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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.

Resistant cultivars are of value for protecting crops from disease, but can be rapidly overcome by pathogens. Several strategies have been proposed to delay pathogen adaptation (evolutionary control), while maintaining effective protection (epidemiological control). Resistance genes can be i) combined in the same cultivar (pyramiding), ii) deployed in different cultivars sown in the same field (mixtures) or in different fields (mosaics), or iii) alternated over time (rotations). The outcomes of these strategies have been investigated principally in pathogens displaying pure clonal reproduction, but sexual reproduction may promote the emergence of superpathogens adapted to all the resistance genes deployed. We improved the spatially explicit stochastic modellandsepito include pathogen sexual reproduction, and then investigate the effect of sexual reproduction on evolutionary and epidemiological outcomes across deployment strategies for two major resistance genes. Sexual reproduction only favours the establishment of a superpathogen when single mutant pathogens are present together at a sufficiently high frequency, as in mosaic and mixture strategies. We concluded that, although sexual reproduction may promote the establishment of a superpathogen, it did not affect the optimal strategy recommendations for a wide range of mutation probabilities, associated fitness costs, and landscape organisations (notably the cropping ratio of resistant fields).

Aphids are the primary vector of plant viruses. Transient aphids, which probe several plants per day, are considered to be the principal vectors of non-persistently transmitted (NPT) viruses. However, resident aphids, which can complete their life cycle on a single host and are affected by agronomic practices, can transmit NPT viruses as well. Moreover, they can interfere both directly and indirectly with transient aphids, eventually shaping plant disease dynamics. By mean of an epidemiological model, originally accounting for ecological principles and agronomic practices, we explore the consequences of fertilization and irrigation, pesticide deployment and roguing of infected plants on the spread of viral diseases in crops. Our results indicate that the spread of NPT viruses can be i) both reduced or increased by fertilization and irrigation, depending on whether the interference is direct or indirect; ii) counter-intuitively increased by pesticide application and iii) reduced by roguing infected plants. We show that a better understanding of vectors’ interactions would enhance our understanding of disease transmission, supporting the development of disease management strategies.

Wetlands should not be considered as independent objects but as dynamically connected objects, collectively known as wetlandscapes. We developed a framework that analyzes the influences of wetland suitability and connectivity on amphibian distributions. We defined two indices: a Wetland Suitability Index describing wetland quality and a Movement Permeability Index characterizing wetland connectivity for amphibian population dynamics. These indices were calculated from raster datasets and time‐varying inundation estimates. The indices were used to define a wetlandscape and an amphibian model was used to simulate population dynamics within the wetlandscape. The framework was applied to the Nose Creek watershed, a highly modified wetlandscape in Alberta, Canada. Two amphibian species were selected with different habitat preferences: the Northern Leopard Frog that prefers wet habitats and has high mobility over land, and the Great Plains Toad that prefers terrestrial habitats and has low mobility over land. We found each amphibian species had a “preferred” wetlandscape, reflecting their life cycle traits and migration strategies which in turn were dependent on the hydrological and ecological connections within the wetlandscape. This study highlights the importance of investigating both individual wetlands and the wetlandscape and considering both wetland habitat quality and connectivity as non‐substitutable properties that act jointly, but differently, on population dynamics.

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Satisfying the demand for agricultural products while also protecting the environment from negative impacts of agriculture is a major challenge for crop management. We used an ecophysiological model of plant-pest interaction and multi-criteria decision analysis to optimize crop management when considering two contrasting objectives: (1) maximizing crop production and (2) minimizing environmental impact related to fertilization, irrigation and pesticide deployment. The model provides an indicator of crop production for 27 management scenarios, obtained combining three levels of fertilization, irrigation and pesticide use, respectively. We computed the environmental impact relevant to each management scenario by means of a weighted sum of costs assigned to fertilization, irrigation and pesticide use. We identified the optimal scenarios with respect to the considered objectives analysing the Pareto front. These scenarios were mostly characterized by high fertilization and no pesticide use. We evaluated the multi-functionality of the optimal scenarios by mean of the Gini coefficient: the scenario better assuring the equality between the two objectives was characterized by high fertilization, intermediate irrigation and no pesticide. Although our results remain qualitative and not immediately transferable to agronomic practices, our analytical framework provides a useful tool to evidence trade-offs among two contrasting objectives and provide solutions to act in an efficient way by leaving a certain degree of freedom to the political decision maker.