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1,604 results for “Wintering”
Fig.4 in Large Herbivore Abundance, Distribution And Winter Pasture Quality In Two Game Farms In North Kazakhstan
Fig.4. Moose wintering concentration places in "Zerenda" game farm.
Fig. 1 in Evaluation Of Winter Hardiness In Different Cultivated Tilia Taxa - Experience Of Some Most Valuable Dendrological Plantations In Central Latvia (Vidzeme) After Extremely Hard Winter In Year 2009/2010
Fig. 1. Location of inventoried dendrological objects in central part of Latvia.
Data from: Climate drives body mass changes in a mountain ungulate: Shorter winters lead to heavier Alpine ibex
<p>Climate affects seasonality and plant phenology, which can influence seasonal body mass dynamics of herbivores in temperate environments. We investigated long-term trends of seasonal body mass changes in male Alpine ibex (<em>Capra ibex</em>). We used SEM to test direct and indirect relationships between body mass, mass changes and environmental and climatic variables. Individually recognizable Alpine ibex were weighed repeatedly between 2000 and 2022 in Gran Paradiso National Park (Italy). Autumn mass increased substantially over these two decades, up to 15% in some age classes. Over the same time frame, both summer mass gain and winter mass loss decreased, suggesting that heavier autumn body mass was due to the cumulative effects of reduced mass loss over several winters. The environmental factor with the strongest effects on winter mass changes was the starting date of vegetation green-up at low altitude, where ibex gather after winter to feed on new growth vegetation. Early springs led to lower winter mass loss, likely because ibex relied on stored fat for a shorter period and had greater access to forage. High population density also increased winter mass loss. Environmental conditions and resource availability, possibly also influenced by density in winter and early spring seem therefore to directly affect the body mass dynamics of male Alpine ibex, while the effect of summer conditions appears less relevant. By affecting seasonal body mass dynamics, climate change may have consequences for life history and population dynamics of mountain herbivores, for example via earlier access of young males to reproduction.</p>
Scripts for "Evaluation and Attribution of a Warm Winter Bias Over Arctic Sea Ice in a Climate Model"
<p>The scripts used to generate the main figures and results of the work entitled ''Evaluation and Attribution of a Warm Winter Bias Over Arctic Sea Ice in a Climate Model'' by Michalezyk et al., submitted for publication in JAMES - AGU in 2024.</p> <p>If you have any questions, please contact Nicolas MICHALEZYK : nicolas.michalezyk@locean.ipsl.fr</p>
Fig. 1 in A Case of winter activity of the Hermann's Tortoise (Testudo hermanni Gmelin, 1789) (Reptilia: Testudinidae) from Bulgaria
Fig. 1. The plantation of Quercus suber and the adult female T. hermanni recorded in it.
Fig. 1 in Circadian activity patterns of the Red fox (Vulpes vulpes) and the Stone marten (Martes foina) in agricultural landscape of Northwestern Bulgaria during autumn-winter period
Fig. 1. Location of the protected area "Zlatiyata" in Northwestern Bulgaria.
Fig. 1 in Notes on autumn-winter stomach contents of the Stone Marten (Martes foina) in the Balkan Mountains, Central Bulgaria
Fig. 1. Location of the study area.
Fig. 1 in Apparent fatal winter tick (Dermacentor albipictus) infestation in captive reindeer (Rangifer tarandus)
Fig. 1. Captive reindeer skin densely infested by Dermacentor albipictus.
Diurnal variability of Black Carbon in Modena: Modeled concentration maps for winter 2020 and 2021
<p>This video presents concentration maps of Black Carbon over the city of Modena during the winters of 2020 and 2021. The concentrations are categorized into Fossil Fuel, Biomass Burning, and their combined totals (Fossil Fuel + Biomass Burning). This supplementary material supports the paper titled "Measurement report: Source attribution and estimation of black carbon levels in an urban hotspot of the central Po Valley: An integrated approach combining high-resolution dispersion modelling and micro-aethalometers," published in EGUsphere (https://doi.org/10.5194/egusphere-2023-2641).</p>
Sustenance of phytoplankton in the subpolar North Atlantic during winter
<p>Related data used for the Journal of Geophysical Research - Oceans paper entitled "Sustenance of phytoplankton in the subpolar North Atlantic during winter" by Karimpour, F., Tandon, A., and Mahadevan, A.</p>
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from LPJ-GUESS winter wheat simulations
This data set contains output data from simulations with the model LPJ-GUESS for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above groun biomass, plant day, maturity day, anthesis day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simlations are based on 31-year simulations using the AgMERRA data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A= 'none', 'regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from pDSSAT winter wheat simulations
This data set contains output data from simulations with the model pDSSAT for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, anthesis day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from EPIC-TAMU winter wheat simulations
This data set contains output data from simulations with the model EPIC-TAMU for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from ORCHIDEE-crop winter wheat simulations
This data set contains output data from simulations with the model ORCHIDEE-crop for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, anthesis day . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from PEPIC winter wheat simulations
This data set contains output data from simulations with the model PEPIC for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from EPIC-IIASA winter wheat simulations
This data set contains output data from simulations with the model EPIC-IIASA for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from GEPIC winter wheat simulations
This data set contains output data from simulations with the model GEPIC for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from PROMET winter wheat simulations
This data set contains output data from simulations with the model PROMET for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, anthesis day, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the ERA-Interim (Dee et al. 2011) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from CARAIB winter wheat simulations
<p>This data set contains output data from simulations with the model CARAIB for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').</p>
AgMIP's global gridded crop model intercomparison (GGCMI) phase II CTWN-A archive: priority 1 outputs from APSIM-UGOE winter wheat simulations
This data set contains output data from simulations with the model APSIM-UGOE for winter wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase II output data set. Output variables included are: crop yield, above-ground biomass, planting day, maturity day, anthesis day, potential irrigation water withdrawal, actual growing season evapotranspiration . Simulations are based on 31-year simulations using the AgMERRA (Ruane et al. 2015) data set with 4 atmospheric CO2 mixing ratios (C=360, 510, 660, 810 ppm) uniform offsets for temperature (T= -1, 0, 1, 2, 3, 4, 6 K), water (W= -50, -30, -20, -10, 0, 10, 20, 30 %, and infinite/irrigated), and 3 nitrogen input levels (N= 10, 60, 200 kgN/ha) using 2 assumptions on adaptation (A0= 'none', A1='regain original growing season').
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