An ecophysiological model of plant–pest interactions: the role of nutrient and water availability

Empirical studies have shown that particular irrigation/fertilization regimes can reduce pest populations in agroecosystems. This appears to promise that the ecological concept of bottom-up control can be applied to pest management. However, a conceptual framework is necessary to develop a mechanistic basis for empirical evidence. Here, we couple a mechanistic plant growth model with a pest population model. We demonstrate its utility by applying it to the peach–green aphid system. Aphids are herbivores which feed on the plant phloem, deplete plants’ resources and (potentially) transmit viral diseases. The model reproduces system properties observed in field studies and shows under which conditions the diametrically opposed plant vigour and plant stress hypotheses find support. We show that the effect of fertilization/irrigation on the pest population cannot be simply reduced as positive or negative. In fact, the magnitude and direction of any effect depend on the precise level of fertilization/irrigation and on the date of observation. We show that a new synthesis of experimental data can emerge by embedding a mechanistic plant growth model, widely studied in agronomy, in a consumer–resource modelling framework, widely studied in ecology. The future challenge is to use this insight to inform practical decision making by farmers and growers.

Light Interception and the Growth of Pastures under Ideal and Stressful Growing Conditions on the Allegheny Plateau

Pasture-based livestock production is impacted by management and weather. In pastures, there is conflict between leaf retention for plant growth and leaf harvest for animal nutrition. Defoliated pastures with low light interception (LI) may have a low forage growth rate (FGR), while excessive growth shades leaves, reducing FGR and resulting in an S-shaped regrowth curve. To optimize production, it is best to keep FGR linear. Three studies were conducted to evaluate the impact of management and weather on FGR. Replicated pastures were used to measure FGR when grazed from 25 to 10 cm and allowed to regrow. The impact of alternative defoliation timings and intensities on FGR were studied using clipped treatments at three recovery intervals and two stubble heights. Variability in FGR was studied using a field validated plant growth model. Of the 24 growth periods studied, two displayed exponential, 12 linear and 10 linear-plateau growth. There was no effect of FM on growth curve form. In May and June, LI increased with canopy height, up to 0.93. Stubble height and days of growth impacted FGR with an interaction. There was no treatment impact on root density. Weather caused variation in FGR. A low FGR risk occurs at high elevations; greater risk occurs east of the plateau.

An ecophysiological model of plant-pest interactions: the role of nutrient and water availability

Empirical studies have shown that particular irrigation/fertilization regimes can control pest populations in agroecosystems. This appears to promise that the ecological concept of bottom-up control can be applied to pest management. However, a conceptual framework is necessary to develop a mechanistic basis for empirical evidence. Here we couple a mechanistic plant growth model with a pest population model. We demonstrate its utility by applying it to the peach - green aphid system. Aphids are herbivores which feed on the plant phloem, deplete plants’ resources and (potentially) transmit viral diseases. The model reproduces system properties observed in field studies and shows under which conditions the diametrically-opposed plant vigour and plant stress hypotheses find support. We show that the effect of fertilization/irrigation on the pest population cannot be simply reduced as positive or negative. In fact, the magnitude and direction of any effect depends on the precise level of fertilization/irrigation and on the date of observation. We show that a new synthesis of experimental data can emerge by embedding a mechanistic plant growth model, widely studied in agronomy, in a consumer-resource modelling framework, widely studied in ecology. The future challenge is to use this insight to inform practical decision making by farmers and growers.