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Climate Factors Contribute to Grassland Net Primary Productivity

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A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Grassland and Pasture Science".

Deadline for manuscript submissions: closed (20 February 2021) | Viewed by 17293

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Special Issue Editors

Dr. Goetz M. Richter

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Guest Editor

Rothamsted Res, Dept Sustainable Soils & Grassland Syst, Harpenden AL5 2JQ, Herts, UK
Interests: acoustics; environment; climate change; soil; remote sensing; geographic information system; environmental science; soil science; meteorology; drought; soil physics

Dr. Kairsty Topp

E-Mail Website
Guest Editor

Scotland's Rural College
Interests: agricultural and biological sciences; modelling tools to compare the sustainability of different farming systems; resilience of farming systems

Special Issue Information

Dear colleagues,

Grasslands represent the main agricultural land resource for animal feed and food for humankind. Climate scenarios for the future will exacerbate climatic pressure on net primary productivity (NPP), forecasting more areas turning too dry or too wet for production more frequently. Often, there is no alternative to grassland due to climatic conditions and soil hydrology.

This Special Issue is dedicated to the sustainable management of this agro-ecosystem, which is under increasing human and environmental pressure. Located between desert and forest, turned into arable or urban land, the value of this resource needs reassessment in the context of all ecosystem services and Sustainable Development Goals.

Considering the potential contribution to climate change of intensive grazing systems, NPP will affect the lockup of carbon in the soil, especially when re-introduced into arable rotation. We envision a series of articles dedicated to the challenges and opportunities that come with climate change, illustrating direct and indirect effects of the (pedo-)climatic factors on grassland NPP across scales.

We wish authors to cover the NPP-governing processes at the plant–soil interface, plant community, and farm to landscape level, proposing the following broader topics (tentative titles are a suggestion only):

Plant and sward development—just a matter of temperature driven acceleration?
Heat and drought stress—new insights into adaptation and breeding of grassland species;
Breeding grasses and managing grass swards in the silvopastoral flood plains;
Soil health—achieving a good balance of biophysical and geochemical processes in grassland;
New modelling approaches to capture the dynamics of genotype x environment x management interaction;
Knowledge transfer/exchange and Decision Support Tools—enabling the land manager.

Dr. Goetz M. Richter
Dr. Kairsty Topp
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. Agronomy is an international peer-reviewed open access monthly 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 2600 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

Physiology of grass growth
Grazing strategy
Soil health
Extreme events
Impact and adaptation
Climate change mitigation
Modelling and decision support tools
Remote sensing
Earth observation

Published Papers (6 papers)

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Editorial

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2 pages, 159 KiB

Open AccessEditorial

Climate Factors Contribute to Grassland Net Primary Productivity

by Goetz M. Richter and Cairistiona F. E. Topp

Agronomy 2021, 11(6), 1076; https://doi.org/10.3390/agronomy11061076 - 26 May 2021

Viewed by 1798

Abstract

Our call set out to enlarge the evidence base and methods for improving and evaluating grasslands in a changing environment as a sustainable ecosystem for all life [...] Full article

(This article belongs to the Special Issue Climate Factors Contribute to Grassland Net Primary Productivity)

Research

Jump to: Editorial

14 pages, 5281 KiB

Open AccessArticle

The Use of Thermal Time to Describe and Predict the Growth and Nutritive Value of Lolium perenne L. and Bromus valdivianus Phil

by Iván Calvache, Oscar Balocchi, Rodrigo Arias and Máximo Alonso

Agronomy 2021, 11(4), 774; https://doi.org/10.3390/agronomy11040774 - 15 Apr 2021

Cited by 5 | Viewed by 3295

Abstract

The thermal time, expressed in accumulated growing degree-days (AGDD), was used as a predictor to describe and simulate the independent growth of two pasture crops, Lolium perenne L. and Bromus valdivianus Phil. Two sinusoidal models (four-parameter Logistic and Gompertz) were applied to the growth variables (total leaf blade length per tiller—LBL, and accumulated herbage mass—AHM). The nutritive value of pastures was predicted and modeled using regression equations (linear and quadratic), depending on each nutrient. Data for modeling were collected from a two-year study, in which LBL, AHM, and nutritive value variables for L. perenne and B. valdivianus pastures were measured at three-day intervals. Defoliation was determined according to the AGDD, such that the swards were defoliated at 90, 180, 270, 360, and 450 AGDD. The Logistic and Gompertz models presented similar values for the growth rate (GR) parameters, superior asymptote (A_sup), inferior asymptote (A_inf), and point of maximum growth (P_max). In both species, the maximum growth was 260 AGDD. The GR was similar for both species in different seasons of the year, but the maximum AHM varied, with B. valdivianus presenting a higher value (+1500 kg DM ha⁻¹) than L. perenne during the spring. The regressions accurately described the nutritive value, demonstrating a positive linear relationship between the AGDD and concentrations of neutral and acid detergent fiber (NDF, ADF), an inverse linear relationship with crude protein (CP), and a quadratic relationship with metabolizable energy (ME) and water-soluble carbohydrate (WSC) concentration. Full article

(This article belongs to the Special Issue Climate Factors Contribute to Grassland Net Primary Productivity)

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15 pages, 3037 KiB

Open AccessArticle

Annual Net Primary Productivity of Different Functional Groups as Affected by Different Intensities of Rainfall Reduction in the Semiarid Grasslands of the Gauteng Province in South Africa

by Thabo Patrick Magandana, Abubeker Hassen and Eyob H. Tesfamariam

Agronomy 2021, 11(4), 730; https://doi.org/10.3390/agronomy11040730 - 9 Apr 2021

Cited by 2 | Viewed by 2183

Abstract

Rainfall variability is expected to change the soil water regime thereby impacting negatively on rangeland species composition, productivity and ecosystem services. The aim of this study was to assess the impact of different intensities of rainfall reduction (RR) on vegetation annual net primary productivity (ANPP). Twenty 7 × 7 m experimental plots with different intensities of RR structures consisting of transparent acrylic bands were built on a natural grassland. The interspaces between acrylic bands varied in size to intercept different intensities of ambient rainfall (0, 15, 30 and 60%) as RR treatments, with each RR treatment replicated five times in a complete randomised block design. A fixed 1 m² quadrat was marked at the centre of each plot and the ANPP within the quadrats was determined by harvesting the quadrant at the end of the growing season. Generally, as compared to the control (ambient rainfall intensity) the overall grass ANPP (P > 0.05) showed resilience to lower and moderate intensities of (15 and 30%) RR, but at a severe intensity of RR (60%) the ANPP was significantly reduced. Compared to the control the percentage contribution of grasses towards the overall ANPP increased at a lower intensity of RR (15%). In contrast, the percentage contribution of forbs towards the overall ANPP significantly reduced at lower intensity of RR. Within the grass species, however, those grasses that decrease when the veld is undergrazed or overgrazed (decreaser grass species) showed resilience at lower intensity (15 and 30%) of RR, while at a severe intensity of RR the ANPP of decreaser grasses were significantly reduced (1841 vs. 220 kg DM/ha). Those grasses that increase with undergrazing or overgrazing (increaser I or increaser II grass species) recorded a higher ANPP at moderate intensity of RR (30% RR) than at a higher intensity of RR, while the difference between 60% RR and 0% RR in terms of increaser grasses ANPP were not significant (P > 0.05) (650 kg DM/ha). Up to 88% reduction in ANPP were recorded for decreaser grass species at severe intensity of RR as compared to the control the corresponding reduction in ANPP noted for increaser grasses were relatively less (up to 56% reduction in ANPP at 60% RR vs. 0% RR). Generally, the overall ANPP yield of the semiarid grassland in Gauteng province showed resilience to a low intensity of RR (15% RR) and moderate intensity of RR (30% RR) partly due to a shift in the species composition of grasses from decreasers to increasers ecological groups, as well as due to a decrease and an increased contribution of forb functional groups at a lower and moderate intensity of RR, respectively. Full article

(This article belongs to the Special Issue Climate Factors Contribute to Grassland Net Primary Productivity)

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21 pages, 1713 KiB

Open AccessArticle

Modelling the Interactions of Soils, Climate, and Management for Grass Production in England and Wales

by Michail L. Giannitsopoulos, Paul J. Burgess, Goetz M. Richter, Matt J. Bell, Cairistiona F. E. Topp, Julie Ingram and Taro Takahashi

Agronomy 2021, 11(4), 677; https://doi.org/10.3390/agronomy11040677 - 2 Apr 2021

Cited by 5 | Viewed by 2612

Abstract

This study examines the effectiveness of a model called LINGRA-N-Plus to simulate the interaction of climate, soil and management on the green leaf and total dry matter yields of ryegrass in England and Wales. The LINGRA-N-Plus model includes modifications of the LINGRA-N model such as temperature- and moisture-dependent soil nitrogen mineralization and differential partitioning to leaves and stems with thermal time from the last harvest. The resulting model was calibrated against the green leaf and total grass yields from a harvest interval x nitrogen application experiment described by Wilman et al. (1976). When the LINGRA-N-Plus model was validated against total grass yields from nitrogen experiments at ten sites described by Morrison et al. (1980), its modelling efficiency improved greatly compared to the original LINGRA-N. High predicted yields, at zero nitrogen application, were related to soils with a high initial nitrogen content. The lowest predicted yields occurred at sites with low rainfall and shallow rooting depth; mitigating the effect of drought at such sites increased yields by up to 4 t ha⁻¹. The results highlight the usefulness of grass models, such as LINGRA-N-Plus, to explore the combined effects of climate, soil, and management, like nitrogen application, and harvest intervals on grass productivity. Full article

(This article belongs to the Special Issue Climate Factors Contribute to Grassland Net Primary Productivity)

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19 pages, 5559 KiB

Open AccessArticle

Analyzing NPP Response of Different Rangeland Types to Climatic Parameters over Mongolia

by Lkhagvadorj Nanzad, Jiahua Zhang, Gantsetseg Batdelger, Til Prasad Pangali Sharma, Upama Ashish Koju, Jingwen Wang and Mohsen Nabil

Agronomy 2021, 11(4), 647; https://doi.org/10.3390/agronomy11040647 - 27 Mar 2021

Cited by 9 | Viewed by 3484

Abstract

Global warming threatens ecosystem functions, biodiversity, and rangeland productivity in Mongolia. The study analyzes the spatial and temporal distributions of the Net Primary Production (NPP) and its response to climatic parameters. The study also highlights how various land cover types respond to climatic fluctuations from 2003 to 2018. The Boreal Ecosystem Productivity Simulator (BEPS) model was used to simulate the rangeland NPP of the last 16 years. Satellite remote sensing data products were mainly used as input for the model, where ground-based and MODIS NPP were used to validate the model result. The results indicated that the BEPS model was moderately effective (R² = 0.59, the Root Mean Square Error (RMSE) = 13.22 g C m⁻²) to estimate NPP for Mongolian rangelands (e.g., grassland and sparse vegetation). The validation results also showed good agreement between the BEPS and MODIS estimates for all vegetation types, including forest, shrubland, and wetland (R² = 0.65). The annual total NPP of Mongolia showed a slight increment with an annual increase of 0.0007 Pg (0.68 g C per meter square) from 2003 to 2018 (p = 0.82) due to the changes in climatic parameters and land cover change. Likewise, high increments per unit area found in forest NPP, while decreased NPP trend was observed in the shrubland. In conclusion, among the three climatic parameters, temperature was the factor with the largest influence on NPP variations (r = 0.917) followed precipitation (r = 0.825), and net radiation (r = 0.787). Forest and wetland NPP had a low response to precipitation, while inter-annual NPP variation shows grassland, shrubland, and sparse vegetation were highly sensitive rangeland types to climate fluctuations. Full article

(This article belongs to the Special Issue Climate Factors Contribute to Grassland Net Primary Productivity)

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13 pages, 1003 KiB

Open AccessArticle

Thermal Time as a Parameter to Determine Optimal Defoliation Frequency of Perennial Ryegrass (Lolium perenne L.) and Pasture Brome (Bromus valdivianus Phil.)

by Iván Calvache, Oscar Balocchi, Máximo Alonso, Juan Pablo Keim and Ignacio F. López

Agronomy 2020, 10(5), 620; https://doi.org/10.3390/agronomy10050620 - 27 Apr 2020

Cited by 13 | Viewed by 3204

Abstract

The herbage mass and nutritional value of harvested forage are fundamental determinants of the production potential of pastoral systems. The objective of this study was to evaluate the growth dynamics and accumulated herbage mass expressed in dry matter (DM) of perennial ryegrass (Lolium perenne L.) and pasture brome (Bromus valdivianus Phil.) pastures, using thermal time (TT) as a defoliation criterion. Thirty plots (15 of L. perenne and 15 of B. valdivianus) were distributed in three field blocks and subjected to five defoliation frequencies (DF) determined by TT, expressed as the accumulated growing degree-days (AGDD; DF1 = 90, DF2 = 180, DF3 = 270, DF4 = 360, and DF5 = 450 AGDD) for one year (2016), at the Austral Agricultural Experimental Station of the Universidad Austral de Chile. Every three days, the total leaf length (TLL) was measured, and the leaf elongation rate (LER, cm L⁻¹), leaf growth rate (LGR, cm L⁻¹), leaf appearance rate (LAR, d L⁻¹), phyllochron (AGDD L−1), and accumulated herbage mass per hectare (kg DM ha⁻¹) were calculated. Defoliations were scheduled according to AGDD, and a sample was taken from each cutting to determine (dry matter ‘DM’, crude protein ‘CP’, neutral detergent fiber ‘NDF’, acid detergent fiber ‘ADF’, water-soluble carbohydrates ‘WSC’ and metabolizable energy ‘ME’). The pastures that were allocated to DF5 presented higher DM yields (12,600 kg DM ha⁻¹ year⁻¹), TLL (54.6 cm), and LER (0.63 cm d⁻¹) compared to pastures with high DF (90 and 180 ADGG). B. valdivianus presented a lower phyllochron than L. perenne (74.4 vs 87.9 AGDD L⁻¹, respectively). Concentrations of CP and ME decreased from the shortest DF (90 AGDD) to the largest DF (450 AGDD), dropping from 221 to 138 g kg⁻¹ CP and from 2.6 to 2.4 Mcal kg⁻¹ DM of ME. All variables were affected by the season (Ssn) (p < 0.001). The AGDD can be used as a defoliation criterion and a tool to balance yield with nutritive value according to the farmer’s needs. Full article

(This article belongs to the Special Issue Climate Factors Contribute to Grassland Net Primary Productivity)

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