Browsing by Subject "phenology models"

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  • Tonnang, Henri E. Z.; Herve, Bisseleua D. B.; Biber-Freudenberger, Lisa; Salifu, Daisy; Subramanian, Sevgan; Ngowi, Valentine B.; Guimapi, Ritter Y. A.; Anani, Bruce; Kakmeni, Francois M. M.; Affognon, Hippolyte; Niassy, Saliou; Landmann, Tobias; Ndjomatchoua, Frank T.; Pedro, Sansao A.; Johansson, Tino Petri; Tanga, Chrysantus M.; Nana, Paulin; Fiaboe, Komi M.; Mohamed, Samira F.; Maniania, Nguya K.; Nedorezov, Lev V.; Ekesi, Sunday; Borgemeister, Christian (2017)
    A wide range of insects affect crop production and cause considerable yield losses. Difficulties reside on the development and adaptation of adequate strategies to predict insect pests for their timely management to ensure enhanced agricultural production. Several conceptual modelling frameworks have been proposed, and the choice of an approach depends largely on the objective of the model and the availability of data. This paper presents a summary of decades of advances in insect population dynamics, phenology models, distribution and risk mapping. Existing challenges on the modelling of insects are listed; followed by innovations in the field. New approaches include artificial neural networks, cellular automata (CA) coupled with fuzzy logic (FL), fractal, multi-fractal, percolation, synchronization and individual/agent based approaches. A concept for assessing climate change impacts and providing adaptation options for agricultural pest management independently of the United Nations Intergovernmental Panel on Climate Change (IPCC) emission scenarios is suggested. A framework for estimating losses and optimizing yields within crop production system is proposed and a summary on modelling the economic impact of pests control is presented. The assessment shows that the majority of known insect modelling approaches are not holistic; they only concentrate on a single component of the system, i.e. the pest, rather than the whole crop production system. We suggest system thinking as a possible approach for linking crop, pest, and environmental conditions to provide a more comprehensive assessment of agricultural crop production.
  • Lundell, Robin; Hänninen, Heikki; Saarinen, Timo; Åström, Helena; Zhang, Rui (2020)
    Bud dormancy of plants has traditionally been explained either by physiological growth arresting conditions in the bud or by unfavourable environmental conditions, such as non-growth-promoting low air temperatures. This conceptual dichotomy has provided the framework also for developing process-based plant phenology models. Here, we propose a novel model that in addition to covering the classical dichotomy as a special case also allows the quantification of an interaction of physiological and environmental factors. According to this plant-environment interaction suggested conceptually decades ago, rather than being unambiguous, the concept of "non-growth-promoting low air temperature" depends on the dormancy status of the plant. We parameterized the model with experimental results of growth onset for seven boreal plant species and found that based on the strength of the interaction, the species can be classified into three dormancy types, only one of which represents the traditional dichotomy. We also tested the model with four species in an independent experiment. Our study suggests that interaction of environmental and physiological factors may be involved in many such phenomena that have until now been considered simply as plant traits without any considerations of effects of the environmental factors.