Spectral indicators of forage quality in West Africa’s tropical savannas

Ferner, Jessica; Linstädter, Anja; Südekum, K. H.; Schmidtlein, Sebastian

doi:10.1016/j.jag.2015.04.019

Cited by 25 publications

(19 citation statements)

References 61 publications

(84 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…; Ferner et al. ). Second, it complicates animal handling and improves habitat for ectoparasites (Archer & Predick ).…”

Section: Introductionmentioning

confidence: 97%

“…Despite facilitative effects of isolated tree canopies on forage provision and plant diversity (Sagar et al 2008;Treydte et al 2008), an increased abundance of trees (and thus a landscape-level increase in canopy density) is regarded as undesirable (Eldridge et al 2011). First, this 'bush encroachment' mostly reduces forage supply for domestic livestock (Scholes & Archer 1997), which is a key ecosystem service of drylands Ferner et al 2015). Second, it complicates animal handling and improves habitat for ectoparasites (Archer & Predick 2014).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Are trees of intermediate density more facilitative? Canopy effects of four East African legume trees

Linstädter

Bora

Tolera

et al. 2015

Applied Vegetation Science

View full text Add to dashboard Cite

Questions Do East African legume trees differ in their canopy effects? Have species with intermediate canopy density more pronounced facilitative effects on understorey primary production, community composition and diversity? How are canopy effects related to species' encroachment status, and modulated by a local aridity gradient? Location Upland and lowland environments of the Borana rangelands, an arid thornbush savanna in southern Ethiopia. Methods We harnessed pastoralists' local ecological knowledge to rank the encroachment status of six legume tree species previously known as Acacia, and correlated this rank to a dendrometric proxy of canopy density. Vegetation relevés (1 m²) were placed in sub‐canopy and adjacent inter‐canopy habitats of four legume tree species that differed in canopy density and encroachment status (Vachellia bussei, V. drepanolobium, V. seyal, V. tortilis). Using mixed‐effects ANOVA, we evaluated effects of tree species and habitat (sub‐canopy or inter‐canopy) on total, forb and grass biomass, and on species diversity, comparing results for lowland and upland sites. Effects on floristic composition were assessed via PERMANOVA and NMDS. Results Species' encroachment status and canopy density were negatively correlated. Most pronounced facilitative effects (more frequent and larger differences between sub‐canopy and inter‐canopy habitats) were found for a species with intermediate canopy density (V. bussei). Diversity in its understorey vegetation increased up to 32% (total biomass: 29%, forb biomass: 40%). In contrast, the species with the most open canopy (V. drepanolobium; also the most encroaching species) never exerted significant facilitative effects. In contrast to expectations, canopy effects were more frequent in (climatically less arid) upland environments, probably due to a redistribution of water within the landscape. Large differences in facilitative effects across tree individuals indicate that a high intraspecific variability of canopy traits and/or small‐scale differences in abiotic site conditions have partly overridden species‐specific differences in canopy architecture. Conclusion Our study provides new insights on why encroaching legume tree species may decrease herbaceous production: they tend to have more open canopies, with small facilitative effects on sub‐canopy herbaceous production. We thus recommend promoting an open savanna with the tree layer dominated by species with a high facilitative potential to maintain forage provision and species diversity.

show abstract

“…; Ferner et al. ). Second, it complicates animal handling and improves habitat for ectoparasites (Archer & Predick ).…”

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Are trees of intermediate density more facilitative? Canopy effects of four East African legume trees

Linstädter

Bora

Tolera

et al. 2015

Applied Vegetation Science

View full text Add to dashboard Cite

show abstract

“…Some of the wavelengths most important for predicting CP included were within the visual range and are related to chlorophyll electron transition 2008, this may be due to the high protein content of chlorophyll [39,46,47]. Predictive wavelengths from the NIR region likely related to N-H asymmetry in protein, and the second overtone of N=H bends in protein [39,46,47]. Often wavelengths in the MIR region 1475-1575 nm are utilised in protein analysis relate to an amide I and Amide II region of the spectrum which may in this case be the 1550 nm and 1545 nm wavelengths [48].…”

Section: Identify Specific Wavelengths Important For Modelling Nv Parmentioning

confidence: 99%

“…Unsurprisingly 2008, many of the wavelengths most important to predicting WSC have been associated with the O-H stretches and deformation in sugar and starch [39,46,49]. For DM, some of the most important wavelengths are associated with absorption by the C-H bond in oil molecules, though it is unclear how this may relate to DM.…”

Section: Identify Specific Wavelengths Important For Modelling Nv Parmentioning

confidence: 99%

Machine Learning Algorithms to Predict Forage Nutritive Value of In Situ Perennial Ryegrass Plants Using Hyperspectral Canopy Reflectance Data

et al. 2020

View full text Add to dashboard Cite

Nutritive value (NV) of forage is too time consuming and expensive to measure routinely in targeted breeding programs. Non-destructive spectroscopy has the potential to quickly and cheaply measure NV but requires an intermediate modelling step to interpret the spectral data. A novel machine learning technique for forage analysis, Cubist, was used to analyse canopy spectra to predict seven NV parameters, including dry matter (DM), acid detergent fibre (ADF), ash, neutral detergent fibre (NDF), in vivo dry matter digestibility (IVDMD), water soluble carbohydrates (WSC), and crude protein (CP). Perennial ryegrass (Lolium perenne) was used as the test crop. Independent validation of the developed models revealed prediction capabilities with R2 values and Lin’s concordance values reported between 0.49 and 0.82, and 0.68 and 0.89, respectively. Informative wavelengths for the creation of predictive models were identified for the seven NV parameters. These wavelengths included regions of the electromagnetic spectrum that are usually excluded due to high background variation, however, they contain important information and utilising them to obtain meaningful signals within the background variation is an advantage for accurate models. Non-destructive field spectroscopy along with the predictive models was deployed infield to measure NV of individual ryegrass plants. A significant reduction in labour was observed. The associated increase in speed and reduction of cost makes targeting NV in commercial breeding programs now feasible.

show abstract

“…Abderrazak et al proposed a spatiotemporal monitoring method of soil salinization in the Tadla plain in Central Morocco using spectral indices derived from Thematic Mapper (TM) and Operational Land Imager (OLI) data [ 13 ]. Ferner et al tested whether spatio-temporal information on the quality (metabolizable energy content, ME) and quantity (green biomass, BM) of West African forage resources can be correlated to in situ-measured reflectance data [ 14 ]. Oz et al found informative spectral bands in three types of models—vegetation indices (VI), neural network (NN), and partial least squares (PLS) regression—for estimating leaf chlorophyll (Chl) and carotenoid (Car) contents of three unrelated tree species and to assess the accuracy of the models using a minimal number of bands [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Grouping Distributed Compressive Sensing Reconstruction of Plant Hyperspectral Data

Liu

Xue

et al. 2017

Sensors

View full text Add to dashboard Cite

With the development of hyperspectral technology, to establish an effective spectral data compressive reconstruction method that can improve data storage, transmission, and maintaining spectral information is critical for quantitative remote sensing research and application in vegetation. The spectral adaptive grouping distributed compressive sensing (AGDCS) algorithm is proposed, which enables a distributed compressed sensing reconstruction of plant hyperspectral data. The spectral characteristics of hyperspectral data are analyzed and the joint sparse model is constructed. The spectral bands are adaptively grouped and the hyperspectral data are compressed and reconstructed on the basis of grouping. The experimental results showed that, compared with orthogonal matching pursuit (OMP) and gradient projection for sparse reconstruction (GPSR), AGDCS can significantly improve the visual effect of image reconstruction in the spatial domain. The peak signal-to-noise ratio (PSNR) at a low sampling rate (the sampling rate is lower than 0.2) increases by 13.72 dB than OMP and 1.66 dB than GPSR. In the spectral domain, the average normalized root mean square error, the mean absolute percentage error, and the mean absolute error of AGDCS is 35.38%, 31.83%, and 33.33% lower than GPSR, respectively. Additionally, AGDCS can achieve relatively high reconstructed efficiency.

show abstract

Spectral indicators of forage quality in West Africa’s tropical savannas

Cited by 25 publications

References 61 publications

Are trees of intermediate density more facilitative? Canopy effects of four East African legume trees

Are trees of intermediate density more facilitative? Canopy effects of four East African legume trees

Machine Learning Algorithms to Predict Forage Nutritive Value of In Situ Perennial Ryegrass Plants Using Hyperspectral Canopy Reflectance Data

Adaptive Grouping Distributed Compressive Sensing Reconstruction of Plant Hyperspectral Data

Contact Info

Product

Resources

About