Modelling above-ground herbage mass for a wide range of grassland community types

Duru, Michel; Adam, Myriam; Cruz, Pablo; Martin, Guillaume; Ansquer, Pauline; Ducourtieux, C.; Jouany, Claire; Theau, Jean-Pierre; Viégas, Julio

doi:10.1016/j.ecolmodel.2008.09.015

Cited by 63 publications

(49 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another good example of how the functional trait approach allows us to model the growth of mixed swards is given by Duru et al (2009). They aggregated sets of plant functional traits to plant functional types and simulated production of grassland vegetation consisting of different percentage contributions of these types.…”

Section: From Empirical To Predictive Approachmentioning

confidence: 99%

Grass strategies and grassland community responses to environmental drivers: a review

Pontes

Maire

Schellberg

et al. 2015

Agron. Sustain. Dev.

View full text Add to dashboard Cite

Grassland covers about one quarter of the Earth's land area and is currently estimated to contribute to the livelihoods of over 800 million people. Grassland provides ecosystem goods and services, mainly through the provisioning of milk and meat. Therefore, the proper use of grasslands will be essential for feeding the nine billion people that will inhabit planet Earth by 2050. In the context of a changing climate, we should better understand the interactions of environment, management and grass crop at individual, community and ecosystem levels. Functional ecology focuses on the roles and functions that species play in the community or ecosystem in which they occur. Functional ecology thus aims to understand how plant species adapt to environmental conditions and how management can alter this adaptation. Here, we review the latest advances in plant functional traits research and on species strategies to the main environmental factors occurring in grassland ecosystems: nutrient availability, grazing, cutting and shading. Functional ecology also provides a framework to better understand how species strategies interact with the species composition at the community level. Therefore, the literature on community assembling theories in relation to ecosystem processes most relevant to grassland management and services is also reviewed. Finally, future research questions and some new orientations for grassland experts are offered in order to meet the challenge of maintaining productivity and preservation of these semi-natural environments in the face of global change.

show abstract

Section: From Empirical To Predictive Approachmentioning

confidence: 99%

Grass strategies and grassland community responses to environmental drivers: a review

Pontes

Maire

Schellberg

et al. 2015

Agron. Sustain. Dev.

View full text Add to dashboard Cite

show abstract

“…Over the years, scientists have proposed tools such as crop models to simulate the crop behaviour under various environmental conditions (Brisson et al, 1998;Duru et al, 2009;Schapendonk et al, 1998). A lot of models were thus proposed in literature ranging from complex approaches simulating growth for different crops such as CERES (Jones et al, 2003), WOFOST (Pogacar and Kajfez-Bogataj, 2009), STICS (Brisson et al, 2003) up to whole farm optimization models such as GRAZEGRO (Barrett et al, 2005), MOD-ERATO (Bergez et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region

Courault

Hadria²,

Ruget³

et al. 2010

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The aim of this study is to propose methods to improve crop and water management in Mediterranean regions. At landscape scale, there is a spatial variability of agricultural practices, particularly for grasslands irrigated by flooding. These grasslands are harvested three times per year and produce high quality hay, but their productions decreased significantly during the last few years because of the water scarcity. It is therefore important to assess the real water requirement for crops in order to predict productions in the case of agricultural practice modifications. Until now, the spatial variability of agricultural practices was obtained through surveys from farmers, but this method was tedious to describe an entire region. Thus, the specific aim of the study is to develop and assess a new method based on a crop model for estimating water balance and crop yield constrained by products derived from optical remote sensing data with high spatio-temporal resolution.A methodology, based on the combined use of FORMOSAT-2 images and the STICS crop model, was developed to estimate production, evapotranspiration and drainage of irrigated grasslands in "the Crau" region in the South Eastern France. Numerous surveys and ground measurements were performed during an experiment conducted in 2006. Simple algorithms were developed to retrieve the dynamic of Leaf Area Index (LAI) for each plot and the main agricultural practices such as mowing and irrigation dates. These variables computed from remote sensing were then used to parameterize STICS, applied at region scale to estimate the spatial variability of water budget associated with the biomass productions. Results are displayed at the farm Correspondence to: D. Courault (courault@avignon.inra.fr) scale. Satisfactory results were obtained when compared to ground measurements. The method for the extrapolation to other regions or crops is discussed as regard to data available.

show abstract

“…The first tactic puts the positive step-change slopes E's from the three factors into the geometric sequence (1) and, thus, it resembles the simple exponential growth model described in Thornley and Johnson (2000). For reproduction and senescence many detailed models of vegetation dynamics use a balancing of basic growth and defoliation rates (Levis et al, 2004;Duru et al, 2009;Wang et al, 2009). This balancing involves growing degree-days to determine both rates (e.g., both growth rate and defoliation are driven by thermal time).…”

Section: Model Trainingmentioning

confidence: 99%

“…In parallel with the retrospective (diagnostic) studies, prognostic phenological modeling has also been developing (Kathuroju et al, 2007;Myneni et al, 2007;Stöckli et al, 2008a;Duru et al, 2009;Gurung et al, 2009;Knorr et al, 2010). Practical phenological models have seen significant…”

Section: Introductionmentioning

confidence: 99%

“…It follows from (3) that the EDPM takes events as signals for change, uses intensities to scale the change, and relies on sensitivities to direct the impacts of events depending on the vegetation type and phenophase. This approach is similar to the use of indices in plant modeling (e.g., Duru et al, 2009) to simplify impacts from changes in nutrient availability and other environmental factors.…”

mentioning

confidence: 99%

See 1 more Smart Citation

A new concept for simulation of vegetated land surface dynamics – Part 1: The event driven phenology model

Kovalskyy

Henebry

2012

Biogeosciences

View full text Add to dashboard Cite

Abstract. Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameriflux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE <0.08; r 2 > 0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons.

show abstract

Modelling above-ground herbage mass for a wide range of grassland community types

Cited by 63 publications

References 53 publications

Grass strategies and grassland community responses to environmental drivers: a review

Grass strategies and grassland community responses to environmental drivers: a review

Combined use of FORMOSAT-2 images with a crop model for biomass and water monitoring of permanent grassland in Mediterranean region

A new concept for simulation of vegetated land surface dynamics – Part 1: The event driven phenology model

Contact Info

Product

Resources

About