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Grasses, Volume 3, Issue 2 (June 2024) – 4 articles

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20 pages, 4052 KiB  
Article
Ecogeography and Climate Change in Forage Grasses from Arid and Semi-Arid Regions of Mexico
by Gabriela Ramírez-Ojeda, Edith Ramírez-Segura, Luis Ángel Barrera-Guzmán and Abieser Vázquez-González
Grasses 2024, 3(2), 110-129; https://doi.org/10.3390/grasses3020008 - 29 May 2024
Viewed by 1033
Abstract
Arid and semi-arid areas are highly productive ecosystems that have a great diversity of species, among which grasses stand out. These species have ecological, environmental, and economic importance. The objective was to identify the ecological descriptors of 15 native species of grasses and [...] Read more.
Arid and semi-arid areas are highly productive ecosystems that have a great diversity of species, among which grasses stand out. These species have ecological, environmental, and economic importance. The objective was to identify the ecological descriptors of 15 native species of grasses and diversity patterns through multivariate analysis techniques (principal component analysis, PCA, and cluster analysis, CA), in addition to identifying potential distribution areas (current and future) and regions of high and low diversity from 3841 accessions and 21 climatic variables. Among the main results, the extreme values, coefficient of variation, and median for each species could be determined. PCA determined that, with 10 variables, it was possible to explain 54.36% of the variation between the analyzed species. CA resulted in the formation of four statistically significant groups, with specific climatic characteristics. Regarding potential distribution areas and climate change, a reduction in distribution is expected (2050) on most of the current surface, with a possible opportunity zone in the north of the country. Finally, two hotspots (high diversity areas) and four coldspots (low diversity areas) were identified among the analyzed species. These results can be used to create strategies for sustainable use and the conservation of these resources. Full article
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26 pages, 11284 KiB  
Article
Using Unmanned Aerial Vehicles and Multispectral Sensors to Model Forage Yield for Grasses of Semiarid Landscapes
by Alexander Hernandez, Kevin Jensen, Steve Larson, Royce Larsen, Craig Rigby, Brittany Johnson, Claire Spickermann and Stephen Sinton
Grasses 2024, 3(2), 84-109; https://doi.org/10.3390/grasses3020007 - 17 May 2024
Cited by 2 | Viewed by 835
Abstract
Forage yield estimates provide relevant information to manage and quantify ecosystem services in grasslands. We fitted and validated prediction models of forage yield for several prominent grasses used in restoration projects in semiarid areas. We used field forage harvests from three different sites [...] Read more.
Forage yield estimates provide relevant information to manage and quantify ecosystem services in grasslands. We fitted and validated prediction models of forage yield for several prominent grasses used in restoration projects in semiarid areas. We used field forage harvests from three different sites in Northern Utah and Southern California, USA, in conjunction with multispectral, high-resolution UAV imagery. Different model structures were tested with simple models using a unique predictor, the forage volumetric 3D space, and more complex models, where RGB, red edge, and near-infrared spectral bands and associated vegetation indices were used as predictors. We found that for most dense canopy grasses, using a simple linear model structure could explain most (R2 0.7) of the variability of the response variable. This was not the case for sparse canopy grasses, where a full multispectral dataset and a non-parametric model approach (random forest) were required to obtain a maximum R2 of 0.53. We developed transparent protocols to model forage yield where, in most circumstances, acceptable results could be obtained with affordable RGB sensors and UAV platforms. This is important as users can obtain rapid estimates with inexpensive sensors for most of the grasses included in this study. Full article
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15 pages, 2910 KiB  
Review
Research Progress in the Application of Google Earth Engine for Grasslands Based on a Bibliometric Analysis
by Zinhle Mashaba-Munghemezulu, Lwandile Nduku, Cilence Munghemezulu and George Johannes Chirima
Grasses 2024, 3(2), 69-83; https://doi.org/10.3390/grasses3020006 - 26 Apr 2024
Viewed by 974
Abstract
Grasslands cover approximately 40% of the Earth’s surface. Thus, they play a pivotal role in supporting biodiversity, ecosystem services, and human livelihoods. These ecosystems provide crucial habitats for specialized plant and animal species, act as carbon sinks to mitigate climate change, and are [...] Read more.
Grasslands cover approximately 40% of the Earth’s surface. Thus, they play a pivotal role in supporting biodiversity, ecosystem services, and human livelihoods. These ecosystems provide crucial habitats for specialized plant and animal species, act as carbon sinks to mitigate climate change, and are vital for agriculture and pastoralism. However, grasslands face ongoing threats from certain factors, like land use changes, overgrazing, and climate change. Geospatial technologies have become indispensable to manage and protect these valuable ecosystems. This review focuses on the application of Google Earth Engine (GEE) in grasslands. The study presents a bibliometric analysis of research conducted between 2016–2023. Findings from the analysis reveal a significant growth in the use of GEE and different remote sensing products for grassland studies. Most authors reported grassland degradation in most countries. Additionally, China leads in research contributions, followed by the United States and Brazil. However, the analysis highlights the need for greater involvement from developing countries, particularly in Africa. Furthermore, it highlights the global distribution of research efforts, emphasizes the need for broader international participation. Full article
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24 pages, 8190 KiB  
Article
Improved Production of Marandu Palisade Grass (Brachiaria brizantha) with Mixed Gelatin Sludge Fertilization
by Eduardo André Ferreira, Joadil Gonçalves de Abreu, Wininton Mendes da Silva, Danielle Helena Müller, Dalilhia Nazaré dos Santos, Cassiano Cremon, Oscarlina Lúcia dos Santos Weber, Aaron Kinyu Hoshide, Daniel Carneiro de Abreu, Maybe Lopes Gonçalves and José Advan Pereira Pedrosa Júnior
Grasses 2024, 3(2), 45-68; https://doi.org/10.3390/grasses3020005 - 4 Apr 2024
Viewed by 1079
Abstract
Gelatin industry residues are increasingly used as fertilizer and soil conditioner. However, correct residue dosage is critical for grass development and minimizing environmental impacts. This randomized block design study determined adequate dosage of mixed gelatin sludge (MGS) for Marandu grass production in wet/dry [...] Read more.
Gelatin industry residues are increasingly used as fertilizer and soil conditioner. However, correct residue dosage is critical for grass development and minimizing environmental impacts. This randomized block design study determined adequate dosage of mixed gelatin sludge (MGS) for Marandu grass production in wet/dry seasons in Brazil. Five MGS levels (0–200% of required nitrogen) were compared to mineral fertilizer. Agronomic/productivity characteristics, bromatological composition, macro/micronutrient composition of leaves, and soil chemical attributes were evaluated. Agronomic/productivity characteristics were influenced by MGS dose in both dry/rainy seasons, except for leaf blade pseudostem ratio and percentage of leaves/pseudostem. Bromatological composition was influenced by MGS doses in dry/rainy seasons except for dry/mineral material quantities. Marandu leaf tissue chemical composition was significantly influenced by MGS dose, except for potassium, boron, and iron. Chemical composition of four soil layers between 0 and 50 cm influenced MGS dose, except for pH, organic matter, magnesium, copper, manganese, and zinc. GMS dose for Marandu production should be 200% of nitrogen requirement. MGS application increased productivity/quality of Marandu grass. Macronutrients (nitrogen, phosphorus) and micronutrients (calcium, magnesium, sulfur, copper, and zinc) increased in Marandu grass and in the soil (calcium, sulfur, and sodium). The increased sodium level was not limiting. Full article
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