Modelling grass yields in northern climates – a comparison of three growth models for timothy

Korhonen, Panu; Palosuo, Taru; Persson, Tomas; Höglind, Mats; Jégo, Guillaume; Oijen, Marcel van; Gustavsson, Anne‐Maj; Bélanger, Gilles; Virkajärvi, Perttu

doi:10.1016/j.fcr.2018.04.014

Cited by 26 publications

(30 citation statements)

References 33 publications

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“…Previous studies showed different responses in gross primary production (Sándor et al, 2016), biomass (Hurtado-Uria et al, 2013;Sándor et al, 2017;Ehrhardt et al, 2018) and N2O emissions (Ehrhardt et al, 2018) for different grassland models when compared under various environmental conditions. As for timothy, Korhonen et al (2018) compared three models for their ability to predict DM yield in Northern Europe and Canada. However, to our knowledge, there are no other published comparisons of the ability of forage grass models to predict nutritive value.…”

Section: Introductionmentioning

confidence: 99%

Simulation of timothy nutritive value: A comparison of three process-based models

Persson

Höglind

Oijen

et al. 2019

Field Crops Research

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Different forage grass models are used to simulate forage yield and nutritive attributes, but these models are seldom compared, particularly those for timothy (Phleum pratense L.), a widely grown forage grass species in agricultural regions with a cold temperate climate. We compared the models BASGRA, CATIMO and STICS for their predictions of timothy crude protein (CP) concentration, neutral detergent fibre (NDF) concentration and NDF digestibility (dNDF), three important forage nutritive attributes. Data on CP and NDF concentrations, and dNDF and the associated weather and soil data for seven cultivars, taken from eight field experiments in Canada, Finland, Norway, and Sweden, were divided into calibration and validation datasets. Model parameters were estimated for each cultivar separately (cultivarspecific calibration) and for all cultivars together (generic calibration), using different methods for the three models. Normalized root mean square error (RMSE) in prediction of CP concentration varied between 16 and 26 % for BASGRA, 45 and 101 % for CATIMO and 27 and 45 % for STICS across the two calibration methods and the calibration and validation datasets. Normalised RMSE in prediction of NDF concentration varied between 8 and 13 % for BASGRA, 14 and 21 % for CATIMO and 8 and 12 % for STICS, while for dNDF it varied between 7 and 22 % for BASGRA, 7 and 38 % for CATIMO and 5 and 6 % for STICS. Cultivar-specific calibration improved the performance of CATIMO and STICS, but not BASGRA, compared with generic calibration. The prediction accuracy for NDF concentration and dNDF with the three models was within the same range or better than that for forage dry matter (DM) yield of timothy. Overall, the three models performed well in predicting some nutritive attributes and yield in Northern Europe and Canada, but improvements are required, particularly to increase the prediction accuracy of CP concentration.

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Section: Introductionmentioning

confidence: 99%

Simulation of timothy nutritive value: A comparison of three process-based models

Persson

Höglind

Oijen

et al. 2019

Field Crops Research

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“…However, the impact of diseases is not yet incorporated into the BASGRA model (Höglind et al 2016). The Korhonen et al (2018) study with BASGRA, Canadian timothy model CATIMO and the soil crop model STIC for timothy included results from Rovaniemi in 1999-2001 for a trial with fertilizer rates and harvesting schedule treatments, and the studied growth models gave rather similar yield predictions as the observed results. Winter damage in that trial was small ranging from 7% to 20% (Nissinen et al 2010).…”

Section: Performance Of Timothy Meadow Fescue and Tall Fescuementioning

confidence: 98%

Increase in perennial forage yields driven by climate change, at Apukka Research Station, Rovaniemi, 1980-2017

Niemeläinen

Hannukkala

Jauhiainen

et al. 2020

AFSci

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The official variety trials at Rovaniemi, Finland (66.58°N, 26.01°E) in 1980–2017 show a substantial increase in dry matter yields (DMY) of timothy (Phleum pratense), meadow fescue (Festuca pratensis) and tall fescue (Festuca arundinacea), coinciding with a 156 °Cd increase in the average growing season Tsum and a 461 °Cd decrease in the average winter frost sum for the same period. The annual DMY of timothy was 3128, 4668, 8385 and 9352 kg ha-1 in the periods (P) 1980–1989 (P1), 1990–1999 (P2), 2000–2009 (P3), and 2010–2017 (P4). The first cut yielded 1792, 2166, 4008 and 4473, and the second cut 1337, 2503, 4378 and 4879 kg ha-1, respectively. Yields of meadow fescue followed a similar pattern. The first cut was about ten days and the second cut about one week earlier on P4 than on P1. Shorter snow cover period, milder winters, higher live ground cover of timothy in spring, and higher temperature sum during the growing season were most likely responsible for the yield increase. The results indicate a strong impact of climate change on DMY of perennial forage crops in the north.

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“…All this means that most BGMs can simulate feedbacks from resource-limitation but not the dynamics of biodiversity and its impacts on ecosystem functioning. For example, there are now multiple grassland BGMs that can simulate the impact of nitrogen availability on grassland production and quality in monocultures [80][81][82], but that capacity has not yet been demonstrated for mixtures.…”

Section: Biogeochemistry Models (Bgms)mentioning

confidence: 99%

Incorporating Biodiversity into Biogeochemistry Models to Improve Prediction of Ecosystem Services in Temperate Grasslands: Review and Roadmap

et al. 2020

Self Cite

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Multi-species grasslands are reservoirs of biodiversity and provide multiple ecosystem services, including fodder production and carbon sequestration. The provision of these services depends on the control exerted on the biogeochemistry and plant diversity of the system by the interplay of biotic and abiotic factors, e.g., grazing or mowing intensity. Biogeochemical models incorporate a mechanistic view of the functioning of grasslands and provide a sound basis for studying the underlying processes. However, in these models, the simulation of biogeochemical cycles is generally not coupled to simulation of plant species dynamics, which leads to considerable uncertainty about the quality of predictions. Ecological models, on the other hand, do account for biodiversity with approaches adopted from plant demography, but without linking the dynamics of plant species to the biogeochemical processes occurring at the community level, and this hampers the models’ capacity to assess resilience against abiotic stresses such as drought and nutrient limitation. While setting out the state-of-the-art developments of biogeochemical and ecological modelling, we explore and highlight the role of plant diversity in the regulation of the ecosystem processes underlying the ecosystems services provided by multi-species grasslands. An extensive literature and model survey was carried out with an emphasis on technically advanced models reconciling biogeochemistry and biodiversity, which are readily applicable to managed grasslands in temperate latitudes. We propose a roadmap of promising developments in modelling.

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Modelling grass yields in northern climates – a comparison of three growth models for timothy

Cited by 26 publications

References 33 publications

Simulation of timothy nutritive value: A comparison of three process-based models

Simulation of timothy nutritive value: A comparison of three process-based models

Increase in perennial forage yields driven by climate change, at Apukka Research Station, Rovaniemi, 1980-2017

Incorporating Biodiversity into Biogeochemistry Models to Improve Prediction of Ecosystem Services in Temperate Grasslands: Review and Roadmap

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