| Records |
| Author |
Schauberger, B.; Rolinski, S.; Müller, C. |
| Title |
A network-based approach for semi-quantitative knowledge mining and its application to yield variability |
Type |
Journal Article |
| Year |
2016 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
| Volume |
11 |
Issue |
12 |
Pages |
123001 |
| Keywords |
yield variability; crop models; interaction network; plant process; wheat; maize; rice; Global Food Security; Climate-Change; Crop Production; Stress Tolerance; Wheat Yields; Heat-Stress; Temperature Variability; Environmental-Factors; United-States; Elevated CO2 |
| Abstract |
Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. Asystematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields. |
| Address |
2017-04-07 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
ISSN  |
1748-9326 |
ISBN |
|
Medium |
Review |
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4942 |
| Permanent link to this record |
| |
|
| |
| Author |
Knox, J.; Daccache, A.; Hess, T.; Haro, D. |
| Title |
Meta-analysis of climate impacts and uncertainty on crop yields in Europe |
Type |
Journal Article |
| Year |
2016 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
| Volume |
11 |
Issue |
|
Pages |
113004 |
| Keywords |
|
| Abstract |
Future changes in temperature, rainfall and soil moisture could threaten agricultural land use and crop productivity in Europe, with major consequences for food security. We assessed the projected impacts of climate change on the yield of seven major crop types (viz wheat, barley, maize, potato, sugar beet, rice and rye) grown in Europe using a systematic review (SR) and meta-analysis of data reported in 41 original publications from an initial screening of 1748 studies. Our approach adopted an established SR procedure developed by the Centre for Evidence Based Conservation constrained by inclusion criteria and defined methods for literature searches, data extraction, meta-analysis and synthesis. Whilst similar studies exist to assess climate impacts on crop yield in Africa and South Asia, surprisingly, no comparable synthesis has been undertaken for Europe. Based on the reported results (n = 729) we show that the projected change in average yield in Europe for the seven crops by the 2050s is +8%. For wheat and sugar beet, average yield changes of +14% and +15% are projected, respectively. There were strong regional differences with crop impacts in northern Europe being higher (+14%) and more variable compared to central (+6%) and southern (+5) Europe. Maize is projected to suffer the largest negative mean change in southern Europe (−11%). Evidence of climate impacts on yield was extensive for wheat, maize, sugar beet and potato, but very limited for barley, rice and rye. The implications for supporting climate adaptation policy and informing climate impacts crop science research in Europe are discussed. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1748-9326 |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CropM, TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5011 |
| Permanent link to this record |
| |
|
| |
| Author |
Kim, D.-G.; Thomas, A.D.; Pelster, D.; Rosenstock, T.S.; Sanz-Cobena, A. |
| Title |
Greenhouse gas emissions from natural ecosystems and agricultural lands in sub-Saharan Africa: synthesis of available data and suggestions for further research |
Type |
Journal Article |
| Year |
2016 |
Publication |
Biogeosciences |
Abbreviated Journal |
Biogeosciences |
| Volume |
13 |
Issue |
16 |
Pages |
4789-4809 |
| Keywords |
nitrous-oxide emissions; soil CO2 efflux; N2O emissions; carbon-dioxide; agroforestry residues; improved-fallow; disturbance gradient; fertilizer; nitrogen; sampling frequency; gaseous emissions |
| Abstract |
This paper summarizes currently available data on greenhouse gas (GHG) emissions from African natural ecosystems and agricultural lands. The available data are used to synthesize current understanding of the drivers of change in GHG emissions, outline the knowledge gaps, and suggest future directions and strategies for GHG emission research. GHG emission data were collected from 75 studies conducted in 22 countries (n = 244) in sub-Saharan Africa (SSA). Carbon dioxide (CO2) emissions were by far the largest contributor to GHG emissions and global warming potential (GWP) in SSA natural terrestrial systems. CO2 emissions ranged from 3.3 to 57.0 Mg CO2 ha(-1) yr(-1), methane (CH4) emissions ranged from -4.8 to 3.5 kg ha(-1) yr(-1) (-0.16 to 0.12 Mg CO2 equivalent (eq.) ha(-1) yr(-1)), and nitrous oxide (N2O) emissions ranged from -0.1 to 13.7 kg ha(-1) yr(-1) (-0.03 to 4.1 Mg CO2 eq. ha(-1) yr(-1)). Soil physical and chemical properties, rewetting, vegetation type, forest management, and land-use changes were all found to be important factors affecting soil GHG emissions from natural terrestrial systems. In aquatic systems, CO2 was the largest contributor to total GHG emissions, ranging from 5.7 to 232.0 Mg CO2 ha(-1) yr(-1), followed by -26.3 to 2741.9 kgCH(4) ha(-1) yr(-1) (-0.89 to 93.2 Mg CO2 eq. ha(-1) yr(-1)) and 0.2 to 3.5 kg N2O ha(-1) yr(-1) (0.06 to 1.0 Mg CO2 eq. ha(-1) yr(-1)). Rates of all GHG emissions from aquatic systems were affected by type, location, hydrological characteristics, and water quality. In croplands, soil GHG emissions were also dominated by CO2, ranging from 1.7 to 141.2 Mg CO2 ha(-1) yr(-1), with -1.3 to 66.7 kgCH(4) ha(-1) yr(-1) (-0.04 to 2.3 Mg CO2 eq. ha(-1) yr(-1)) and 0.05 to 112.0 kg N2O ha(-1) yr(-1) (0.015 to 33.4 Mg CO2 eq. ha(-1) yr(-1)). N2O emission factors (EFs) ranged from 0.01 to 4.1 %. Incorporation of crop residues or manure with inorganic fertilizers invariably resulted in significant changes in GHG emissions, but results were inconsistent as the magnitude and direction of changes were differed by gas. Soil GHG emissions from vegetable gardens ranged from 73.3 to 132.0 Mg CO2 ha(-1) yr(-1) and 53.4 to 177.6 kg N2O ha(-1) yr(-1) (15.9 to 52.9 Mg CO2 eq. ha(-1) yr(-1)) and N2O EFs ranged from 3 to 4 %. Soil CO2 and N2O emissions from agroforestry were 38.6 Mg CO2 ha(-1) yr(-1) and 0.2 to 26.7 kg N2O ha(-1) yr(-1) (0.06 to 8.0 Mg CO2 eq. ha(-1) yr(-1)), respectively. Improving fallow with nitrogen (N)-fixing trees led to increased CO2 and N2O emissions compared to conventional croplands. The type and quality of plant residue in the fallow is an important control on how CO2 and N2O emissions are affected. Throughout agricultural lands, N2O emissions slowly increased with N inputs below 150 kg N ha(-1) yr(-1) and increased exponentially with N application rates up to 300 kg N ha(-1) yr(-1). The lowest yield-scaled N2O emissions were reported with N application rates ranging between 100 and 150 kg N ha(-1). Overall, total CO2 eq. emissions from SSA natural ecosystems and agricultural lands were 56.9 +/- 12.7 x 10(9) Mg CO2 eq. yr(-1) with natural ecosystems and agricultural lands contributing 76.3 and 23.7 %, respectively. Additional GHG emission measurements are urgently required to reduce uncertainty on annual GHG emissions from the different land uses and identify major control factors and mitigation options for low-emission development. A common strategy for addressing this data gap may include identifying priorities for data acquisition, utilizing appropriate technologies, and involving international networks and collaboration. |
| Address |
2016-10-18 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1726-4170 |
ISBN |
|
Medium |
Article |
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4687 |
| Permanent link to this record |
| |
|
| |
| Author |
Bannink, A.; van Lingen, H.J.; Ellis, J.L.; France, J.; Dijkstra, J. |
| Title |
The contribution of mathematical modeling to understanding dynamic aspects of rumen metabolism |
Type |
Journal Article |
| Year |
2016 |
Publication |
Frontiers in Microbiology |
Abbreviated Journal |
Frontiers in Microbiology |
| Volume |
7 |
Issue |
|
Pages |
1820 |
| Keywords |
lactating dairy-cows; milk urea concentration; fatty-acid production; ruminal fermentation; mechanistic model; holstein cows; beef-cattle; stoichiometric parameters; methane production; feeding frequency |
| Abstract |
All mechanistic rumen models cover the main drivers of variation in rumen function, which are feed intake, the differences between feedstuffs and feeds in their intrinsic rumen degradation characteristics, and fractional outflow rate of fluid and particulate matter. Dynamic modeling approaches are best suited to the prediction of more nuanced responses in rumen metabolism, and represent the dynamics of the interactions between substrates and micro-organisms and inter-microbial interactions. The concepts of dynamics are discussed for the case of rumen starch digestion as influenced by starch intake rate and frequency of feed intake, and for the case of fermentation of fiber in the large intestine. Adding representations of new functional classes of micro-organisms (i.e., with new characteristics from the perspective of whole rumen function) in rumen models only delivers new insights if complemented by the dynamics of their interactions with other functional classes. Rumen fermentation conditions have to be represented due to their profound impact on the dynamics of substrate degradation and microbial metabolism. Although the importance of rumen pH is generally acknowledged, more emphasis is needed on predicting its variation as well as variation in the processes that underlie rumen fluid dynamics. The rumen wall has an important role in adapting to rapid changes in the rumen environment, clearing of volatile fatty acids (VFA), and maintaining rumen pH within limits. Dynamics of rumen wall epithelia and their role in VFA absorption needs to be better represented in models that aim to predict rumen responses across nutritional or physiological states. For a detailed prediction of rumen N balance there is merit in a dynamic modeling approach compared to the static approaches adopted in current protein evaluation systems. Improvement is needed on previous attempts to predict rumen VFA profiles, and this should be pursued by introducing factors that relate more to microbial metabolism. For rumen model construction, data on rumen microbiomes are preferably coupled with knowledge consolidated in rumen models instead of relying on correlations with rather general aspects of treatment or animal. This helps to prevent the disregard of basic principles and underlying mechanisms of whole rumen function. |
| Address |
2017-01-06 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1664-302x |
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
LiveM, ft_MACSUR |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4932 |
| Permanent link to this record |
| |
|
| |
| Author |
Paas, W.; Kanellopoulos, A.; van de Ven, G.; Reidsma, P. |
| Title |
Integrated impact assessment of climate and socio-economic change on dairy farms in a watershed in the Netherlands |
Type |
Journal Article |
| Year |
2016 |
Publication |
NJAS – Wageningen Journal of Life Sciences |
Abbreviated Journal |
NJAS – Wageningen Journal of Life Sciences |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
climate change; bio-economic model; explorations; land-use; 2050-scenario |
| Abstract |
Climate and socio-economic change will affect the land use and the economic viability of Dutch dairy farms. Explorations of future scenarios, which include different drivers and impacts, are needed to perform ex-ante policy assessment. This study uses a bio-economic farm model to assess impacts of climate and socio-economic change on dairy farms in a sandy area in the Netherlands. Farm data from the Farm Accountancy Data Network provided information on the current production levels and available farm resources. First, the farm plans of individual farms were optimized in the current situation to benchmark farms and assess the current scope for improvement. Secondly, simulations for two scenarios were included: a Global Economy with 2 °C global temperature rise (GE/W+) and a Regional Community with 1 °C global temperature rise (RC/G). The impacts of climate change, extreme events, juridical change (including abolishment of milk quota), technological change and price changes were evaluated in separate model runs within the predefined scenarios. We found that farms can increase profit both by intensification and land expansion; the latter especially for medium sized farms (less than 70 cows). Climate change including the effect of increased occurrence of extreme events may negatively affect farm gross margin in the GE/W+ scenario. Lower gross margins are compensated for by the effects of technology and price changes. In contrast with the GE/W+ scenario, climate change has positive impacts on farm profit in RC/G, but less favourable farm input-output price ratios have a negative effect. Technological change is needed to compensate for revenue losses due to higher input prices. In both GE/W+ and RC/G scenarios, dairy farms increase production and the use of artificial fertilizer. Medium sized farms have more options to increase profit than the large farms: they benefit more from the abolishment of the milk quota and better adapt to negative and positive impacts of climate change. While the exact impact of different drivers will always remain uncertain, this study showed that changes in prices, technology and markets have a relatively larger impact than climate change, even when extreme events are taken into account. By using whole farm plans as activities that can be selected, the model is grounded in observations, and it was shown that half of the farms are gross margin maximizers as assumed in the model. The model therefore indicates ‘what could happen if’, and gives insights in drivers and impacts of dairy farming in the region. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
English |
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
1573-5214 |
ISBN |
|
Medium |
Article |
| Area |
|
Expedition |
|
Conference |
|
| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4712 |
| Permanent link to this record |
