scholarly journals Consequences of climate-induced vegetation changes exceed those of human disturbance for wild impala in the Serengeti ecosystem

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
L Hunninck ◽  
R May ◽  
C R Jackson ◽  
R Palme ◽  
E Røskaft ◽  
...  
Keyword(s):  
Human Disturbance ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Strategies ◽  
Forage Quality ◽  
Serengeti Ecosystem ◽  
Human Land Use ◽  
Faecal Samples ◽  
Dry Seasons ◽  
Positive Effect

Abstract In East Africa, climate change is predicted to reduce vegetation quality, and pervasive human disturbance has already resulted in significant declines in biodiversity. We studied the combined effects of reduced forage quality and human disturbance on faecal glucocorticoid metabolite (FGM) concentrations. We predicted that decreasing nutritional quality and increasing human disturbance would have an additive positive effect on FGM levels in wild impala (Aepyceros melampus). Employing a space-for-time approach, we used normalized difference vegetation index (NDVI) as a measure of forage quality, combined with spatially explicit proxies of human disturbance across areas of different protection management strategies in the Serengeti ecosystem. We collected 639 faecal samples, spread over 4 years, including both wet and dry seasons. Impala FGM levels increased significantly with declining NDVI and, to a lesser extent, with increasing proxies for human disturbance. However, we found no interaction between the two, such that impala had elevated FGM levels with low NDVI and low FGM levels with high NDVI regardless of human disturbance levels. This implies that impala will have high FGM levels if forage quality is poor, even with significant protection and reduced human disturbance. Understanding how animals respond to and cope with changes in forage quality and human land use across different protected areas is important for conservationists and managers to better protect species at risk and predict population viability.

scholarly journals Spatial variability of vegetation index and soil properties in an integrated crop-livestock system

2017 ◽  
Vol 21 (8) ◽  
pp. 513-518 ◽  
Author(s):  
Alberto C. de C. Bernardi ◽  
Célia R. Grego ◽  
Ricardo G. Andrade ◽  
Ladislau M. Rabello ◽  
Ricardo Y. Inamasu
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Strategies ◽  
Exchange Capacity ◽  
Soil Parameters ◽  
Forage Production ◽  
Soil P ◽  
Livestock System

ABSTRACT The knowledge of soil property spatial variability is useful for determining the rational use of inputs, such as the site-specific application of lime and fertilizer. The objective of this study was to evaluate the vegetation index and spatial variability of physical and chemical soil properties in an integrated crop-livestock system (ICLS). Soil samples were taken from a 6.9 ha area in a regular hexagon grid at 0-0.20 m depths. Soil P, K, Ca, Mg, and cation exchange capacity - CEC; base saturation; clay and sand were analyzed. Soil electrical conductivity (ECa) was measured with a contact sensor. The site was evaluated at the end of the corn season (April) and during forage production (October) using Landsat 5 images, remote sensing techniques and a geographic information system (GIS). Results showed that the normalized difference vegetation index (NDVI) was associated with ECa and soil parameters, indicating crop and pasture variations in the ICLS. Geostatistics and GIS were effective tools for collecting data regarding the spatial variability of soil and crop indicators, identifying variation trends in the data, and assisting data interpretation to determine adequate management strategies.

scholarly journals Temporal Patterns of Precipitation and Vegetation Variability over Zimbabwe during Extreme Dry and Wet Rainfall Seasons

2014 ◽  
Vol 53 (12) ◽  
pp. 2790-2804 ◽  
Author(s):  
Seth Mberego ◽  
Juliet Gwenzi
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Variability ◽  
Temporal Distribution ◽  
Climate Extremes ◽  
Temporal Patterns ◽  
Distribution Patterns ◽  
Dry Spells ◽  
Dry Conditions ◽  
Dry Seasons

AbstractClimatic variability over southern Africa is a well-recognized phenomenon, yet knowledge about the temporal variability of extreme seasons is lacking. This study investigates the intraseasonal progression of extreme seasons over Zimbabwe using precipitation and normalized difference vegetation index (NDVI) data covering the 1981–2005 period. Results show that the greatest deficits/surpluses of precipitation occur during the middle of the rainfall season (January and February), and the temporal distribution of precipitation during extreme dry seasons seems to shift earlier than that of extreme wet seasons. Furthermore, anomalous wet (dry) conditions were observed prior to the development of extreme dry (wet) seasons. Impacts of precipitation variations on vegetation lag by approximately 1–2 months. The semiarid southern region experiences more variability of vegetation cover than do the northern and eastern regions. Three distinct temporal patterns of dry years were noted by considering the maximum NDVI level, the mid-postseason NDVI condition, and nested dry spells. The findings of this study emphasize that climate extremes ought not to be simply understood in terms of total seasonal precipitation, because they may have within them some nested distribution patterns that may have a strong influence on primary production.

scholarly journals Developing Active Canopy Sensor-Based Precision Nitrogen Management Strategies for Maize in Northeast China

2019 ◽  
Vol 11 (3) ◽  
pp. 706 ◽  
Author(s):  
Xinbing Wang ◽  
Yuxin Miao ◽  
Rui Dong ◽  
Zhichao Chen ◽  
Yanjie Guan ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Field Experiments ◽  
Management Strategies ◽  
N Fertilizer ◽  
Yield Potential ◽  
Maize Production ◽  
N Management

Precision nitrogen (N) management (PNM) strategies are urgently needed for the sustainability of rain-fed maize (Zea mays L.) production in Northeast China. The objective of this study was to develop an active canopy sensor (ACS)-based PNM strategy for rain-fed maize through improving in-season prediction of yield potential (YP0), response index to side-dress N based on harvested yield (RIHarvest), and side-dress N agronomic efficiency (AENS). Field experiments involving six N rate treatments and three planting densities were conducted in three growing seasons (2015–2017) in two different soil types. A hand-held GreenSeeker sensor was used at V8-9 growth stage to collect normalized difference vegetation index (NDVI) and ratio vegetation index (RVI). The results indicated that NDVI or RVI combined with relative plant height (NDVI*RH or RVI*RH) were more strongly related to YP0 (R2 = 0.44–0.78) than only using NDVI or RVI (R2 = 0.26–0.68). The improved N fertilizer optimization algorithm (INFOA) using in-season predicted AENS optimized N rates better than the N fertilizer optimization algorithm (NFOA) using average constant AENS. The INFOA-based PNM strategies could increase marginal returns by 212 $ ha−1 and 70 $ ha−1, reduce N surplus by 65% and 62%, and improve N use efficiency (NUE) by 4%–40% and 11%–65% compared with farmer’s typical N management in the black and aeolian sandy soils, respectively. It is concluded that the ACS-based PNM strategies have the potential to significantly improve profitability and sustainability of maize production in Northeast China. More studies are needed to further improve N management strategies using more advanced sensing technologies and incorporating weather and soil information.

The utility of normalized difference vegetation index for predicting African buffalo forage quality

2012 ◽  
Vol 76 (7) ◽  
pp. 1499-1508 ◽  
Author(s):  
Sadie J. Ryan ◽  
Paul C. Cross ◽  
John Winnie ◽  
Craig Hay ◽  
Justin Bowers ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Forage Quality ◽  
African Buffalo

scholarly journals Normalized difference vegetation index, temperature and age affect faecal thyroid hormone concentrations in free-ranging African elephants

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Isabelle D Szott ◽  
Yolanda Pretorius ◽  
Andre Ganswindt ◽  
Nicola F Koyama
Keyword(s):  
Energy Expenditure ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Large Population ◽  
African Elephants ◽  
Large Herbivores ◽  
Factors Affecting ◽  
Animal Populations ◽  
Faecal Samples ◽  
Free Ranging

Abstract Conservation biologists can use hormone measurements to assess animals’ welfare, reproductive state, susceptibility to stressors, as well as energy expenditure. Quantifying hormone concentrations from faecal samples is particularly advantageous as samples can be collected without disturbing animals’ behaviour. In order for an endocrine marker to be useful for wildlife managers, we need to understand how extrinsic and intrinsic factors affect hormone concentrations in free-ranging animal populations. Thyroid hormones are linked to basal metabolic rate and energy expenditure. Previous research demonstrated that triiodothyronine (T3) can be measured successfully in faecal matter of African elephants, Loxodonta africana. However, to our knowledge, research into factors affecting changes in elephant T3 levels has only been carried out in captive elephants so far. Thus, we present the first study of faecal T3 metabolite (mT3) concentrations of a large population of free-ranging African elephants. Over 15 months, we collected faecal samples from identified (n = 43 samples) and unidentified (n = 145 samples) individuals in Madikwe Game Reserve, South Africa. We investigated whether vegetative productivity [normalized difference vegetation index (NDVI)] in interaction with mean monthly temperature, age and sex affected mT3 concentrations. We found a significant negative interaction effect of NDVI and temperature. Increasing NDVI was related to higher concentrations of mT3, but increasing temperature was related to a decrease in mT3 concentrations in individually identified and unidentified elephants. In unidentified individuals, juvenile elephants had significantly higher mT3 concentrations compared to adult elephants. Faecal T3 can successfully be quantified in samples from free-ranging elephant populations and thus provides insight into energy expenditure in large herbivores.

scholarly journals Effect of a Biostimulant on Bermudagrass Fall Color Retention and Spring Green-Up

Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 608
Author(s):  
Verónica De Luca ◽  
Diego Gómez de Barreda
Keyword(s):  
Amino Acid ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cynodon Dactylon ◽  
Field Research ◽  
Dry Weight ◽  
Green Color ◽  
Positive Effects ◽  
Color Retention ◽  
Positive Effect

Field research was conducted in 2017–2019 on “Princess 77” bermudagrass (Cynodon dactylon (L.) Pers.) to determine whether an amino acid based biostimulant program applied in the late season (October-November) and early season (March-April) could extend fall color retention (FCR) or hasten the spring green-up (SGU), respectively. Bermudagrass was treated with the biostimulant under five different managements: non-treated; 6 times at 5 L ha−1 weekly; 3 times at 5 L ha−1 in a 14-day interval; 6 times at 10 L ha−1 weekly; and 3 times at 10 L ha−1 in a 14-day interval. Normalized difference vegetation index (NDVI) and visual ratings (turf green color and percentage of green coverage in the subplot) were determined weekly, and turf clipping dry weight for the SGU studies. At the end of the FCR studies (2017 and 2018), there was no effect of the biostimulant; although, some isolated positive effects were detected during the experiment in 2017 on bermudagrass treated weekly at 10 L ha−1 for NDVI. However, there was a slight positive effect on SGU when this physiological process occurred slowly (year 2018) and the biostimulant was applied weekly at 10 L ha−1 (4.4 kg N ha−1), compared to another performed management and warmer years (2017 and 2019).

scholarly journals Mapping Mangrove Density from Rapideye Data in Central America

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Nguyen-Thanh Son ◽  
Chi-Farn Chen ◽  
Cheng-Ru Chen
Keyword(s):  
Central America ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Management Strategies ◽  
Current Status ◽  
Support Vector ◽  
Mangrove Forests ◽  
Red Edge ◽  
Wide Range ◽  
Edge Band

AbstractMangrove forests provide a wide range of socioeconomic and ecological services for coastal communities. Extensive aquaculture development of mangrove waters in many developing countries has constantly ignored services of mangrove ecosystems, leading to unintended environmental consequences. Monitoring the current status and distribution of mangrove forests is deemed important for evaluating forest management strategies. This study aims to delineate the density distribution of mangrove forests in the Gulf of Fonseca, Central America with Rapideye data using the support vector machines (SVM). The data collected in 2012 for density classification of mangrove forests were processed based on four different band combination schemes: scheme-1 (bands 1–3, 5 excluding the red-edge band 4), scheme-2 (bands 1–5), scheme-3 (bands 1–3, 5 incorporating with the normalized difference vegetation index, NDVI), and scheme-4 (bands 1–3, 5 incorporating with the normalized difference red-edge index, NDRI). We also hypothesized if the obvious contribution of Rapideye red-edge band could improve the classification results. Three main steps of data processing were employed:

scholarly journals Detecting Phenological Development of Winter Wheat and Winter Barley Using Time Series of Sentinel-1 and Sentinel-2

2021 ◽  
Vol 13 (24) ◽  
pp. 5036
Author(s):  
Katharina Harfenmeister ◽  
Sibylle Itzerott ◽  
Cornelia Weltzien ◽  
Daniel Spengler
Keyword(s):  
Time Series ◽  
Winter Wheat ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Stem Elongation ◽  
Management Strategies ◽  
Local Maximum ◽  
Winter Barley ◽  
Optical Data ◽  
Sentinel 2

Monitoring the phenological development of agricultural plants is of high importance for farmers to adapt their management strategies and estimate yields. The aim of this study is to analyze the sensitivity of remote sensing features to phenological development of winter wheat and winter barley and to test their transferability in two test sites in Northeast Germany and in two years. Local minima, local maxima and breakpoints of smoothed time series of synthetic aperture radar (SAR) data of the Sentinel-1 VH (vertical-horizontal) and VV (vertical-vertical) intensities and their ratio VH/VV; of the polarimetric features entropy, anisotropy and alpha derived from polarimetric decomposition; as well as of the vegetation index NDVI (Normalized Difference Vegetation Index) calculated using optical data of Sentinel-2 are compared with entry dates of phenological stages. The beginning of stem elongation produces a breakpoint in the time series of most parameters for wheat and barley. Furthermore, the beginning of heading could be detected by all parameters, whereas particularly a local minimum of VH and VV backscatter is observed less then 5 days before the entry date. The medium milk stage can not be detected reliably, whereas the hard dough stage of barley takes place approximately 6–8 days around a local maximum of VH backscatter in 2018. Harvest is detected for barley using the fourth breakpoint of most parameters. The study shows that backscatter and polarimetric parameters as well as the NDVI are sensitive to specific phenological developments. The transferability of the approach is demonstrated, whereas differences between test sites and years are mainly caused by meteorological differences.

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