Mahayana Permaculture

Mahayana Permaculture is a company that designs, grows and manages food production systems based on permaculture principles. Permaculture is a design science based on mimicking efficient natural systems for productivity. 

Huge swaths of land are deforested for food and energy production in Indonesia, contributing to global climate change. Despite this, hunger and malnutrition remains a national problem. This scenario is a microcosm of problems in other tropical developing countries. 

Our solution is to convert degraded lands into permaculture forests that produce food and bioenergy. By emulating nature, we can create a biodiverse system that requires minimal input for maximum yields with numerous positive externalities that a tropical forest brings. This creates a highly efficient, closed loop, and carbon negative system.

Upscaled to 50 million hectares globally, our system can potentially improve the livelihoods of 1 billion people worldwide and halve global agricultural emissions by 2050. 

We aim to solve the problem of deforestation driven climate-change, malnutrition and poverty. 

Deforestation-based agriculture practices in Indonesia has led to high CO2 emissions, greatly contributing to climate change. The year 2019, saw Indonesia lose more than 850,000 hectares of rainforests and emitted 709 million tons of CO2, equalling the annual emissions of Canada.

This same industry is where 32% of Indonesians earn their livelihoods. Most agricultural workers live in poverty in rural areas. Recent improvements in our country's poverty levels (9.22%) threatens to be reversed by the COVID-19 induced economic crisis.  

Poverty correlates greatly with malnutrition. Stunting is one of the principal indicators of malnutrition, and in Indonesia, 1 in 3 children below the age of 5 are stunted. 

This business as usual approach produces food high in saturated fat and low in micronutrients, reduced food diversity, high logistical costs for transport to urban centers, and puts stress on our water supplies. Hence, current practices of conventional food production aren't sustainable, scalable, and certainly inappropriate for the future.

All this despite having 10 million ha of unproductive degraded lands. They are the byproduct of over-logging, encroaching human settlements, and agricultural expansions. These can be developed into biodiverse agroforests.

Converting degraded forests into a food production system that caters to the triple bottom line (People, Planet, and Profit).

Using permaculture design principles, we will convert these forests into productive, and biodiverse food forests. Creating a food forests involves many complex interactions between different elements and energy flows. This includes a diverse selection of productive tree species, domesticated animals, mycorrhizae, and biochar. AI will be used to find the optimal configuration of the complex interactions between these elements for maximum productivity.

Utilizing biochar in our system allows us to directly store stable carbon in the soil for centuries, leading to a true removal of CO2 from the atmosphere. In addition, biochar based soil amandements helps build organic matter in the soil, and increases carbon storage capacity in living biomass (vegetation and fungal). 

The end goal is to create a biodiverse, perennial agroforest system that can continuously produce vegetables, fruits, protein and sugars (which can be distilled into bio-ethanol). This productive forest system also performs numerous positive ecosystem services such as water retention, erosion control and micro-climate regulation. 

Our operations lies in a 20ha plot of degraded land within a 170,000ha former logging concession in East Kalimantan. 30,000+ people in this area’s proximity are unemployed, despite having skills in agroforestry.

Jobs in agriculture are grueling; work is heavy, tiring, often dirty, in harsh environmental conditions like extreme heat and insect disturbances. Most farmers operate in the informal sector, with virtually no job security, making them susceptible to both market and environmental shocks.

Initially, we will introduce three welfare improvement measures:

1. Forest schools: Forest farmers will be trained to improve yields and increase the productivity of the land in an environmentally sound manner.
2. Permaculture design for efficiency: Creating a system of design geared towards operational efficiency, site resilience, greatly contributing to food security for the farmers.
3. Appropriate technologies that take the burden off laborious reforestation processes.

The farmers will initially receive a living wage. As the system is refined, we will move towards a profit sharing system that further incentivises high productivity from the farmer’s part. Ultimately, the use of AI will contribute to the refinement of the system by aggregating the data that has been collected from these farmers as the basis of our machine learning algorithm.

By replacing degraded forests with polyculture agroforests we can grow a biodiverse range of nutritious food in abundance. 

Rapid biomass is the building blocks for sustainable protein production. With ample amounts of sunlight and rainfall, the tropics is the best place to do so. Integrating fast-growing nitrogen fixing fodder trees with livestock is crucial in the initial agroforest setup to ensure soil nutrient generation. The numerous positive externalities of polyculture agroforests include, carbon sequestration, building topsoil, and water retention. 

Forest farmers will gain the knowledge to improve yields and increase land productivity, further localizing and diversifying their food sources.

Our solution is directly comparable to both conventional farming and BECCS, with major improvements in all aspects including in efficiency and yields:

1. Space and time stacking

We improve on the inefficiencies of conventional farming and BECCS by utilizing the vertical space (trees) and timing of forest successions (time). E.g. In year 1, we plant fast growing nitrogen fixing trees that feeds livestock. In year 7, we can start tapping sugar palms for its sugar.

2. Non-deforestation

Our system converts unproductive degraded forests to productive ones that caters to the triple bottom line. We synegize wealth with ecological function to create powerful incentives for people to care, rather than degrade the ecology that supports them. 

3. Biodiverse system

By utilizing layers of the food forest we can mix and match more than 12 species per hectare to accomodate the needs for production. This resilient system simultanoeusly produces food, fuel, and timber at the same time.

Competitors in Agroforestry

Compared to other players in agroforestry, our competitive advantage lies with the use of Arenga pinnata, biochar, and automated forest design with AI.

Arenga pinnata (Sugar, not Oil Palms) enables us to produce 30-130 barrels of ethanol/ha/year from it's distilled sugar sap. This palm only grows in biodiverse forest systems, not peatlands or monoculture systems.

Biochar allows us to store more carbon into the soil. With those two, our system's carbon offset is tremendous (44 tonnes/ha/year). 

AI will help us scale exponentially, globally.

The main technologies that powers Mahayana Permaculture’s systems are biochar and the relationship between elements in our agroforest. For the purposes of permaculture design, these elements are further processed using AI, to be optimized based on local terroir for maximum site productivity. This enables us to rapidly expand throughout the global tropics. 

The production of biochar in our system converts the degraded forests’ biomass into stable carbon. Most degraded forests or secondary forests will not succeed into primary forest, due to the loss of their natural seed dispersal spiecies (e.g. orangutans and birds). Thus it will die off, decompose, and releases carbon into the atmosphere. Instead of being a source of emission, we convert it into biochar that acts as carbon sink, builds the soil, and increases the land’s water retention.

There exists multiple interactions between the numerous elements in our food forest, lending to it's productivity and zero-waste nature. One small example is the role of livestock, specifically goats, in our system. The goats eats our nitrogen fixing fodder trees. Leftover branches are pyrolyzed into biochar and inoculated with their effluents to fertilize the soil. Through this process our food forests are fertilized, helping grow later succesion fruit trees. This system produces food in the form of protein and fruits, increases soil fertility, and simultanously sequesters carbon. It is a closed loop system that mimics natural systems by working with, rather than against it. 

Our mentor and project supervisor, Dr. Willie Smits has 35+ years of experience in tropical reforestation. He is best know for the Samboja Lestari project, which reforested 2000 hectares of degraded land. Physicist Amory Lovins states that Samboja Lestari is “the finest example of ecological and economic restoration in the Tropics.” The principles of this project are ready to be optimized and upscaled worldwide. 

Rattan Lal (2010) stated that restoring soils of degraded ecosystems via agroforestry methods that combines crops, trees, and animal husbandry has the potential to store an additional 1-3 billion tons of carbon annually into the soil. That is equivalent to about 3.5-11 billion tons of CO2 emissions annually. This is before the additional biochar added to the soil that we use in our systems, adding 18 tons/ha/year (Tsai et al., 2018)

The benefits of biochar for the soil is enormous and it is very fitting to be used in the tropics. Firstly, biochar enhances the growth of perennial crops, adds nutrient avalability, and increases soil pH (Hamzah and Shuhaimi, 2018) which is very useful in tropical soils where acidic soil is common. Secondly, biochar significantly improves biological nitrogen fixation (Guerena et al., 2015; Rondon et al., 2007). Thirdly, biochar increases mychorrizal colonization by more than 70%, which also plays an important role in carbon sequestration (Godbold et al., 2006). The aforementioned mychorrizha helps with plant’s Phosphorus uptake (Vance, 2001) and thus eliminating the need for Synthetic fertilizer.

YEAR 2020-2021: 20 ha, 2 Forest Farmers (FF), 2 construction workers - increase to 6 FFs to improve data collection for animal systems, reforestation, and honey production. 

Our core reforestation system is solid, but several variables need to be optimized. 

Element efficiency, tool efficiency, rate of progress will be measured in this 20 ha plot. Data collection is key, as it serves as the foundation for upscaling elements via AI. This plot will also serve as the first “forest school” where farmers will learn the details of growing a forest system, along with its numerous benefits. 

YEAR 2021-2022: 20 ha, 12 FFs

Additional variables will arise within the next year and more units will be needed to tend to those variables, as well as collect additional data. Integration of appropriate technologies will reduce labor intensity of the forest farmers, improving their working conditions.

YEAR 2025++

In five years, we aim to replicate our system on 2000 hectares of land based on findings within the initial 20 hectare plot. Several key infrastructures will be present here; a central processing hub, which includes a small scale sugar factory, a small scale abattoir, nutrient cycling plant, and another forest school for new trainees. By then, we will provide income, localized access to nutrient dense food for at least 900 people, whilst regulating the micro-climate and water cycle locally.

Our system is designed to self-regulate and provide fast feedback. Improvements made in key metrics will be recorded and implemented to scale. Ultimately, the end product would be an AI that is able to create the most efficient food forest based upon soil type, weather, existing vegetation, watershed, labor availability, geolocation, and market price for each forest product. AI is paramount for rapid scaling to 50 million hectares worldwide by 2050.

Success is measured by improvements in 4 key metrics:

1. Water retention 
2. Energy balance (Food and Fuel) - labor, water, energy and time needed for each unit of energy produced.
3. Economic returns
4. Carrying capacity

ENVIRONMENTAL

2021 - Increase water holding capacity of our 20 ha land by 30%, while experimenting on permaculture systems that improves our success metrics above. 

2025 - Increase the water holding capability of 2000 ha plot by 30%, aim for a carrying capacity of 10 people/ha, and streamline our permaculture systems using our AI.

SOCIAL

2021 - Provide resilient and increased income with improved working conditions for 6 families.

2025 - Resiliently increase income for at least 225 families and provide surplus nutritious food and energy supply. Improving future mortality rates, health, and well being. 

ECONOMIC

Revenue generation: 

2021 - $175/ha/month for 20ha pilot plot ($3500/month). 

2025 - $350,000/month from our 2000ha plot. 

Adopting a circular economic model with the potential to become a net food and energy exporter, our system can create long term economic sustainability for tropical countries. 

Unknown variables - Possible bottleneck

Forest farming involves numerous species and multiple interactions between elements. Introducing new elements or species to our system would create an exponential amount of unknowns. For example, 2 elements has one interaction that might be bidirectional. 10 elements might have 45 interactions that also has the possibility of being bidirectional. It is a complete directed graph problem that requires time and feedback to judge whether or not an element or species is beneficial to the overall system.

Reduced labor intensity

One of our success metrics is to reduce labor intensity, whilst simultaneosly increasing yield and economic income. Lowering labor intensity requires significant time, money, effort and possibly procurement of appropriate technologies. 

Methodology of labor becomes a problem when new elements arise within the system. This is due to the numerous changes in variables associated with introducing a new element. Approaches to decreasing labor intensity and improving labor methodology can come from many perspectives. These include tech, design, infrastructure and critical appraisal of the work being done in relation to the end goal. 

The goal is to optimize the methodology of labor such that it reduces labor intensity. 

Competitiveness

Cost/unit of yield remains a difficult barrier to overcome. Conventional farming in most developing countries are subsidized, Indonesia included. To be able to compete, we need to have competitive prices for all our products. Hence the need to scale our production capacity.

When dealing with tons of unknown variables, it is best to speed up data collection of said unknowns. Data is used to determine the utility of an additional element for the overall system. Creating a data aggregator and fast data collection requires considerable operational hours. Hence the need to recruit more forest farmers within our system, aided by technologies such as LIDAR to eliminate bottlenecks. With a rapid data collection system, our machine learning algorithm can be deployed to quickly scale our systems.

This year we aim to start selling our forest products. However, with our current production scale, we will initially enter the growing organic/premium market, instead of directly competing against subsidized conventional farming. The organic market in Indonesia is a 13.8M USD industry and is expected to grow 8.4% annually. Generating cashflow within 1 year from our pilot 20ha plot is necessary to validate our economic model, and plays an important part in perfecting our permaculture systems. Scaling will allow us to compete with conventional subsidized farming.

Natural conditions of the tropics gives us a production advantage. Abundant sunlight and rainfall makes it the best place to produce biomass in the world. This falls in our favor because the produce we grow and the forest system we deploy, along with the energy flows involved are very suited for production in the tropics.

Start small, work with what works within the system, make small adjustments on what works without breaking the system. 

Full-time: 5 Personel

Part-time: 2 Personel

Forest Farmers: 2 Personel

Andhana Taufik (Chairman & Project Leader)

Permaculture designer specializing in perennial food production with seven years of first-hand experience. Responsible for Agroforestry, livestock and food production.

Pradipta Rohimone (CEO)

Background in computer science and business management. Proficient in data & computer modeling, stats analysis, and software design. Has been practicing permaculture since 2015.

Aulia Reinozha (COO)

Having a background of running a logistical company and has been practicing permaculture since 2016. A pro at logistical organisation, field operations, data collection and record keeping.

Rayi Raditia (CDO)

Trained permaculture designer.  Has been constructing various permaculture infrastructures since 2016. Responsible for technical and infrastructure design.

Dr. Willie Smits (Mentor & Project Supervisor)

A microbiologist, wilderness engineer, conservationist, and social entrepreneur. Has developed more than 100 conservation programs. Has worked more than 35 years in regenerating tropical forests.

ARSARI Enviro Industries - a bio-energy agroforestry company . The company holds a permit to develop more than 100,000 hectares of degraded lands in East Kalimantan. Additionally, they also hold a couple of patents regarding ethanol production using the Arenga pinnata (Sugar Palm). We are currently involved with their R&D division to look for any feasible and scalable permaculture food forest systems to compliment the mixed sugar palm forests that will be deployed in their concession. 

Direct Sales 

For the next 2 years our revenue model involves directly selling (B2C) our forest products from our 20 hectare plot. Our strategy is to sell our products locally within East Kalimantan and premium, non perishable products, such as palm sugar and honey domestically. We aim to generate $175/ha/month in revenue. Upscaling to 2000 hectares with this revenue system as our benchmark will be the next step.

Initial products include

Food items:
Goat meat
Poultry meat and eggs
Honey
Palm sugar
Fast growing fruits: bananas, papaya, mulberry, passionfruit

Non-food items:
Vermicompost
Biochar
Lemna minor (fodder)

Permaculture Design as a Service 

With sufficient data collected, our system will continue to improve and be ready to scale, allowing us to shift our business model as a Design Service (B2B). 

Using permaculture principles - we design agroforestry systems to be implemented on a client’s plot of land, creating an “operating system” that best suits their needs. This could be a mix of productivity, carbon sequestration and positive externalities such as water retention and erosion control, for example. Support and maintenance assistance will also be given to the clients. 

Sufficient data collection from 2000 ha of land allows us to roll out our AI for design purposes. This automated system eliminates the time consuming and cost-intensive site design process, making it easy for clients to get the most of their plot of land in a sustainable manner. Our potential customers include big timber corporations, agribusinesses, to small holder farmers/cooperatives that want to sustainably improve their land's productivity.

We would like to scale our food production capacity and accelerate the adoption of our permaculture systems exponentially throughout tropical developing countries. Our biggest roadblock right now is funding. Additional funding is needed to first improve our data collection method. To improve our data collection, we need to increase our data collection capacity. This includes increasing the number of forest farmers operating within our system whilst using technologies such as LIDAR to eliminate manual data collection bottlenecks.

Second, to integrate appropriate technology for elements within our system. Efficient technologies that could aid our permaculture design and reforestation process in an environmentally sound manner. These include low emission and non-compaction causing technologies that can maneuver through mixed terrains, or large scale monitoring technologies to efficiently gather data (GIS + LIDAR images).

Third, to scale our food production system, allowing it to compete with commodities, offering healthier alternatives grown regeneratively. Through Solve we are hoping to find potential backers, partners, and solutions that can complement and support our system.

Our system is currently in the process of optimization; figuring out which element works, good enough to scale, or which breaks the system when scaled. Access to recruit capable mechanical engineers, industrial engineers, software engineers, and green architects would be most useful in an effort to streamline and manifest our permaculture systems as a whole.

Currently our business model relies too heavily on the assumption that we provide everything for forest farmers since day one (housing, electricity, infrastructure etc). This requires huge upfront capital that might not be suitable when scaled. Hence the need for feedback by industry experts on what arrangements or financing schemes are suitable to allow our system to scale.

One of our aims is to make forest farming as efficient and easy as possible, eliminating drudgery. Often laborious tasks include planting, multiple species harvesting, to infrastructure building. Mechanical engineers, industrial engineers, software engineers, and green architects that understand our system as a whole would help make our solution a reality. These engineers will alleviate heavy work associated with agroforestry, by creating an efficient flow of forest farming from upstream until downstream. This might include designing appropriate tools, automation, and IoT for forest farming. This requires different backgrounds and faculties to work together. Thus, suitable candidates for this partnership are MIT CEE, MIT MechE, and EECS.

Additionally, existing geospatial and big data companies, such as Trimble and Palantir. Geospatial companies will help us to classify trees in a dense forest while big data companies will help us set up our AI infrastructure. With both tree classifier and AI infrastructure we just need to bridge the gap with data collection and data visualization through GIS.

Our goal is to turn 50 million hectares of degraded tropical forests all over the world into our productive permaculture food forest systems. Our means to that end is to create an AI that is able to design the previous. The main purpose of the AI is to create and optimize recipes of species or elements on a a system that is suitable for any given land in the tropics with our 4 main criterias in mind.

1. Water retention
2. Energy balance (Food and Fuel) - labor, water, energy and time needed for each unit of energy produced
3. Economic returns
4. Carrying capacity

As mentioned above, one of our main problems is the unknown variables bottleneck. Dealing with tropical food forest systems means that we are dealing with the biodiversity of the tropics. An additional element or species added to our recipes within our system means it can create up to n amount of bidirectional connections to other elements. One recipe of our food forest systems may contain more than 12 species per hectares, which means it may contain more than 12 permutations and not to mention, there are more than 40,000 tree species in the tropics. There are just too many variables. Scaling up to 1 million hectares worldwide is practically impossible without an AI, let alone 50 million hectares.

There are two ways to approach this problem. The first method is to create databases that aggregates all data (energy input, energy output, water consumption etc.)  from users of our systems worldwide. This is an abstraction approach. We use this data as the basis of our machine learning algorithm to optimize our system in relation to the geographical location it is being deployed. This means that we need more users or adopters to help us collect data.

The second method is to simulate how food forest systems grow in relation to time. It is a predictive model based on plant's anatomy, weather, soil type, etc. Through this simulation, we are able to create recipes - which plants, species, or elements are suitable for a given piece of land. This requires an in depth biological look at how trees grow and interact with their surroundings.

Both methods require huge amount of resources. A combination of both is perfect, but one is enough for us to scale globally.

Proving that permaculture based systems can be scaled up in a profitable way for investors, people and nature while drawing down CO2 from the atmosphere

Project objectives

1. Demonstrate and prove that it is possible to come up with a methodology for permaculture that is operationally feasible and financially profitable -  Permaculture has been around for many years and has many followers, both practitioners as well as people that attended a PDC (Permaculture Design Course) and apply some of the principles in their daily life. The ideologies of permaculture are most admirable and based upon sound insights in what makes an ecosystem perform optimally with minimal external inputs. Unfortunately there are still very few permaculture enthusiasts that can truly maintain that lifestyle simply because of the economic returns still being very low because of issues of scale and market access. 

2. Quantification of permaculture outcomes - The second objective concerns data collection and analyses. There are many beautiful demonstration projects that show the qualitative success of permaculture approaches, like hydrology, appropriate combinations of plant species, etc.. But many focus more on demonstration than proving sustainable and profitable outcomes. This project is about collecting quantitative data on productivity, material inputs, capital expenditure, skill sets needed, amount of carbon sequestrated, establishing time lines, etc. So the second goal of the project is the 

3. Transfer of operational knowledge - Thirdly we need to build a physical environment for a tropical permaculture training centre that will not just hold meetings and give demonstrations but also provide serious permaculturists with an opportunity to learn the nitty gritty of making a project work, including planning, tool use, administration and setting up cooperatives to scale up production. 

4. Lastly we want to provide an example that gives hope by showing that we can make self-sustaining systems that do not depend upon fossil fuels but through biodiverse land utilization and the application of biochar can actually draw down CO2 from the atmosphere. In combination with the proof of economic feasibility and technical feasibility we hope to inspire others to copy our model in other locations.

Methodology

Location

We will use a 23 hectare plot of available for the next 20 years near the end of the Bay of Balikpapan as the demonstration and research site as well as a training centre for the distribution of technologies implemented here. It is located very close to the location of the new capital city for Indonesia and is easily reachable within 90 minutes from the Balikpapan International Airport. The location comprises two sub-watersheds and includes a lake of 4.7 hectares. It has flat and steep areas, existing sugar palms and a mixed vegetation of planted trees and natural secondary forest regeneration in a mosaic of open and tree-covered terrain as can be seen in the image below.

Logistics

Mahayana Permaculture comprises a group of young Indonesians that all graduated in a variety of fields in universities in the USA and Australia. The team works full time on location and are committed to working here for several years to dedicate themselves for this project. The location is accessible by public road.

Data recording and modelling

This is the main approach. Basically we will collect detailed data on what inputs are needed to achieve what outputs. This involves everything of importance to provide an accurate insight in the costs and benefits of applying permaculture systems per management unit and the advantage of having many units working in unison to optimize. We will also produce video material to become practical instruction modules for others to learn from.

An important part of our project is the carbon balance determination. By applying biochar for instance we not only directly store stable carbon for centuries or millennia in the soil, meaning a true removal of CO2 from the atmosphere, but also building up more organic matter in the soil and a higher storage of carbon in living biomass in the vegetation but also the soil micro flora and fauna such as the large amount of fungal biomass.

Activities

There will be a wide range of activities that we will execute varying from practical planting trials and application of organic fertilizers and their effect on production and quality of the products up to the construction of a relational database with parameters that will allow the results of the work to be implemented anywhere else in the tropics by using their local data for the various parameters. We will use the degraded forests in East Kalimantan as the starting point for the new permaculture units that we call forest farmer units. Degraded forests are now more prevalent and located nearer to human needs then remaining good quality forests. Of course the model will also be insightful for other land conditions where we start for instance from the most degraded grasslands to recreate an ecologically healthy and profitable rehabilitation scheme.

Some of the activities are:

1. Practical fieldwork: We will look at factors like synergism and allelopathy between different plant species in various field trials. We will measure how these impact productivity in terms of volume but also in terms of economic returns.

2. Time studies: We will look in detail to the inputs needed for each activity within the permaculture model in terms of man power and what level of skill is needed for each of those activities. We will also try to relate the manpower requirements with different degrees of more advanced tool use, e.g. use of a tractor versus working with hand tools. These data then allow anyone to assess whether a certain model is feasible or not in different regions with different income standards and labour availability.

3. Development of a relational database that can serve to quickly assess feasibility of certain permaculture models in different regions by inputting the standard data as defined under activities 1 and 2.

4. Prepare facilities and materials to provide on location training to interested parties to study our approaches. This will include the production of teaching materials, a curriculum, teaching equipment, etc.

5. For the carbon balances and assessment of climate benefits we will need to conduct lots of sampling and analysing of the samples. This can be done by sending samples to nearby laboratories in combination with doing our  local assessments. 

Benefits

The main benefit of this project is to provide an easy and quick insight to interested parties about the feasibility of permaculture based production systems in their respective parts of the world. In addition another important benefit is the possibility of acquiring detailed practical on the ground training in the application of these systems. The overall benefit and ultimate goal is to support more sustainable ways of providing the needs of people, nature and the climate.