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Landscape heterogeneity affects population dynamics, which determine species persistence, diversity and interactions. These relationships can be accurately represented by advanced spatially‐explicit models (SEMs) allowing for high levels of detail and precision. However, such approaches are characterised by high computational complexity, high amount of data and memory requirements and spatio‐temporal outputs may be difficult to analyse. A possibility to deal with this complexity is to aggregate outputs over time or space, but then interesting information may be masked and lost, such as local spatio‐temporal relationships or patterns. An alternative solution is given by meta‐models and meta‐analysis, where simplified mathematical relationships are used to structure and summarise the complex transformations from inputs to outputs. Here, we propose an original approach to analyse SEM outputs. By developing a meta‐modelling approach based on spatio‐temporal point processes (STPPs), we characterise spatio‐temporal population dynamics and landscape heterogeneity relationships in agricultural contexts. A landscape generator and a spatially‐explicit population model simulate hierarchically the pest–predator dynamics of codling moth and ground beetles in apple orchards over heterogeneous agricultural landscapes. Spatio‐temporally explicit outputs are simplified to marked point patterns of key events, such as local proliferation or introduction events. Then, we construct and estimate regression equations for multi‐type STPPs composed of event occurrence intensity and magnitudes. Results provide local insights into spatio‐temporal dynamics of pest–predator systems. We are able to differentiate the contributions of different driver categories (i.e. spatio‐temporal, spatial, population dynamics). We highlight changes in the effects on occurrence intensity and magnitude when considering drivers at global or local scale. This approach leads to novel findings in agroecology where, for example, we show that the organisation of cultivated patches and semi‐natural elements play different roles for pest regulation depending on the scale considered. It aids to formulate guidelines for biological control strategies at global and local scale. [ABSTRACT FROM AUTHOR]

In agricultural landscapes, the amount and organization of crops and semi-natural habitats (SNH) have the potential to promote a bundle of ecosystem services due to their influence on ecological community at multiple spatio-temporal scales. SNH are relatively undisturbed and are often source of complementary resources and refuges, therefore supporting more diverse and abundant natural pest enemies. However, the nexus of SNH proportion and organization with pest suppression is not trivial. It is thus crucial to understand how the behavior of pest and natural enemy species, the underlying landscape structure, and their interaction, may influence conservation biological control (CBC). Here, we develop a generative stochastic landscape model to simulate realistic agricultural landscape compositions and configurations of fields and linear elements. Generated landscapes are used as spatial support over which we simulate a spatially explicit predator-prey dynamic model. We find that increased SNH presence boosts predator populations by sustaining high predator density that regulates and keeps pest density below the pesticide application threshold. However, predator presence over all the landscape helps to stabilize the pest population by keeping it under this threshold, which tends to increase pest density at the landscape scale. In addition, the joint effect of SNH presence and predator dispersal ability among hedge and field interface results in a stronger pest regulation, which also limits pest growth. Considering properties of both fields and linear elements, such as local structure and geometric features, provides deeper insights for pest regulation; for example, hedge presence at crop field boundaries clearly strengthens CBC. Our results highlight that the integration of species behaviors and traits with landscape structure at multiple scales is necessary to provide useful insights for CBC. Author summary: In the agricultural context, the loss of semi-natural surfaces often results in high pest abundance requiring elevated pesticide loads. Habitat heterogeneity resulting from the agricultural intermixing of arable fields and semi-natural areas is key to allow organism fluxes across agro-ecological interfaces by influencing ecological processes. Semi-natural habitats (SNH) are often restricted to linear structures, such as hedgerows, but they play an important role by hosting a large number of species. However, the effect of hedgerows is controversial, as it could result in a positive, ineffective or negative effect for CBC. Usually, the impacts of landscape structure on pest population dynamics and resulting CBC are assessed through field experiments with a specific focus, which cannot be generalized, lack flexibility and are limited by the need to manipulate relatively large landscapes. Here, we tackle the challenge to investigate the controversial role of semi-natural habitats for CBC by presenting a simulation-based approach, which allows us to characterize the joint influence of landscape structure and species traits on CBC service. Our study corroborates that spatial heterogeneity, species traits and their interactions are fundamental for CBC. We show that hedge presence alone is not sufficient to lead to strong pest reduction, but hedge-based predators help to maintain the pest density under the pesticide threshold. Instead, SNH presence coupled with appropriate predator traits leads to stronger decrease of pest population. Moreover, we highlight an important scaling effect of SNH, which at the local scale has an even more important impact on CBC as local properties are considered. [ABSTRACT FROM AUTHOR]

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. Research Impact Statement: Both wetland habitat quality and connectivity act jointly but differently on amphibian population dynamics and should both be considered when managing wetlandscapes. [ABSTRACT FROM AUTHOR]

Wetlands have been degraded and destroyed, resulting in the decline of many wetland-dependent species populations. Many conservation efforts are based on protection of individual wetlands; however, fluxes of energy, materials and organisms between wetlands create important structural and functional connections upon which several species depend. We investigated the role of individual wetlands within a wetlandscape in sustaining an amphibian population. Wetlandscapes were represented as networks, where nodes were wetlands and links were flows of organisms described by an amphibian population model. Relationships between a wetland’s connectivity to the other wetlands and the abundance of amphibians under different wetland management strategies were examined. The first finding was that wetlands within a network can be classified into sinks (where local mortality exceeds birth rate), sources (where local birth rate exceeds mortality), and pseudo-sinks (where excessive immigration maintains the population above the carrying capacity). These three wetland classes have low, medium, and high Indegree (a parameter reflecting a wetland’s connectivity), respectively. The second finding was that management interventions in wetlands have different consequences according to the wetland’s Indegree : wetland removal has the worst impact on amphibian populations if the wetland is a source , and wetland restoration has the best impact if the wetland is a pseudo-sink . These findings provide support for policies that managing wetlands not as independent objects but as integral parts of the wetlandscape. [ABSTRACT FROM AUTHOR]

Climate change is expected to affect substantially future water availability and temperature across many watersheds in Europe potentially impacting hydropower generation and cooling efficiency of thermo-nuclear power plants. On the other hand, increasing Renewable Energy Sources (RES) penetration will substantially modify energy portfolios across Europe. As a consequence, prices will become more volatile, requiring more system flexibility. This study aims to explore the following key questions for supporting the definition and implementation of EU transition policies driving investments in the energy sector: 1) How climate change impacts on the hydrological system propagate to the energy system? 2) Can hydropower provide additional flexibility to a high RES-based energy system? To answer these questions, we developed an integrated modelling approaches combining a conceptual hydrological model (HBV) and an energy system model (PRIMES-IEM). Based on daily air temperature and precipitation, HBV computes daily streamflow for each power plant. Water temperature is obtained from air temperature using an empirical formula. These two variables are used to define the constraints to the energy model PRIMES-IEM, a power market simulator of the European electricity markets.Our analysis focuses on Iberian Peninsula and Danube region in 2040. Both regions' energy mix have a significant share of hydropower and rely significantly on thermo-nuclear power plants. In addition, both systems have already been under stress conditions due to heatwaves and droughts over the last years. On the climate side, we downscaled projected air temperature and precipitation projections for the RCP2.6 and RCP8.5 scenarios, covering the full range of possible climate futures from very low emission pathways to very high ones. On the energy side, we also consider two scenarios representative of the current system and of a future decarbonized system complying with European climate targets at 2030 and 2050. Despite some differences across the two regions, numerical results suggest some general trends: hot and dry climate futures significantly impact on the energy system because either increasing water temperature produces heavy stress due to thermonuclear generation curtailment or declining water availability limits hydropower generation forcing the energy system to shift to other technologies in order to maintain its reliability. [ABSTRACT FROM AUTHOR]

Modern agriculture faces the dual challenges of feeding a growing human population, while preserving natural resources and slowing current trends in climate change and its impacts. A deep understanding of the functioning of agricultural landscapes appears crucial if we are to move towards sustainable, complex and resilient agroecosystems. Modelling is a powerful tool to address these issues since it can inform these transformations by simulating the multiscale ecological flows and myriad interactions agroecosystems host, and the multilevel stakeholder actions and their feedbacks in landscapes. This chapter shows that models can provide guidance on the transition towards future multifunctional agricultural landscapes. We have focused on process-based models, which allow for a more thorough understanding of the underlying mechanisms and how these may be manipulated. We first examine how models can simulate the structure and the dynamics of agricultural landscapes, emphasizing the complex mosaic of urban, peri-urban, rural and seminatural habitats. Then, we consider the simulation of biotic and abiotic flows and their complex interactions in the mosaic habitats. Using formalisms from the social sciences, we integrate human decision-making and actions into the landscape models, thereby encompassing a major component in the landscape transformation process. Finally, we outline some avenues for future research. We have focused on improvements to landscape representation, and have suggested ways to bridge the gap between future landscape conception and manipulation, thus providing operational guidance for the transition towards future agricultural landscapes that achieve our objectives. [ABSTRACT FROM AUTHOR]