Annals of Forest Science, is a source of information about current developments and trends in forest research and forestry

The European Food Safety Authority concluded in February 2018 that "most uses of neonicotinoid insecticides represent a risk to wild bees and honeybees". In 2016, the French government passed a law banning the use of the five neonicotinoids previously authorized: clothianidin, imidacloprid, thiamethoxam, acetamiprid and thiacloprid. In the framework of an expert assessment conducted by the French Agency for Food, Environmental and Occupational Health and Safety to identify possible derogations, we performed a thorough assessment of the available alternatives to the five banned neonicotinoids. For each pest targeted by neonicotinoids use, we identified the main alternative pest management methods, which we then ranked for (i) efficacy for controlling the target pest, (ii) applicability (whether directly useable by farmers or in need of further research and development), (iii) durability (risk of resistance in targeted pests), and (iv) practicability (ease of implementation by farmers). We identified 152 authorized uses of neonicotinoids in France, encompassing 120 crops and 279 pest insect species (or genera). An effective alternative to neonicotinoids use was available in 96% of the 2968 case studies analyzed from the literature (single combinations of one alternative pest control method or product × one target crop plant × one target pest insect). The most common alternative to neonicotinoids (89% of cases) was the use of another chemical insecticide (mostly pyrethroids). However, in 78% of cases, at least one non-chemical alternative method could replace neonicotinoids (e.g. microorganisms, semiochemicals or surface coating). The relevance of non-chemical alternatives to neonicotinoids depends on pest feeding habits. Leaf and flower feeders are easier to control with non-chemical methods, whereas wood and root feeders are more difficult to manage by such methods. We also found that further field studies were required for many promising non-chemical methods before their introduction into routine use by farmers. Our findings, transmitted to policymakers, indicate that non-chemical alternatives to neonicotinoids do exist. Furthermore, they highlight the need to promote these methods through regulation and funding, with a view to reducing pesticide use in agriculture.

Functional–structural plant models (FSPMs) explore and integrate relationships between a plant's structure and processes that underlie its growth and development. In recent years, the range of topics being addressed by scientists interested in functional–structural plant modelling has expanded greatly. FSPM techniques are now being used to dynamically simulate growth and development occurring at the microscopic scale involving cell division in plant meristems to the macroscopic scales of whole plants and plant communities. The plant types studied also cover a broad spectrum from algae to trees. FSPM is highly interdisciplinary and involves scientists with backgrounds in plant physiology, plant anatomy, plant morphology, mathematics, computer science, cellular biology, ecology and agronomy. This special issue of Annals of Botany features selected papers that provide examples of comprehensive functional–structural models, models of key processes such as partitioning of resources, software for modelling plants and plant environments, data acquisition and processing techniques and applications of functional–structural plant models for agronomic purposes.

Background and Aims Predicting light partitioning in crop mixtures is a critical step in improving the productivity of such complex systems, and light interception has been shown to be closely linked to plant architecture. The aim of the present work was to analyse the relationships between plant architecture and light partitioning within wheat–pea (Triticum aestivum–Pisum sativum) mixtures. An existing model for wheat was utilized and a new model for pea morphogenesis was developed. Both models were then used to assess the effects of architectural variations in light partitioning. Methods First, a deterministic model (L-Pea) was developed in order to obtain dynamic reconstructions of pea architecture. The L-Pea model is based on L-systems formalism and consists of modules for ‘vegetative development’ and ‘organ extension’. A tripartite simulator was then built up from pea and wheat models interfaced with a radiative transfer model. Architectural parameters from both plant models, selected on the basis of their contribution to leaf area index (LAI), height and leaf geometry, were then modified in order to generate contrasting architectures of wheat and pea. Key results By scaling down the analysis to the organ level, it could be shown that the number of branches/tillers and length of internodes significantly determined the partitioning of light within mixtures. Temporal relationships between light partitioning and the LAI and height of the different species showed that light capture was mainly related to the architectural traits involved in plant LAI during the early stages of development, and in plant height during the onset of interspecific competition. Conclusions In silico experiments enabled the study of the intrinsic effects of architectural parameters on the partitioning of light in crop mixtures of wheat and pea. The findings show that plant architecture is an important criterion for the identification/breeding of plant ideotypes, particularly with respect to light partitioning.