Records |
Author |
Fan, F.; Henriksen, C.B.; Porter, J. |
Title |
Relationship between stoichiometry and ecosystem services: A case study of it organic farming systems |
Type |
Journal Article |
Year |
2018 |
Publication |
Ecological Indicators |
Abbreviated Journal |
Ecological Indicators |
Volume |
85 |
Issue |
|
Pages |
400-408 |
Keywords |
Ecosystem services; Organic farming; Stoichiometry; Field practices; Soil Carbon Storage; Ecological Stoichiometry; Agricultural Management; Earthworm Populations; Nitrogen-Fixation; Cropping Systems; New-Zealand; Quantification; Valuation; Matter |
Abstract |
Over the past five decades, the delivery of global Ecosystem Services (ES) has diminished and this has been driven partly by anthropogenic activities. Agro-ecosystems cover almost 40% of the terrestrial surface on Earth, and have been considered as one of the most significant ecological experiments with a potential to both contribute to and mitigate global ES loss. In the present study, six different ES (food and fodder production, carbon sequestration, biological pest control, soil water storage, nitrogen regulation and soil formation) were quantified in various organic farming systems and the hypothesis that there is a link between these ES and C:N, C:O and H:O stoichiometric ratios in farming systems was experimentally tested. The results show that different ES are correlated with the stoichiometric ratios to different extents. There are significant positive linear correlations between C:N stoichiometric ratios and all measured ES in the investigated organic farming systems, while not all the ES are correlated with the C:O and H:O ratios. This study has expanded the horizons of stoichiometry by linking a fundamental chemical property of molecules with an emergent property of organic farming systems, namely their ecosystem service provision. |
Address |
2018-06-07 |
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Language |
English |
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Original Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1470-160x |
ISBN |
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Conference |
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Notes |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
5201 |
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Author |
Müller, C. |
Title |
African lessons on climate change risks for agriculture |
Type |
Journal Article |
Year |
2013 |
Publication |
Annual Review of Nutrition |
Abbreviated Journal |
Ann. Rev. Nutr. |
Volume |
33 |
Issue |
1 |
Pages |
395-411 |
Keywords |
Africa/epidemiology; *Climate Change/economics; Crops, Agricultural/economics/*growth & development; Diet/adverse effects/economics; Forecasting; *Global Health/economics/trends; Humans; Malnutrition/economics/epidemiology/prevention & control; *Models, Theoretical; Risk; Soil/chemistry; Water Resources/economics |
Abstract |
Climate change impact assessments on agriculture are subject to large uncertainties, as demonstrated in the present review of recent studies for Africa. There are multiple reasons for differences in projections, including uncertainties in greenhouse gas emissions and patterns of climate change; assumptions on future management, aggregation, and spatial extent; and methodological differences. Still, all projections agree that climate change poses a significant risk to African agriculture. Most projections also see the possibility of increasing agricultural production under climate change, especially if suitable adaptation measures are assumed. Climate change is not the only projected pressure on African agriculture, which struggles to meet demand today and may need to feed an additional one billion individuals by 2050. Development strategies are urgently needed, but they will need to consider future climate change and its inherent uncertainties. Science needs to show how existing synergies between climate change adaptation and development can be exploited. |
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English |
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Edition |
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ISSN |
0199-9885 1545-4312 |
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Article |
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Notes |
CropM |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4496 |
Permanent link to this record |
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Author |
Moriondo, M.; Ferrise, R.; Trombi, G.; Brilli, L.; Dibari, C.; Bindi, M. |
Title |
Modelling olive trees and grapevines in a changing climate |
Type |
Journal Article |
Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
Volume |
72 |
Issue |
|
Pages |
387-401 |
Keywords |
tree crops; climate change; simulation models; crop yield; vitis-vinifera l.; air co2 enrichment; soil-water content; elevated co2; mediterranean basin; cropping systems; growth; yield; carbon; simulation |
Abstract |
The models developed for simulating olive tree and grapevine yields were reviewed by focussing on the major limitations of these models for their application in a changing climate. Empirical models, which exploit the statistical relationship between climate and yield, and process based models, where crop behaviour is defined by a range of relationships describing the main plant processes, were considered. The results highlighted that the application of empirical models to future climatic conditions (i.e. future climate scenarios) is unreliable since important statistical approaches and predictors are still lacking. While process-based models have the potential for application in climate-change impact assessments, our analysis demonstrated how the simulation of many processes affected by warmer and CO2-enriched conditions may give rise to important biases. Conversely, some crop model improvements could be applied at this stage since specific sub-models accounting for the effect of elevated temperatures and CO2 concentration were already developed. (C) 2014 Elsevier Ltd. All rights reserved. |
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ISSN |
1364-8152 |
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Article |
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Notes |
CropM, ftnotmacsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4691 |
Permanent link to this record |
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Author |
Dumont, B.; Vancutsem, F.; Seutin, B.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
Title |
Simulation de la croissance du blé à l’aide de modèles écophysiologiques: Synthèse bibliographique des méthodes, potentialités et limitations |
Type |
Journal Article |
Year |
2012 |
Publication |
Biotechnologie, Agronomie, Société et Environnement |
Abbreviated Journal |
Biotechnologie, Agronomie, Société et Environnement |
Volume |
163 |
Issue |
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Pages |
376-386 |
Keywords |
crops; growth; soil; Triticum; wheats; calibration; optimization methods |
Abstract |
Crop models describe the growth and development of a crop interacting with its surrounding agro-environmental conditions (soil, climate and the close conditions of the plant). However, the implementation of such models remains difficult because of the high number of explanatory variables and parameters. It often happens that important discrepancies appear between measured and simulated values. This article aims to highlight the different sources of uncertainty related to the use of crop models, as well as the actual methods that allow a compensation for or, at least, a consideration of these sources of error during analysis of the model results. This article presents a literature review, which firstly synthesises the general mathematical structure of crop models. The main criteria for evaluating crop models are then described. Finally, several methods used for improving models are given. Parameter estimation methods, including frequentist and Bayesian approaches, are presented and data assimilation methods are reviewed. |
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Language |
French |
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Notes |
CropM, ftnotmacsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4584 |
Permanent link to this record |
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Author |
Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
Title |
Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions |
Type |
Journal Article |
Year |
2015 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
Volume |
16 |
Issue |
4 |
Pages |
361-384 |
Keywords |
nitrogen management; climatic variability; lars-wg weather generator; stics soil-crop model; pearson system; probability risk assessment; crop model stics; fertilizer nitrogen; generic model; wheat yield; maize; simulation; skewness; field; agriculture; scenarios |
Abstract |
At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution. |
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English |
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Series Editor |
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Edition |
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ISSN |
1385-2256 |
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Notes |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4519 |
Permanent link to this record |