scholarly journals Quantifying Changes in Plant Species Diversity in a Savanna Ecosystem Through Observed and Remotely Sensed Data

2020 ◽  
Vol 12 (6) ◽  
pp. 2345
Author(s):  
Lazarus Chapungu ◽  
Luxon Nhamo ◽  
Roberto Cazzolla Gatti ◽  
Munyaradzi Chitakira
Keyword(s):  
Climate Change ◽  
Species Diversity ◽  
Plant Species ◽  
Vegetation Index ◽  
Shannon Index ◽  
Plant Species Diversity ◽  
Impact Of Climate Change ◽  
Normalised Difference Vegetation Index ◽  
The Impact ◽  
Index Of Diversity

This study examined the impact of climate change on plant species diversity of a savanna ecosystem, through an assessment of climatic trends over a period of forty years (1974–2014) using Masvingo Province, Zimbabwe, as a case study. The normalised difference vegetation index (NDVI) was used as a proxy for plant species diversity to cover for the absence of long-term historical plant diversity data. Observed precipitation and temperature data collected over the review period were compared with the trends in NDVI to understand the impact of climate change on plant species diversity over time. The nonaligned block sampling design was used as the sampling framework, from which 198 sampling plots were identified. Data sources included satellite images, field measurements, and direct observations. Temperature and precipitation had significant (p < 0.05) trends over the period under study. However, the trend for seasonal total precipitation was not significant but declining. Significant correlations (p < 0.001) were identified between various climate variables and the Shannon index of diversity. NDVI was also significantly correlated to the Shannon index of diversity. The declining trend of plant species in savanna ecosystems is directly linked to the decreasing precipitation and increasing temperatures.

Indicator plant species selection for monitoring the impact of climate change based on prediction uncertainty

2013 ◽  
Vol 29 ◽  
pp. 307-315 ◽  
Author(s):  
Motoki Higa ◽  
Katsuhiro Nakao ◽  
Ikutaro Tsuyama ◽  
Etsuko Nakazono ◽  
Masatsugu Yasuda ◽  
...  
Keyword(s):  
Climate Change ◽  
Plant Species ◽  
Species Selection ◽  
Indicator Plant ◽  
Impact Of Climate Change ◽  
Prediction Uncertainty ◽  
Selection For ◽  
The Impact

scholarly journals Analysis of meteorological variations on wheat yield and its estimation using remotely sensed data. A case study of selected districts of Punjab Province, Pakistan (2001-14)

2017 ◽  
Vol 12 (3) ◽  
Author(s):  
Rafia Mumtaz ◽  
Shahbaz Baig ◽  
Iram Fatima
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Crop Yield ◽  
Vegetation Index ◽  
Wheat Yield ◽  
Least Square ◽  
Wheat Crop ◽  
Main Challenge ◽  
Normalised Difference Vegetation Index ◽  
The Impact

Land management for crop production is an essential human activity that supports life on Earth. The main challenge to be faced by the agriculture sector in coming years is to feed the rapidly growing population while maintaining the key resources such as soil fertility, efficient land use, and water. Climate change is also a critical factor that impacts agricultural production. Among others, a major effect of climate change is the potential alterations in the growth cycle of crops which would likely lead to a decline in the agricultural output. Due to the increasing demand for proper agricultural management, this study explores the effects of meteorological variation on wheat yield in Chakwal and Faisalabad districts of Punjab, Pakistan and used normalised difference vegetation index (NDVI) as a predictor for yield estimates. For NDVI data (2001-14), the NDVI product of Moderate Resolution Imaging spectrometer (MODIS) 16-day composites data has been used. The crop area mapping has been realised by classifying the satellite data into different land use/land covers using iterative self-organising (ISO) data clustering. The land cover for the wheat crop was mapped using a crop calendar. The relation of crop yield with NDVI and the impact of meteorological parameters on wheat growth and its yield has been analysed at various development stages. A strong correlation of rainfall and temperature was found with NDVI data, which determined NDVI as a strong predictor of yield estimation. The wheat yield estimates were obtained by linearly regressing the reported crop yield against the time series of MODIS NDVI profiles. The wheat NDVI profiles have shown a parabolic pattern across the growing season, therefore parabolic least square fit (LSF) has been applied prior to linear regression. The coefficients of determination (<em>R</em><sup>2</sup>) between the reported and estimated yield was found to be 0.88 and 0.73, respectively, for Chakwal and Faisalabad. This indicates that the method is capable of providing yield estimates with competitive accuracies prior to crop harvest, which can significantly aid the policy guidance and contributes to better and timely decisions.

Precipitation of the warmest quarter and temperature of the warmest month are key to understanding the effect of climate change on plant species diversity in Southern African savannah

2013 ◽  
Vol 52 (2) ◽  
pp. 209-216 ◽  
Author(s):  
Isaiah Gwitira ◽  
Amon Murwira ◽  
Munyaradzi Davis Shekede ◽  
Mhosisi Masocha ◽  
Christopher Chapano
Keyword(s):  
Climate Change ◽  
Species Diversity ◽  
Plant Species ◽  
Plant Species Diversity

How to include the impact of climate change in the extinction risk assessment of policy plant species?

2018 ◽  
Vol 44 ◽  
pp. 43-49 ◽  
Author(s):  
Fabio Attorre ◽  
Thomas Abeli ◽  
Gianluigi Bacchetta ◽  
Alessio Farcomeni ◽  
Giuseppe Fenu ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Plant Species ◽  
Extinction Risk ◽  
Impact Of Climate Change ◽  
Extinction Risk Assessment ◽  
The Impact

scholarly journals Selective habitat utilisation and impact on vegetation by African elephant within a heterogeneous landscape

Koedoe ◽  
2001 ◽  
Vol 44 (1) ◽  
Author(s):  
A. Steyn ◽  
M. Stalmans
Keyword(s):  
Species Diversity ◽  
Plant Species ◽  
Woody Species ◽  
Plant Species Diversity ◽  
Conservation Areas ◽  
Management Objectives ◽  
Heterogeneous Landscape ◽  
Pterocarpus Angolensis ◽  
Reserve Forest ◽  
The Impact

Since 1992, a total of 33 elephants have been reintroduced to a 31 000 ha game-fenced section of the Songimvelo Game Reserve in the Barberton Mountainland, South Africa. The impact from elephant was assessed on the attainment of the primary management objectives which are the conservation of plant community and plant species diversity. A total of 160 semi-quantitative plots were systematically sampled along foraging paths. Vegetation was assessed in terms of dominant species composition and species utilised. Elephant activity is mostly confined to a rugged 1 200 ha portion of the reserve. Forest, thickets and woodlands are positively selected, whereas shrublands and grasslands are little utilised. A total of 73 woody species were recorded within the sample plots. Thirtynine of these species were utilised in the woodlands, 31 in the forest and thickets, and only 18 in the shrublands. Acacia ataxacantha, Dalbergia armata and Acacia caffra are ranked highest in dominance and in utilisation values. In contrast, Cussonia spicata and Pterocarpus angolensis are less common but are much selected. Continued utilisation at present levels could significantly threaten their persistence. These preliminary results indicate that the present low overall density of elephants relative to many other conservation areas already has a marked effect on certain plant species. Absolute elephant density figures are relatively meaningless within a heterogeneous landscape. The specific community and species make-up of the landscape needs to be taken into account for the determination of bounds to elephant numbers in order to ensure the maintenance of present plant species diversity levels.

A fusion of UAVs, digital cameras and micrometeorology to quantify the link between phenology and the carbon balance of a temperate peatland

2021 ◽  
Author(s):  
Gillian Simpson ◽  
Carole Helfter ◽  
Caroline Nichol ◽  
Tom Wade
Keyword(s):  
Climate Change ◽  
Carbon Balance ◽  
Vegetation Index ◽  
Natural Capital ◽  
Carbon Sink ◽  
Sink Strength ◽  
Environmental Controls ◽  
Spatial Coverage ◽  
Normalised Difference Vegetation Index ◽  
The Impact

&lt;p&gt;Peatland ecosystems are historical carbon sinks of global importance, whose management and restoration are becoming an increasingly popular approach to reach climate change targets via natural capital. However, the Net Ecosystem Exchange (NEE) of carbon dioxide (CO&lt;sub&gt;2&lt;/sub&gt;) can exhibit substantial variability on seasonal and inter-annual timescales, with some peatlands shifting from being a sink to a source of CO&lt;sub&gt;2&amp;#160;&lt;/sub&gt;between years. This variability is due to the complex interaction between factors such as meteorology and phenology, which are both known to control a peatland&amp;#8217;s net carbon sink strength. An improved understanding of these two drivers of peatland carbon cycling is needed to allow for better prediction of the impact of climate change on these ecosystems. This task requires us to study these environmental controls at multiple spatial and temporal scales. The role of vegetation in regulating NEE however, can be difficult to determine over shorter timescales (e.g. seasonal) and especially in peatland landscapes, which typically display strong spatial heterogeneity at the microsite scale (&lt; 0.5 m). Digital phenology cameras (PhenoCams) and Unmanned Aerial Vehicles (UAVs), offer novel opportunities to improve the temporal resolution and spatial coverage of traditional vegetation survey approaches. UAVs in particular are a more flexible, often cheaper alternative to satellite products, and can be used to collect data at the sub-centimetre scale. We employ PhenoCam imagery and UAV surveys with a Parrot Sequoia multispectral camera to map vegetation and track its phenology using vegetation indices such as the Normalised Difference Vegetation Index (NDVI) over the course of two growing seasons at Auchencorth Moss, a Scottish temperate peatland. By combining this digital camera imagery with in-situ NEE measurements (closed chambers and eddy-covariance) and meteorological data, we seek to quantify the impact of weather and phenology on carbon balance at the site.&lt;/p&gt;

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