Marthijn P.W. Sonneveld

Panarchy rules : rethinking resilience of agroecosystems, evidence from Dutch dairy - farming

Resilience has been growing in importance as a perspective for governing social-ecological systems. The aim of this paper is first to analyze a well-studied human dominated agroecosystem using five existing key heuristics of the resilience perspective and second to discuss the consequences of using this resilience perspective for the future management of similar human dominated agroecosystems. The human dominated agroecosystem is located in the Dutch Northern Frisian Woodlands where cooperatives of dairy farmers have been attempting to organize a transition toward more viable and environmental friendly agrosystems. A mobilizing element in the cooperatives was the ability of some dairy farmers to obtain high herbage and milk yield production with limited nitrogen fertilizer input. A set of reinforcing measures was hypothesized to rebalance nitrogen flows and to set a new equilibrium. A dynamic farm model was used to evaluate the long-term effects of reinforcing measures on soil organic matter content, which was considered the key indicator of an alternative system state. Simulations show that no alternative stable state for soil organic matter exists within a plausible range of fertilizer applications. The observed differences in soil organic matter content and nutrient use efficiency probably represent a time lag of long-term nonequilibrium system development. The resilience perspective proved to be especially insightful in addressing interacting long-term developments expressed in the panarchy. Panarchy created a heterogeneity of resources in the landscape providing local landscape-embedded opportunities for high N-efficiencies. Stopping the practice of grassland renewal will allow this ecological landscape embedded system to mature. In contrast, modern conventional dairy farms shortcut the adaptive cycle by frequent grassland renewals, resulting in high resilience and adaptability. This comes at the cost of long-term accumulated ecological capital of soil organic matter and transformability, thus reinforcing the incremental adaptation trap. Analysis of such a human dominated agroecosystem reveals that rather than alternative states, an alternative set of relationships within a multiscale setting applies, indicating the importance for embedding panarchy in the analysis of sustainable development goals in agroecosystems.

Simulation of soil water regimes including pedotransfer functions and land-use related preferential flow

Abstract Differences in land use history among taxonomically identical soils often result in different hydraulic properties, derived from either laboratory measurements or pedotransfer functions (PTFs). Additionally, flow mechanisms in sandy soils may also change through differences in water repellency associated with land use history. The soil water regimes for three sandy soils of the same taxonomic unit and under pasture but with differences in land use history were simulated. The land use histories were old grassland (site A), recently reseeded grassland (site B) and previous maize-cultivated land (site C). Degrees of water repellency, as indicated by the Water Drop Penetration Time (WDPT) test, were found to be highest for the topsoil of sites A and B. Initial simulations, using continuous pedotransfer functions to derive the Mualem–Van Genuchten parameters, corresponded poorly with field measurements (TDR). Additional laboratory measurements did not result in a better correspondence. Taking account of preferential flow in sites A and B, using the mobile/immobile concept, improved modelling performance significantly. Model simulations for a limited time period showed that water storage in the top 50 cm was on average 59 mm higher for site C compared with site A, and 23 mm higher for site B compared with site A. Downward fluxes at 50-cm depth were especially larger for site A compared with sites B and C.

Comparison of methods to identify crop productivity constraints in developing countries. A review

Selecting a method for identifying actual crop productivity constraints is an important step for triggering innovation processes. Applied methods can be diverse and although such methods have consequences for the design of intervention strategies, documented comparisons between various methods are scarce. Different variables can be used to characterize these methods. To typify them, we used two of these variables in a heuristic model: control over the research process and represented opinion. Here, we review 16 published papers that present outcomes of different methods to identify productivity constraints. The major findings are the following: (1) Variation in methods is wide. (2) Applying the heuristic model results in three main clusters of methods: farmer-control/farmer-opinion, scientist-control/scientist-opinion, and scientist-control/farmer-opinion. (3) These clusters are scale level dependent. As a follow up, we compared in a case study the three different methods, representative for the three main clusters of the heuristic model, in order to assess their congruency. These methods (focus group discussion, individual surveys, and contextual data collection) were applied in four localities in Tigray, Northern Ethiopia. We found that congruency between the methods, as indicated by Spearman-ρ correlations, was not significant. In addition, we found that outcomes of individual surveys and contextual data collection among the different locations were correlated (R > 0.70). No such correlation was found using focus group discussion. Both findings indicate that for a specific location different methods yielded different constraints and that variability between the locations is not reflected by using individual surveys and contextual data collection. Combined the review and case study demonstrate that process control and represented opinion have a manifest impact on generated outcomes. Because outcomes of productivity constraints assessments are methodology dependent, researchers are recommended to justify a priori their choice of method using the presented heuristic model.