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Animals
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Advanced Grazing Management: Applied Nutritional and Foraging Ecology
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Advanced Grazing Management: Applied Nutritional and Foraging Ecology

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Cattle".

Deadline for manuscript submissions: closed (5 December 2022) | Viewed by 6379

Special Issue Editors

Prof. Dr. Pablo Gregorini

E-Mail Website
Guest Editor
Faculty of Agriculture and Life Sciences, Lincoln University, P.O. Box 85084, Lincoln 7647, New Zealand
Interests: nutritional foraging ecology; grazing management; pastoral agricultural systems
Dr. Matthew Beck

E-Mail Website
Guest Editor
USDA-ARS, Livestock Nutrient Management Research Unit, 300 Simmons Drive, Unit 10, Bushland, TX 79012, USA
Interests: ruminant nutrition

Special Issue Information

Dear Colleagues,

‘Grazing’ livestock fulfil essential roles in ecology, agriculture, economies, and cultures throughout the world. Not only do livestock provide food wealth but they also deliver ecological services. ‘Grazing’ as an adjective, locates livestock within a particular spatial and temporal pastoral context in which they naturally graze or are grazed. The purpose of this Special Issue and book of Animals is to deal with both the active and passive voices of the verb ‘graze’, exploring the new dynamics of grazing management and practices. Considering ‘dynamics’ as forces and or properties that stimulate change within a system or process, new and advanced thinking, as well as an understanding of grazing on the basis of nutritional and foraging ecology, will allow for a more functional and contextual view of grazing management and the spatiotemporal dynamics and impact of pastoral livestock production on landscapes.

Prof. Dr. Pablo Gregorini
Dr. Matthew Beck
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • foraging
  • ruminants
  • ecology
  • pastoral livestock

Published Papers (3 papers)

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Research

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19 pages, 510 KiB  
Article
Dietary and Animal Strategies to Reduce the Environmental Impact of Pastoral Dairy Systems Result in Altered Nutraceutical Profiles in Milk
by Cameron Joel Marshall, Konagh Garrett, Stephan Van Vliet, Matthew Raymond Beck and Pablo Gregorini
Animals 2022, 12(21), 2994; https://0-doi-org.brum.beds.ac.uk/10.3390/ani12212994 - 31 Oct 2022
Cited by 1 | Viewed by 1815
Abstract
The objective of this study was to evaluate and provide further insights into how dairy cows genetically divergent for milk urea N breeding values [MUNBV, high (2.21 ± 0.21) vs. low (−1.16 ± 0.21); µ ± SEM], consuming either fresh cut Plantain ( [...] Read more.
The objective of this study was to evaluate and provide further insights into how dairy cows genetically divergent for milk urea N breeding values [MUNBV, high (2.21 ± 0.21) vs. low (−1.16 ± 0.21); µ ± SEM], consuming either fresh cut Plantain (Plantago lanceolata L., PL) or Ryegrass (Lolium perenne L., RG) herbage, impacted the nutraceutical profile of whole milk by investigating amino and fatty acid composition and applying metabolomic profiling techniques. Both diet and MUNBV, and their interaction term, were found to affect the relative abundance of alanine, glycine, histidine, and phenylalanine in the milk (p < 0.05), but their minor absolute differences (up to ~0.13%) would not be considered biologically relevant. Differences were also detected in the fatty acid profile based on MUNBV and diet (p < 0.05) with low MUNBV cows having a greater content of total unsaturated fatty acids (+16%) compared to high MUNBV cows and cows consuming PL having greater content of polyunsaturated fatty acids (+92%), omega 3 (+101%) and 6 (+113%) compared to RG. Differences in the metabolomic profile of the milk were also detected for both MUNBV and dietary treatments. Low MUNBV cows were found to have greater abundances of choline phosphate, phosphorylethanolamine, N-acetylglucosamine 1-phosphate, and 2-dimethylaminoethanol (p < 0.05). High MUNBV cows had a greater abundance of methionine sulfoxide, malate, 1,5-anhydroglucitol (1,5-AG), glycerate, arabitol/xylitol, 3-hydroxy-3-methylglutarate, 5-hydroxylysine and cystine (p < 0.05). Large differences (p < 0.05) were also detected as a result of diet with PL diets having greater abundances of the phytochemicals 4-acetylcatechol sulfate, 4-methylcatechol sulfate, and p-cresol glucuronide whilst RG diets had greater abundances of 2,6-dihydroxybenzoic acid, 2-acetamidophenol sulfate, and 2-hydroxyhippurate. The results of this study indicate the potential to alter the nutraceutical value of milk from dietary and genetic strategies that have been previously demonstrated to reduce environmental impact. Full article
(This article belongs to the Special Issue Advanced Grazing Management: Applied Nutritional and Foraging Ecology)
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Review

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29 pages, 1163 KiB  
Review
Creating a Design Framework to Diagnose and Enhance Grassland Health under Pastoral Livestock Production Systems
by Fabiellen C. Pereira, Carol M. S. Smith, Stuart M. Charters and Pablo Gregorini
Animals 2022, 12(23), 3306; https://0-doi-org.brum.beds.ac.uk/10.3390/ani12233306 - 26 Nov 2022
Cited by 2 | Viewed by 2381
Abstract
Grasslands and ecosystem services are under threat due to common practices adopted by modern livestock farming systems. Design theory has been an alternative to promote changes and develop more sustainable strategies that allow pastoral livestock production systems to evolve continually within grasslands by [...] Read more.
Grasslands and ecosystem services are under threat due to common practices adopted by modern livestock farming systems. Design theory has been an alternative to promote changes and develop more sustainable strategies that allow pastoral livestock production systems to evolve continually within grasslands by enhancing their health and enabling the continuous delivery of multiple ecosystem services. To create a design framework to design alternative and more sustainable pastoral livestock production systems, a better comprehension of grassland complexity and dynamism for a diagnostic assessment of its health is needed, from which the systems thinking theory could be an important approach. By using systems thinking theory, the key components of grasslands—soil, plant, ruminant—can be reviewed and better understood from a holistic perspective. The description of soil, plant and ruminant individually is already complex itself, so understanding these components, their interactions, their response to grazing management and herbivory and how they contribute to grassland health under different climatic and topographic conditions is paramount to designing more sustainable pastoral livestock production systems. Therefore, by taking a systems thinking approach, we aim to review the literature to better understand the role of soil, plant, and ruminant on grassland health to build a design framework to diagnose and enhance grassland health under pastoral livestock production systems. Full article
(This article belongs to the Special Issue Advanced Grazing Management: Applied Nutritional and Foraging Ecology)
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Other

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16 pages, 787 KiB  
Systematic Review
Meta-Regression to Develop Predictive Equations for Urinary Nitrogen Excretion of Lactating Dairy Cows
by Matthew Beck, Cameron Marshall, Konagh Garrett, Terra Campbell, Andrew Foote, Ronaldo Vibart, David Pacheco and Pablo Gregorini
Animals 2023, 13(4), 620; https://0-doi-org.brum.beds.ac.uk/10.3390/ani13040620 - 10 Feb 2023
Cited by 1 | Viewed by 1506
Abstract
Dairy cows’ urinary nitrogen (N) excretion (UN; g/d) represents a significant environmental concern due to their contribution to nitrate leaching, nitrous oxide (a potent greenhouse gas), and ammonia emissions (contributor to N deposition). The first objective of the current study was to determine [...] Read more.
Dairy cows’ urinary nitrogen (N) excretion (UN; g/d) represents a significant environmental concern due to their contribution to nitrate leaching, nitrous oxide (a potent greenhouse gas), and ammonia emissions (contributor to N deposition). The first objective of the current study was to determine the adequacy of existing models to predict UN from total mixed ration (TMR)-fed and fresh forage (FF)-fed cows. Next, we aimed to develop equations to predict UN based on animal factors [milk urea nitrogen (MUN; mg/dL) and body weight (BW, kg)] and to explore how these equations are improved when dietary factors, such as diet type, dry matter intake (DMI), or dietary characteristics [neutral detergent fiber (NDF) and crude protein (CP) content], are considered. A dataset was obtained from 51 published experiments composed of 174 treatment means. The whole dataset was used to evaluate the mean and linear biases of three existing equations including diet type as an interaction term; all models had significant linear and mean biases and two of the three models had poor predictive capabilities as indicated by their large relative prediction error (RPE; root mean square error of prediction as a percent of the observed mean). Next, the complete data set was split into training and test sets, which were used to develop and to evaluate new models, respectively. The first model included MUN and BW, and there was a significant interaction between diet type and the coefficients. This model had the worst 1:1 agreement [Lin’s concordance correlation coefficient (CCC) = 0.50] and largest RPE (24.7%). Models that included both animal and dietary factors performed the best, and when included in the model, the effect of diet type was no longer significant (p > 0.10). These models all had very good agreement (CCC ≥ 0.86) and relatively low RPE (≤13.1%). This meta-analysis developed precise and accurate equations to predict UN from dairy cows in both confined and pasture-based systems. Full article
(This article belongs to the Special Issue Advanced Grazing Management: Applied Nutritional and Foraging Ecology)
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