrated to be a simple useful tool for evaluating the impact of weather and is recommended for use in new studies.

Weather variation and temporary labor migration: a panel data analysis for select semi-arid villages in India

2019 ◽  
Vol 9 (2) ◽  
pp. 291-322
Author(s):  
Kalandi Charan Pradhan ◽  
K. Narayanan
Keyword(s):  
Data Analysis ◽  
Panel Data ◽  
Labor Migration ◽  
Panel Data Analysis ◽  
Weather Variation ◽  
Temporary Labor ◽  
Semi Arid

scholarly journals Satellite-Based Observations Reveal Effects of Weather Variation on Rice Phenology

2020 ◽  
Vol 12 (9) ◽  
pp. 1522
Author(s):  
Hongfei Wang ◽  
Aniruddha Ghosh ◽  
Bruce A. Linquist ◽  
Robert J. Hijmans
Keyword(s):  
Survey Data ◽  
Ecosystem Function ◽  
Satellite Data ◽  
Growing Season ◽  
Phenological Stages ◽  
Mean Temperature ◽  
Weather Variation ◽  
Harvest Dates ◽  
Phenology Model ◽  
Rice Phenology

Obtaining detailed data on the spatio-temporal variation in crop phenology is critical to increasing our understanding of agro-ecosystem function, such as their response to weather variation and climate change. It is challenging to collect such data over large areas through field observations. The use of satellite remote sensing data has made phenology data collection easier, although the quality and the utility of such data to understand agro-ecosystem function have not been widely studied. Here, we evaluated satellite data-based estimates of rice phenological stages in California, USA by comparing them with survey data and with predictions by a temperature-driven phenology model. We then used the satellite data-based estimates to quantify the crop phenological response to changes in weather. We used time-series of MODIS satellite data and PhenoRice, a rule-based rice phenology detection algorithm, to determine annual planting, heading and harvest dates of paddy rice in California between 2002 and 2017. At the state level, our satellite-based estimates of rice phenology were very similar to the official survey data, particularly for planting and harvest dates (RMSE = 3.8–4.0 days). Satellite based observations were also similar to predictions by the DD10 temperature-driven phenology model. We analyzed how the timing of these phenological stages varied with concurrent temperature and precipitation over this 16-year time period. We found that planting was earlier in warm springs (−1.4 days °C−1 for mean temperature between mid-April and mid-May) and later in wet years (5.3 days 100 mm-1 for total precipitation from March to April). Higher mean temperature during the pre-heading period of the growing season advanced heading by 2.9 days °C−1 and shortened duration from planting to heading by 1.9 days °C−1. The entire growing season was reduced by 3.2 days °C−1 because of the increased temperature during the rice season. Our findings confirm that satellite data can be an effective way to estimate variations in rice phenology and can provide critical information that can be used to improve understanding of agricultural responses to weather variation.

scholarly journals Imported Dengue Cases, Weather Variation and Autochthonous Dengue Incidence in Cairns, Australia

PLoS ONE ◽  
2013 ◽  
Vol 8 (12) ◽  
pp. e81887 ◽  
Author(s):  
Xiaodong Huang ◽  
Gail Williams ◽  
Archie C. A. Clements ◽  
Wenbiao Hu
Keyword(s):  
Weather Variation

Weather Variation and Modification

2015 ◽  
pp. 40-50
Author(s):  
Richard A. Schleusener ◽  
Lewis O. Grant
Keyword(s):  
Weather Variation

Effects of Ungulate Disturbance and Weather Variation onPediocactus winkleri: Insights from Long-Term Monitoring

2015 ◽  
Vol 75 (1) ◽  
pp. 88-101
Author(s):  
Deborah J. Clark ◽  
Thomas O. Clark ◽  
Michael C. Duniway ◽  
Cody Flagg
Keyword(s):  
Weather Variation ◽  
Long Term Monitoring ◽  
Term Monitoring

The influence of weather variation on regional growth of Douglas fir stands in the U.S. Pacific Northwest

1990 ◽  
Vol 54 (1) ◽  
pp. 295-305 ◽  
Author(s):  
Charles E. Peterson ◽  
Linda S. Heath
Keyword(s):  
Pacific Northwest ◽  
Regional Growth ◽  
Douglas Fir ◽  
Weather Variation ◽  
The U.S

Effects of weather variation on a declining population of Slavonian Grebes Podiceps auritus

2013 ◽  
Vol 154 (4) ◽  
pp. 995-1006 ◽  
Author(s):  
Steven R. Ewing ◽  
Stuart Benn ◽  
Neil Cowie ◽  
Lorraine Wilson ◽  
Jeremy D. Wilson
Keyword(s):  
Weather Variation

scholarly journals Effects of weather variation on waterfowl migration: lessons from a continental-scale generalizable avian movement and energetics model

2021 ◽  
Author(s):  
Kevin Aagaard ◽  
Eric Lonsdorf ◽  
Wayne Thogmartin
Keyword(s):  
Bird Species ◽  
Model Performance ◽  
Population Level ◽  
Weather Data ◽  
Breeding Period ◽  
Land Use Land Cover ◽  
Continental Scale ◽  
Weather Variation ◽  
Daily Weather Data ◽  
Average Proportion

We developed a nonbreeding period continental-scale energetics-based model of daily waterfowl movement to predict year-specific migration and overwinter occurrence. The model approximates energy-expensive movements and energy-gaining stopovers as functions of metabolism and weather, in terms of temperature and frozen precipitation (i.e., snow). The model is a Markov process operating at the population level and is parameterized through a review of literature. We examined model performance against 62 years of non-breeding period daily weather data. The average proportion of available habitat decreased as weather severity increased, with mortality decreasing as the proportion of available habitat increased. The most commonly used nodes during the course of the nonbreeding period were generally consistent across years, with the most inter-annual variation present in the overwintering area. Our model revealed that the distribution of birds on the landscape changed more dramatically when the variation in daily available habitat was greater. The main routes for avian migration in North America were predicted by our simulations: the Eastern, Central, and Western flyways. Our model predicted an average of 77.4% survivorship for the nonbreeding period across all years (range = 76.4 – 78.4%), with lowest survivorship during the fall, intermediate survivorship in the winter, and greatest survivorship in the spring. We provide the parameters necessary for exploration within and among other taxa to leverage the generalizability of this migration model to a broader expanse of bird species, and across a range of climate change and land use/land cover change scenarios.

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