scholarly journals Monitoring Climate Impacts on Annual Forage Production across U.S. Semi-Arid Grasslands

2021 ◽  
Vol 14 (1) ◽  
pp. 4
Author(s):  
Markéta Poděbradská ◽  
Bruce K. Wylie ◽  
Deborah J. Bathke ◽  
Yared A. Bayissa ◽  
Devendra Dahal ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Climatic Factors ◽  
Climate Impacts ◽  
Soil Survey ◽  
Growth Potential ◽  
Forage Production ◽  
Growth Variability ◽  
Seasonal Climate ◽  
Arid Grasslands ◽  
Semi Arid

The ecosystem performance approach, used in a previously published case study focusing on the Nebraska Sandhills, proved to minimize impacts of non-climatic factors (e.g., overgrazing, fire, pests) on the remotely-sensed signal of seasonal vegetation greenness resulting in a better attribution of its changes to climate variability. The current study validates the applicability of this approach for assessment of seasonal and interannual climate impacts on forage production in the western United States semi-arid grasslands. Using a piecewise regression tree model, we developed the Expected Ecosystem Performance (EEP), a proxy for annual forage production that reflects climatic influences while minimizing impacts of management and disturbances. The EEP model establishes relations between seasonal climate, site-specific growth potential, and long-term growth variability to capture changes in the growing season greenness measured via a time-integrated Normalized Difference Vegetation Index (NDVI) observed using a Moderate Resolution Imaging Spectroradiometer (MODIS). The resulting 19 years of EEP were converted to expected biomass (EB, kg ha−1 year−1) using a newly-developed relation with the Soil Survey Geographic Database range production data (R2 = 0.7). Results were compared to ground-observed biomass datasets collected by the U.S. Department of Agriculture and University of Nebraska-Lincoln (R2 = 0.67). This study illustrated that this approach is transferable to other semi-arid and arid grasslands and can be used for creating timely, post-season forage production assessments. When combined with seasonal climate predictions, it can provide within-season estimates of annual forage production that can serve as a basis for more informed adaptive decision making by livestock producers and land managers.

scholarly journals Drivers and Environmental Impacts of Vegetation Greening in a Semi-Arid Region of Northwest China since 2000

2021 ◽  
Vol 13 (21) ◽  
pp. 4246
Author(s):  
Zhenzong Wu ◽  
Jian Bi ◽  
Yifei Gao
Keyword(s):  
Arid Region ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Agricultural Practices ◽  
Northwest China ◽  
Terrestrial Vegetation ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Semi Arid Region ◽  
Semi Arid ◽  
Dynamics Of Vegetation

The dynamics of terrestrial vegetation have changed a lot due to climate change and direct human interference. Monitoring these changes and understanding the mechanisms driving them are important for better understanding and projecting the Earth system. Here, we assessed the dynamics of vegetation in a semi-arid region of Northwest China for the years from 2000 to 2019 through satellite remote sensing using Vegetation Index (VI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and analyzed the interannual covariation between vegetation and three climatic factors—air temperature, precipitation, and vapor pressure deficit (VPD)—at nine meteorological stations. The main findings of this research are: (1) herbaceous land greened up much more than forests (2.85%/year vs. 1.26%/year) in this semi-arid region; (2) the magnitudes of green-up for croplands and grasslands were very similar, suggesting that agricultural practices, such as fertilization and irrigation, might have contributed little to vegetation green-up in this semi-arid region; and (3) the interannual dynamics of vegetation at high altitudes in this region correlate little with temperature, precipitation, or VPD, suggesting that factors other than temperature and moisture control the interannual vegetation dynamics there.

scholarly journals Advanced Method to Capture the Time-Lag Effects between Annual NDVI and Precipitation Variation Using RNN in the Arid and Semi-Arid Grasslands

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1789
Author(s):  
Taosuo Wu ◽  
Feng Feng ◽  
Qian Lin ◽  
Hongmei Bai
Keyword(s):  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Time Lag ◽  
Time Lags ◽  
Lag Effects ◽  
Precipitation Variation ◽  
Arid Grasslands ◽  
Successful Capture ◽  
Semi Arid

The latest research indicates that there are time-lag effects between the normalized difference vegetation index (NDVI) and the precipitation variation. It is well known that the time-lags are different from region to region, and there are time-lags for the NDVI itself correlated to the precipitation. In the arid and semi-arid grasslands, the annual NDVI has proved not only to be highly dependent on the precipitation of the concurrent year and previous years, but also the NDVI of previous years. This paper proposes a method using recurrent neural network (RNN) to capture both time-lags of the NDVI with respect to the NDVI itself, and of the NDVI with respect to precipitation. To quantitatively capture these time-lags, 16 years of the NDVI and precipitation data are used to construct the prediction model of the NDVI with respect to precipitation. This study focuses on the arid and semi-arid Hulunbuir grasslands dominated by perennials in northeast China. Using RNN, the time-lag effects are captured at a 1 year time-lag of precipitation and a 2 year time-lag of the NDVI. The successful capture of the time-lag effects provides significant value for the accurate prediction of vegetation variation for arid and semi-arid grasslands.

THE CLASSIFICATION OF LAND ACCORDING TO THE DEGREE OF RABBIT INFESTATION IN CENTRAL OTAGO

1987 ◽  
pp. 65-70
Author(s):  
I.G.C. Kerr ◽  
J.M. Williams ◽  
W.D. Ross ◽  
J.M. Pollard
Keyword(s):  
Carrying Capacity ◽  
Mediterranean Climate ◽  
Natural Habitat ◽  
Public Funding ◽  
Soil Survey ◽  
European Rabbit ◽  
Cultural Modification ◽  
Classification Information ◽  
Semi Arid

The European rabbit (Oryctolagus cuniculus) introduced into New Zealand in the 183Os, has consistently flourished in Central Otago, the upper Waitaki, and inland Marlborough, all areas of mediterranean climate. It has proved difficult to manage in these habitats. The 'rabbit problem' is largely confined to 105,000 ha of low producing land mostly in semi arid areas of Central Otago. No field scale modifications of the natural habitat have been successful in limiting rabbit numbers. The costs of control exceed the revenue from the land and continued public funding for control operations appears necessary. A system for classifying land according to the degree of rabbit proneness is described. Soil survey and land classification information for Central Otago is related to the distribution and density of rabbits. This intormation can be used as a basis for defining rabbit carrying capacity and consequent land use constraints and management needs. It is concluded that the natural rabbit carrying capacity of land can be defined by reference to soil survey information and cultural modification to the natural vegetation. Classification of land according to rabbit proneness is proposed as a means of identifying the need for, and allocation of, public funding tor rabbit management. Keywords: Rabbit habitat, rabbit proneness, use of rabbit prone land.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

scholarly journals Forage Production of the Argentine Pampa Region Based on Land Use and Long-Term Normalized Difference Vegetation Index Data

2009 ◽  
Vol 62 (2) ◽  
pp. 163-170 ◽  
Author(s):  
Carlos M. Di Bella ◽  
Ignacio J. Negri ◽  
Gabriela Posse ◽  
Florencia R. Jaimes ◽  
Esteban G. Jobbágy ◽  
...  
Keyword(s):  
Land Use ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Forage Production ◽  
Index Data ◽  
Pampa Region

scholarly journals Modelling spatial and temporal dynamics of gross primary production in the Sahel from earth-observation-based photosynthetic capacity and quantum efficiency

2017 ◽  
Vol 14 (5) ◽  
pp. 1333-1348 ◽  
Author(s):  
Torbern Tagesson ◽  
Jonas Ardö ◽  
Bernard Cappelaere ◽  
Laurent Kergoat ◽  
Abdulhakim Abdi ◽  
...  
Keyword(s):  
Primary Production ◽  
Quantum Efficiency ◽  
Vegetation Index ◽  
Photosynthetic Capacity ◽  
Gross Primary Production ◽  
Earth Observation ◽  
Arid Ecosystems ◽  
Spatially Explicit ◽  
Equivalent Water Thickness ◽  
Semi Arid

Abstract. It has been shown that vegetation growth in semi-arid regions is important to the global terrestrial CO2 sink, which indicates the strong need for improved understanding and spatially explicit estimates of CO2 uptake (gross primary production; GPP) in semi-arid ecosystems. This study has three aims: (1) to evaluate the MOD17A2H GPP (collection 6) product against GPP based on eddy covariance (EC) for six sites across the Sahel; (2) to characterize relationships between spatial and temporal variability in EC-based photosynthetic capacity (Fopt) and quantum efficiency (α) and vegetation indices based on earth observation (EO) (normalized difference vegetation index (NDVI), renormalized difference vegetation index (RDVI), enhanced vegetation index (EVI) and shortwave infrared water stress index (SIWSI)); and (3) to study the applicability of EO upscaled Fopt and α for GPP modelling purposes. MOD17A2H GPP (collection 6) drastically underestimated GPP, most likely because maximum light use efficiency is set too low for semi-arid ecosystems in the MODIS algorithm. Intra-annual dynamics in Fopt were closely related to SIWSI being sensitive to equivalent water thickness, whereas α was closely related to RDVI being affected by chlorophyll abundance. Spatial and inter-annual dynamics in Fopt and α were closely coupled to NDVI and RDVI, respectively. Modelled GPP based on Fopt and α upscaled using EO-based indices reproduced in situ GPP well for all except a cropped site that was strongly impacted by anthropogenic land use. Upscaled GPP for the Sahel 2001–2014 was 736 ± 39 g C m−2 yr−1. This study indicates the strong applicability of EO as a tool for spatially explicit estimates of GPP, Fopt and α; incorporating EO-based Fopt and α in dynamic global vegetation models could improve estimates of vegetation production and simulations of ecosystem processes and hydro-biochemical cycles.

Assessing the impact of seasonal precipitation and temperature on vegetation in a grass-dominated rangeland

2014 ◽  
Vol 36 (2) ◽  
pp. 185 ◽  
Author(s):  
Fang Chen ◽  
Keith T. Weber
Keyword(s):  
Vegetation Index ◽  
Climatic Factors ◽  
Growing Season ◽  
Vegetation Growth ◽  
Factors Affecting ◽  
Growing Seasons ◽  
Normalised Difference Vegetation Index ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Impact ◽  
Precipitation And Temperature

Changes in vegetation are affected by many climatic factors and have been successfully monitored through satellite remote sensing over the past 20 years. In this study, the Normalised Difference Vegetation Index (NDVI), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, was selected as an indicator of change in vegetation. Monthly MODIS composite NDVI at a 1-km resolution was acquired throughout the 2004–09 growing seasons (i.e. April–September). Data describing daily precipitation and temperature, primary factors affecting vegetation growth in the semiarid rangelands of Idaho, were derived from the Surface Observation Gridding System and local weather station datasets. Inter-annual and seasonal fluctuations of precipitation and temperature were analysed and temporal relationships between monthly NDVI, precipitation and temperature were examined. Results indicated NDVI values observed in June and July were strongly correlated with accumulated precipitation (R2 >0.75), while NDVI values observed early in the growing season (May) as well as late in the growing season (August and September) were only moderately related with accumulated precipitation (R2 ≥0.45). The role of ambient temperature was also apparent, especially early in the growing season. Specifically, early growing-season temperatures appeared to significantly affect plant phenology and, consequently, correlations between NDVI and accumulated precipitation. It is concluded that precipitation during the growing season is a better predictor of NDVI than temperature but is interrelated with influences of temperature in parts of the growing season.

scholarly journals The influence of the climatology of the semi-arid from Alagoas-Brazil on the raw milk microbiota

2017 ◽  
Vol 3 (1) ◽  
pp. 27
Author(s):  
Ticiano Gomes do Nascimento ◽  
Euridice Farias Falcão ◽  
Maria Cristina Delgado da Silva ◽  
Josicleide Nascimento Oliveira Silvino ◽  
Pierre Barnabé Escodro ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Thermal Comfort ◽  
Vegetation Index ◽  
Raw Milk ◽  
Climatic Conditions ◽  
The State ◽  
Maximum Temperature ◽  
Climatic Data ◽  
Microbiological Analysis ◽  
Semi Arid

This study aimed to evaluate the influence of the climatology of the semi-arid from Alagoas-Brazil on the raw milk microbiota in semi-arid area of the 07 micro-regions of the State of Alagoas of Alagoas, Brazil. The climatic data were extracted from National Institute of Meteorology from the Brazilian government. The raw milk was collected after the dairy cow milking process in 12 small rural associations of the semi-arid from the State of Alagoas, during the 4 seasons and the raw milk was carried out procedures of sampling, transportation and microbiological analysis. A total of 58 samples were counted coliforms at 45°C, <em>Escherichia coli</em> and coagulase-positive <em>Staphylococcus</em>. Only 02 rural associations presented low levels of microbiological contamination, which were located in areas of climatic conditions and parameters of thermal comfort index and vegetation index favorable, but 10 rural associations presented high counting of coliforms at 45°C, <em>Escherichia coli</em>. The climatologic parameters (maximum temperature, atmospheric pressure), bovine comfort thermal index and vegetation index have showed to influence the growth of the coliforms at 45°C and <em>Escherichia coli</em> with high incidence during the summer weather. The precipitation parameter, bovine thermal comfort and vegetation index have displayed to influence coagulase-positive<em> Staphylococcus</em> counting especially during the period between the summer end and the autumn beginning seasons. New Actions, and Rural Education and Health Programs should be implemented as politics of Food Safety. New strategies and programs for dissemination more effective on the risks of transmission of pathogens and Foodborne Diseases are necessary as the part of emergence politics of the health and education areas. Regulatory Actions should be encouraged within the processes that improve the quality control of raw milk as well its bioproducts, with professional assistance relevant in agriculture area.

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