Consultancyonderzoek naar mogelijke oorzaken uitval bij Mandevilla

Abstract Wageningen UR Greenhouse Horticulture and Marcel Lieffering Kamer- en Perkplantenadviesburo conducted exploratory research, funded by the Dutch Product Board for Horticulture, into the loss of plants in Mandevilla growing. In literature, the diseases Pythium, Phytophthora, Fusarium oxysporum, Agrobacterium and Ralstonia were mentioned. In an experimental production test, only Phytophthora was found. In this experiment, differences in crop loss were mainly related to the origin. The differences in crop loss between substrates and pH levels were clearly smaller. Origin also had a major impact on plant quality: one origin was much better than the other two

Climate Change Is Likely to Increase the Development Rate of Anthelmintic Resistance in Equine Cyathostomins in New Zealand

Climate change is likely to influence livestock production by increasing the prevalence of diseases, including parasites. The traditional practice of controlling nematodes in livestock by the application of anthelmintics is, however, increasingly compromised by the development of resistance to these drugs in parasite populations. This study used a previously developed simulation model of the entire equine cyathostomin lifecycle to investigate the effect a changing climate would have on the development of anthelmintic resistance. Climate data from six General Circulation Models based on four different Representative Concentration Pathways was available for three New Zealand locations. These projections were used to estimate the time resistance will take to develop in the middle (2040–49) and by the end (2090–99) of the century in relation to current (2006–15) conditions under two treatment scenarios of either two or six yearly whole-herd anthelmintic treatments. To facilitate comparison, a scenario without any treatments was included as a baseline. In addition, the size of the infective and parasitic stage nematode population during the third simulation year were estimated. The development of resistance varied between locations, time periods and anthelmintic treatment strategies. In general, the simulations indicated a more rapid development of resistance under future climates coinciding with an increase in the numbers of infective larvae on pasture and encysted parasitic stages. This was especially obvious when climate changes resulted in a longer period suitable for development of free-living parasite stages. A longer period suitable for larval development resulted in an increase in the average size of the parasite population with a larger contribution from eggs passed by resistant worms surviving the anthelmintic treatments. It is projected that climate change will decrease the ability to control livestock parasites by means of anthelmintic treatments and non-drug related strategies will become increasingly important for sustainable parasite control

Projecting grassland sensitivity to climate change from an ensemble of models

The grassland biome covers about one-quarter of the earth’s land area and contributes to the livelihoods of ca. 800 million people. Increased aridity and persistent droughts are projected in the twenty-first century for most of Africa, southern Europe and the Middle East, most of the Americas, Australia and South East Asia. A number of these regions have a large fraction of their land use covered by grasslands and rangelands. Grasslands are the ecosystems that respond most rapidly to precipitation variability. However, global projections of climate change impacts on grasslands are still lacking in the scientific literature. Within AgMIP, based on the C3MP protocol initially developed for crops, we have explored the sensitivity of temperate grasslands to climate change drivers with an ensemble of models. Site calibrated models are used to provide projections under probabilistic climate change scenarios, which are defined by a combination of air temperature, precipitation and atmospheric CO2 changes resulting in 99 runs for each model times site combination. This design provides a test of grassland production, GHG (N2O and CH4) emissions and soil carbon sensitivity to climate change drivers. This integrated approach has been tested for 12 grassland simulation models applied to 19 sites over three continents. We show here that a single polynomial emulator can be fitted with high significance to the results of all models and sites, when these are expressed as relative changes from the optimal combination of climate drivers. This polynomial emulator shows that elevated atmospheric CO2 expands the thermal and hydric range which allows for the development of temperate grasslands. Moreover, we calculate the climatic response surface of GHG emissions per unit grassland production and we show that this surface varies with elevated CO2. From these results we provide first estimates of the impacts of climate change on temperate grasslands based on a range of climate scenarios

Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland

Process‐based models are useful for assessing the impact of changing management practices and climate on yields and greenhouse gas (GHG) emissions from agricultural systems such as grasslands. They can be used to construct national GHG inventories using a Tier 3 approach. However, accurate simulations of nitrous oxide (N$_{2}$O) fluxes remain challenging. Models are limited by our understanding of soil‐plant‐microbe interactions and the impact of uncertainty in measured input parameters on simulated outputs. To improve model performance, thorough evaluations against in situ measurements are needed. Experimental data of N$_{2}$O emissions under two management practices (control with typical fertilization versus increased clover and no fertilization) were acquired in a Swiss field experiment. We conducted a multimodel evaluation with three commonly used biogeochemical models (DayCent in two variants, PaSim, APSIM in two variants) comparing four years of data. DayCent was the most accurate model for simulating N$_{2}$O fluxes on annual timescales, while APSIM was most accurate for daily N$_{2}$O fluxes. The multimodel ensemble average reduced the error in estimated annual fluxes by 41% compared to an estimate using the Intergovernmental Panel on Climate Change (IPCC)‐derived method for the Swiss agricultural GHG inventory (IPCC‐Swiss), but individual models were not systematically more accurate than IPCC‐Swiss. The model ensemble overestimated the N$_{2}$O mitigation effect of the clover‐based treatment (measured: 39–45%; ensemble: 52–57%) but was more accurate than IPCC‐Swiss (IPCC‐Swiss: 72–81%). These results suggest that multimodel ensembles are valuable for estimating the impact of climate and management on N$_{2}$O emissions

Evaluating the Potential of Legumes to Mitigate N2_{2}O Emissions From Permanent Grassland Using Process-Based Models

A potential strategy for mitigating nitrous oxide (N$_{2}$O) emissions from permanent grasslands is the partial substitution of fertilizer nitrogen (N$_{fert}$) with symbiotically fixed nitrogen (N$_{symb}$) from legumes. The input of N$_{symb}$ reduces the energy costs of producing fertilizer and provides a supply of nitrogen (N) for plants that is more synchronous to plant demand than occasional fertilizer applications. Legumes have been promoted as a potential N$_{2}$O mitigation strategy for grasslands, but evidence to support their efficacy is limited, partly due to the difficulty in conducting experiments across the large range of potential combinations of legume proportions and fertilizer N inputs. These experimental constraints can be overcome by biogeochemical models that can vary legume‐fertilizer combinations and subsequently aid the design of targeted experiments. Using two variants each of two biogeochemical models (APSIM and DayCent), we tested the N$_{2}$O mitigation potential and productivity of full factorial combinations of legume proportions and fertilizer rates for five temperate grassland sites across the globe. Both models showed that replacing fertilizer with legumes reduced N$_{2}$O emissions without reducing productivity across a broad range of legume‐fertilizer combinations. Although the models were consistent with the relative changes of N$_{2}$O emissions compared to the baseline scenario (200 kg N ha$^{-1}$ yr$^{-1}$; no legumes), they predicted different levels of absolute N$_{2}$O emissions and thus also of absolute N$_{2}$O emission reductions; both were greater in DayCent than in APSIM. We recommend confirming these results with experimental studies assessing the effect of clover proportions in the range 30–50% and ≤150 kg N ha$^{-1}$ yr$^{-1}$ input as these were identified as best‐bet climate smart agricultural practices

Modelling biological N fixation and grass-legume dynamics with process-based biogeochemical models of varying complexity

This work was conducted by the Models4Pastures consortium project under the auspices of FACCE-JPI. Funding was provided by: the New Zealand Government to support the objectives of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases; AgResearch’s Strategic Science Investment Fund as a contribution to the Forages for Reduced Nitrate Leaching (FRNL) research programme; the input of UK partners was funded by DEFRA and also contributes to the RCUK-funded projects: N-Circle (BB/N013484/1), UGRASS (NE/M016900/1) and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE-JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc.Mobility fellowship (SNSF funded project: P1EZP2_172121). Lorenzo Brilli, Camilla Dibari and Marco Bindi acknowledge funding received from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF).Peer reviewedPublisher PD

Evaluating the Potential of Legumes to Mitigate N2O Emissions From Permanent Grassland Using Process-Based Models

Funding Information: This modeling study was a joint effort of the Models4Pastures project within the framework of FACCE-JPI. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE-JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc. Mobility fellowship (SNSF funded project: P1EZP2_172121). Lutz Merbold further acknowledges the support received for CGIAR Fund Council, Australia (ACIAR), Irish Aid, the European Union, the Netherlands, New Zealand, Switzerland, UK, USAID, and Thailand for funding to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) as well as for the CGIAR Research Program on Livestock. The NZ contributors acknowledge funding from the New Zealand Government Ministry of Primary Industries to support the aims of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases and from AgResearch's Strategic Science Investment Fund (the Forages for Reduced Nitrate Leaching (FRNL) research program). The UK partners acknowledge funding by DEFRA and the RCUK projects: N-Circle (BB/N013484/1), UGRASS (NE/M016900/1), and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lorenzo Brilli, Camilla Dibari, and Marco Bindi received funding from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF). The FR partners acknowledge funding from CN-MIP project funded by the French National Research Agency (ANR-13-JFAC-0001) and from ADEME (no. 12-60-C0023). Open access funding enabled and organized by Projekt DEAL Funding Information: This modeling study was a joint effort of the Models4Pastures project within the framework of FACCE‐JPI. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE‐JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc. Mobility fellowship (SNSF funded project: P1EZP2_172121). Lutz Merbold further acknowledges the support received for CGIAR Fund Council, Australia (ACIAR), Irish Aid, the European Union, the Netherlands, New Zealand, Switzerland, UK, USAID, and Thailand for funding to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) as well as for the CGIAR Research Program on Livestock. The NZ contributors acknowledge funding from the New Zealand Government Ministry of Primary Industries to support the aims of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases and from AgResearch's Strategic Science Investment Fund (the Forages for Reduced Nitrate Leaching (FRNL) research program). The UK partners acknowledge funding by DEFRA and the RCUK projects: N‐Circle (BB/N013484/1), UGRASS (NE/M016900/1), and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lorenzo Brilli, Camilla Dibari, and Marco Bindi received funding from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF). The FR partners acknowledge funding from CN‐MIP project funded by the French National Research Agency (ANR‐13‐JFAC‐0001) and from ADEME (no. 12‐60‐C0023). Open access funding enabled and organized by Projekt DEAL Publisher Copyright: ©2020. The Authors. Open access funding enabled and organized by Projekt DEALPeer reviewedPublisher PD

The AgMIP Coordinated Climate-Crop Modeling Project (C3MP): Methods and Protocols

Climate change is expected to alter a multitude of factors important to agricultural systems, including pests, diseases, weeds, extreme climate events, water resources, soil degradation, and socio-economic pressures. Changes to carbon dioxide concentration ([CO2]), temperature, andwater (CTW) will be the primary drivers of change in crop growth and agricultural systems. Therefore, establishing the CTW-change sensitivity of crop yields is an urgent research need and warrants diverse methods of investigation. Crop models provide a biophysical, process-based tool to investigate crop responses across varying environmental conditions and farm management techniques, and have been applied in climate impact assessment by using a variety of methods (White et al., 2011, and references therein). However, there is a significant amount of divergence between various crop models’ responses to CTW changes (R¨otter et al., 2011). While the application of a site-based crop model is relatively simple, the coordination of such agricultural impact assessments on larger scales requires consistent and timely contributions from a large number of crop modelers, each time a new global climate model (GCM) scenario or downscaling technique is created. A coordinated, global effort to rapidly examine CTW sensitivity across multiple crops, crop models, and sites is needed to aid model development and enhance the assessment of climate impacts (Deser et al., 2012)..

Long-term atmospheric carbon dioxide enrichment decreases soil phosphorus availability in a grazed temperate pasture

Elevated atmospheric carbon dioxide (eCO₂) associated with climate change increases plant production and soil nutrient transformations. However, changes in soil phosphorus (P) availability and dynamics are unclear. We used the long-term New Zealand Free Air CO₂ Enrichment (FACE) experiment to quantify changes in P availability and soil P fractions as well as chemical and biological parameters in response to ambient and elevated CO₂ (up to 500 ppm) concentrations. Results revealed that labile and moderately labile soil inorganic P decreased in response to eCO₂, while organic P increased. Accumulation of organic P was related to enhanced biological activity, increased inputs of organic P from root detritus, and immobilization on reactive mineral surfaces. The findings of this study confirmed that elevated CO₂ had a major impact on the dynamics and bioavailability of soil P under grazed pasture, which may be further impacted by continued climate change