Sustainable agriculture

Sustainable agriculture

What is the problem with the current model of monoculture-based agriculture? The research done on improvement of agricultural practices and environmentally friendly methods has mainly focused on one single plant or crop, adapting its properties to the needs of the human users, or adapting the environment to the requirements of the crops. While this has proven efficient, some environmental concerns and economical limitations motivate the search for other improvement areas. Therefore, many suggestions are drawn, aiming at reducing the environmental footprint of agriculture which is also one of the biggest water consumer and a cause of several health issues.

What is the limitation of the already existing alternative models, in particular pluricultures?

The best-known model pictured as alternative is organic farming, which focuses on the environmental impact of pesticides and their impact on human health. While is shows real effect on the quality of the crops produces, it is often criticized for its lower yield and its lower capacity to resist pests. Furthermore, it does not offer in this form a real way out from the industrial concept, therefore also depending on parallel energy- and technology chains. Additionally, the issue about the competing space of crops is not addressed.

On the other hand, some promising research has been done on intercropping, agroforestry and similar biomimicry-based practices. The potential of biomimicry, in this case of synergetic interactions between plants and with other symbiotic organisms is often overseen, neglected or limited to very few applications in the organic agriculture or aesthetical, private gardening.

However, the limited knowledge or reproducibility, the idea of stepping out of a well-established production chain organized on monoculture, the time consumption of new trials and failures, with the risk of harvest losses and its accompanying human consequences have put a brake to the application of plant grouping into agricultural methods.

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How to choose wisely and efficiently clusters of plants who can remediate and area, while preserving the environment on the long term and providing a useful output -crops or other income related activities – for locals? 

We suggest deepening this approach by overcoming some of the current hurdles associated with agriculture, offering tools for the development and application of acceptable alternatives, in particular for the choice of crop partnerships.

Toward a solution: Trust the Cluster

Let’s start filling this gap through a tool enabling to design simplified ecosystem-inspiredclusters, or bio-clusters, a tool which would be 1) a method which allows the collection and accessibility of reliable information about plants and alternative systems to a large number of users, 2) a prediction model for known and potential win-win partnerships of plant clusters, flexible enough to exploit information about local conditions, and 3) a tool improving as new information is acquired. This tool should be developed further as more information is acquired, into a prediction and simulation model for several-component ecosystem-like systems over time.

The basics

collection of current knowledge in a reliable and organized way and its availability to a large number of users,

The tool proposed consists of an interactive flora and microorganism database. It will contain a catalogue of plant categories and properties, their ecological strength and partners, but will also provide a list of possible plant or microorganism partnerships adapted to the conditions required. It should be able to answer questions about present knowledge about botanics and practices, organise knowledge about soil/plant compatibilities and known symbiotic partners.

The cluster proposer

a prediction model which suggests potential win-win plant- or other symbiotic partnerships, as adapted as possible to the given soil/climatic conditions, especially where no knowledge is available

The tool is thought to provide enough reliable information in order to establish a more ecosystem-based way to conceive cultivation and vegetation, by growing more than one species at the time, as a system rather than a single isolated species. We name this association a “cluster”.

The user will choose requirements from soil, climate, plant partners or other known local specificities to filter a choice of plant clusters with the highest probability of growth under the given criteria and present knowledge. The ranking of these suggestions will be based on a score given based on the match with the given conditions on one side, and on the availability and reliability of data on the other side.

Improving by using

a tool improving as new information is acquired: dynamic acquisition of data while experiments or applications are run

It is meant to become a growing interactive tool. The more knowledge is added, the more solid the suggestions will be. So it can be extended to an open source database, where users can use their experiments as new input to improve further use. In this way, introducing a quality standard for input data, users could also become contributors to a more complex and useful version of this tool, towards simulation and prediction. The functioning tool will therefore accelerate the collection of a new type of data, the methodology and results of harvest and sustainability.

The cluster simulator

a prediction model for harvest and system resilience against climatic or pest events

Using data that include dynamics or a time line, as soil % coverage, biomass produced, harvest, resistance and recovery against hazards (pests, extreme or unexpected weather/climatic events), ecological impact, interaction with other organisms (insects, mammals, etc.). This tool will be able provide, at a later development stage, an estimation of the gains (compared with a monoculture), and a time scale, allowing a real simulation for several-component ecosystem-like systems over time. In this way, it will be really able to establish a solid base to support alternative plant growth models, providing realistic expectations about growth and harvest over time, including ecological criteria as biodiversity.

In practice – Trust the Cluster

Examples of data output

Example of an imaginary interactive overview page for interactions. Different commands, filters and levels can be chosen from
  • (1) One circlecontains Kingdom or Family or Species, chosen through the level comand (size: number of species listed under the family/kingdom)
  • (2) Circle colordepends on command (according to higher level classification – for example all Fabaceae green at species level, all plants green at family level, or all trees brown if classified by trivial classification or space organization)
  • (3) Connection lines: Thickness corresponds to the number of known connections (color code stating if symbiosis, synergy or antagonism, or controversial data, who depend on variety, age, etc)
  • (4) Commandsallow to choose level (species, botanical family, trivial classification, only plants, also fungi and bacteria, etc. )
  • (5) A filtercan also be applied to hide species from certain climate zones, show only plants with certain properties etc.

To improve the readability, a useful feature would be passing the mouse over a circle causing enlarging names in small circles, and also showing specifically the connections of this circle, fading the rest.

Example 2 of an imaginary result sheet. Harvest over the years, long term gains are shown. Some crops mature later, some crops can be planted and therefore produce only while other are not fully grown.
Example 3 of an imaginary result sheet. 2 clusters proposed with proportions, harvest time, and experience about the combination; the user can evaluate between fast gain and fast renewal or slower gain and long-term harvest – optional add-on: biodiversity points and pest- fitness

The output simulation can also be displayed as a time lapse, with different aspect shown: soil coverage, water storage, metal content, yield, resilience level, biodiversity level, etc. (different possibilities can be evaluated; growth/metal content/yield curves with a moving curser over the time axis, or as a schematic plant organization and changing soil coverage).

In practice - Application example: Remediation of an urban or peri-urban site, embedment in a local fiber processing stream

This example presents in simplified manner the application of the tool and the corresponding agricultural method to the revival of an abandoned urban or peri-urban industrial site, with a local community with history or potential in fiber manufacturing.

After an evaluation of existing or reusable resources on one hand, and an evaluation of areas in need of restructuration (buildings and soil), the cluster tool helps to choose the adapted clusters for remediation (of industrial pollution, depletion) and value creation (fertilization, fiber production). Together with the conception of restructuration and repurposing (where to do what), the practical part includes the physical preparation of clusters (seeds, seedlings, sheets, nutrients) and soil preparation: de-paving and setting of remediation of soil (clusters) – re-use and remediate pavement. The participation of locals and specialists in fiber manufacturing is a critical factor for the success.

Embedding the bio-cluster in a decomposable cloth sheet

Embedding the bio-cluster (= starter set of seeds and microbiological plant partners) in a decomposable cloth sheet is at the same time a mean for remediation and a possible product for the harvested plants.

The characteristics and advantages of such a design are:

  • Synergetic strategic plant combination, with a preference for perennials or perennials & annuals
  • Addition of organic C to soil
  • Less erosion, more soil stability
  • Faster re-vegetation
  • Useful for conservation (dry) and transportation
  • Low on-site technology need
  • Protection of seeds against birds
  • Good reproducibility for experiments
  • Possible use of low quality fibers to make the sheets

Schematic action plans for the revival of a site and integration of the soil remediation through the bio cluster in a fiber manufacture.


The proposed bio-cluster designing tool is a way to close the gap between the current model for monoculture-, high human input-based system and a polyculture-, high resilience, lower ecological footprint-based system.

This should be a step towards a better usability of already existing data, giving a motivation to save years of hazardous experimenting and a chance to improve growth or resilience of cultivations, especially where little knowledge is present (remediation plants, challenging soil conditions).

Furthermore, as a universal, open-source prediction model for known and potential win-win partnerships of plant clusters, flexible enough to exploit information about local conditions, it will accelerate the applicability of intercropping–type methods. The user will choose requirements from soil, climate, plant partners or other known local specificities to filter a choice of plant clusters with the highest probability of growth under the given criteria and present knowledge, keeping in mind an improving tool the more it gets used.

In order to ease the application of such new concepts, the tool shall propose already some optimized clusters as “base packages” or “model systems” for a given climatic zone and common encountered soil or other conditions (= list of cluster plants and their proportions + planting and settling steps + microbial partners + description of their uses and advantages), which allows also the development of adapted harvest techniques and down-stream processing.

Other possible kits:

  • Fast revegetation kit
  • Erosion protection
  • Soil fertility increase
  • Pollinator mixture
  • Remediation combination
  • Soil decompaction
  • Intercropping for food
  • Intercropping for fibres

…Or combinations or thereof

As an open-source tool embedded in a human network, this can ease a conversion to an agroforestry model, partly resolving the deforestation/agriculture dilemma, can give an alternative to deforestation through coppicing and inter-cultures to sustain the soil in the main time, and will have significant consequences on soil stability, climate and pollination. It can also reduce the impact of the dependency on one species and empowers the local initiatives and cultures.

My name is Tsilla Boisselet, I was born and raised in France and Austria, and lived in several countries in Europe and outside. I am an environmental scientist, a wife, mother and sister, and a fervent learner and teacher, with a passion for nature, languages, recycling and geography. My drive to see the whole picture and understand the complexity of interactions motivated my choice to dive into the environmental sciences professionally. The ecology is indeed the crossing point of applied chemistry, biology, physics and geology, and influences also many aspects of human activity. Apprehending the world as an ecosystem with the human in it spurs me to embrace (bio)diversity, balance and cooperation.

I believe ecological issues are deeply linked to human activities and therefore solutions come from connecting human needs with environmental stability. So, as cooperation rimes with solution, and social rimes with environmental, I dream of finding creative solutions for environmental sustainability by re-establishing soils and developing connections, from flora over microorganisms to human beings. I love to associate things that do not have obvious links, I find the strength in cooperation, I believe in remediation and see the forest beyond the seeds and search for the value beyond the exhausted surface of a soil.

I think making sure knowledge is accessible, shared and transmitted across disciplines, generations and cultures is crucial for a sustainable future; connecting this knowledge allows to make seen what is yet to be started: that forest beyond the seeds.

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