Initial modelled outputs at field scale

This report comprises Deliverable 6.16 in the project, which contributes to the third objective as it presents field-scale evaluation of innovations, in order to adapt and evaluate agroforestry designs and practices for locations where agroforestry is currently not-widely practised or declining. The modelling of outputs at field scale to support best agroforestry practices is an ongoing activity during the AGFORWARD project. This report highlights some of the outputs which has been produced in the form of three papers (either submitted or about to be submitted to a peer-reviewed journal) or in four presentations at the Third European Agroforestry Conference in May 2016N/

How is agroforestry perceived in Europe? An assessment of positive and negative aspects by stakeholders

Whilst the benefits of agroforestry are widely recognised in tropical latitudes few studies have assessed how agroforestry is perceived in temperate latitudes. This study evaluates how stakeholders and key actors including farmers, landowners, agricultural advisors, researchers and environmentalists perceive the implementation and expansion of agroforestry in Europe. Meetings were held with 30 stakeholder groups covering different agroforestry systems in 2014 in eleven EU countries (Denmark, France, Germany, Greece, Hungary, Italy, Netherlands, Portugal, Spain, Sweden and the United Kingdom). In total 344 valid responses were received to a questionnaire where stakeholders were asked to rank the positive and negative aspects of implementing agroforestry in their region. Improved biodiversity and wildlife habitats, animal health and welfare, and landscape aesthetics were seen as the main positive aspects of agroforestry. By contrast, increased labour, complexity of work, management costs and administrative burden were seen as the most important negative aspects. Overall, improving the environmental value of agriculture was seen as the main benefit of agroforestry, whilst management and socio-economic issues were seen as the greatest barriers. The great variability in the opportunities and barriers of the systems suggests enhanced adoption of agroforestry across Europe will be most likely to occur with specific initiatives for each type of system

Hi-sAFe: a 3D agroforestry model for integrating dynamic tree–crop interactions

Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree–crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree–tree and tree–crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model’s 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice

Anisotropic diffusion equations for adaptive quadratic representations

Adaptive diffusion techniques for processing timefrequency representations were first proposed by Payot and Gonçalvès in 1998 as an application of the Perona and Malik adaptive diffusion. In this communication we consider both this technique and the anisotropic diffusion of Weickert, which allows to tune orientation and shape of smoothing kernels. We propose a new adaptive diffusion scheme where the strength and the orientation of the anisotropic kernel are locally tailored to the processed time-frequency representation. We provide a comparison with other signal-dependent techniques. Finally we define a diffusion tensor that can be used to process time-frequency representations of the affine class, ensuring the preservation of their covariance properties. 1

Diffusion equations for adaptive affine distributions

In this paper, we propose an extension of the adaptive diffusion technique for time-frequency representations proposed by Payot and Gonçalvès in 1998. Instead of processing time-frequency representations and keeping the covariance with respect to time and frequency shifts untouched, our adaptive filtering technique processes time-scale representations of the affine class while preserving the covariance properties of such representations. In order to obtain representations with improved readability, we aim at removing cumbersome interference terms while not blurring the signal terms. We show that the association of a conductance function to our diffusion scheme can make significant improvement toward reaching this goal. Indeed a conductance function provides a way to adapt locally the amount of smoothing to the representation. Note that the adaptivity of this affine technique is not based on any waveform dictionary as matching pursuit algorithms. 1