Context dependency of the implementation of the practices and systems (D3.3)

The work builds on a structured literature scan that identified recurrent site-specific factors influencing IPM efficiency. These were synthesised into six context dependency indicators: 1) climate and weather, 2) soil characteristics and hydrology, 3) landscape structure and topography, 4) biodiversity and ecosystem functions, 5) pest pressure and biotic risk, and 6) temporal or legacy effects. This framework formed the basis for a systematic review of European studies, analysing the frequency of each indicator, how indicators co-occur and identifying major remaining knowledge gaps. The methodology was applied to three case studies: codling moth management in apple orchards, powdery mildew control in vineyards, and weed management in cereals. 

Across literature and case study evidence, pest pressure / biotic risk context and climate and weather conditions consistently emerged as the most influential indicators of IPM performance. Sub-factors such as spatial variability of pest populations, temporal pest dynamics, and macro- and microclimatic variables were repeatedly linked to high context dependency across systems. In cereals, soil  characteristics & hydrology and temporal / legacy effects played a larger role, while perennial fruit systems (apple and grapevine) showed higher relevance of landscape structure & topography and, to a lesser extent, biodiversity & ecosystem functions.

A scoring system was then developed to classify the degree of context dependency (0–3 scale) for IPM practices. This integrates the six indicators with the ASP metrics from WP2, which measure agronomic service provision (ASP) and improvement relative to current practice. Combining context dependency with efficiency enables transparent assessment of whether practices are suitable for binding rules or require local adaptation.

The relationship between ASP and context dependency was generally weak, confirming that both dimensions must be considered jointly. High agronomic benefits can occur in both low- and high-dependency contexts, and conversely, low ASP practices may be either broadly robust or highly site-specific. Time of Anticipation showed only a modest trend toward higher context dependency with longer implementation horizons, with substantial variability within each anticipation class.