The Miyawaki Method
By Umang Rajpurohit
What is Miyawaki method ?
Miyawaki method is the most famous method of creating the Xylo(fancy name for forest). Created by one of the greatest botanist of japan Mr. Akira Miyawaki, also regarded as the pioneer of nature conservation. He developed a method or we can say a way of creating the healthy forest. The beauty of the Miyawaki method is that creates the dense plantation of native trees or plants and takes 2-3 years to fully grow.
The biggest reason why Miyawaki came up with this method was to:
1. Bring back potential natural vegetation.
2. To prove that it does not require much space to build a forest.
3. Native trees are the best suited for the location's ecosystem.
Miyawaki talks alot about the soil condition and how it is totally dependent on the health of the microorganisms. As many ecologists and environmentalist like Dr. Erach Bharucha and Dr. Vandana Shiva talks talks about the importance of the microbes and how this mighty creatures are the key components of soil generation.
How it's done ?
1. Surveying the land
- Surveying the local forest to get the idea of which are the native trees of that specific location. For example if we will survey in an area like coorg, then the native plants of that place will be black wood, kino, matthi, benteak etc.
2. Picking up the seeds
- For this, you have to visit the native forest and have to pick and gather all the seeds from the native trees.
- This guarantees the proper growth of the forest as the seeds belongs to the local forest.
3. Soil preparation
- Question may arise that how can we prepare the soil, isn't it already prepared by the nature ? Yes, but with time as all the organisms loose it's ability to perform certain tasks. Same goes with the soil as it's nutrients gets absorbed with time making it of no use after a period of time. Therefore, there is a need to prepare the soil for further production of forest.
- So first the soil is digged using various machinery and then 3-4 types of biomass is added to the soil. This biomass provide nutrition to the soil attracting the microbes.
4. Reintroduction of microbes.
- As i remember, once Dr. Bharucha while giving a lecture shared a story of a African fellow who provided him with the wisdom that how the indigenous microorganisms are the major role player for the forest's promotion of the forest.
- By making the compost tea, the microbes are fermented which are found in the natural forest, until the forest produce humus layer.
5. Planting the forest
- Now here's the thing, after collecting the seeds from the native forest we have to grow them into plants saplings in a nursery. Planting the sapling so much close, that after the forest is fully grown, you shouldn't be able to walk in the forest.
6. Mulching
-New term right ? Nothing fancy. Mulching is the covering of the plant, means you put the the mulch around the plant for the efficiency and for saving water around the plant. It prevents the UV-sterilization and helps the forest reach it's fuller potential.
Credits: As written the method belongs to Mr. Miyawaki and all the methods and ways to create the forest is beautifully explained by Mr. Shubhendu Sharma. For more information you can visit his youtube channel and website named as "Afforestt".
2 Comments
ReplyDeleterm(list=ls())
library(dplyr)
file.choose()
compensation <- read.csv("D:/Umang R\\compensation.csv")
names(compensation)
head(compensation)
dim(compensation)
str(compensation)
glimpse(compensation)
tibble(compensation)
library(dplyr)
glimpse(compensation)
tibble(compensation)
summary(compensation)
select(compensation,Fruit)
select(compensation, -Root)
slice(compensation, 2)
slice(compensation,2:10)
filter(compensation,Fruit>80)
filter(compensation,Fruit==80)
filter(compensation,Fruit!=80)
filter(compensation,Fruit<=80)
filter(compensation,Fruit>80|Fruit<20)
filter(compensation,Fruit>80&Root<2.3)
#to get the fruit having greater than 80 and less than 20
lo_hi_fruit <-filter(compensation, Fruit>80|Fruit<20)
#to add new column which shows the logarithm of fruit= logFruit
mutate(compensation, logFruit=log(Fruit))
head(compensation)
arrange(compensation,Fruit)
select(filter(compensation,Fruit>80),Root)
compensation %>% filter(Fruit>80)%>%select(Root)
Install.packages("dplyr")
ReplyDeleteinstall.packages("ggplot2")
install.packages("maps")
install.packages("rnaturalearth")
library(dplyr)
library(ggplot2)
library(maps)
library(rnaturalearth)
storms75 <- filter(storms,year ==1975)
storms75
ggplot(data = storms75, aes(x = long, y = lat) + geom_point ()
ggplot(data = storms75, aes (x = long, y = lat, color = name)) + geom_point()