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Blue carbon ecosystems are complex, requiring a complex and sustainable restoration strategy, undertaken at the landscape level.


Description

Summary

 

Blue carbon is the term used to describe the carbon stored in coastal and marine ecosystems, including mangroves. It is sequestered in their biomass and extensively in the coastal soils, where it can remain trapped for long periods of time, resulting in very large carbon stocks (Howard et al. 2014). The carbon stocks in mangroves are the highest of any ecosystem on earth, storing 4 times as much carbon as tropical rainforests (Donato et al. 2011; Figure 1).


Figure 1. Total ecosystem carbon pools for forest cover types of the world (Donato et al. 2011).

Mangroves play a pivotal role in fish production and nutrient cycling, occurring in tropical and sub-tropical tidal areas (Figure 2).  

Figure 2. Global mangrove species distribution zones (NOAA 2014).

 Mangroves have among the highest rates of deforestation of any forest ecosystem (Duke et al. 2007). Agriculture, development and aquaculture are the main drivers.

Considerable international scientific effort and expense is being assigned to the development and application of methods for assessing carbon stocks and emission factors in mangroves (Howard et al. 2014, UNEP 2014, Kauffman and Donato 2012, Abd Rahman et al. 2014, Adame et al. 2013). However, the same technology and expertise isn’t assigned to their restoration.

The destruction of these precious ecosystems continues, primarily for aquaculture. Globally, 52% of mangrove loss has resulted from clearing for aquaculture, which is the largest single driver in SE Asia (Chen et al. 2013,Valiela et al. 2001).

Remote sensing (RS), involving both passive and active sensors is being utilized in the mapping and estimation of biomass (carbon) in mangroves and peat lands. However there is an urgent need for mangrove restoration, a process which hasn’t been addressed by any robust methodology to date. This proposal suggests a more intensive RS analysis using LIDAR and Radar generated products, in combination with geospatial integration of land cover, soil and vegetation maps.


What actions do you propose?


In order to develop a viable proposal for the restoration of mangroves, it has been necessary to consult those that are already involved in that task, as there is certainly no “magic bullet”.

Jurgenne Primavera is the Chief Scientific Advisor on Mangroves for the Zoological Society of London. She advocates for a holistic approach to mangrove restoration, termed “ridge to reef”, from the mountains to the coral reefs, whereby the task of mangrove restoration isn’t approached as an isolated habitat. For example, if the upland forest is degraded, the subsequent runoff will suffocate the mangroves. Furthermore, elevation is an important determinant of the frequency and duration of tidal flooding, which subsequently affects species distribution and production.

To date, there have been two approaches when addressing mangrove restoration. The first approach that has been used extensively, particularly prior to 1982 is the artificial re-vegetation or plantation approach. It has a poor success rate due to a failure to appreciate the physiological tolerances of mangroves to tidal inundation (Lewis III 2001).  It is inexpensive, costing approximately USD $100-200/ha. The second approach is Ecological Mangrove Rehabilitation (EMR) (Figure 3), which focuses on correcting hydrological features of the site, thereby creating a foundation to increase plant species diversity naturally (Lewis III 1999). Mangrove forests can recover without active restoration efforts (Lewis III 2001). Thus, it is important to assess whether the normal tidal hydrology is disrupted. If there is a disruption, the restoration methodology must include a plan to remove that blockage prior to attempting anything else (Cintron-Molero 1992). This may involve excavation or filling works, which incurs huge expense due to large scale earth moving equipment. This methodology is only viable in more developed countries.


Figure 3. The Six-Step Ecological Mangrove Rehabilitation (EMR) Methodology (Lewis and Brown 2014)

Some important lessons are to be learnt from the failures that have frequently occurred in mangrove restoration. Most commonly, they involve the mass planting of mangroves (seeds, seedlings or propagules) on mud-flats. These planting sites are often destroyed by high tides and waves, sedimentation, barnacle infestation and macro-algae. For example, in  the Philippines, USD $17.6 million was spent over a 20 year period to plant 44,000 ha of mangrove plants  which was not successful, largely due to drowning of the seedlings, wave action, erosion and macro-algae.

This highlights the importance of EMR, where consideration is given to biophysical parameters, such as elevation, plant succession and tidal information. The planting of mangroves can be integrated into EMR but only following a full EMR assessment has been undertaken.

Two international case studies are presented (Lewis and Brown 2014), where the application of EMR resulted in the successful rehabilitation of the mangroves..

1. A 500 ha mangrove restoration project was undertaken in West Lake Park, Hollywood, Florida. Figure 4 demonstrates the time sequence of the restoration effort over 78 months. It is important to note that not a single mangrove was planted. They are known as volunteer mangroves that colonize the site, without assistance if appropriate biophysical conditions are established. Prior to this restoration, a three year pilot project established the target topographic elevation that would facilitate natural recruitment of mangroves (Lewis III 2001). It involved the construction of a tidal creek (hydrological restoration), which replicated the natural tidal creeks present in all mangrove forests. The project  commenced in May 1986 and was completed in May 1995, costing USD $5,000,000.


Figure 4.Time sequence of mangrove restoration over 78 months in West Lake Park, Hollywood, Florida (Lewis and Brown 2014)

2. A 425 ha mangrove rehabilitation was undertaken in disused aquaculture ponds on Tanakeke Island, South Sulawesi, Indonesia (Figure 5). It involved an expanded 10-step EMR methodology, which facilitated local communities being involved. It is outlined below.

  • Rapid assessments
  • Social assessments
  • EMR technical training
  • Baseline Biophysical surveys
  • Stakeholder meetings and EMR design
  • Implementation
  • As-built surveys
  • Development of Forest Management Learning groups
  • Mid-course corrections
  • Monitoring

Figure 5. (Lewis and Brown 2014) A. Hand-digging 1.2km tidal channel to facilitate drainage of disused shrimp ponds(mid-course corrections, 12 months after initial rehabilitation) B. The resultant tidal channel C. Natural recruitment of mangroves 32 months after initial rehabilitation D. Middle of disused ponds are being recruited as well

This rehabilitation project cost USD $440,000, which included physical rehabilitation, community organizing and governance work. An additional $150,000 was required to support Mangrove Action Project (MAP) staff assigned to EMR over a 4-year period. In total, 425 ha of restoration cost $590,000 or $1388/ha.

In addition to these approaches, hydrological restoration of mangroves may also be part of a shift to sustainable practices by local communities. Silvo-fishery is the integration of aquaculture and forestry (planting mangroves) in the aquaculture pond area, as illustrated in Figure 6.


Figure 6 Examples of Silvofisheries in Java, Indonesia.

Evaluation of mangrove restoration efforts in general, has proven difficult due to significant lack of monitoring documentation and inconsistencies in data collection. Unsuccessful or partially successful) projects are rarely documented (Lewis III 2001).

This proposal will integrate steps towards successful mangrove restoration (Ecological Mangrove Rehabilitation EMR; Lewis 2005, Lewis 2009, Lewis and Brown 2014), illustrated in Figure 3, with both active and passive remote sensing techniques. Steps 1, 2, 4, 6 in the EMR methodology are integrated with a range of remote sensing products, as outlined below.

1. The preliminary assessment already involves the integration of optical remote sensing, which would traditionally be Landsat derived land-use map and aerial photographs. Different combinations of Landsat wavelengths are used to detect vegetation health, seasonal variability, land-cover change, deforestation and afforestation. Depending on  the scale of the project, I suggest that optical data (Landsat 25m resolution) be employed to generate land-cover maps, as well as Enhanced Vegetation Index (EVI2) maps, which provides the most accurate estimates of vegetation intensity in coastal ecosystems (Rahman and Simard 2014). Furthermore, the generation of landcover and EVI2 maps can also be undertaken using MODIS data, which is an effective tool for studying temporal changes in the coastal regions. 

Radar data (PALSAR) can be used for land-use assessment and provision of structural information in relation to mangrove zonation (Lucas et al., 2007).

2. The biophysical assessment is the step most assisted by active remote sensing integration. Traditionally, this assessment would involve significant field time in order to determine the normal hydrology of the site. The normal hydrology  (depth, duration and frequency of tidal flooding) of the existing natural mangrove plant community in the area in which restoration is planned, is the single most important factor in designing a successful mangrove restoration project (Lewis III 2001). To date, the surrogate for costly tidal data gathering or modelling is the use of a tidal benchmark and survey of existing mangroves (Lewis III 2001).

Digital Elevation Models (DEMs) are generated using SRTM (radar) or ICESat/GLAS (LiDAR) data and are used to characterise the geomorphology of the coastline. Destruction of the mangroves means that there is no floristic indicator (of temperature and salinity conditions) or topographic indicators (tidal flat elevation, slope angle, existence of channels) that would reveal the level of the ebb and tide. Thus, it is necessary to use precise intertidal DEMs to explore the micro-topography and tidal hydrodynamics, generated by SAR interferometry and LiDAR.

MODIS OWL (Open Water Likelihood Algorithm) Surface water maps are sensitive to the dynamics of water movement and thus is suitable for the identification and mapping of inundation extent at large regional basin scales (Ticehurst et al. 2014). These maps are used for the analysis over time in detecting the historic presence of water, in areas that are currently degraded.

Fine beam PALSAR data can be used to make digital elevation model (DEM) maps and extract topographic information. Coastal vegetation information can be extracted from Principal Component Analysis (PCA) of PALSAR data. Specifically, PCA-1  can clearly distinguish between water and vegetation, facilitating the mapping of mangrove deforestation (Rahman and Simard 2014). Multi-temporal PALSAR is used to characterize hydrologic dynamics.

It is anticipated that the combination of the remote sensing products used in the biophysical assessment will provide information on abandoned tidal networks in areas of mangrove degradation, that would benefit from hydrological restoration.

4. Appraisal and selection of sites will be significantly aided by data fusion techniques (Figure 7), which increase the dimensionality of the information. This step will be supported by a GIS into which all aforementioned remote sensing products and secondary data (soil maps, previous vegetation maps, topographic maps, mangrove zonation maps, tidal information, management history) will be converted and processed into geospatial coverages.

A Geographic Information System (GIS) will be employed as a basic analysis tool for the assessment of the spatial relationships between the various data inputs. On the basis of the GIS analysis, appropriate locations for mangrove restoration will be selected and subsequently discussed with mangrove ecologists to determine viability of selected locations. Field accuracy assessment and planning can then take place.

6. Monitoring

Indeed, remote sensing technology is currently being employed in mangrove restoration efforts around the world (UNEP GRID 2014). A change detection methodology (using primarily optical data), whereby the changes in the extent of the mangroves are mapped between different dates, lends itself to monitoring rehabilitation efforts.

However, active remote sensing (LiDAR and RaDAR) can also play an important role in monitoring the restoration of mangroves. For example, multi-temporal PALSAR colour composites can identify mangrove regeneration (Lucas et al., 2007), which is hard to detect using single date PALSAR imagery or optical imagery due to the distinction between mature and degraded forest difficult to identify as the regenerating mangroves become larger.

Figure 7. Steps for processing remotely sensed imagery (Rahman and Simard 2014).

The complexity of the restoration process is amplified by mangrove forest often existing on land which is collectively owned and controlled. Furthermore, poor governance, inconsistent local and national laws, policies, subsidies and incentives that contribute to mangrove loss and conversion further complicate the restoration process. 

The mangrove restoration process requires collaboration on multiple levels involving multiple experts. Lets begin.

 


Who will take these actions?

My suggestion would be that the Centre for International Forestry Research (CIFOR) be responsible for this work. CIFOR is a non-profit, scientific research  organization, focusing on the use and management of tropical forests in developing countries. 

An additional two groups work closely with mangrove forests in SE Asia.

1. The Mangrove Lab which is affiliated with the National University of Singapore

2. Mangrove Action Project (MAP)

These groups currently collaborate with each other and would be able to provide ancillary information in relation to site selection (e.g. tidal information, vegetation maps, roads and infrastructure coverages). They also would have local contacts in various locations across Indonesia. Furthermore, they have relationships with local Indonesian Universities and are able to arrange fieldwork assistance (e.g., students and equipment).

 


Where will these actions be taken?

Indonesia. There are more mangroves in Indonesia than anywhere else in the world (Figure 8). CIFOR has its headquarters in Bogor Indonesia. CIFOR has a relationship with the Indonesian Government and has worked with research institutions at the national and local levels. They are involved in the protocols for the measurement, monitoring and reporting of structure, biomass and carbon stocks in mangrove forests (Kauffman and Donato 2012), as well as the drivers behind the destruction of mangrove forests.

Specifically, Manando in North Sulawesi Province is a region where considerable mangrove destruction has taken place. Furthermore, field-work involving members from CIFOR, The Mangrove Lab, MAP and Charles Darwin University in Australia, has been undertaken in this area.

Figure 8 shows the top ten countries containing mangroves and the proportion that is unprotected. 

 


Figure 8.  Proportion of remaining mangroves in the ten largest mangrove nations (UNEP 2014)


How much will emissions be reduced or sequestered vs. business as usual levels?


Emissions or sequestration of CO2 vary according to the types of mangrove being rehabilitated or converted (i.e., low, medium or tall mangroves; Figure 9).

The emissions calculated as the difference between the mean C stock (average of low, medium and tall mangroves) and that of abandoned shrimp ponds (Figure 10) was 2637 Mg CO2 e/ha for a site in the Dominican Republic (Kauffman et al. 2014). To date, emissions estimates of rehabilitated mangroves at different sites have been compared, however, the sequestration of emissions at a single site, between dates, has not.

Figure 9. Total ecosystem carbon stocks by vegetation type in the Dominican Republic (Kauffman et al. 2014)

 


 

Figure 10. Potential C emissions from the conversion of tropical ecosystems (Kauffman et al. 2014). Converted mangroves are represented by Donato et. al. and Pendleton et al. on the chart, based on different assumptions.CO2 equivalents are obtained by multiplying C emissions by 3.67, the molecular ratio of CO2 to C.


What are other key benefits?

 

In addition to carbon sequestration, mangroves provide an extensive range of ecosystem services (Figure 11.). These include the preservation of biodiversity, provision of spawning grounds and nurseries for many marine animals, water and waste water services and assistance in mitigating the effects of climate change by reducing the impact of storm surges. 

The restoration will facilitate the assessment of biomass and carbon stocks and subsequent quantification of carbon storage potential, which will realign mangrove ecosystems as attractive investments for protection and/or restoration e.g. REDD+.

Figure 11. The impact of diminishing ecosystem services derived by mangroves to human well-being (UNEP 2014)

 


What are the proposal’s costs?

Mangrove restoration is a very difficult activity for which to budget. Generally, the larger the project the cheaper the cost  per hectare if adhering to hydrological rehabilitation method (i.e., that which is used by EMR; Figure 3).

Landsat, MODIS, SRTM, PALSAR and ICESat/GLAS are spaceborne datasets, appropriate for mangrove ecosystems studies at global scales and are freely available to download (Rahman and Simard 2014). 

Table 1. Proposal Budget 

 

1.      If the remote sensing component was undertaken by a university with a remote sensing capacity, then the cost of the software licenses would be significantly reduced.

2.      Inclusive of breakfast and dinner

3.      Inclusive of all sustenance costs (lunch and water)

4.      The EMR implementation would have most likely involved a mangrove expert, car and boat hire, accommodation and transport costs which would have been factored into the $590,000 estimate, however, since the breakdown for the costs wasn’t provided, I included these costs in my proposal. Consequently, I may have over-budgeted.


Time line

 

Short term (5-15 years)

Year 1

January: Planning for trip (plane tickets, hotel bookings, ordering supplies and equipment. Downloading Landsat, SRTM, IceSAT/GLAS, ALOS PALSAR and MODIS datasets for region in North Sulawesi, Indonesia.

February-June: Obtain and process satellite imagery for current extent and conditions. Obtain and process digital secondary data (road coverages, vegetation maps from CIFOR)

July-September: Selection of sites (Integration of Steps 1,2,4 of EMR, Figue 3)

October-December : Field survey of selected sites. Gather hard-copy information from Government Departments, CIFOR. Meet with mangrove forestry experts, ecologists and obtain guides. Take geo-referenced photos using GPS-Photo Link to verify mangrove locations and conditions. Establish ground control points for geo-reference.

Year 2 

January- March : Development of the thematic layers of the model for site suitability maps

April-June: Map production

July-December: Implentation of EMR (inital EMR- Figure 3, Step 6)

Year 3

January-July: Implentation of EMR (inital EMR- Figure 3, Step 6)

Year 5 (Mid-course corrections - Figure 3)

Repeat Year 1 steps again. Make mid-course corrections as required.

Medium term (15-50 years)

Development of Adaptive Collaborative management of scaling up of EMR (Lewis and Brown 2014) - Figure 3

Quantification of carbon stocks from restored mangroves using methodology of Rahman and Simard (2014) and field sampling methodology (soil and vegetation) of Howard et al. (2014) to facilitate participation in climate change mitigation strategies (e.g., Reducing Emissions from Deforestation and Degradation REDD+).

Monitoring of restored mangroves using active and passive remotely sensing data.

Long term (50-100 years)

Quantification of carbon stocks from restored mangroves using methodology of Rahman and Simard (2014) and field sampling methodology (soil and vegetation) of Howard et al. (2014).

Monitoring of restored mangroves using active and passive remotely sensing data.


Related proposals


References

Abd Rahman, K., Mohamad Danial, M. S., Muhammad Faiz, K., Birigazzi, L. 2014. Inventory of volume and biomass allometric equations for Southeast Asia. FRIM, Kepong, UNFAO, Rome, Italy

Adame, F., Kauffman, J., Medina, I., Gamboa, J., Torres, O., Caamal, J., Reza, M., Herrera-Silveira, J. (2013). Carbon Stocks of Tropical Coastal Wetlands within the Karstic Landscape of the Mexican Caribbean. http://bit.ly/1WNaFgP

Chen, C., Son, N., Chang, N., Chen, C., Change, L., Valdez, M., Centeno, G., Thompson, C., Aceituno, J. (2013). Multi-Decadal Mangrove Forest Change Detection and Prediction in Honduras, Central America, with Landsat Imagery and a Markov Chain Model. Remote Sens. 5: 6408-6426.

Cintron-Molero, G. (1992) Restoring Mangrove Systems, in .W. Thayer, ed., Restoring the Nations Marine Environment, College Park: Maryland Seagrant Program, 223-227.

Donato, D., Kauffman, J., Murdiyarso, D., Kurnianto, S., Stidham, M.,Kanninen, M. (2011). Mangroves among the most carbon-rich forests in the tropics. Nature Geoscience. 4: 293-297.

Duke, N. , Meynecke, J., Dittmann, S. , Ellison, A. , Anger, K. , Berger, U. , Cannicci, S. , Diele, K. , Ewel, K. , Field, C. , Koedam, N. , Lee, S. , Marchand, C. , Nordhaus, I., Dahdouh-Guebas, F. (2007): A World Without Mangroves, Science, 317 (5834):41-42

Howard, J., Hoyt, S., Isensee, K., Pidgeon, E., Telszewski, M. (eds.) (2014). Coastal Blue Carbon: Methods for assessing carbon stocks and emissions factors in mangroves, tidal salt marshes, and seagrass meadows. Conservation International, Intergovernmental Oceanographic Commission of UNESCO, International Union for Conservation of Nature. Arlington, Virginia, USA.

Kauffman, J.B. and Donato, D.C. (2012). http://bit.ly/1PsZRfY

Kauffman et al. (2014). http://bit.ly/1VYnjIG

Lovelock, C., Megonigal, J., Saintilan, N. (2014). How to estimate carbon dioxide emissions in Howard et al. (2014)

Lewis III, R. R. (1999). Key concepts in successful ecological restoration of mangrove forests. Pages 19-32 in Proceedings of the TCE-Workshops No. II, Coastal Environmental Improvement in Mangrove/Wetland Ecosystems, Bangkok, Thailand, August 18-23, 1998. Danish-SE Asian Collaboration in Tropical Coastal Ecosystems (TCE) Research and Training, Bangkok, Thailand.

Lewis III (2005). http://bit.ly/1UtPIVV

Lewis III (2001). http://bit.ly/1YqO1dE

Lewis, R.R. (2009a). Mangrove field of dreams: If you build it, they will come. Society of Wetland Scientists – SWS Research Brief. No 2009-0005

Lewis,R., Brown, B. (2014). A Field Manual for Practitioners.

http://bit.ly/25WGmcz

Lucas et al., (2007). http://bit.ly/1USZxbO

Quarto (2012) Ecological mangrove restoration: re-establishing a more biodiverse and resilient coastal ecosystem with community participation http://bit.ly/28DaOHE

Rahman, A., Simard, M. (2014). “Remote Sensing and Mapping”, Coastal Blue Carbon: Methods for assessing carbon stocks and emissions factors in mangroves, tidal salt marshes, and seagrass meadows. in (Howard et al. 2014)