Please go ahead and play with the full-screen map here.
This map Application is developed to support the Guidelines for Sustainable Development of Natural Rubber, which led by China Chamber of Commerce of Metals, Minerals & Chemicals Importers & Exporters with supports from World Agroforestry Centre, East and Center Asia Office (ICRAF). Asia produces >90% of global natural rubber primarily in monoculture for highest yield in limited growing areas. Rubber is largely harvested by smallholders in remote, undeveloped areas with limited access to markets, imposing substantial labor and opportunity costs. Typically, rubber plantations are introduced in high productivity areas, pushed onto marginal lands by industrial crops and uses and become marginally profitable for various reasons.
Fig. 1. Rubber plantations in tropical Asia. It brings good fortune for millions of smallholder rubber farmers, but it also causes negative ecological and environmental damages.
The online map tool is developed for smallholder rubber farmers, foreign and domestic natural rubber investors as well as different level of governments.
The online map tool entitled “Sustainable and Responsible Rubber Cultivation and Investment in Asia”, and it includes two main sections: “Rubber Profits and Biodiversity Conservation” and “Risks, SocioEconomic Factors, and Historical Rubber Price”.
The main user interface looks like the graph (Fig 2). There are 4 theme graphs and maps.
Fig. 2. The main user interface of the online map tool.
. Section 1
This graph tells the correlation between “Minimum Profitable Rubber (USD/kg)” (the x-axis of the graph, and “Biodiversity (total species number)” in 2736 county that planted natural rubber trees in eight countries in tropical Asia. There are 4312 counties in total, and in this map tool, we only present county that has the natural rubber cultivated.
Fig. 3. How to read and use the data from the first graph. Each dot/circle represents a county, the color, and size of it indicates the area of natural rubber are planted. When you move your mouse closer to the dot, you will see “(2.34, 552) 400000 ha @ Xishuangbanna, China”, 2.34 is the minimum profitable rubber price (USD/kg), 552 is the total wildlife species including amphibians, reptiles, mammals, and birds. “400000 ha” is the total area of planted natural rubber plantation from satellite images between 2010 and 2013. “@ Xishuangbanna, China” is the geolocation of the county.
Don’t be shy, please go ahead and play with the full-screen map here. The minimum profitable rubber price is the market price for national standard dry rubber products that would help you to start makes profits. For example, if the market price of natural rubber is 2.0 USD/kg in the county your rubber plantation located, but your minimum profitable rubber price is 2.5 USD/kg means you will lose money by just producing rubber products. However, if your minimum profitable rubber price is 1.5 USD/kg means you will still make about 0.5 USD/kg profit from your plantation.
The county that has a lower minimum profitable price for natural rubber is generally going to make better rubber profit in the global natural rubber market. However, as scientists behind this research, we hope that when you rush to invest and plant rubber in a certain county, please also think about other risks, e.g. biodiversity loss, topographic, tropical storm, frost as well as drought risks. They are going to be shown later in this demonstration.
Fig. 4. The first map is the “Rubber Cultivation Area”, which shows the each county that has rubber trees from low to high in colors from yellow to red. The second map “Minimum Profitable Rubber Price”(USD/kg), again the higher the minimum profitable price is the fewer rubber profits that farmers and investors are going to receive. The third map is ” Biodiversity (Amphibians, Reptiles, Mammals, and Birds)”, data was aggregated from IUCN-Redlist and BirdLife International.
. Section 2
We also demonstrated different types of risks that investors and smallholder farmers would face when they invest and plant rubber trees. Rubber tree doesn’t produce rubber latex before 7 years old, and the tree owners won’t make any profit until the tree is around 10 years old in general. In this section, we presented “Topographic Risk”, ” Tropical Storm”, “Drought Risk”, and “Frost Risk”.
Fig. 5. Section 2 ” Risks, SocioEconomic Factors and Historical Rubber Price” has seven different theme maps and interactive graphs. They are “Topographic Risk”, ” Tropical Storm”, “Drought Risk”, and “Frost Risk”, “Average Natural Rubber Yield (kg/ha.year)”, “Minimum Wage for the 8 Countries (USD/day)”, and ” 10 years Rubber price”.
If you are interested in how the risk theme maps were produced, Dr. Antje Ahrends and her other coauthors have a peer-reviewed article published in Global Environmental Change in 2015. “Average Natural Rubber Yield (kg/ha.year)” and “Minimum Wage for the 8 Countries (USD/day)” dataset was obtained from International Labour Organization (ILO, 2014) and FAO.” 10 years Rubber price” was scraped from IndexMudi Natural Rubber Price.
Dr. Chuck Cannon and I are wrapping up a peer-reviewed journal article to explain the data collection, analysis, and policy recommendations based on the results, and we will share the link to the article once it’s available. Dr. Xu Jianchu and Su Yufang have shaped and provided guidance to shape the online map tool development. We could not gather the datasets and put insights to see how we could cultivate, manage, and invest in natural rubber responsibly without other scientists and researchers study and contribute to field for years. We appreciated Wildlife Conservation Society, many other NGOs and national department of rubber research in Thailand and Cambodia for their supports during our field investigation in 2015 and 2016.
We have two country reports for natural rubber in Thailand, and natural rubber and land conflict in Cambodia, a report support this online map tool is finalizing and we will share the link soon when it’s ready.
The research and analysis were done in R, and you could find my code here.
The visualization is purely coded in R too, isn’t R is such an awesome language? You could see my code for the visualization here.
To render geojson format of multi-polygon, you should use:
library(rmapshaper) county_json_simplified <- ms_simplify(<your geojson file>)
My original geojson for 4000+ county weights about 100M but this code have help to reduce it to 5M, and it renders much faster on Rpubs.com.
I learnt a lot from this blog on manipulating geojson with R and another blog on using flexdashboard in R for visualization. Having an open source and general support from R users are great.