Method of Quantifying interactions and its types

Agroforestry

1. College of Forestry and Research Station Mahatma Gandhi University of horticulture & Forestry sankra-patan , durg ( c.g. ) SESSION :- 2023-24 Topic :- Method for quantifying interactions and common multipurpose tree species suitable for agroforestry, purpose wise multipurpose tree species. Submitted to Submitted by Dr. Satya Prakash Vishwakarma Mr. Nishikant Krishan M.Sc.Forestry 1 st Sem.(SAF)

2. Content Methods of quantifying interaction in agroforestry Major tree -crop models available Wanulcas 2.0 Apsim crop Hypar or parch Wimisa Hi-safe-tree model Common and purposewise multipurpose tree species

3. Methods of quantifying interaction in agroforestry Introduction It is more meaningful to quantify tree crop interactions in terms of the various benefits and changes commonly observed in agroforestry system such as fertility improvement, soil moisture status and microclimate modification. To quantify effects of various factors in an agroforestry, a simple tree crop interaction (TCI) equation has been developed by Anon. (1993). TCI = F-C ± M ± P+L F - Benefits from agroforestry system(%) C - Yield reduction of field crops(%) M - Microclimatic changes viz.,temperature , light, humidity (%) P - Changes in soil properties(%) L - Benefits of soil conservation (%)

4. ICFRAF researchers have developed an equation for quantifying tree crop interactions ( I ), considering positive effects of trees and crop yields through soil fertility enrichment ( F ) and negative effects through competition (C ) for growth resources between crop and tree. I = F – C If F > C then the interaction is positive If F < C then the interaction is negative

5. MAJOR TREE -CROP MODELS AVAILABLE Wanulcas 2.0 Apsim crop Hypar or parch Wimisa Hi-safe-tree model

6. Wanulcas 2.0 The wanulcas 2.0 tree-crop model functions as a biophysical model designed to replicate the dynamic relationships between trees and crops within agroforestry systems . This model operates on a process-based approach, considering the physiological processes of both trees and crops, along with the environmental physical processes. It proves versatile in simulating various agroforestry systems, such as hedgerow intercropping, alley cropping, and fallows.

7. The Wanulcas 2.0 model comprises three primary submodels : The Tree submodel replicates the growth of trees, encompassing factors such as leaf area, root distribution, and nutrient uptake. The Crop submodel mimics the growth of crops, including considerations of leaf area, root distribution, and nutrient uptake. The Soil submodel emulates the movement of water and nutrients within the soil. Wanulcas 2.0 model serves as a potent instrument for: Designing and assessing agroforestry systems Evaluating the influence of agroforestry on crop yields Investigating the interactions between trees and crops Formulating management practices for agroforestry systems

8. APSIM CROP MODEL APSIM, the agricultural production systems simulator is a modelling platform for simulation of biophysical processes in cropping systems, particularly those relating to the production and ecological outcomes of management practices in the face of climate risk. It resulted from a need for research tools that provided accurate predictions of crop production in relation to climate, genotype, soil and farmer management factors while addressing the long-term natural resource management issues. A particular focus is the simulation of sequences of crops, rotations, and fallow periods, rather than just single crops in their response to daily soil and climate variables.

9. MODEL FEATURE Growth and yield simulation of more than 25 crops. Growth and biomass simulation of pastures. Growth and biomass of trees. Crop growth and development, yield, soil water and nitrogen dynamics either for single crop or crop rotations in response to climatic and management changes. Apsim is capable of carrying out simulation studies for various farming systems and weed competition. Carbon decomposition and surfaces residues .The effect of climate change simulation. Production of socio-economic effects simulation

10. HYPAR AND PARCH MODEL Hypar is a limited “hybrid” forest model and “PARCH” (predicting arable resource capture in hostile environments) crop model that was recently used for the evaluation of different management options under AFS . Previously it has been used to predict AF productivity. Although, it is a biophysical process-based model and has the potential to simulate light, water, nutrient competition, and daily carbon allocation, its use is limited due to complex challenges and poor responses to interaction processes. The 3d approach is also being used for water and nutrient competition depending on the root length density The tree model simulates competition based on physiology (photosynthesis, stomatal conductance, and transpiration) and canopy height, while nutrient fluxes are determined at different soil depths.

11. Wimisa Model Wimisa (windbreak-millet- sahel ) is a tree-crop competition model designed for modelling millet growth in windbreak-shielded fields in the sahel . A bilateral symmetry along the windbreak line was assumed, reducing the modelling to only one. Side of the windbreak Three crop zones were modelled. Wimisa does not model the influence of the crop competition on the tree growth. The windbreak is therefore a fixed component in the system, making the wimisa model only a partial tree-crop interaction model. Therefore, wimisa can not be used in modelling dynamic tree-crop temperate systems, where tree inter-annual dynamics are influenced by the crop. Application of the model in niger showed that the water consumption by the windbreak was not compensated by a reduction of evaporation of the protected crop.

12. Hi-Safe Model Hi-safe, a three-dimensional (3D), process-based, biophysical model that integrates tree–crop interactions in agroforestry systems. Hi-safe has been under development since 2002 via the silvoarable agroforestry for europe (SAFE) project and was partially described by talbot . the model attempts to overcome the gaps and weaknesses of existing agroforestry models by capturing spatial and temporal heterogeneity.

13. main hypotheses directed Hi- sAFe development Productivity of an agroforestry system depends on the acquisition of heterogeneously distributed resources by trees and crops . Tree–crop interactions are, in part, governed by aboveground, belowground, and phenological plasticity . To explore these hypotheses, the specific objectives of hi-safe development were to create a model that could simulate: Three-dimensional tree–crop interactions for light, water, and nitrogen; Plastic aboveground and belowground tree architecture responsiveness to resource availability; The full lifetime of the system, from tree planting to harvest, on a daily time-step; and The principal agroforestry design and management strategies, such as branch pruning, tree thinning, root pruning, and the incorporation of an uncropped area around each tree or strip along the tree row.

14. COMMON AND PURPOSEWISE MULTIPURPOSE TREE SPECIES MPTS as windbreaks and living fences SPECIES CLIMATE OTHER USE Acacia nilotica arid, semiarid tropics beverage, fuelwood Acacia tortillis semiarid tropics fuelwood Azadirachta indica semiarid tropics timber, lumber, manure, essential oils, fuelwood Casuarina equisetifolia humid tropics fuelwood, timber Eucalyptus camaldulensis humid tropics fuelwood, timber Gliricidia sepium humid tropics food, fuelwood, poles, fodder Grevillea robusta subhumid tropics, humid tropics timber, fuelwood, building materials Leucaena leucocephala humid subtropics, humid tropics fuelwood, poles timber fodder Sesbania grandiflora humid tropics fodder, fuelwood, food

15. SPECIES CLIMATE OTHER USE Acacia tortillis semiarid tropics Fuelwood Albizia lebbek humid tropics, semiarid tropics fuelwood, timber Calliandra calothyrsus humid tropics lumber, fuelwood Dalbergia sissoo semiarid tropics timber, fuelwood Gliricidia sepium humid tropics food, fuelwood, poles Leucaena leucocephala humid subtropics, humid tropics fuelwood, poles, crop shade, timber Prosopis cineraria semiarid tropics, arid tropics Windbreak Sesbania grandiflora humid tropics fuelwood, food Ziziphus mauritiana semiarid tropics, subhumid tropics food, shade

16. References https://www.treesforlife.info/gmptsf/mptinaf.htm Dupraz , C., Wolz , K.J., Lecomte , I., Talbot, G., Vincent, G., Mulia , R., Bussière , F., Ozier -Lafontaine, H., Andrianarisoa , S., Jackson, N. and Lawson, G., 2019. Hi- sAFe : a 3D agroforestry model for integrating dynamic tree–crop interactions. Sustainability, 11(8), p.2293. Ahrends , H.E., Raza, A. and Gaiser , T., 2023. Current approaches for modeling ecosystem services and biodiversity in agroforestry systems: Challenges and ways forward.  Frontiers in Forests and Global Change ,  5 , p.1032442. Dupraz , C., 2002. Tree-crops interaction model. State of the art report. Deliverable 1.1. 1 of the SAFE Europeans Research Contract (p. 32). QLK5-CT-2001-00560. Gaydon, D., 2014. The APSIM model–An overview. SAC Monograph: The SAARC-Australia Project Developing Capacity in Cropping Systems Modelling for South Asia, pp.15-31. Khasanah , N., van Noordwijk , M., Slingerland, M., Sofiyudin , M., Stomph , D., Migeon , A.F. and Hairiah , K., 2020. Oil palm agroforestry can achieve economic and environmental gains as indicated by multifunctional land equivalent ratios. Frontiers in Sustainable Food Systems, 3, p.122. Mutanal , S.M. and Nadagoudar , B.S., 2010. Quantifying Tree-Crop Interaction in Agroforestry System. Karnataka Journal of Agricultural Sciences, 17(4).