Landscape allocation: stochastic generators and statistical inference

In agricultural landscapes, the composition and spatial configuration of cultivated and semi-natural elements strongly impact species dynamics, their interactions and habitat connectivity. To allow for landscape structural analysis and scenario generation, we here develop statistical tools for real landscapes composed of geometric elements including 2D patches but also 1D linear elements such as hedges. We design generative stochastic models that combine a multiplex network representation and Gibbs energy terms to characterize the distributional behavior of landscape descriptors for land-use categories. We implement Metropolis-Hastings for this new class of models to sample agricultural scenarios featuring parameter-controlled spatial and temporal patterns (e.g., geometry, connectivity, crop-rotation). Pseudolikelihood-based inference allows studying the relevance of model components in real landscapes through statistical and functional validation, the latter achieved by comparing commonly used landscape metrics between observed and simulated landscapes. Models fitted to subregions of the Lower Durance Valley (France) indicate strong deviation from random allocation, and they realistically capture small-scale landscape patterns. In summary, our approach of statistical modeling improves the understanding of structural and functional aspects of agro-ecosystems, and it enables simulation-based theoretical analysis of how landscape patterns shape biological and ecological processes

A Simplified Water Accounting Procedure to Assess Climate Change Impact on Water Resources for Agriculture across Different European River Basins

[EN] European agriculture and water policies require accurate information on climate change impacts on available water resources. Water accounting, that is a standardized documentation of data on water resources, is a useful tool to provide this information. Pan-European data on climate impacts do not recognize local anthropogenic interventions in the water cycle. Most European river basins have a specific toolset that is understood and used by local experts and stakeholders. However, these local tools are not versatile. Thus, there is a need for a common approach that can be understood by multi-fold users to quantify impact indicators based on local data and that can be used to synthesize information at the European level. Then, policies can be designed with the confidence that underlying data are backed-up by local context and expert knowledge. This work presents a simplified water accounting framework that allows for a standardized examination of climate impacts on water resource availability and use across multiple basins. The framework is applied to five different river basins across Europe. Several indicators are extracted that explicitly describe green water fluxes versus blue water fluxes and impacts on agriculture. The examples show that a simplified water accounting framework can be used to synthesize basin-level information on climate change impacts which can support policymaking on climate adaptation, water resources and agriculture.This research was funded by Horizon 2020 IMPREX project, grant number 641811Hunink, J.; Simons, G.; Suárez-Almiñana, S.; Solera Solera, A.; Andreu Álvarez, J.; Giuliani, M.; Zamberletti, P.... (2019). A Simplified Water Accounting Procedure to Assess Climate Change Impact on Water Resources for Agriculture across Different European River Basins. Water. 11(10):1-29. https://doi.org/10.3390/w11101976S1291110Jacob, D., Kotova, L., Teichmann, C., Sobolowski, S. P., Vautard, R., Donnelly, C., … van Vliet, M. T. H. (2018). Climate Impacts in Europe Under +1.5°C Global Warming. Earth’s Future, 6(2), 264-285. doi:10.1002/2017ef000710Koutroulis, A. G., Grillakis, M. G., Daliakopoulos, I. N., Tsanis, I. K., & Jacob, D. (2016). Cross sectoral impacts on water availability at +2 °C and +3 °C for east Mediterranean island states: The case of Crete. Journal of Hydrology, 532, 16-28. doi:10.1016/j.jhydrol.2015.11.015Dezsi, Ş., Mîndrescu, M., Petrea, D., Rai, P. K., Hamann, A., & Nistor, M.-M. (2018). High-resolution projections of evapotranspiration and water availability for Europe under climate change. International Journal of Climatology, 38(10), 3832-3841. doi:10.1002/joc.5537Forzieri, G., Feyen, L., Russo, S., Vousdoukas, M., Alfieri, L., Outten, S., … Cid, A. (2016). Multi-hazard assessment in Europe under climate change. Climatic Change, 137(1-2), 105-119. doi:10.1007/s10584-016-1661-xRuosteenoja, K., Markkanen, T., Venäläinen, A., Räisänen, P., & Peltola, H. (2017). Seasonal soil moisture and drought occurrence in Europe in CMIP5 projections for the 21st century. Climate Dynamics, 50(3-4), 1177-1192. doi:10.1007/s00382-017-3671-4Stahl, K., Kohn, I., Blauhut, V., Urquijo, J., De Stefano, L., Acacio, V., … Van Lanen, H. A. J. (2015). Impacts of European drought events: insights from an international database of text-based reports. doi:10.5194/nhessd-3-5453-2015Van Lanen, H. A. J., Laaha, G., Kingston, D. G., Gauster, T., Ionita, M., Vidal, J., … Van Loon, A. F. (2016). Hydrology needed to manage droughts: the 2015 European case. Hydrological Processes, 30(17), 3097-3104. doi:10.1002/hyp.10838Moore, F. C., & Lobell, D. B. (2014). Adaptation potential of European agriculture in response to climate change. Nature Climate Change, 4(7), 610-614. doi:10.1038/nclimate2228Iglesias, A., & Garrote, L. (2015). Adaptation strategies for agricultural water management under climate change in Europe. Agricultural Water Management, 155, 113-124. doi:10.1016/j.agwat.2015.03.014Llop, M., & Ponce-Alifonso, X. (2016). Water and Agriculture in a Mediterranean Region: The Search for a Sustainable Water Policy Strategy. Water, 8(2), 66. doi:10.3390/w8020066Escribano Francés, G., Quevauviller, P., San Martín González, E., & Vargas Amelin, E. (2017). Climate change policy and water resources in the EU and Spain. A closer look into the Water Framework Directive. Environmental Science & Policy, 69, 1-12. doi:10.1016/j.envsci.2016.12.006Bastiaanssen, W. G. M., & Steduto, P. (2017). The water productivity score (WPS) at global and regional level: Methodology and first results from remote sensing measurements of wheat, rice and maize. Science of The Total Environment, 575, 595-611. doi:10.1016/j.scitotenv.2016.09.032Simons, G. W. H. (Gijs), Bastiaanssen, W. G. M. (Wim), & Immerzeel, W. W. (Walter). (2015). 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Climatic Change, 135(2), 341-355. doi:10.1007/s10584-015-1570-4Samaniego, L., Thober, S., Kumar, R., Wanders, N., Rakovec, O., Pan, M., … Marx, A. (2018). Anthropogenic warming exacerbates European soil moisture droughts. Nature Climate Change, 8(5), 421-426. doi:10.1038/s41558-018-0138-5Panagopoulos, Y., Stefanidis, K., Faneca Sanchez, M., Sperna Weiland, F., Van Beek, R., Venohr, M., … Birk, S. (2019). Pan-European Calculation of Hydrologic Stress Metrics in Rivers: A First Assessment with Potential Connections to Ecological Status. Water, 11(4), 703. doi:10.3390/w11040703Macknick, J., Newmark, R., Heath, G., & Hallett, K. C. (2012). Operational water consumption and withdrawal factors for electricity generating technologies: a review of existing literature. Environmental Research Letters, 7(4), 045802. doi:10.1088/1748-9326/7/4/045802Koutroulis, A. G., Papadimitriou, L. V., Grillakis, M. G., Tsanis, I. K., Wyser, K., & Betts, R. A. (2018). Freshwater vulnerability under high end climate change. A pan-European assessment. Science of The Total Environment, 613-614, 271-286. doi:10.1016/j.scitotenv.2017.09.074Lobanova, A., Liersch, S., Nunes, J. P., Didovets, I., Stagl, J., Huang, S., … Krysanova, V. (2018). Hydrological impacts of moderate and high-end climate change across European river basins. Journal of Hydrology: Regional Studies, 18, 15-30. doi:10.1016/j.ejrh.2018.05.003Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., … Wood, E. F. (2017). Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling. Hydrology and Earth System Sciences, 21(12), 6201-6217. doi:10.5194/hess-21-6201-2017Naz, B. S., Kurtz, W., Montzka, C., Sharples, W., Goergen, K., Keune, J., … Kollet, S. (2019). Improving soil moisture and runoff simulations at 3 km over Europe using land surface data assimilation. Hydrology and Earth System Sciences, 23(1), 277-301. doi:10.5194/hess-23-277-2019Haro, D., Solera, A., Paredes, J., & Andreu, J. (2014). Methodology for Drought Risk Assessment in Within-year Regulated Reservoir Systems. Application to the Orbigo River System (Spain). Water Resources Management, 28(11), 3801-3814. doi:10.1007/s11269-014-0710-3Zaniolo, M., Giuliani, M., Castelletti, A. F., & Pulido-Velazquez, M. (2018). Automatic design of basin-specific drought indexes for highly regulated water systems. Hydrology and Earth System Sciences, 22(4), 2409-2424. doi:10.5194/hess-22-2409-2018Koutroulis, A. G., Tsanis, I. K., Daliakopoulos, I. N., & Jacob, D. (2013). Impact of climate change on water resources status: A case study for Crete Island, Greece. Journal of Hydrology, 479, 146-158. doi:10.1016/j.jhydrol.2012.11.055Vargas-Amelin, E., & Pindado, P. (2014). The challenge of climate change in Spain: Water resources, agriculture and land. Journal of Hydrology, 518, 243-249. doi:10.1016/j.jhydrol.2013.11.035Giuliani, M., Li, Y., Castelletti, A., & Gandolfi, C. (2016). A coupled human-natural systems analysis of irrigated agriculture under changing climate. Water Resources Research, 52(9), 6928-6947. doi:10.1002/2016wr019363Giuliani, M., & Castelletti, A. (2016). Is robustness really robust? How different definitions of robustness impact decision-making under climate change. Climatic Change, 135(3-4), 409-424. doi:10.1007/s10584-015-1586-9Grindlay, A. L., Zamorano, M., Rodríguez, M. I., Molero, E., & Urrea, M. A. (2011). Implementation of the European Water Framework Directive: Integration of hydrological and regional planning at the Segura River Basin, southeast Spain. Land Use Policy, 28(1), 242-256. doi:10.1016/j.landusepol.2010.06.005Quevauviller, P., Barceló, D., Beniston, M., Djordjevic, S., Harding, R. J., Iglesias, A., … Werner, M. (2012). Integration of research advances in modelling and monitoring in support of WFD river basin management planning in the context of climate change. Science of The Total Environment, 440, 167-177. doi:10.1016/j.scitotenv.2012.07.055Edens, B., & Graveland, C. (2014). Experimental valuation of Dutch water resources according to SNA and SEEA. Water Resources and Economics, 7, 66-81. doi:10.1016/j.wre.2014.10.003Pedro-Monzonís, M., Jiménez-Fernández, P., Solera, A., & Jiménez-Gavilán, P. (2016). The use of AQUATOOL DSS applied to the System of Environmental-Economic Accounting for Water (SEEAW). Journal of Hydrology, 533, 1-14. doi:10.1016/j.jhydrol.2015.11.034Gouveia, C. M., Trigo, R. M., Beguería, S., & Vicente-Serrano, S. M. (2017). Drought impacts on vegetation activity in the Mediterranean region: An assessment using remote sensing data and multi-scale drought indicators. Global and Planetary Change, 151, 15-27. doi:10.1016/j.gloplacha.2016.06.011Borrego-Marín, M., Gutiérrez-Martín, C., & Berbel, J. (2016). Water Productivity under Drought Conditions Estimated Using SEEA-Water. Water, 8(4), 138. doi:10.3390/w8040138Vardon, M., Lenzen, M., Peevor, S., & Creaser, M. (2007). Water accounting in Australia. Ecological Economics, 61(4), 650-659. doi:10.1016/j.ecolecon.2006.07.033Pedro-Monzonís, M., del Longo, M., Solera, A., Pecora, S., & Andreu, J. (2016). Water Accounting in the Po River Basin Applied to Climate Change Scenarios. Procedia Engineering, 162, 246-253. doi:10.1016/j.proeng.2016.11.051Momblanch, A., Andreu, J., Paredes-Arquiola, J., Solera, A., & Pedro-Monzonís, M. (2014). Adapting water accounting for integrated water resource management. The Júcar Water Resource System (Spain). Journal of Hydrology, 519, 3369-3385. doi:10.1016/j.jhydrol.2014.10.002Karimi, P., Bastiaanssen, W. G. M., & Molden, D. (2012). Water Accounting Plus (WA+) – a water accounting procedure for complex river basins based on satellite measurements. doi:10.5194/hessd-9-12879-2012Karimi, P., Bastiaanssen, W. G. M., Molden, D., & Cheema, M. J. M. (2013). Basin-wide water accounting based on remote sensing data: an application for the Indus Basin. Hydrology and Earth System Sciences, 17(7), 2473-2486. doi:10.5194/hess-17-2473-2013Orth, R., & Destouni, G. (2018). Drought reduces blue-water fluxes more strongly than green-water fluxes in Europe. Nature Communications, 9(1). doi:10.1038/s41467-018-06013-7Van den Hurk, B., Hirschi, M., Schär, C., Lenderink, G., van Meijgaard, E., van Ulden, A., … Jones, R. (2005). Soil Control on Runoff Response to Climate Change in Regional Climate Model Simulations. Journal of Climate, 18(17), 3536-3551. doi:10.1175/jcli3471.1Bergström, S., Carlsson, B., Gardelin, M., Lindström, G., Pettersson, A., & Rummukainen, M. (2001). Climate change impacts on runoff in Sweden-assessments by global climate models, dynamical downscaling and hydrological modelling. Climate Research, 16, 101-112. doi:10.3354/cr016101Arnell, N. W. (1999). The effect of climate change on hydrological regimes in Europe: a continental perspective. Global Environmental Change, 9(1), 5-23. doi:10.1016/s0959-3780(98)00015-6Teuling, A. J., Van Loon, A. F., Seneviratne, S. I., Lehner, I., Aubinet, M., Heinesch, B., … Spank, U. (2013). Evapotranspiration amplifies European summer drought. Geophysical Research Letters, 40(10), 2071-2075. doi:10.1002/grl.50495Destouni, G., & Prieto, C. (2018). Robust Assessment of Uncertain Freshwater Changes: The Case of Greece with Large Irrigation—and Climate-Driven Runoff Decrease. Water, 10(11), 1645. doi:10.3390/w10111645Suárez-Almiñana, S., Pedro-Monzonís, M., Paredes-Arquiola, J., Andreu, J., & Solera, A. (2017). Linking Pan-European data to the local scale for decision making for global change and water scarcity within water resources planning and management. Science of The Total Environment, 603-604, 126-139. doi:10.1016/j.scitotenv.2017.05.259Huang, Z., Hejazi, M., Tang, Q., Vernon, C. R., Liu, Y., Chen, M., & Calvin, K. (2019). Global agricultural green and blue water consumption under future climate and land use changes. Journal of Hydrology, 574, 242-256. doi:10.1016/j.jhydrol.2019.04.046Kahil, M. T., Connor, J. D., & Albiac, J. (2015). Efficient water management policies for irrigation adaptation to climate change in Southern Europe. Ecological Economics, 120, 226-233. doi:10.1016/j.ecolecon.2015.11.004Velasco-Muñoz, J., Aznar-Sánchez, J., Belmonte-Ureña, L., & López-Serrano, M. (2018). Advances in Water Use Efficiency in Agriculture: A Bibliometric Analysis. Water, 10(4), 377. doi:10.3390/w10040377Berbel, J., & Mateos, L. (2014). Does investment in irrigation technology necessarily generate rebound effects? A simulation analysis based on an agro-economic model. Agricultural Systems, 128, 25-34. doi:10.1016/j.agsy.2014.04.002Pedro-Monzonís, M., Ferrer, J., Solera, A., Estrela, T., & Paredes-Arquiola, J. (2014). Water Accounts and Water Stress Indexes in the European Context of Water Planning: The Jucar River Basin. Procedia Engineering, 89, 1470-1477. doi:10.1016/j.proeng.2014.11.431Vanham, D., Hoekstra, A. Y., Wada, Y., Bouraoui, F., de Roo, A., Mekonnen, M. M., … Bidoglio, G. (2018). Physical water scarcity metrics for monitoring progress towards SDG target 6.4: An evaluation of indicator 6.4.2 «Level of water stress». Science of The Total Environment, 613-614, 218-232. doi:10.1016/j.scitotenv.2017.09.056Liu, J., Yang, H., Gosling, S. N., Kummu, M., Flörke, M., Pfister, S., … Oki, T. (2017). Water scarcity assessments in the past, present, and future. 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Agricultural landscape structure and biological control

La structure du paysage agricole est définie par l’hétérogénéité spatiale de la mosaïque de parcelles cultivées et de la matrice des habitats naturels. L’organisation spatiale des parcelles influence fortement le fonctionnement des agro-écosystèmes en déterminant les ressources disponibles, la diversité des espèces et les interactions entre le milieu cultivé et les espaces naturels. En particulier, la structure des habitats naturels et semi-naturels peut favoriser un ensemble de services écosystémiques, tels que la lutte biologique contre les ravageurs. Si la complexité paysagère est souvent associée à une plus forte régulation des ravageurs des cultures, cette relation peut être aussi ambiguë. Les habitats semi-naturels favorisent la présence et la diversité des espèces auxiliaires mais n’induisent pas forcément par un meilleur service de régulation. En effet, les espèces auxiliaires diffèrent dans leur cycle de vie, leurs comportements et leurs stratégies de prédation, s’influençant mutuellement de manière positive ou négative. Dans le cadre de cette thèse, nous approfondissons différents aspects de la complexité du paysage et des interactions entre espèces afin de mieux comprendre leurs effets sur le contrôle biologique. Dans une première partie nous abordons la question de la représentation de paysages agricoles réels pour permettre l’analyse structurelle du paysage et la génération de scénarios paysagers. Nous développons des outils statistiques pour représenter des paysages composés d’éléments surfaciques et linéaires. En particulier, nous nous intéressons à la distribution des catégories d’occupation du sol. Nous proposons une méthode de validation des modèles reposant sur un ensemble de métriques paysagères et nous développons un outil permettant la simulation de paysages agricoles. Les données paysagères proviennent de la basse vallée de la Durance (France). Dans une deuxième partie, nous définissons, sur les paysages simulés, un modèle proie-prédateur décrivant la dynamique de ravageurs et d’auxiliaires. Le modèle est spatialement explicite, il considère la dispersion des organismes à la fois dans les parcelles et le long des haies, ainsi que de potentiels traitements phytosanitaires. Nous démontrons que l’hétérogénéité spatiale du paysage et les traits d’histoire de vie du ravageur et de son auxiliaire jouent conjointement un rôle clé dans l’efficacité du service de contrôle du ravageur. Nous ne limitons pas notre analyse à l’échelle globale mais nous proposons aussi une nouvelle méthode pour étudier la dynamique du système à plusieurs échelles. Plus précisément, nous définissons un processus ponctuel spatio-temporel comme méta-modèle pour étudier le lien entre la dynamique localisée des pullulations de ravageur et les caractéristiques du paysage à différentes échelles spatiales. Enfin, dans une troisième partie, nous étendons nos recherches aux aspects évolutifs en abordant deux questions. Dans une première nous étudions comment l’hétérogénéité environnementale influence la structure phénotypique d’une population dont les traits de dispersion et de croissance sont soumis à un compromis évolutif. Ce travail est basé sur un modèle de type paysage adaptatif et nous nous attachons à caractériser de façon analytique les équilibres du système.Agricultural landscape structure is defined by the heterogeneity arising from a mosaic of cultivated patches within a natural matrix. The spatial arrangement of these agricultural habitats strongly influences ecosystem functioning and, therefore, determines environmental resources, species diversity and interactions. Specifically, the amount and the organisation of natural and semi-natural habitats can promote a bundle of desired ecosystem services, such as biological pest control. However, the relationships among desired effects and landscape complexity can be ambiguous. Even if semi-natural area favours natural enemy species presence and diversity, this might not be directly translated into a profitable advantage for natural pest suppression. The reason is that enemy species differ in their lifecycle, their behaviours and predating strategy, influencing each other in positive or negative ways. In this thesis, we deepen various aspects of the landscape complexity, population dynamics and their relationships to better understand the effect on conservation biological control. Firstly, we deal with the representation of real agricultural landscapes to allow for landscape structural analysis and scenario generation. We develop statistical tools to represent real landscapes composed by patches and linear elements, to capture the distribution of landscape features, and to simulate land-use category allocation. We estimate model parameters for sub-regions of the Lower Durance Valley (France), validate the model based on a diversity of landscape metrics and implement simulations of agricultural scenarios.Secondly, we couple landscape generation with population dynamics based on the landscape model through a spatially explicit predator-pest model taking into account pesticide applications, which are employed when biological control through predator efforts is not enough. We demonstrate that spatial heterogeneity, species traits and their interactions jointly play a key role for biological control outcomes. Since we recognise that integration of species traits with landscape structure at multiple scales are needed, and that the output aggregation over time and space cause information loss, we do not limit our analysis to the global scale. We propose a more parsimonious representation to take into account all the relevant information of spatially-explicit outputs to fully characterise spatio-temporal pestpredator dynamics. Specifically, we recur to meta-models based on spatio-temporal point processes. Through this multi-scale approach, we gain insights on both local and global spatio-temporal dynamics of predator-pest systems. Finally, we extend our analyses to theassessment of genetic diversity and behavioural strategies to better represent species adaptation to different drivers like environmental conditions and different predating pressure. During this thesis, we explore and integrate different spatio-temporal ranges (i.e., linear and areal landscape elements, global and local scales, temporal pest and predator evolution) and different biodiversity levels (multi-species, behavioural diversity and genetic diversity). By focusing on different perspectives, we enrich the existing knowledge and highlight the necessity of more integrated methods and efforts to better account for the various important dimensions of biodiversity, jointly with agricultural landscape complexity

Structure du paysage agricole et régulation des ravageurs : Effet de l'hétérogénéité spatiale du paysage sur la dynamique éco-évolutive d'un système prédateur-proie

Agricultural landscape structure is defined by the heterogeneity arising from a mosaic of cultivated patches within a natural matrix. The spatial arrangement of these agricultural habitats strongly influences ecosystem functioning and, therefore, determines environmental resources, species diversity and interactions. Specifically, the amount and the organisation of natural and semi-natural habitats can promote a bundle of desired ecosystem services, such as biological pest control. However, the relationships among desired effects and landscape complexity can be ambiguous. Even if semi-natural area favours natural enemy species presence and diversity, this might not be directly translated into a profitable advantage for natural pest suppression. The reason is that enemy species differ in their lifecycle, their behaviours and predating strategy, influencing each other in positive or negative ways. In this thesis, we deepen various aspects of the landscape complexity, population dynamics and their relationships to better understand the effect on conservation biological control. Firstly, we deal with the representation of real agricultural landscapes to allow for landscape structural analysis and scenario generation. We develop statistical tools to represent real landscapes composed by patches and linear elements, to capture the distribution of landscape features, and to simulate land-use category allocation. We estimate model parameters for sub-regions of the Lower Durance Valley (France), validate the model based on a diversity of landscape metrics and implement simulations of agricultural scenarios.Secondly, we couple landscape generation with population dynamics based on the landscape model through a spatially explicit predator-pest model taking into account pesticide applications, which are employed when biological control through predator efforts is not enough. We demonstrate that spatial heterogeneity, species traits and their interactions jointly play a key role for biological control outcomes. Since we recognise that integration of species traits with landscape structure at multiple scales are needed, and that the output aggregation over time and space cause information loss, we do not limit our analysis to the global scale. We propose a more parsimonious representation to take into account all the relevant information of spatially-explicit outputs to fully characterise spatio-temporal pestpredator dynamics. Specifically, we recur to meta-models based on spatio-temporal point processes. Through this multi-scale approach, we gain insights on both local and global spatio-temporal dynamics of predator-pest systems. Finally, we extend our analyses to theassessment of genetic diversity and behavioural strategies to better represent species adaptation to different drivers like environmental conditions and different predating pressure. During this thesis, we explore and integrate different spatio-temporal ranges (i.e., linear and areal landscape elements, global and local scales, temporal pest and predator evolution) and different biodiversity levels (multi-species, behavioural diversity and genetic diversity). By focusing on different perspectives, we enrich the existing knowledge and highlight the necessity of more integrated methods and efforts to better account for the various important dimensions of biodiversity, jointly with agricultural landscape complexity.La structure du paysage agricole est définie par l’hétérogénéité spatiale de la mosaïque de parcelles cultivées et de la matrice des habitats naturels. L’organisation spatiale des parcelles influence fortement le fonctionnement des agro-écosystèmes en déterminant les ressources disponibles, la diversité des espèces et les interactions entre le milieu cultivé et les espaces naturels. En particulier, la structure des habitats naturels et semi-naturels peut favoriser un ensemble de services écosystémiques, tels que la lutte biologique contre les ravageurs. Si la complexité paysagère est souvent associée à une plus forte régulation des ravageurs des cultures, cette relation peut être aussi ambiguë. Les habitats semi-naturels favorisent la présence et la diversité des espèces auxiliaires mais n’induisent pas forcément par un meilleur service de régulation. En effet, les espèces auxiliaires diffèrent dans leur cycle de vie, leurs comportements et leurs stratégies de prédation, s’influençant mutuellement de manière positive ou négative. Dans le cadre de cette thèse, nous approfondissons différents aspects de la complexité du paysage et des interactions entre espèces afin de mieux comprendre leurs effets sur le contrôle biologique. Dans une première partie nous abordons la question de la représentation de paysages agricoles réels pour permettre l’analyse structurelle du paysage et la génération de scénarios paysagers. Nous développons des outils statistiques pour représenter des paysages composés d’éléments surfaciques et linéaires. En particulier, nous nous intéressons à la distribution des catégories d’occupation du sol. Nous proposons une méthode de validation des modèles reposant sur un ensemble de métriques paysagères et nous développons un outil permettant la simulation de paysages agricoles. Les données paysagères proviennent de la basse vallée de la Durance (France). Dans une deuxième partie, nous définissons, sur les paysages simulés, un modèle proie-prédateur décrivant la dynamique de ravageurs et d’auxiliaires. Le modèle est spatialement explicite, il considère la dispersion des organismes à la fois dans les parcelles et le long des haies, ainsi que de potentiels traitements phytosanitaires. Nous démontrons que l’hétérogénéité spatiale du paysage et les traits d’histoire de vie du ravageur et de son auxiliaire jouent conjointement un rôle clé dans l’efficacité du service de contrôle du ravageur. Nous ne limitons pas notre analyse à l’échelle globale mais nous proposons aussi une nouvelle méthode pour étudier la dynamique du système à plusieurs échelles. Plus précisément, nous définissons un processus ponctuel spatio-temporel comme méta-modèle pour étudier le lien entre la dynamique localisée des pullulations de ravageur et les caractéristiques du paysage à différentes échelles spatiales. Enfin, dans une troisième partie, nous étendons nos recherches aux aspects évolutifs en abordant deux questions. Dans une première nous étudions comment l’hétérogénéité environnementale influence la structure phénotypique d’une population dont les traits de dispersion et de croissance sont soumis à un compromis évolutif. Ce travail est basé sur un modèle de type paysage adaptatif et nous nous attachons à caractériser de façon analytique les équilibres du système

Polymorphic population expansion velocity in a heterogeneous environment

How does the spatial heterogeneity of landscapes interact with the adaptive evolution of populations to influence their spreading speed? This question arises in agricultural contexts where a pathogen population spreads in a landscape composed of several types of crops, as well as in epidemiological settings where a virus propagates among individuals with distinct immune profiles. To address it, we introduce an analytical method based on reaction-diffusion models. We focus on spatially periodic environments with two distinct patches, where the dispersing population consists of two specialized morphs, each potentially mutating to the other. We present clear formulas for the speed together with criteria for persistence, accounting for both rapidly and slowly varying environments, as well as small and large mutation rates. Altogether, our analytical and numerical results yield a comprehensive understanding of persistence and spreading dynamics. Notably, compared to a situation without mutations or to a single morph propagating in a heterogeneous landscape, the introduction of mutations to a second morph with reverse specialization, while consistently impeding persistence, can significantly increase speed, even if the mutation rate between the two morphs is very small. Additionally, we find that the amplitude of the spatial fragmentation effect is significantly amplified in this case. This has implications for agroecology, emphasizing the higher importance of landscape structure in influencing adaptation-driven population dynamics

Markov random field models for vector-based representations of landscapes

International audienceIn agricultural landscapes the spatial distribution of cultivated and semi-natural elements strongly impacts habitat connectivity and species dynamics. To allow for landscape structural analysis and scenario generation, we here develop statistical tools for real landscapes composed of geometric elements, including 2D patches but also 1D linear elements (e.g., hedges). Utilizing the framework of discrete Markov random fields, we design generative stochastic models that combine a multiplex network representation, based on spatial adjacency, with Gibbs energy terms to capture the distribution of landscape descriptors for land-use categories. We implement simulation of agricultural scenarios with parameter-controlled spatial and temporal patterns (e.g., geometry, connectivity, crop rotation), and we demonstrate through simulation that pseudo-likelihood estimation of parameters works well. To study statistical relevance of model components in real landscapes, we discuss model selection and validation, including cross-validated prediction scores. Model validation with a view toward ecologically relevant landscape summaries is achieved by comparing observed and simulated summaries (network metrics but also metrics and appropriately defined variograms using a raster discretization). Models fitted to subregions of the Lower Durance Valley (France) indicate strong deviation from random allocation and realistically capture landscape patterns. In summary, our approach improves the understanding of agroecosystems and enables simulation-based theoretical analysis of how landscape patterns shape biological and ecological processes

Spatial heterogeneity alters the trade-off between growth and dispersal during a range expansion

Individuals who invest more in the development of their dispersal-related traits often reduce their investment in reproduction. Thus, there are two possible eco-evolutionary strategies: grow faster or disperse faster (R − D arbitrage). Here we explore, through a reaction-diffusion model, how spatial heterogeneity can shape the R − D trade-off by studying the spreading dynamics of a consumer species exploiting a resource in a spatially fragmented environment. Based on numerical simulations and analytical solutions derived from simpler models, we show that the classical mathematical symmetry between the effects of growth and dispersal on the spatial spreading speed is broken in the presence of competition between phenotypes. At the back of the forefront, the dynamics is almost always driven by the R specialists. On the forefront, R-strategies are favored in spatially homogeneous environments, but the introduction of heterogeneity leads to a shift towards D-strategies. This effect is even stronger when spatial heterogeneity affects the diffusion term and when spatial fragmentation is lower. Introducing mutations between phenotypes produces an advantage towards the R-strategy and homogenizes the distribution of phenotypes, also leading to more polymorphism on the forefront

Stochastic geometry and graph-based modeling of agricultural landscapes: towards better understanding of population dynamics in biological control

National audienc

High spatial resolution assessment of climate change impact on an Alpine watershed

ISSN:1029-7006ISSN:1607-796

More pests but less pesticide applications: Ambivalent effect of landscape complexity on conservation biological control

International audienceIn 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