Julien Malard-Adam
@ird.fr
Chargé de recherche, G-Eau
Institut de recherche pour le développement
Scopus Publications
Scopus Publications
Juliana Isaac, Jaime Luís Carrera, Ottoniel Monterroso Rivas, Juventino Gálvez Ruano, María Rueda Martínez, Azam Khowaja, Julian Russell, Julien Malard‐Adam, Humberto Monardes, Jan Adamowski,et al.
Wiley
AbstractVarious methods have been proposed to analyze national trends of malnutrition and food insecurity; however, these methods often fail to consider regional specificities that drive national food security dynamics. This case study seeks to close this gap through the novel use of participatory causal loop diagrams (CLDs) to analyze the malnutrition crisis and food security dynamics across diverse regions of Guatemala. Stakeholders from six municipalities with divergent food security outcomes, within territories of similar socioeconomic composition, created CLDs by identifying trends, causes, and consequences of malnutrition and food security. Characterizing and assessing these trends, referred to as the food security dynamic, are the primary goals of this paper. Key results include identification of the complex reinforcing relationship between marginalization, education, and health, which affects food insecurity and malnutrition in Guatemala in a nonlinear way. These results elucidate how similar communities can experience divergent food security outcomes and inform locally appropriate solutions. © 2023 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.
Joel Z. Harms, Julien J. Malard-Adam, Jan F. Adamowski, Ashutosh Sharma, and Albert Nkwasa
Copernicus GmbH
Abstract. Participatory water resource management requires modeling techniques that are accurate and flexible yet stakeholder-friendly. While different modeling frameworks offer advantages and disadvantages, system dynamics (SDs) models have seen sustained use as a stakeholder-friendly approach for participatory water resource modeling. Physically based models (e.g., SWAT+) have seen sustained use to model the hydrological components of water systems. Proposed as a way to combine the relative strengths of both modeling paradigms, model coupling allows researchers to, for example, build participatory SD models with stakeholders, while delegating the hydrological components of the overall model to an external hydrological model. Recently developed to facilitate model coupling, the Tinamït Python package presents an extensible, outward-facing application programming interface (API). It allows for the development of extensions (wrappers) that expand compatibility with different physically based models. However, no watershed hydrological model has yet been connected to this API. In the present study, a socket and JavaScript Object Notation (JSON)-based communication protocol was developed with the goal of facilitating the coupling of models written in languages such as Fortran. This novel protocol served to develop a Tinamït-compatible wrapper for the hydrological model SWAT+, allowing it to be coupled to human–water SD models. The novel coupling protocol was then applied to a case study of Tanzania's Usa river catchment. This approach provides the modeler with the benefits of both physically based and SD models, thereby allowing the detection of potentially far-reaching effects of policy-makers' decisions.
Jessica A. Bou Nassar, Julien J. Malard, Jan F. Adamowski, Marco Ramírez Ramírez, Wietske Medema, and Héctor Tuy
Copernicus GmbH
Abstract. Unconventional sources of data that enhance our understanding of internal interactions between socio-economic and hydrological processes are central to modeling human–water systems. Participatory modeling (PM) departs from conventional modeling tools by informing and conceptualizing human–water systems through stakeholder engagement. However, the implementation of many PM processes remains biased, particularly in regions where marginalized communities are present. Many PM processes are not cognizant of differentiation and diversity within a society and tend to treat communities as homogeneous units with similar capabilities, needs, and interests. This undifferentiation leads to the exclusion of key actors, many of whom are associated with marginalized communities. In this study, a participatory model-building framework (PMBF), aiming to ensure the inclusiveness of marginalized stakeholders – who (1) have low literacy, (2) are comparatively powerless, and/or (3) are associated with a marginalized language – in participatory modeling, is proposed. The adopted approach employs interdisciplinary storylines to inform and conceptualize human–water systems. The suggested method is underpinned by the multi-level perspective (MLP) framework, which was developed by Geels et al. (2002) to conceptualize socio-technical transitions and modified in this study to accommodate the development of interdisciplinary storylines. A case study was conducted in Atitlán Basin, Guatemala, to understand the relationships that govern the lake's cultural eutrophication problem. This research integrated key stakeholders from the Indigenous Mayan community, associated with diverse literacy ranges, and emerging from three different marginalized linguistic backgrounds (Kaqchikel, Tz'utujil, and K'iche'), in the PM activity. The proposed approach facilitated the participation of marginalized stakeholders. Moreover, it (1) helped develop an understanding of mechanisms governing the eutrophication of the lake, (2) initiated a dialogue between Indigenous Peoples and non-Indigenous stakeholders, and (3) extracted potential solutions targeting the system's leverage points. The participatory model-building activity generated three submodules: (1) agriculture, (2) tourism, and (3) environmental awareness. Each submodule contained socioculturally specific mechanisms associated with nutrient discharge to Lake Atitlán. The delineation of such nuanced relationships helps develop well-targeted policies and best management practices (BMPs). Additionally, the suggested process helped decrease the impact of power imbalances in water resources management and empowered community-based decision-making.
Jordan M. Carper, Mohammad Reza Alizadeh, Jan F. Adamowski, Azhar Inam, and Julien J. Malard
Resilience Alliance, Inc.
In classic resilience thinking, there is an implicit focus on controlling functional variation to maintain system stability. Modern approaches to resilience thinking deal with complex, adaptive system dynamics and true uncertainty; these contemporary frameworks involve the process of learning to live with change and make use of the consequences of transformation and development. In a socio-environmental context, the identification of metrics by which resilience can be effectively and reliably measured is fundamental to understanding the unique vulnerabilities that characterize coupled human and natural systems. We developed an innovative procedure for stakeholder-friendly quantification of socio-environmental resilience metrics. These metrics were calculated and analyzed through the application of discrete disturbance simulations, which were produced using a dynamically coupled, biophysical-socioeconomic modeling framework. Following the development of a unique shock-response assessment regime, five metrics (time to baseline-level recovery, rate of return to baseline, degree of return to baseline, overall post-disturbance perturbation, and corrective impact of disturbance) describing distinct aspects of systemic resilience were quantified for three agroecosystem variables (farm income, watertable depth, and crop revenue) over a period of 30 years (1989–2019) in the Rechna Doab basin of northeastern Pakistan. Using this procedure, we determined that farm income is the least resilient variable of the three tested. Farm income was easily diverted from the “normal” functional paradigm for the Rechna Doab socio-environmental system, regardless of shock type, intensity, or duration combination. Crop revenue was the least stable variable (i.e., outputs fluctuated significantly between very high and very low values). Water-table depth was consistently the most robust and resistant to change, even under physical shock conditions. The procedure developed here should improve the ease with which stakeholders are able to conduct quantitative resilience analyses.
Julien Malard, Jan Adamowski, Jessica Bou Nassar, Nallusamy Anandaraja, Héctor Tuy, and Hugo Melgar-Quiñonez
Ecological Modelling Elsevier BV
Abstract Correct modelling of relationships between predators and prey is crucial to ecological and population dynamics models. However, and despite a long-standing competition between ratio and prey-dependent models (and a few alternative intermediate forms) in the literature, most equations currently used to represent such relationships do not meet theoretical criteria for biological consistency. This research proposes a set of universally applicable criteria for all predation equations and shows that the most commonly used predation equations in the literature fail to meet these same criteria. We follow with a proposal for a new predation equation that does meet these criteria, which combines both prey and ratio-dependent concepts while giving reasonable predictions in the cases of both high predator or high prey densities. We show its empirical performance by applying the new equation, along with existing alternatives, to various experimental predation datasets from the literature. Results show that the new equation is not only more mathematically consistent than existing equations, but also performs more consistently empirically across different datasets from various ecological situations. This research is the first to propose a systematic set of criteria to evaluate predation equations and then to offer an equation that meets these criteria and also performs well both theoretically and empirically across datasets from a wide range of predation systems.
Julien J Malard, Jan Franklin Adamowski, Marcela Rojas Díaz, Jessica Bou Nassar, Nallusamy Anandaraja, Héctor Tuy, Luís Andrés Arévalo-Rodriguez, and Hugo Ramiro Melgar-Quiñonez
European Journal of Agronomy Elsevier BV
Abstract Agroecological food web modelling, which models trophic relationships between the species present in agricultural fields, has significant potential uses in the fields of theoretical and practical agroecology, specifically regarding the planning and evaluation of integrated pest management and biocontrol strategies. However, the practical use of such models with field data has been hindered by their complexity and difficulty in calibration, as well as the lack of software tools to streamline and standardise their development and evaluation. In this research we present a new modular software tool, Tiko’n, which allows users to rapidly (within a few lines of Python code) develop, calibrate and validate agroecological food web population dynamics models based on observed field population data. We then demonstrate its use in developing a food web model of a coconut pest in Sri Lanka and apply the model to assessing the potential impact of alternative biocontrol strategies. The software allowed for very rapid model development and adjustment and showed that smaller parasitoid releases may be more efficient than a single, larger application. It is the authors’ hope that this tool will contribute to a more widespread use of agroecological food web modelling in research and agronomic practice.
Julien J Malard, Jan Franklin Adamowski, Marcela Rojas Díaz, Jessica Bou Nassar, Nallusamy Anandaraja, Héctor Tuy, Luís Andrés Arévalo-Rodriguez, and Hugo Ramiro Melgar-Quiñonez
Ecological Modelling Elsevier BV
Abstract The question of whether organic or conventional agriculture is most suitable for meeting world food requirements and improving resilience to climate change is the topic of much current research. Most comparisons, however, focus either on output efficiency such as yields or on impacts of different nutrient management strategies on the sustainability of the agrosystems, and the impacts of each on the agricultural food webs and beneficial insects responsible for pest control – or outbreaks – has been often overlooked. While standard cropping models can explain if, why and how organic nutrient and crop management work and how they should be adapted to climate change, the lack of mechanistic models of agroecology prevents us from explaining why and how passive and active biocontrol and integrated pest management function, when they do not function, and what optimal management strategies could be employed. In this research, we show that agroecological food web models calibrated with field population dynamics data can be used to demonstrate the mechanisms behind food web dynamics that have been previously observed in the field. Results of scenario simulations show that chemical control provides immediate relief from pest pressures, but at high risk of later pest resurgence if control is not repeated; on the contrary, biological control requires more time to reduce pest populations to acceptable levels but with minimal risk of causing resurgence. In all cases, success of pest control measures is highly dependent on the date of action. In addition, the use of modelling tools to optimise biological control application dates led to much better control than either fixed date or pest population threshold-based applications. These analyses and resulting integrated pest management intervention recommendations are only possible with agroecological food web population dynamics models. We encourage future studies to examine more complex food webs from a variety of agroecosystems to test whether functional responses differ significantly, and hope that this approach will succeed in bringing agroecological food web predictive modelling to the level where it can routinely be used as a decision-making support tool, as hydrological and crop models are employed today.
Günter Blöschl, Marc F.P. Bierkens, Antonio Chambel, Christophe Cudennec, Georgia Destouni, Aldo Fiori, James W. Kirchner, Jeffrey J. McDonnell, Hubert H.G. Savenije, Murugesu Sivapalan,et al.
Informa UK Limited
ABSTRACT This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.
Azhar Inam, Jan Adamowski, Shiv Prasher, Johannes Halbe, Julien Malard, and Raffaele Albano
Elsevier BV
Azhar Inam, Jan Adamowski, Shiv Prasher, Johannes Halbe, Julien Malard, and Raffaele Albano
Elsevier BV
J.J. Malard, A. Inam, E. Hassanzadeh, J. Adamowski, H.A. Tuy, and H. Melgar-Quiñonez
Elsevier BV
Andres Sierra-Soler, Jan Adamowski, Julien Malard, Zhiming Qi, Hossein Saadat, and Santosh Pingale
Informa UK Limited
Satellite observations of the spectral properties of vegetation can provide insights on crop conditions and yield, and, furthermore, can monitor the impact of droughts. In the case of rainfed crops grown for self-sufficiency, a drought can result in significant human suffering, highlighting the need to understand how droughts affect the landscape in such regions. This paper uses remote sensing to assess the phenomenological impacts of two isolated droughts, distinguishing the response of different vegetation covers in semiarid developing regions where rainfed agriculture is common. Using the standardized precipitation index, one normal and two dry years were selected (2000, 2005, and 2011, respectively). An original protocol for land use land cover (LULC) classification that combines climatic, topographic, and reflectance information from 18 Landsat ETM+ images was applied to subsequently distinguish drought effects in different classes through the selected years. Finally, two vegetation indices (normalized difference vegetation index (NDVI) and vegetation condition index (VCI)) were calculated to detect drought severity impacts over the different LULC classes. This approach was tested in Central Mexico and provided accurate information on the location and extent of areas affected by drought. The proposed approach can be used as a system for drought risk management in semi-arid developing regions.
Bogdan Ozga-Zielinski, Maurycy Ciupak, Jan Adamowski, Bahaa Khalil, and Julien Malard
Elsevier BV
A.A. Tagar, Ji Changying, Ding Qishuo, Jan Adamowski, Julien Malard, and Farid Eltoum A
Elsevier BV
A. Araghi, M. Mousavi Baygi, J. Adamowski, J. Malard, D. Nalley, and S.M. Hasheminia
Elsevier BV
A.A. Tagar, Ji Changying, Jan Adamowski, Julien Malard, Chen Shi Qi, Ding Qishuo, and N.A. Abbasi
Elsevier BV