DO NOT CITE OR QUOTE

1

4 CHAPTER 4

2COASTAL WETLANDSDRAFT 2013 Wetlands Supplement

Chapter 4

4.1

Chapter 4

Table of Contents

3

4

DO NOT CITE OR QUOTE

4Coastal Wetlands ............................................................................................................................................ 1

5

4.1

Introduction ........................................................................................................................................... 3

6

4.2

General Methodological Framework ..................................................................................................... 4

7

4.2.1

Change in soil carbon ................................................................................................................... 7

8

4.2.2

Change in Biomass Carbon Stocks ............................................................................................. 10

9

4.2.3

Change in Dead Organic Matter Carbon Stocks ......................................................................... 16

10

4.2.4

Non-CO2 Emissions .................................................................................................................... 17

11

4.2.5

Choice of activity data ................................................................................................................ 18

12

4.2.6

Uncertainty assessment ............................................................................................................... 19

13

4.3

Management Changes in Coastal Wetlands......................................................................................... 20

14

4.3.1

Description of Activities ............................................................................................................. 20

15

4.3.2

Specific Methodological Approach ............................................................................................ 22

16

4.3.3

Soil Carbon ................................................................................................................................. 23

17

4.3.4

Biomass....................................................................................................................................... 24

18

4.3.5

Dead Organic Matter .................................................................................................................. 26

19

4.3.6

Non-CO2 emissions..................................................................................................................... 27

20

4.4

Drainage of Coastal Wetlands ............................................................................................................. 28

21

4.4.1

Description of Activities ............................................................................................................. 28

22

4.4.2

Soil carbon .................................................................................................................................. 28

23

4.4.3

Biomass....................................................................................................................................... 30

24

4.4.4

Dead Organic Matter .................................................................................................................. 33

25

4.4.5

Non-CO2 emissions..................................................................................................................... 34

26

4.5

Rewetting and Restoration of Coastal Wetlands ................................................................................. 34

27

4.5.1

Description of activities .............................................................................................................. 34

28

4.5.2

Soil Carbon ................................................................................................................................. 35

29

4.5.3

Biomass....................................................................................................................................... 37

30

4.5.4

Dead Organic matter ................................................................................................................... 39

31

4.5.5

Non-CO2 emissions..................................................................................................................... 39

32

4.6

Completeness, Times Series consistency, Quality Assurance and Quality Control ............................ 40

33

4.6.1

Completeness .............................................................................................................................. 40

34

4.6.2

Developing a consistent time series ............................................................................................ 41

35

4.6.3

Quality assurance and quality control ......................................................................................... 41

36

4.6.4

Reporting and documentation ..................................................................................................... 41

37

4.7

Future Methodological Development .................................................................................................. 42

38

Annex 4.1 .............................................................................................................................................................. 42

39

References ............................................................................................................................................................. 43

4.2

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 440

4.1

INTRODUCTION

4142This chapter provides guidance on estimating and reporting anthropogenic greenhouse gas (GHG) emissions andremovals from managed coastal wetlands.

43
44
45
46
47
48
49
50
51

Coastal wetlands are defined here as organic and mineral soils vegetated by vascular plants (eg. marsh grasses,
seagrasses, mangroves) that are covered or saturated for all or part of the year by tidal freshwater or salt water(>0.5ppt). The boundary of coastal wetlands is recognized as the landward extent of tidal inundation andextending seaward to the depth of vascular vegetation. This definition is very similar to a recent definition in a
specialized treatise on coastal wetlands (Perillo et al. 2009). In the 2006 IPCC Guidelines for National
Greenhouse Gas Inventories, wetlands were defined as any land that is covered or saturated with water for all orpart of the year, and that does not fall into the Forest Land, Cropland, or Grassland categories. While thisdefinition should still be used for classifying land and for reporting emissions, the guidance in this chapter
applies to all coastal wetlands whatever IPCC land class they fall into.

52
53
54
55
56
57
58
59
60

Coastal wetlands are important habitats for both ecological and economic reasons, providing numerous
ecosystem services for humanity, including food, fuel, and building material (Walters et al 2008; Geden et al2009). Coastal wetlands play a wide spectrum of roles as nursery grounds for many terrestrial and marine species,
in maintaining coastal water quality, in preventing or ameliorating land erosion, in sequestering carbon and otherelements, and as important transformers of nutrients often derived from land and sea. Coastal wetlands are foundon all continents and at all latitudes, covering more than 1,250,000 km2 of coastline worldwide, and are vital
links between land and the open ocean. It is estimated that globally up to 50% of historic natural coastal
wetlands have been degraded or converted to other land uses by human activities. Conversion of coastal
wetlands continues.

61
62
63
64
65

For ease of use, methods and guidance are given in three discrete sections: Management Changes in Coastal
Wetlands (Section 4.3), Drainage of Coastal Wetlands (Section 4.4), Rewetting and Restoration of Coastal
Wetlands (Section 4.5), and as defined in Table 4.1. This chapter covers coastal wetlands that have been clearedor degraded, restored, created or constructed, and where resource extraction occurs with little or no apparent
degradation (e.g., selective logging of mangrove trees).

66
TABLE 4.1
SECTIONS ADDRESSING MAJOR GREENHOUSE GAS EMISSIONSFROM MANAGED COASTAL WETLANDS
Land-use category/GHG

SectionManagement Changes in in Coastal Wetlands (This section covers coastal
wetland converted to other land uses in which the vegetation is altered (e.g. suchas harvesting mangrove trees), or through disruption of natural drainage, and/or
modifications to soils.

CO2
CH4
N2O

Section 4.3.2, 4.3.3, 4.3.4
Section 4.3.5
Section 4.3.5

Drainage of Coastal Wetlands (This section covers wetlands that have been
drained in which the soil water table is lowered, such as conversion for arable
agriculture and urban settlement).

CO2
CH4
N2O

Section 4.4.2, 4.4.3, 4.4.4
Section 4.4.5
Section 4.4.5

Rewetting and Restoration of Coastal Wetlands (This section covers rewetting ofcoastal wetlands that occurs where hydrology has been altered but soil is at
appropriate elevation for establishment of functioning vegetation).

CO2
CH4
N2O

Section 4.5.2, 4.5.3, 4.5.4
Section 4.5.5
Section 4.5.5

67

DRAFT 2013 Wetlands Supplement

4.3

Chapter 4

DO NOT CITE OR QUOTE

68

H uman Activ it ies and S ub - cat egor ie s

69
70

Coastal wetlands are managed for a wide variety of purposes, and for guidance, we have categorized wetland
type further in relation to the specific type of human impact in Table 4.2.
TABLE 4.2

CLASSIFICATION OF KNOWN HUMAN IMPACTS ON COASTAL WETLANDS, THEIR LAND-USE
CHANGE, AND THE CORRESPONDING SECTION IN THIS CHAPTER FOR GUIDANCEMANAGEMENT CHANGES IN COASTAL WETLANDS: CHAPTER SECTION: 4.3
Activity

Sub-category

Aquaculture

Fish or Shrimp Ponds; Fish Cages

Salt Production
Extraction

Dredging, Ports, Harbors; Beach Nourishment

Nutrient Enrichment
Nutrient Management

Addition; Removal

Hydrological/Sediment Diversion

Impoundments; Barriers

Nutrient Management

Addition; Removal

Fire Management
Harvesting

Fish, Shellfish; Wood and Non-Wood Products; Grass/Forbs

Recreation

Boat Anchoring, Mooring; Boating; Hunting

Grazing (Soil + Fauna)

Cattle, Sheep, Camel, Horse

DRAINAGE OF COASTAL WETLANDS (W-D): CHAPTER SECTION: 4.4
Modified Vegetation

Afforestation/Reforestation; Alteration of Vegetation

Hydrological/Sediment Diversion

Impoundments; Barriers

Ditching

Vector Control; Access Regulation

Agriculture

Arable Grass; Pasture

Draining and Filling

Settlement; Urbanization

Salt Production
REWETTING AND RESTORATION OF COASTAL WETLANDS (D-W): CHAPTER SECTION: 4.5
Restored Hydrology

Rewetting of drained soils; Restored Tidal (frequency), Connectivity

Revegetation

Afforestation/Reforestation; Reseeding; Alteration of Vegetation

Restoration through sedimentmodifications or enhancement

Sediment Removal; Ditch Filling; Sediment Resupply

71
72
73
74
75
76
77

Methodological assumptions and issues more specific to the three wetland-use categories are discussed in thecorresponding sections of this chapter. Readers are referred to Chapter 2 (Generic Methodologies Applicable toMultiple Land-Use Categories) of Volume 4 of the 2006 IPCC Guidelines for the basic equations to estimate
greenhouse gas emissions but guidance is duplicated here for the convenience of the inventory compiler. The
sections below are intended to provide carbon emissions and removals utilizing approaches based on emissions
and changes in carbon stocks.

78

4.2

79
80

The general methods used follow the guidance given in the 2006 Guidelines, Volume 4, especially chapter 2.
This section highlights some specific considerations for coastal wetlands.

4.4

GENERAL METHODOLOGICAL FRAMEWORKDRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

81
82
83
84
85
86
87
88

Chapter 4

The general methodological framework and generic methods described herein can be applied when reporting
removals and emissions associated with the land use activity changes in Management Changes of Coastal
Wetlands (Section 4.3), Drainage of Coastal Wetlands (Section 4.4), Rewetting and Restoration of Coastal
Wetlands (Section 4.5). The specific use of the generic methods described in Section 4.2 is provided under eachof these sub-section headings. The reader is referred to Table 4.2 for guidance related to a specific activity andthe subsection in which it is included. Following the general approach of the 2006 GLs, land use activity changes
can result in emissions and removals in each carbon pool (soil, biomass, dead organic matter) and in non-CO2
emissions. These changes are summed within each pool.

89
90
91
92
93
94
95

EQUATION 4.1
ANNUAL CARBON STOCK CHANGES FOR COASTAL WETLANDS AS A
SUM OF CHANGES IN ALL POOLS AND LAND USE ACTIVITY CHANGES∆CCW = ∆CM + ∆CD + ∆CR∆Ci = ∆CABi + ∆CBBi + ∆CDWi + ∆CLIi + ∆CSOi + ∆CHWPi
Where:∆CCW= carbon stock changes for Coastal Wetlands

∆CM
∆CD
∆CR

= Management Changes in Coastal Wetlands= Drainage of Coastal Wetlands= Rewetting and Restoration of Coastal Wetlands

∆CABi
∆CBBi
∆CDWi
∆CLIi
∆CSOi
∆CHWPi= carbon stock changes for aboveground biomass= carbon stock changes for belowground biomass= carbon stock changes for dead wood
= carbon stock changes for litter= carbon stock changes for soil
= carbon stock changes for harvested wood products

96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120

Emissions and removals of CO2 are based on changes in ecosystem C stocks for each management change foreach pool of Coastal Wetlands using either the Gain-Loss Method (2006 GL, Vol. 4, Eq. 2.4) or the StockDifference Method (2006 GL, Vol. 4, Eq. 2.5). Non-CO2 emissions are estimated with an emission rate from asource directly to the atmosphere (Volume 4, pg. 2.10). CO2 emissions may also be estimated using an emission
rate but is here considered as a parameter within the soil pool estimate. The use of each methodological approachis based on the activity that is reported. Clear guidance on using these methods are provided under each of thesubsections detailed in this Chapter. Refer to Table 4.2 for guidance related to a specific activity and thesubsection in which it is included. The guidance has been developed to allow the inventory compiler theflexibility to report on an activity that may not be included in this methodological guidance of this Chapter,
especially where Tier 2 methods should be applied. It is good practice to report neither over- or under-estimates
and to perform validation checks that all pools have been considered and to avoid possible omissions or doublecounting (eg. transition matrices Table 2.1, pg. 2.19).

121
122
123
124

The choice of Tier level for estimating emissions and removals associated with management changes, drainage
or rewetting and restoration in coastal wetlands is determined following a decision tree with decisions based on
available data and key category analysis (Figure 4.1). The decision tree applies similarly for each of the C pools
and non-CO2 emissions as for activity data.

DRAFT 2013 Wetlands Supplement

4.5

Chapter 4

DO NOT CITE OR QUOTEStart

Are detailed information
available on coastal wetlands
that have been altered, drainedor rewetted?

Estimate emissions
using country-specificmethodology andemission factors(Tier 3).

Yes

No

Are historical and current data
available on the area of managed
coastal wetlands?

Yes

Were domestic studies
conducted on
GHG emissions/removals on
managed coastal
wetlands?

No

Are managed coastal wetlands a
key category?

Yes

Estimate emissions
using default method
and country-specificdata (Tier 2).

No

Yes

Collect or compile
relevant datasets

Estimate emissions using
default method andemission factors andnational activity data
(Tier 1)

No

Estimate emissions using
default emission factors
and activity data (Tier 1)

125
126
127
128

Figure 4.1 Decision tree for identification of appropriate Tier to estimate changes in carbon
emissions and removals in Coastal Wetlands.

129
130
131

4.6

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

132

4.2.1

Change in soil carbon

133
134
135
136

Activities associated with land-use change in coastal wetlands can influence organic, mineral and inorganic
stocks of C in soils. While data on inorganic stocks of C (i.e. dissolved inorganic carbon) are not sufficient toprovide generic methodologies, the methodological approach provided here takes into account the possible
emissions and removals associated with changes in C of organic and mineral soils.

137
138
139
140
141
142

Previous guidance on C in organic soils (Chapter 2, pg. 2.28 and Chapter 7) omitted C gains that are possible
through coastal wetland restoration. This supplement includes good practice methodologies to report on C gains
and C losses. Activities in coastal wetlands such as restoration where C gains should be reported are presented
along with methodologies to estimate CH4 losses. This is especially important for some coastal wetlands where
CH4 emissions are low or considered to be negligible (Bridgham et al, 2006; Poffenbarger et al 2011) and forhigher Tier methods.

143

TIER 1

144
145
146
147
148
149
150
151
152

Many land-use (i.e. management) activities specific to coastal wetlands can result in changes to soil carbon
stocks. For mineral and organic soils, the generic default method is the same at Tier 1 level of estimation. As
mineral and organic soils are difficult to differentiate using activity data that would likely be used for coastal
wetlands at Tier 1 level of estimation, the following methodology assumes they are aggregated. The equation for
estimating the total change in soil C stocks has been adapted from Equation 2.24 in the 2006 GLs to include C
gain and is given in Equation 4.2. Depending on management activity, the parameters used to determine
emissions and removals from coastal wetland soils vary. Thus, inventory compilers are thus referred to theactivity sections 4.3-4.5 (below) for more detailed guidance and for emission/removal and stock change factors
specific to those activities.

153
154
155
156
157

EQUATION 4.2
ANNUAL CHANGE IN CARBON STOCKS IN SOILS∆CSO = ∆CMIN/ORG + ∆CINORGANIC
Where:

158

∆CSO

159

∆CMIN/ORG

160
161∆CInorganic= annual change in inorganic carbon stocks from soils, tonnes C yr-1 (assumed to be zerounless using a Tier 3 approach)

162
163
164
165

Soil organic C in mineral soils is assumed to exist to a default depth of 1m. While changes in soil organic C inorganic soils can occur throughout the depth profile, they are assumed to occur within 1 m for Tier 1 estimates;
in wetlands, carbon content in soils generally declines with increasing depth. Residue/litter C stocks are notincluded because they are addressed by estimating dead organic matter stocks.

166
167
168
169

In a similar fashion to the methodological approaches applied for soils in the 2006 GL, it is possible thatcountries will use different Tiers to estimate emissions and removals from C stocks in mineral and organic soils
and inorganic C. The inventory compiler can refer to the Decision Tree found in Figures 2.4 and 2.5 on pgs. 2.32
and 2.33 of the AFOLU Volume for guidance on Tier levels that should be applied.

170
171
172
173

Depending on management activity, C changes in organic soils may be determined by: 1) assigning an annual
emission or removal factor that estimates losses or gains of C following an activity (Equation 4.3) or 2) stockchange factor approach (Equation 4.4). Whether approach 1 or 2 is used for estimating C change in organic soils,
non-CO2 emissions must also be reported.

174

Tier 1, Approach 1 – Annual Emission /Removal Factor

175
176
177
178
179

= annual change in carbon stocks in soils, tonnes C yr-1
= annual change in organic carbon stocks in mineral and organic soils, tonnes C yr-1

EQUATION 4.3
ANNUAL CHANGE IN CARBON STOCKS IN SOILS∆CMIN/ORG = GMIN/ORG – LMIN/ORG
GMin/Org = ∑c,s,e (Ac,s,e • RFLUc,s,e)
LMin/Org = ∑c,s,e (Ac,s,e • EFLUc,s,e)
Where:

180

GMin/Org = annual carbon gain from rewetted or restored soils, tonnes C yr-1

181

LMin/Org = annual carbon loss from drained soils, tonnes C yr-1

DRAFT 2013 Wetlands Supplement

4.7

Chapter 4

DO NOT CITE OR QUOTE

182

A= land area of drained organic soils

183c= climate zones

184s= salinity level (if applicable)

185
186

e

= ecosystem type (i.e. mangrove, tidal freshwater wetland, seagrass, salt marsh; oceanic,
estuarine)

187
188

RFLUc,s,e = removal factor for each land-use subsystem resulting in rewetting or restoration (i.e.
management activity) disaggregated climate, salinity level and ecosystem type

189
190

EFLUc,s,e = emission factor for each land-use subsystem resulting in drainage (i.e. management activity)
disaggregated climate, salinity level and ecosystem type

191
192
193
194

Tier 1, Approach 2 – Stock Change Factor

195
196
197
198

For all soils, the default methods are based on changes in soil C stocks over a finite period of time (40 year
transition period). The change is calculated based on C stock after the management changes relative to thecarbon stock in a reference condition (i.e native vegetation that is not degraded or otherwise altered). At Tier 1
the following assumptions are made:In the case where coastal wetlands can be disaggregated by soil type (e.g. where land areas are classified by soil
type and higher level ecosystem type classifications are not available), the stock change factor approach toestimating the change in C in organic soils is the appropriate Tier 1 default method.

199
200

(i)

Over time, soil organic C reaches a spatially-averaged, stable equilibrium value specific to the
management state. This implies C fluxes approach zero in the equilibrium state; and

201

(ii)

Soil organic C stock changes during the transition to a new equilibrium occur linearly.

202
203
204
205
206
207
208
209
210

While soils in wetlands subject to tidal flooding continuously accumulate Carbon (Chmura et al. 2003), this rateof accumulation can be small in the absence of changes in water level. For the purpose of Tier 1 estimation
however, the assumption is a 40 year transition period, with C changes occurring linearly, until equilibrium atthe end of the transition period. Under some management conditions, such as those that include drainage, any
accumulation stops and soils may tend towards an equilibrium C content. Emissions for CO2 from coastalorganic soils are comparable with emissions from terrestrial organic soils for a given management practice andclimate zone (e.g. Deverel and Rojstaczer, 1996; Deverel and Loughton, 2010; Yit et al., 2011, Zenello et al.,2011). Although soil C changes in response to management changes may better be described by other simple
model fits, assumption (ii) greatly simplifies the Tier 1 methodology.

211
212
213
214
215
216
217

Using the default method, changes in soil C stocks are computed over an inventory time period, likely
established based on the years in which the management activity data are collected. Thus, management activity
data collected in 1990, 1995, 2000 would correspond to inventory periods 1990-1995 and 1995-2000. The stockchange factor approach described here takes the difference in SOC between periods of change in management
activities based on multiplying the reference C stocks by the stock change factors. Annual rates of carbon stockchange are then estimated using a Stock-Difference Method (i.e. as the difference in stocks at two points in time
divided by the time dependence of the stock change factors.

218

The following was adapted from Equation 2.25 (Volume 4, Chapter 2):

219
220
221
222
223

EQUATION 4.4
ANNUAL CHANGE IN ORGANIC CARBON STOCKS IN COASTAL WETLAND SOILS∆CMIN/ORG = (SOCM/O,a – SOCM/O,b)/D
SOC = ∑c,s,e (SOCREFc,s,e • FLUc,s,e • FMGc,s,e • Ac,s,e)

224
225

∆CMIN/ORG = annual change in C stocks in coastal wetland soils, tonnes C yr-1

226

SOCM/O,a = equilibrium soil organic carbon stock following a change in management tonnes C

227

SOCM/O,b = equilibrium soil organic carbon stock before a change in management tonnes C

228

D= number of years for transition to take place, default = 40 yr

229c= climate zones

230s= salinity level (if applicable)

231
232

e

4.8

= ecosystem type (i.e. mangrove, tidal freshwater wetland, seagrass, tidal salt marsh; oceanicand estuarine)

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

233

SOCREF= the reference carbon stock, tonnes C ha -1

234

FLU

= stock change factor for land-use subsystem (i.e. management activity)

235

FMG

= stock change factor for management regime (i.e. intensity)

236

A = land area of the stratum being estimated, ha

237
238
239
240
241
242
243
244
245
246

SOCM/O,a and SOCM/O,b are calculated using the SOC equation above where the reference carbon stocks andstock change factors are assigned according to the land-use subsystem, management regime (if applicable) andcorresponding areas at each point in time. The time dependence of stock change factors (D) is the default time
period for transition between equilibrium SOC values (40 years). The time dependence considers assumptions
made in computing the stock change factors FLU and FMG. In disaggregating land area (A), all land in a stratum
should have common biophysical conditions and management history over the inventory time period. For
wetlands on mineral soils, assume that 50% of organic material held within the top 1 meter of soils is emitted
over a 40 year period and that the remaining carbon is recalcitrant. For example, temperate wetland converted toarable land or settlement EF = (0.5 * 351)/40 Mg C ha-1 yr-1 over a 40 year period.

247
248
249
250
251
252

Inventory calculations are based on land areas that are disaggregated by climate zones, salinity level andecosystem type where stock change factors for management activities apply. All levels of disaggregation MAY
or MAY NOT be included in estimation of soil C stock change as not all management activities apply in all
ecosystems at all salinity levels at any Tier level approach. However, where a management activity is a key
category, countries should disaggregate to the level that will provide the best estimation possible utilizing
country-specific data.

253
254
255
256

See land-use subsections 4.3 – 4.5 for tables of soil stock change factors where applicable. Refer to pg. 2.34, Box
2.1 for more information on alternative formulations of Equations 4.5 and 4.6 when using different land
representation approaches for activity data. Methods are presented for separating stocks and stock change factors
at these levels of disaggregation based on available data or for a Tier 2 or higher level of estimation.

257
TABLE 4.3. DEFAULT VALUES FOR CARBON STORED IN COASTAL WETLANDS (SOCREF) BASED UPONAVERAGE CARBON DENSITY MEASURED IN TOP 1 M.
Climate Zone

Ecosystem

Number of
Observations

Mean (Mg C
Ha-1)

Range (Mg C
ha-1)

Boreal andTemperate

Tidal Marshes

134

351

47-19001

Tropical and
Sub tropicalMangroves

94

485

155-11501

GlobalSeagrass

89

194.2±20.2

9 – 6281

Sources: Chmura et al . 2003, Silfleet et al., 2011, Donato et al., 2011; Fourqurean et al., 2012;
Data for tidal marsh soil stocks is derived from the following locations (with number ofobservations): Northeast Canada (37), Gulf of Mexico (Louisiana, Texas, Mississippi) (26), New
England (20), Chesapeake Bay (12), California (6), North Carolina (6), UK, (6), California (5),
Florida (5), Netherlands (4), Denmark (2), Rhone Delta, France (1), British Columbia, Canada(1). Data for mangrove soil stocks is derived from the following locations (with number ofobservations): Orinoco Delta, Venezuela (40), Florida, USA (12), Kosrae (7), Sulawesi (6),Borneo (5), Yap (5), Boca Chica, Mexico (4), Umengi estuary, South Africa (4); Pohnpei Island,
Micronesia (3); Columbia (3); Sundarbans, Bangladesh (2); Java (2), Palau (1).
258
259

TIER 2

260
261
262
263
264
265
266

Many land-use (i.e. management) activities specific to coastal wetlands can result in changes to carbon stocks inboth organic and mineral soils. Tier 2 methods assume that mineral and organic soils can be disaggregatedwithin ecosystem type. Other methods may be more appropriate depending on national circumstances.
Regardless of the method used, Tier 2 and higher level of estimation require country-specific data which, to theextent possible, should be disaggregated by climate type and ecosystem type. The equation for estimating thetotal change in soil C stocks has been adapted from Equation 2.24 in the 2006 GLs to include C gain and is given
in Equation 4.5:

267

DRAFT 2013 Wetlands Supplement

4.9

Chapter 4

268
269
270
271

DO NOT CITE OR QUOTE

EQUATION 4.5
ANNUAL CHANGE IN CARBON STOCKS IN SOILS∆CSO = ∆CMINERAL + ∆CORGANIC + ∆CINORGANIC
Where:

272

∆CSO

273

∆CMineral = annual change in organic carbon stocks in mineral soils, tonnes C yr-1

274

∆COrganic = annual change in organic carbon stocks in organic soils, tonnes C yr-1

275
276

∆CInorganic= annual change in inorganic carbon stocks from soils, tonnes C yr-1 (assumed to be zerounless using a Tier 3 approach)

277
278
279
280
281
282
283
284
285

For Tier 2 methods, soil organic C in mineral soils is assumed to exist to a default depth of 1m. For wetlands onmineral soils, assume that 50% of organic material held within the top 1 meter of soils is emitted over a 40 year
period and that the remaining carbon is recalcitrant. Residue/litter C stocks are not included because they are
addressed by estimating dead organic matter stocks. While changes in soil organic C in organic soils can occur
throughout the depth profile, carbon content in soils generally declines with increasing depth, but should also be
considered. In disaggregating land area (A), all land in a stratum should have common biophysical conditions
and management history over the inventory time period. For both mineral and organic soils, Tier 2 methods
should apply different model assumptions about the fit of the decay or accumulation curves. Compilers should
also develop national factors and parameters to match their national conditions.

286
287
288
289

In a similar fashion to the methodological approaches applied for soils in the 2006 GL, it is possible thatcountries will use different Tiers to estimate emissions and removals from C stocks in mineral and organic soils
and inorganic C. The inventory compiler can refer to the Decision Tree found in Figures 2.4 and 2.5 on pgs. 2.32
and 2.33 of the AFOLU Volume for guidance on Tier levels that should be applied.

290

4.2.2

291
292
293
294
295
296
297
298

Changes in biomass stocks follow guidance provided in the 2006 GL, Vol. 4, Chapter 2 and Chapter 4 for coastal
wetland ecosystem types with woody biomass (i.e. mangroves and some salt marshes) and Chapter 2 andChapter 6 for coastal wetland ecosystem types with non-woody biomass (most salt marshes and seagrasses).
While biomass stock changes are typically not estimated for ecosystems with non-woody biomass at the Tier 1
level which are based on a steady-state assumption, it is good practice to evaluate the appropriateness of thisassumption, and to report changes in non-woody biomass when it is not met or the management activity is
associated with a key category. This assumption and steady-state consideration for non-woody biomass follows
that for Grasslands in the 2006 GL and applies for non-woody coastal wetland ecosystems.

299
300
301
302
303
304
305

The decision tree in, Figure 4.1 provides guidance for selecting the appropriate Tier level for the implementationof estimation procedures for biomass associated with the rewetting of previously drained coastal wetlands.
Estimation of changes in biomass requires an estimate of changes in above-ground vegetation and changes in
below-ground biomass. Countries should use the highest Tier possible given national circumstances. It is goodpractice to use a Tier 2 or Tier 3 approach if carbon emissions and removals in coastal wetlands is a key
category or if the sub-category of biomass is considered significant, based on principles outlined in Volume 1,
Chapter 4.

306
307

Biomass stock changes can be estimated with either Gain-Loss or Stock-Difference methods as presented in
Equations 2.7 and 2.8, Volume 4, Chapter 2, and summarized below.

308
309
310
311
312
313
314
315

Gain-Loss Method (see Equation 2.7): This method involves estimating the area of each type of conversion
associated with rewetting of land that was previously a coastal wetland and the average annual transfer into andout of biomass stocks. This requires: (i) an estimate of the area under Rewetting of Coastal Wetlands according
to different ecosystem type, different species within a particular ecosystem that could be related to climate orsalinity or other ecological zoning of vegetation, disturbance regime, management regime, or other factors
significantly affecting biomass carbon pools; (ii) the quantity of biomass accumulating in the biomass stocks;
and (iii) the quantity of biomass lost from the biomass stocks on per hectare basis according to different type ofvegetation that grows after rewetting due to the restoration of hydrology.

316
317
318
319

Stock-Difference Method (see Equation 2.8): This method involves estimating the area of each type of land
conversion associated with change in the biomass stocks at two periods of time, t1 and t2. The biomass stockchanges for the inventory year are obtained by dividing the stock changes by the period (years) between two
measurements. The Stock-Difference Method is feasible for countries that have periodic inventories, and is more

4.10

= annual change in carbon stocks in soils, tonnes C yr-1

Change in biomass carbon stocks

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4320
321

suitable for countries adopting Tier 3 methods. This method may not be well suited to regions with very variableclimates and may produce spurious results unless annual inventories can be made.

322

TIER 1

323
324
325
326
327
328
329
330
331
332
333
334
335

The Tier 1 method, when combined with default biomass growth rates, or change in stocks, for a management
activity allows any country to calculate the annual increase in biomass, using estimates of area and mean annual
biomass increment for each stratum. In the case of coastal wetlands, these strata include possible disaggregation
by climate, ecosystem type and salinity level. All levels of disaggregation may not be applicable. The Tier 1
level only considers biomass changes associated with woody vegetation. Biomass changes in non-woody
vegetation are considered negligible except in the case of higher level Tier estimations or where there is a change
in intensity of management in which case the assumption of biomass at an approximate steady-state (i.e., carbon
accumulation through plant growth is roughly balanced by losses through grazing, decomposition and fire) is not
valid, and the carbon stock changes can be significant. If it is reasonable to assume that coastal wetlands are notpart of a key source, a country may apply the Tier 1 assumption of no change in biomass. However, if
information is available to develop reliable estimates of rates of change in biomass, a country may use a higher
Tier, even if C stock changes in coastal wetlands are not a key source, particularly if management changes arelikely.

336
337
338
339
340
341
342
343
344
345

The change in biomass carbon stock on under Tier 1 should be estimated using Equation 2.15 of the 2006
guidelines. The average carbon stock change is equal to the sum of increase in carbon stock due to biomass
growth following conversion, changes due to actual conversion (difference between biomass stocks before andafter conversion), and decrease in carbon stocks due to losses after conversion. As a simplification for Tier 1, it
is assumed that all biomass is lost immediately from the land after a conversion (Equation 2.16), even when
there is no abrupt change. In this case the residual biomass (BAFTER) is assumed to be zero, (i.e., the vegetationthat characterizes the previous state, for example scrubland on drained wetland, is cleared of all vegetation
before the new, coastal wetland state is established). In this case there is no transfer of biomass from the biomasspool to the dead wood pool, for example. Default values for mangrove, seagrass and salt marsh biomass prior toconversion can be found in Tables 4.4-4.8).

346

TIER 2

347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364

The Tier 2 calculations differ structurally in a number of ways from Tier 1. First, Tier 2 estimates use the twophase approach described earlier. Tier 2 relies on country-specific estimates of the biomass in initial and final
land uses rather than the defaults, as in Tier 1. Land area estimates may be disaggregated at higher resolution
spatial scales than in Tier 1 to capture country wide regional variations within and between the different coastal
wetland ecosystems that result from the rewetting. Second, for Tier 2 countries may modify the assumption thatbiomass immediately following conversion is zero. This enables countries to take into account land-use
transitions where some, but not all, vegetation from the original land use is removed. In addition, under Tier 2, itis possible to account for biomass accumulation following establishment of the rewetted coastal ecosystem overa several year period (rather than accounting all biomass stock change in the year of conversion) if data are
available to estimate the time to full biomass establishment and the annual stock changes. Third, under Tier 2, itis good practice to apportion transfers of carbon between pools. Some of the rewetted coastal ecosystems may
not contain significant carbon in the dead wood or litter pools, but woody biomass may persist that had
previously accumulated during a particular land use on a previously drained coastal wetland. If the rate of land
conversion is more or less constant, the assumption that all carbon in theses pools was lost at the time of
conversion would be a reasonable first approximation. Where the rate of land conversion varies over time, it isappropriate to try to account for the transfer and release of carbon from litter, dead wood, and soil carbon pools.
It is therefore necessary to distinguish immediate losses due to the conversion activities from the losses that
occur in the years following the land conversion.

365
366
367
368
369
370
371
372
373

The immediate and abrupt carbon stock change in biomass due to rewetting of previously drainage of coastal
wetlands under Tiers 2 and 3 will be estimated using Equation 2.16 in Chapter 2, where BAFTER is assumed to be
zero. During the transition period, pools that gain or lose C often have a non-linear loss or accumulation curvethat can be represented through successive transition matrices. For Tier 2, a linear change function can beassumed. For a Tier 3 approach based upon these methods, it is good practice to use the true shapes of the curves.
These curves are to be applied to each cohort that is under transition during the reporting year to estimate theannual change in the biomass carbon pools. For the estimation of changes in biomass carbon during thetransition phase, two methods are suggested. The equations, related to the Gain-Loss Method and StockDifference Method are the same as those used in Chapter 2 of the 2006 guidelines.

374

TIER 3

375
376
377

Tier 3 methods are used where countries have country-specific emission factors, and substantial national data.
Country-defined methodology may be based on detailed inventories of permanent sample plots for each coastal
wetland ecosystem created through rewetting and/or models. For Tier 3, countries should develop their own

DRAFT 2013 Wetlands Supplement

4.11

Chapter 4

DO NOT CITE OR QUOTE

378
379
380

methodologies and parameters for estimating changes in biomass. These methodologies may be derived frommethods specified above, or may be based on other approaches. The method used needs to be clearly
documented.

381
382
383
384
385
386
387
388

Tier 3 involves inventory systems using statistically-based sampling of biomass over time and/or process models,
stratified type of coastal wetland ecosystem by management regime, climate and salinity. For example, if apreviously drained coastal wetland was being used as pastureland and it was converted to salt march wheninundated by seawater, validated species-specific growth models that incorporate management effects such as
grazing intensity and fertilization, with corresponding data on management activities, could be used to estimate
net changes biomass in the rewetted coastal ecosystem, over time. Models, together with periodic samplingbased biomass estimates, could be applied to estimate stock changes to make spatial extrapolations for areas ofrewetting of previously drained coastal wetland.

389
390
391
392
393

Key criteria in selecting appropriate models include the ability to represent all of the ecosystem conversions andmanagement practices that are represented in the activity data. It is critical that the model be validated withindependent observations from country-specific or region-specific field locations that are representative of thevariability of local environmental change as well as climate, salinity, soil and vegetation management systems in
the country.

394
395
396
397

If possible, spatially explicit area estimates should be used to facilitate complete coverage of the converted area
represented by the rewetting of previously drained coastal wetlands and ensure that areas are not over- or
underestimated. Furthermore, spatially explicit area estimates can be related to locally relevant carbon
accumulation and removal rates, and restocking and management impacts, improving the accuracy of estimates.

398
399
400
401
402
403
404
405
406
407
408
409

Regardless of Tier estimation method used, it is good practice, if possible, to develop and use a disturbancematrix (Example, 2006GL, Vol. 4, Table 2.1) for each biomass, dead organic matter and soil carbon pool, theproportion of the carbon remaining in that pool, and the proportions transferred to other pools, to harvested wood
products and to the atmosphere, during the disturbance event. The proportions in each row always sum to 1 toensure conservation of carbon. The value entered in cell A is the proportion of above-ground biomass remaining
after a disturbance (or 1 – fd, where fd, the fraction of biomass lost in the disturbance, is defined in Equation 2.14,
Volume 4, Chap 2). The Tier 1 assumption is that all of fd is emitted in the year of disturbance: therefore thevalue entered in cell F is fd. For higher Tiers, only the proportion emitted in the year is entered in cell F and theremainder is added to cells B and C in the case of fire, and B, C, and E in the case of harvest. It is good practice
to develop disturbance matrix even under Tier 1 to ensure that all carbon pool transfers are considered, though
all biomass carbon is assumed to be emitted in the year of land conversion. It is important to note that some of
the transfers could be small or insignificant.

410
411

4.12

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

TABLE 4.4 RATIO OF BELOW-GROUND BIOMASS TO ABOVE-GROUND BIOMASS (R)DomainVegetation type

TropicalMangroveR mean [tonne root d.m.
(tonne shoot d.m.)-1

0.67

R range orerror [tonne
root d.m.
(tonne shootd.m.)-1
0.53-0.77

1.4

0.2-5.5/1.2

0.89

0.35-1.43

References

Donato et al. 2012 ;Kauffman et al. 2011 ;Komiyama et al. 2008
Liao et al. 1991 ; Lin and
Lin 1988 ; Lin and Lu
1990

Salt marsh

Subtropical/low
Temperate

Seagrass(global average)
Mangrove

Salt marsh (lowmarsh, highmarsh)

0.42, 3.4

±16%*,±230%*

Temperate

Salt marsh

0.91

±27%*

Mediterranean

Salt marsh

2.5

±89%*

BorealSalt marsh

Duarte & Chiscano 1999
Komiyama et al. 2008
Lin and Lin 1988
Buresh et al 1980; Darby
and Turner 2008; Edwards
and Millis 2005; Dunton etal 2001
Whindham 2001
Curco et al 2002; Neves etal 2007*95% CI

412
3

TABLE 4.5 DEFAULT BIOMASS CONVERSION AND EXPANSION FACTORS (BCEF), TONNES BIOMASS (M OF WOOD VOLUME)-1(IPCC 2006)
BCEF for expansion of merchantable growing stock volume to above-ground biomass (BCEFs), for conversion of net annual
increment (BCEFI) and for conversion of wood and fuelwood removal volume to above-ground biomass removal (BCEFR)
Climatic
ForestBCEF
Growing stock level (m3)
zone
type
<10
11-20
21-40
41-60
61-80
80-120120-200>200
Humid
Tropicalnaturalforests

BCEFS
BCEFI
BCEFR

9.0
(4.0-12.0)

4.0(2.5-4.5)

2.8(1.4-3.4)

2.05(1.2-2.5)

1.7(1.2-2.2)

1.5(1.0-1.8)

1.3(0.9-1.6)

0.95(0.7-1.1)

4.5
10.0

1.6
4.44

1.1
3.11

0.93
2.28

0.9
1.89

0.87
1.67

0.86
1.44

0.85
1.05

Note: Lower values of the ranges for BCEFS apply if growing stock definition includes branches, stem tops and cull trees; upper values apply if
branches and tops are not part of growing stock, minimum top diameters in the definition of growing stock are large, inventoried volume falls near the
lower category limit or basic wood densities are relatively high. Continuous graphs, functional forms and updates with new studies can be found at theforest- and climate- change website at: http://www.fao.org/forestry/
Average BCEF for inhomogeneous forests should be derived as far as possible as weighted averages. It is good practice to justify the factors chosen.
To apply BCEFI, an estimate of the current average growing stock is necessary. It can be derived from FRA 2005 at http://www.fao.org/forestry/
BCEFR values are derived by dividing BCEFS by 0.9
Sources: Brown S. et al., 1989; Brown S. and A. Lugo, 1992; Brown S., 2002; Fang J.Y., 2001.

413
414

DRAFT 2013 Wetlands Supplement

4.13

Chapter 4

DO NOT CITE OR QUOTETABLE 4.6 DEFAULT VALUES FOR ABOVE-GROUND BIOMASS OF MANGROVE AND TIDAL SALT MARSH WETLANDS(TO BE COMPLETED)
DomainTropical

Vegetation
type

Continent

Species

Mangrove

Pacific andAustralia

A. marina
B. gymnorrhiza

Atlantic
and Africa

Above-groundbiomass (tonnes
d.m. ha-1)
144.5
305.5 (97.6-436.4)

B. sexangula
R. apiculata
Sonneratia spp.
Mixed mangrove
forests
Mixed mangrove
forestB. gymnorrhiza

179.9 (79.0-279.0)
249.2 (40.7-460.0)
225.2 (169.1-281.2)

C. tagalL. racemosa
R. mangle
R. mucronata
Mixed mangrove
forests
A. alba

40.1
51.7 (31.5-71.8)
147.5 (62.9-233.0)
249.0

References

Briggs 1977
Komiyama etal. 2008

107.1 (57.0-172.0)
392.0 (262-522)
47.3 (37.2-76.7)

Donato et al.
2012
Liao et al.
1991

151.2 (56.0-315.0)
22.5 (21.1-23.3)

Mitra et al.
2011

A. marina

341.0

Mackey 1993

B. gymnorrhiza

94.5

A. marina

341.0

Komiyama etal. 2008
Mackey 1993

Salt marsh
Subtropical

SubtropicalMangrove

Mangrove

Pacific andAustralia
Atlantic
and Africa
Pacific andAustralia

Salt marsh
Temperate

Salt marsh

BorealSalt marsh

415
416
TABLE 4.7 DEFAULT VALUES FOR ABOVE-GROUND GROWTH IN MANGROVE AND TIDAL SALT MARSHWETLANDS

Climate Zone

4.14

Country

Species

Net growth in aboveground biomass (tonnes
d.m. ha-1 yr-1)

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Tropical

Chapter 4

R. mangle

1.6agerminans

5.9

L. racemosa

5.4

Sonneratia apetala

12.5

S. caseolaris

26.4

A. officinalis

7.6

A. marina

4.4

A. alba

2.1

gymnorrhiza

0.6

Bruguiera sexangula

0.1

Excoecaria agallocha

4.7

Xylocarpus moluccensis

0.5

B. parviflora

27.4

R. apiculata, B.
gymnorrhiza

8.7

Micronesia

Mixed species

4.2

VietnamR. apiculata

4.9

R. apiculata

19.0

K. candel

5.3

K. candel

13.4

R. apiculata

15.7

R. apiculata

10.6

China

K. candel

24.4

Dominican
Republic

Mixed species (R. mangle,
A. germinans, L. racemosa)

19.7

Guadeloupe

Mixed species (R. mangle,
A. germinans, L. racemosa)21.2 (fringe), 6.2 (dwarf)

HawaiiR. mangle

29.1

Sri Lanka

R. mucronata, A. marina

11.0

Cuba

Bangladesh

Malaysia

ThailandSource: Table 2.9 in Alongi 2010

417
418
419

DRAFT 2013 Wetlands Supplement

4.15

Chapter 4

DO NOT CITE OR QUOTETABLE 4.8 DEFAULT VALUES FOR ABOVE-GROUND BIOMASS AND NET GROWTH OF SEAGRASSES

Seagrass (Species)
Amphibolis antarctica
Cymodocea nodosa
Cymodocea rotundata
Cymodocea serrulata
Enhalus acoroides
Halodule uninervis
Halodule wrightii
Halophila ovalis
Heterozostera tasmanica
Phyllospadix
Posidonia oceanica
Ruppia maritima
Syringodium filiforme
Syringodium isoetifolium
Thalassia hemprichii
Thalassia testudinum
Thalassodendron ciliatum
Zostera capricorni
Zostera marina
Zostera noltii

Number ofobservations
1
14
3
4
6
6
17
7
5
1
8
3
2
3
3
12
2
1
43
5

Mean
(max biomass,
g C m-2)
660
81
10
31
92
115
49
15
103
1
213
56
45
22
73
342
53
96
139
36

Std Dev(max biomass,
g C m-2)
81
6
17
69
242
26
7
47
132
19
30
16
57
750
7
140
26

Source: Duarte and Chiscano 1999

420

421

4.2.3

422
423
424
425
426
427
428
429
430
431
432

The dead organic matter pool in coastal wetlands includes coarse woody debris, dead roots as well as fine littermaterials, and varies depending on tidal inundation and frequency, as well as soil oxidation and vegetation cover.
Fine litter can be exported with tidal activity while senesced woody biomass is buried or decomposes in-situ to
influence soil organic C stocks. Due to the extent of tidal action, accumulation of fine litter is difficult toestimate because exports can be large. Turnover of course woody debris and woody material is also difficult toestimate because of slow decay rates. Partitioning these materials from peat soils also poses estimationdifficulties. However, as coverage in this chapter is meant to be applicable to all coastal wetland types,
especially mangrove, tidal salt marsh, tidal freshwater marsh, and seagrass ecosystems, coastal wetlands coveredin this chapter include both wetlands of herbaceous and woody vegetation cover and thus approaches forincluding changes in dead organic matter C stocks. Countries are encouraged to use Tier 2 or higher methods
when changes in dead organic matter C stocks are a key category.

433

FORESTED COASTAL WET LANDS

434
435
436
437
438
439
440
441
442
443
444
445
446

For ecosystems with woody vegetation, management activities that result in vegetation disturbance or recovery
will influence C emissions and removals. Following Tier 1 methodologies, changes in dead organic matter C
stocks with a management activity that result in conversion of another land-use to a forested coastal wetland (e.g.
restoration) or conversion of a forested coastal wetland to another land-use (e.g. clearing for aquaculture),
general methodologies developed for forestland conversion should be followed. All C in DOM stocks are
considered lost in the year of conversion when converting to another land-use category, management regime or
disturbance event. Thus, the carbon in biomass killed during a disturbance or management event (less removal of
harvested wood products (HWP), depending on how HWP is treated) is assumed to be released entirely to theatmosphere in the year of the event. When conversion to a forested coastal wetland occurs, dead organic matterstocks are considered to start at 0 with linear accumulation over a transition period. In forestland conversions,this is estimated as 40 yr. The transition period from live woody biomass to dead wood (i.e. course woody debris)is dependent on biomass turnover which would vary as a result of soil oxidation, nutrient availability, andclimate domain as well as time since other types of disturbance. During transition periods, changes in dead

4.16

Change in Dead Organic Matter Carbon Stocks

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4447
448

organic matter stocks following land-use conversion require that the area subject to land-use change be tracked
for the duration of the transition period on an annual time step.

449
450
451

When applying Tier 1, harvesting or other vegetation disturbance that results in a change from a forested coastal
wetland to a non-forested coastal wetland should also be estimated Regardless of whether the vegetation
disturbance results in another coastal wetland type.

452
453
454

The methods for estimating changes in forested coastal wetlands follow generic equations for dead organic
matter stock changes as provided in Volume 4, Chapter 2 of the 2006 GL. both changes in dead wood and littershould be reported and summed to obtain changes in total dead organic matter.

455
456
457
458
459
460
461
462
463
464
465

In Tier 1 estimations, a land-use conversion or management activity that results in a disturbance to vegetation
follows the assumption that all C from biomass loss results in a CO2 emission to the atmosphere. Conversely, fora change that results in a conversion to forested coastal wetland from non-forested coastal wetland, the Carbon
stock in dead wood and litter is assumed to increase linearly from 0. At the Tier 1 level of estimation, litter anddead wood exports (due to tidal activity) are considered to be unchanged before and after the conversion or
activity. Countries using a Tier 1 approach can use the default dead wood and litter stocks in Table 4.8. The
difference between litter carbon stocks were not significantly different for tropical and subtropical mangrovesites and they were thus aggregated. Countries with dead organic matter stocks as a component of key category
land use or management activities should use Tier 2 or higher methods and country estimates to report Cemissions and removals. In these cases, exports of dead wood and litter should also be estimated and reported.

466
TABLE 4.9 TIER 1 DEFAULT VALUES FOR DEAD WOOD AND LITTER CARBON STOCKS
ClimateDead wood carbon stocksE(tonnes C ha-1)

Litter carbon stocksF(tonnes C ha-1)

TropicalAestuarine

13.2 (3.4)

oceanic28.0 (5.7)

estuarine

9.9 (2.1)

estuarineC

0.037 (0.009);
0.026 - 0.053

NE Brazil (tropical,
urbanized watershed)

Estuarine

0.192 (0.144)

Mexico (tropical, coastallagoon)Estuarine

0.106 (0.032)

SubtropicalB

Source: Donato et al. 2011, Robertson and Daniel 1989, Krauss et al. 2005, Twilley et al. 1986, Chen et al. 2008, Imgraben and Dittman 2008,
Twilley et al 1997, Flores-Verdugoet al.1987, Silva et al 1998; ATropical dead wood stocks are estimates for Indo-Pacific mangroves only;B
Subtropical dead wood stocks are estimates for S. Florida mangroves only; CLitter C stocks for tropical and subtropical estuarine mangroves
were aggregated; Estandard error; F95% CI

467

NON-FORESTED COASTAL WET LANDS

468
469
470
471

For coastal ecosystems with non-woody vegetation, Tier 1 methodologies for changes in dead organic matter are
followed assuming no change in the dead organic matter C stocks. This is the default assumption in the case of
any land-use conversion involving lands that are not forested. Where a land use activity results in no change tothe forested vegetation, Tier 1 default of 0 is similarly employed. Thus, Tier 1 value for ∆CDOM = 0 in these cases.

472
473
474
475
476
477

Tier 2 methodologies should employ Equation 2.17 & 2.23, Volume 4, Chap 2 of the 2006 GLs wheremanagement activities or land-use results in changes to herbaceous vegetation. For instance, after a management
activity that results in a change from non-vegetated or dominant vegetation with different aboveground biomass
stocks, conversion of aboveground biomass to dead organic matter as litter can be significant. Countries should
use in such cases national estimates for litter stocks for non-forested coastal wetlands disaggregated by climate,vegetation type and salinity where applicable.

478

4.2.4

479
480
481
482

Some coastal wetlands in intertidal settings are regularly flooded by incoming tides. In this situation, their soils,
altering between anoxic and aerobic conditions, favor nitrification, denitrification and methanogenesis. The
reduced and anoxic environments enable methanogens, sulfurgens and others bacteria to decompose part of theorganic matter with CH4 as a product. Nitrous oxide is produced naturally in soils through the processes of

Non-CO 2 Emissions

DRAFT 2013 Wetlands Supplement

4.17

Chapter 4

DO NOT CITE OR QUOTE

483
484
485
486

nitrification and denitrification. Nitrification is the aerobic microbial oxidation of ammonium to nitrate anddenitrification is the anaerobic microbial reduction of nitrate to nitrogen gas (N2). Nitrous oxide is a gaseousintermediate in the reaction sequence of denitrification and a by-product of nitrification that leaks from microbial
cells into the soil and ultimately into the atmosphere.

487
488
489
490
491
492

Non-CO2 emissions (i.e. CH4 and N2O) are covered in the following subsections for reporting of specificmanagement activities in coastal wetlands. There are two fundamental assumptions: (1) under a given set ofmanagement conditions, soils tend toward equilibrium non-CO2 gas emissions; and (2) coastal vegetation is not asource of these non-CO2 gases. Gas fluxes from coastal wetland soils vary greatly in time and space. Despite
great variations the assumptions of gas fluxes being in equilibrium will make estimations easier. Non-CO2
emissions are estimated using Equation 2.6, Vol. 4, Chapter 2.

493

4.2.5

494
495
496
497
498
499
500
501
502

To account for changes in soil C stocks associated with Coastal Wetlands, countries need to have, at a minimum,
estimates of wetland areas at the beginning and end of the inventory time period and classification of new land
use and land use activities (management data). If land-use and management data are limited, aggregate data,such as FAO statistics on mangroves (Food and Agricultural Organization of the United Nations, 2007), can beused as a starting point, along with knowledge of country experts about the approximate distribution of land
management systems. Land use classes must be stratified according to climate regions and major vegetation orsoil types, which could either be based on default or country-specific classifications. This can be accomplishedwith overlays of land use on suitable soil and climate maps, or classifying climate zones based upon publishedclimate norms (e.g., www.ncdc.noaa.gov/oa/wdc/index.php?name=worldweatherrecords).

503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521

All Tiers require estimates of wetland areas. The same area data should be used for biomass calculations, deadorganic matter, and the soil carbon estimates. If necessary, area data used in the soils analysis can be aggregatedto match the spatial scale required for lower order estimates of biomass; however, at higher Tiers, stratification
should take account of major soil types. Area data should be obtained using the methods described in Chapter 3of the 2006 Guidelines. Cross-checks should be made to ensure complete and consistent representation ofannually converted lands in order to avoid possible omissions or double counting. If possible, data should bedisaggregated according to the general climatic categories and type of ecosystem that results from the rewettingof previously drained coastal wetlands. Tier 3 inventories will require more comprehensive information on theestablishment of the coastal ecosystems as a result of rewetting and inundation by seawater, with refined soil
classes, climates, and spatial and temporal resolution. All changes having occurred over the number of years
selected as the transition period should be included with transitions older than the transition period (to be definedon a country specific basis) reported as a subdivision of the category of land use that results after rewetting ofpreviously drained coastal wetlands. Higher Tiers require greater detail and the areas of land that have significant
change in biomass and are under-going conversion and they should be identified separately. This implies that atleast partial knowledge of the land-use change matrix, and therefore, where Approaches 1 and 2 from Chapter 3of the 2006 Guidelines are used to estimate land area are being used, supplementary surveys may be needed to
identify the relevant area of land being converted. As pointed out in Chapter 3 of the 2006 Guidelines, where
surveys are being set up, it will often be more accurate to seek to establish directly areas undergoing conversion
than to estimate these from the differences in total land areas under particular uses at different times.

522

TIER 1

523
524
525
526
527
528
529
530
531
532
533

Estimates of wetland areas disaggregated by activity type. The methodology assumes that area estimates are
based on a one-year time frame, after they are transferred to the coastal ecosystem. If area estimates are assessedover longer time frames, they should be converted to average annual areas to match the carbon stock values used.
If countries do not have these data, partial samples may be extrapolated to the entire land base or historic
estimates of conversions may be extrapolated over time based on the judgement of country experts. Tier 1
approaches may use average annual rates of conversion and estimated areas in place of direct estimates. For
mangroves, Tier 1 uses data of area of mangroves, which can be obtained through national statistics,
conservation agencies and survey and mapping agencies. If no country data are available, aggregate information
can be obtained from international data. The inventory also requires data on wood removals, including fuelwood
removals and biomass losses due to disturbances, in order to calculate biomass stock changes and carbon pooltransfers.

534

TIER 2

535
536
537

It is good practice to use actual area estimates for all possible transitions. Complete reporting can beaccomplished either through analysis of periodic remotely sensed images of land-use and land-cover patterns,
and/or periodic ground-based sampling of land-use patterns, or hybrid inventory systems. For mangroves, Tier 2

4.18

Choice of activity data

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4538
539

uses country-defined national data sets, according to different mangrove types, climate, management systems,
and regions, with a resolution sufficient to ensure appropriate representation of individually relevant land areas.

540

TIER 3

541
542
543
544
545
546
547

Activity data used in Tier 3 calculations should provide a full accounting of all possible transitions disaggregatedto account for different conditions within a country. Disaggregation can occur along political boundaries (county,
province, etc.), biome area, climate zone, or on a combination of these parameters. In many cases countries may
have information on multi-year trends in land conversion (from periodic sample based or remotely sensed
inventories of land use and land cover). For mangroves, Tier 3 uses country-specific data on managed
mangroves from different sources, notably mangrove national inventories, registers of land-use changes, or
remote sensing. These data should be disaggregated along climate, soil, and vegetation types.

548

4.2.6

549

SOIL

550
551
552
553
554
555
556
557

Three broad sources of uncertainty exist in soil C inventories: 1) uncertainties in land-use and management
activity and environmental data; 2) uncertainties in reference soil C stocks if using a Tier 1 or 2 approach(mineral soils only); and 3) uncertainties in the stock change/emission factors for Tier 1 or 2 approaches, model
structure/parameter error for Tier 3 model-based approaches, or measurement error/sampling variability
associated with Tier 3 measurement-based inventories. In general, precision of an inventory is increased andconfidence ranges are smaller with more sampling to estimate values for the three broad categories, while
reducing bias (i.e., improve accuracy) is more likely to occur through the development of a higher Tier inventory
that incorporates country-specific information.

558
559
560
561
562
563
564

For Tier 1, uncertainty estimates are provided with the reference C stocks in the first footnote in Table 4.3 and inrespective sections for emission and stock change factors. Uncertainties in land-use and management data willneed to be addressed by the inventory compiler, and then combined with uncertainties for the default factors andreference C stocks using an appropriate method, such as simple error propagation equations. If using aggregate
land-use area statistics for activity data (e.g., FAO data), the inventory agency may have to apply a default levelof uncertainty for the land area estimates (+50%). However, it is good practice for the inventory compiler toderive uncertainties from country-specific activity data instead of using a default level.

565
566
567
568
569
570
571
572
573
574

Default reference C stocks and stock change factors for mineral and organic soils and emission factors fororganic soils can have inherently high uncertainties, particularly bias, when applied to specific countries.
Defaults represent globally averaged values of land-use and management impacts or reference C stocks that mayvary from region-specific values (Powers et al. 2004; Ogle et al. 2006). Bias can be reduced by deriving countryspecific factors using a Tier 2 method or by developing a Tier 3 country-specific estimation system. The
underlying basis for higher Tier approaches will be experiments in the country or neighbouring regions that
address the effect of land use and management on soil C. In addition, it is good practice to further minimize bias
by accounting for significant within-country differences in land-use and management impacts, such as variation
among climate regions and/or soil types, even at the expense of reduced precision in the factor estimates (Ogle etal. 2006).

575
576
577

Bias is considered more problematic for reporting stock changes because it is not necessarily captured in theuncertainty range (i.e., the true stock change may be outside of the reported uncertainty range if there issignificant bias in the factors).

578

BIOMASS

579
580
581

As biomass methods follow that of the 2006 GL, uncertainties described there also pertain to biomass estimation
methods and default data described in this supplement chapter on Coastal Wetlands. See Chapter 7, this
supplement for further detail.

582

DEAD ORGANIC MATTER

583
584
585
586
587

In general, the magnitude of uncertainty in dead organic matter pools is larger than the uncertainty in biomass
estimates because much less data are typically available for DOM pools compared to biomass pools.
Uncertainties in area estimates made using the approaches suggested in Chapter 3, Volume 4 are indicated inTable 3.7 and uncertainties in assessing dead organic matter carbon stock changes may be several times larger
than the uncertainty of biomass stock change estimates using default coefficients.

588
589
590

Although relatively few estimates of uncertainty, in changes in carbon stock in DOM pools, are available in theliterature or elsewhere, several sources of uncertainty can be identified for the estimates of changes in carbon
stock in dead organic matter pools. First, the assumption that carbon stocks in DOM are zero in non-forest land

Uncertainty assessment

DRAFT 2013 Wetlands Supplement

4.19

Chapter 4

DO NOT CITE OR QUOTE

591
592
593
594
595
596
597
598
599
600

is not always justified. Underestimating the true initial DOM stock size will lead to overestimates of the true
accumulation rates. Second, the default values for litter and dead wood carbon stock sizes are likely to be biased
by being based upon estimates from land that was Forest Land for a long period of time. Thus the stock sizes atthe end of the transition period may be overestimated, again, leading to overestimates of the accumulation rates.
Third, the default transition period may be too long for litter carbon stocks, leading to underestimates of the true
accumulation rates. For the dead wood pool, however, the current default assumption of a 40-year transition
period is likely to be too short. Thus, the rate of carbon accumulation in the dead wood pool may beoverestimated. Finally, litter and dead wood that may have otherwise accumulated can be exported through tidal
advection thus also resulting in an overestimation of the carbon accumulation rate in the dead organic matter
pool.

601

NON-CO 2 EMISSIONS

602
603
604

As non-CO2 emission methods follow that of the 2006 GL, uncertainties described there also pertain to non-CO2
estimation methods and default data described in this supplement chapter on Coastal Wetlands. See Chapter 7,
this supplement for further detail.

605

607

MANAGEMENT CHANGES IN COASTALWETLANDS

608
609

This section describes various human activities that impact of coastal wetlands either through disruption ofnatural drainage and / or modification to vegetation or soils.

610

4.3.1

611
612
613
614
615
616
617
618
619
620

Aquaculture (shrimp ponds, fish ponds, fish cages). Loss of marshes mangroves and seagrass meadows has
been associated with a range of aquaculture practices including bivalve and fish farming and shrimp ponds.
Commercial bivalve farming can either simply augment the natural density of bivalves in seagrass meadows or,
be associated with the creation of structures fixed directly to, or above the sediment that house the bivalves(Dumbauld et al. 2009). Bivalve farming may be locally important, for example 90% of the clams consumed in
Portugal are produced in one location, the Ria Formosa (Guimarães et al. 2012). Clam farming, as practiced
here, takes place in intertidal seagrass meadows where seagrasses are deliberately removed by ploughing. Less
intensive culture, where bivalve are left to grow naturally in the seagrass bed can be more sustainable, althoughcompetition between cultured bivalves and eelgrass occurs. Physical disturbance is obviously an issue with onground shellfish culture (Dumbauld et al. 2009).

621
622
623
624

Shrimp and fish ponds are constructed by clearing ground, leveling and excavation of surface soils to build
containing berms within which waters are held. Carbon from cleared biomass and excavated soils is lost fromstorage (Lovelock et al., 2011). Shrimp and fish ponds on organic coastal soils have often resulted in pollution
through the buildup of acid sulfate soil conditions and release of acidic water.

625
626
627
628
629
630

Fish farming activities are frequently reported to deteriorate their immediate surrounding environment: uneaten
food and fish faeces can result in nutrient over-enrichment of the water column and organic enrichment of thesediments beneath and adjacent to fish farms. Nutrient over-enrichment of seagrass meadows has led to waterand sediment quality deterioration, decreased light, algal overgrowth, seagrass shading and eventually seagrass
die-off (Apostolaki et al. 2010; Apostolaki et al. 2012). Human activities, such as construction of shrimp ponds,
have also been shown to have a deleterious effect on seagrass distribution (Yang and Yang 2009).

631
632
633
634
635

Other activities which will result in similar partial drainage of wetland soils and carbon loss are excavation andpiling of soils. Excavation of channels (generally <1 m) for mosquito control and canals (tens of meters wide)
for boat access results in drainage of the excavated soil (if piled in embankments) and an increase in depth towater table in wetland areas adjacent to the channels or canals.

636
637
638
639
640
641
642
643

Salt production. The Ramsar convention recognizes "salt exploitation sites" or solar salterns as a type of
wetland. These are sites where salt is produced along marine coasts by evaporating tidal water, or in inland
regions by evaporating water from brine springs. If solar salterns have displaced tidal marshes or mangroves it
must be assumed that these were at salinities >18 ppt. Many solar salterns have long histories, on the order ofcenturies (Thiery and Puente 2002), and some are undergoing restoration. However, there is a report ofrelatively recent establishment of a salt production system displacing mangroves on the coast of Java (Sukardjo
1993). Establishment of the production system required clearing vegetation, levelling, diking and constructing
channels over a 496 ha area. Some of the production sites in both in San Francisco Bay and on the Camargue

606

4.3

4.20

Description of Activities

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4644
645

have been abandoned and restoration activities are underway. Emission factors will vary for each stage: (1)construction,( 2) maintenance, and ( 3) restoration.

646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662

Extraction (Dredging, Ports, Harbors, Beach Nourishment). Dredging excavates soil from the seafloor
causing adverse effects on seagrass meadows and tidal wetlands that often lead to their loss, either directly byphysical removal and/or burial, or indirectly through lack of light due to high turbidity (Erftemeijer and Robin
Lewis III 2006). Although the purpose for dredging is varied, the main documented removal of seagrass has been
associated with the deepening and maintainance of navigation channels and harbor entrances (Larkum and West
1990; Da Silva et al. 2004) and sand and gravel excavation for construction and land reclamation (Zainal et al.
1993). Other activities that cause direct loss of seagrass due to their excavation and removal are mining for
cement production (Penn 1981), for the improvement of bathing for tourists at beach hotels (Daby 2003) anddredge-fill activities during the deployment of pipes and cables for gas, water transport and communication(Badalamenti et al. 2011). Enhanced sediment supply from construction, beach stabilization, dredging and excess
siltation from changes in land catchments may enhance suspended sediment loads. Smothering, due to thesettling of sediment on seagrass leaves and burial, at higher sedimentation rates can result in a major die back
(Cyrus et al. 2008) and/or seagrass loss, with the capacity of seagrass species to withstand sediment burial being
species specific and size-dependent (Cabaço et al. 2008). The re-suspended sediment also reduces lightavailability (Onuf 1994) and the capacity of seagrass species to survive below its minimum light requirement isagain species specific depending, in this case, on the amount of below-ground biomass (Erftemeijer and Robin
Lewis III 2006).

663
664
665
666

Nutrient enrichment. The production of greenhouse gases from soils are mainly due to microbiologicalprocesses controlled by several biological, chemical and physical factors in soil, especially the nutrients (Allen etal. 2007; Huang et al. 2009; Chen et al. 2010). Therefore, the changes in soil and water borne nutrients affect the
microbiological

667
668
669
670
671
672
673
674
675

Anthropogenic N, as nitrate, is the dominant input from rivers and groundwater to many coastal ecosystems(Moseman-Valtierra et al. 2011). There have also been many examples showing that estuaries directly or
indirectly (through organic nitrogen mineralization) receive a large amount of ammonium (Dai et al. 2008).With
nutrient enrichment, low oxygen availability due to rapid consumption of oxygen by aerobic microorganisms
promotes anaerobic microbial processes, including those that lead to emissions of N2O and CH4. Strauss andLamberti (2000) found that the addition of organic carbon increased microbial respiration rates, but decreased
nitrification rates in a hydric ecosystem. Increased anthropogenic nutrient inputs are known to increase thesemicrobial processes in coastal water and soil, and hence enhance the emissions of greenhouse gases fromwetlands to the atmosphere (Purvaja and Ramesh 2001; Kreuzwieser et al. 2003).

676
677
678
679
680
681

Decline of seagrass populations has been observed in many estuarine embayments, and the declines are often
associated with anthropogenic nutrient loading (Waycott et al. 2009). Increased availability of nutrients inenriched embayments may lead to blooms of macroalgae, phytoplankton, and epiphytes, all of which shade
seagrass, reducing the light available for photosynthesis and decreasing seagrass productivity. The N load per
estuary that relates to complete loss of seagrass has been predicted to be at loading values between 100 and 175
kgN ha-1 yr-1 (Steward and Green 2007; Latimer and Rigo 2010).

682
683
684
685
686
687
688

Nutrient management. Nutrient availability is known to mediate plant community structure in coastal wetlands.
Numerous studies concerning plant production suggest that productivity may be limited by availability ofnitrogen (Loveland and Ungar 1983). Many fertilization experiments have been conducted in tidal salt marshes
as the salt marshes are generally nitrogen limited (Pennings et al. 2002). Fertilization of salt marsh vegetation
with nitrogen leads to an increase in plant height, photosynthetic rates, biomass production (Leendertse et al.
1997; Pennings et al. 2002). The high primary productivity in tidal salt marshes is known to translate into
exceptionally high rates of carbon sequestration (Chmura et al. 2003).

689
690
691
692
693
694
695
696
697

Up to now, tentative studies have demonstrated that nitrogen fertilization in salt marsh results in increased N2Oemission, based on simulative/control experiments, with inorganic nitrogen as fertilizer. However, this researchshows inconsistent effects of nitrogen fertilization on CO2 or CH4 emission. Moseman-Valtierra et al. (2011)
found that short-term nitrogen additions can shift a coastal wetland from a sink to a source of N2O, but thechanges in CO2 and CH4 emission are not significant. Slightly higher CH4 flux was recorded in Spartina
alterniflora tidal salt marsh with N fertilizer (Ding et al. 2010), but there was no significant effect of N
fertilization on CH4 emission in the S. salsa wetland (Zhang et al. 2010); soil CH4 and CO2 production were
inhibited by nitrogen (nitrate) addition (Wang et al. 2010). Changes in CO2 and CH4 emission seem much lessintensive than N2O due to N fertilization.

698
699
700
701

Hydrological/sediment diversion. Tidal wetlands in many coastal settings are impacted by upstream diversionsof water and sediment. Declines in sediment supply reduce the capacity to maintain elevations against sea levelrise, or in the case of deltas as the coastline subsides and conversion of vegetated wetlands to open water results.
Reduction in water supply in arid areas may result in hyper salinization and death of vegetated coastal wetlands.

DRAFT 2013 Wetlands Supplement

4.21

Chapter 4

DO NOT CITE OR QUOTE

702
703
704
705

The capacity of tidal wetlands to maintain their elevation against sea level rise and natural coastal subsidence (asfound for example in large coastal deltas) is supported by the supply of mineral sediments, derived from nearby
rivers, cliffs or seabeds. Reduction of sediment delivery brought about by construction of river dams or coastal
structures can result in sediment starvation and erosion of coastal wetland and release of stored carbon.

706
707
708

Modification to hydrology may result in a response of natural wetlands. For example, diversion of freshwatersupply to coastal mangroves has been linked to increased salinization of wetland soils leading to the death ofmangrove vegetation (Baumann et al. 1984; McKee and Mendelssohn 1988).

709
710
711
712

Fire management. Fire is used in tidal wetlands as a tool for remediation of oil spills (Baustian et al. 2010) andto encourage growth of marsh species favorable to target wildlife (Mitchell et al. 2006; Owens et al. 2007;
Leonard et al. 2010). A common practice is to set fires during periods when the marsh is saturated to avoid
burning of soil organic matter (Gabry and Afton, 2001).

713

Harvesting (Marine resources (fish/shellfish), wood, non-wood forest products.

714
715
716
717
718
719
720

1.Non-wood products. Physical disturbance is obviously an issue with harvesting marine resources such asbivalves. On-ground shellfish culture and harvest methods can result in trampling and disturbance from boat
wakes and propeller scars in shallow waters (Dumbauld et al. 2009). Intertidal seagrass beds can be particularly
impacted by bait collection, through digging and trenching as well as pumping of sediment for prawns (Pillay et
al. 2010) and associated trampling. These activities have been implicated in the loss of 40% of seagrass inLangebaan, part of the Western Cape, which was once one of the major areas of seagrass cover in South Africa(Barnes and Ellwood 2011).

721
722
723
724
725
726

Harvest of aboveground biomass in tidal marshes dominated by herbaceous vegetation is assumed to havenegligible impacts on carbon stocks due to relatively rapid turnover rates. However, where tidal wetlands are
dominated by woody vegetation (e.g., shrubs in marshes of mediterranean climates) change in carbon stocks
must be calculated. Although plant-mediated transport of methane has been documented in wetlands(Kreuzwieser et al. 2003; Cheng et al. 2007) available data is inadequate to develop emissions factors formethane. There is no evidence to suggest a change in nitrous oxide emissions with harvests.

727
728
729

2.Wood products. Mangrove harvesting is a ubiquitous activity in all areas of the tropics. Mangrove wood isharvested locally for fuelwood, charcoal and construction (Ellsion and Farnsworth 1996, Walters et al 2008)
Bark removal and selective harvesting of individual trees also occurs, but with lower impact on biomass stocks .

730

Other Activities

731
732
733
734
735
736
737
738
739
740

1.Recreation (Boating and associated activities). Associated with increasing coastal populations is an increased
threat to seagrass beds from recreational boaters. Propeller scars are formed when boat propellers strike bottom
in shallow seagrass beds and destroy leaves, roots, and rhizomes. The disturbance extends beyond the formationof the physical scar because exposed sediments are more readily suspended by erosional forces, and increased
turbidity limits growth of the light sensitive seagrasses surrounding the scar (Martin et al. 2008). One of the mostprevalent and destructive effects of recreational boating is the destabilization of the seabed due to anchoring
particularly the degradation of seagrass habitats, which are particularly sensitive to structural damage fromdragging anchors. In some Thalassia testudinum-dominated systems, vessel damage may persist for years or
decades, and even small scars may leave seagrass habitat susceptible to severe erosion by wind and wave-driven
currents and storms (Hammerstrom et al. 2007).

741
742
743
744
745

2.Grazing (fauna and soil). Cattle, horses, goats, buffalo, and sheep all have been deliberately pastured on
undrained tidal wetlandsMesleard et al. 1991; Sukardjo 1993; Burnside et al. 2007; Yu and Chmura 2010; Olsonet al. 2011). Most studies of grazed marsh have focused on plant diversity and very few have reported data thatcan be used to assess carbon stocks or potential greenhouse gas emissions associated with these activities fromtidal wetlands soils.

746

4.3.2

747
748
749
750
751
752

Management activities described in this section can affect one or many carbon pools as well as non-CO2
emissions. For instance, aquaculture can effect changes in soil, biomass and DOM pools and in non-CO2
emissions. However, with no changes in water table or frequency of inundation, the tier 1 assumption is that
there are only affects to non-CO2 emissions for nutrient enrichment/management. These effects are summarizedin Table 4.10. When reporting on coastal wetland management changes, activity data for different managementchanges are required where changes in coastal wetlands are a key category.

Specific Methodological Approach

753
754

4.22

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

TABLE 4.10. TIER 1 METHODOLOGICAL CONSIDERATIONS FOR MANAGEMENT CHANGES IN COASTALWETLANDS
Activity

CO2

Non-CO2

Soil

Biomass

DOM

Aquaculture (∆CAQ)

X

X

X

Salt Production(∆CSP)X

X

X

Extraction (∆CEXT)

X

X

X

X

Nutrient Enrichment(∆CNE)*

X

Nutrient Management(∆CNM)*

X

Hydrologic/Sediment
Diversion (∆CHSD)
Harvesting (∆CH)

X

X

Other Activities*Inventory compiler is directed to section 4.3.6 on non-CO2 emissions. C pool changes are assumed to be zero atTier 1 level for nutrient management and nutrient enrichment.

755
756

Thus, in order to insure full coverage of C pools for each activity, equation 4.6 should be employed.

757
758
759
760
761

EQUATION 4.6
ANNUAL CARBON STOCK CHANGES FOR MANAGEMENT CHANGES IN COASTAL WETLANDS AS A
SUM OF POOL CHANGES ASSOCIATED WITH LAND USE ACTIVITIES∆CM = ∆CAQ + ∆CSP + ∆CEXT + ∆CNE + ∆CNM + ∆CHSD + ∆CH
Where:∆CM= Management Changes in Coastal Wetlands

∆CAQ
∆CSP
∆CEXT
∆CNE
∆CNM
∆CHSD
∆CH

= carbon stock changes for aquaculture= carbon stock changes for salt production= carbon stock changes for extraction= carbon stock changes for nutrient enrichment (assumed to be zero for C pools)= carbon stock changes for nutrient management (assumed to be zero for C pools)= carbon stock changes for hydrologic/sediment diversion= carbon stock changes for harvesting

762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781

In the cases of aquaculture, salt production and extraction, C pool changes for soil, biomass and dead organic
matter must be estimated and summed at Tier 1 level. Additionally, in the case of aquaculture, the inventory
compiler is referred to section 4.3.6 for guidance on estimating non-CO2 emissions associated with nutrient
enrichment. Where changes in CO2 emissions or removals do not occur in soil, biomass or dead organic matter C
pools (i.e. nutrient enrichment and nutrient management), the Tier 1 assumption is that the value for theparameter is zero. However, the inventory compiler is directed to section 4.3.6 for methodological guidance on
non-CO2 emissions associated with changes in CH4 and N2O. While hydrologic and sediment diversions are
excepted to have important changes in soil and biomass C stocks, the literature is not yet developed enough toprovide default emission factors. Finally, with regard to harvesting, changes in the soil C or DOM pools are
assumed to be zero at the Tier 1 level of estimation, and only changes in biomass are reported.

782

4.3.3

783
784
785
786

This section deals with anthropogenic impacts to wetland soil organic C stocks, primarily C emissions from soil
and soil C storage, by activities affecting soil drainage either through modification of the water table, mechanicaldisturbance to soils, and disruption to mineral sediment supply. General information and guidance for estimatingchanges in soil C stocks are provided in Section 4.2.

Soil Carbon

DRAFT 2013 Wetlands Supplement

4.23

Chapter 4

DO NOT CITE OR QUOTE

787
788
789

Total emissions from soil C stocks for Management Changes in Coastal Wetlands are estimated using Equation
4.3 to account for soil C losses or possible soil C gains. Mangrove or salt marsh should be further disaggregatedby soil type for Tier 2 estimation.

790

4.3.3.1

791
792
793
794
795

For Management Changes in Coastal Wetlands, soils are maintained wet (though may be temporarily dried
during the land-use transition phase) and changes in C storage result from land-use activity. Mechanicaldisturbance associated with pond construction for aquaculture are assumed to release carbon from the top 1
meter of the soil profile. As the water table is maintained at or above the graded soil surface further emissions ofsoil carbon are assumed to be zero.

796
797
798

For wetlands that are not revegetated (e.g. aquacultural ponds, marshes denuded of vegetation) further soil C
input is assumed to be zero. For aquacultural ponds labile carbon will be supplied to accumulating muds but thisis assumed to be released through pond management practices or through respiration.

C HOICE OF METHOD

799
800

4.3.3.2

CHOICE OF EMISSION / REMOVAL FACTORS801

MINERAL /ORGANIC SOILS

802
803
804
805

Tier 1

806
807
808

Tier 2

809
810
811
812
813
814
815

Tier 3

Changes in stocks of organic carbon are estimated following Equation 4.3 to estimated C losses. The
methodology stratifies managed organic soils by climate region and ecosystem type and assigns an annual
emission rate. Land areas are multiplied by the emission factor and then summed to derive annual C emissions.
The Tier 2 approach also applies Equation 4.3, but country-specific information is incorporated to better specify
emission factors, climate regions, and/or the land management classification system.
Tier 3 approaches for organic carbon use dynamic models and/or measurement networks. A variety of models
designed to simulate soil carbon dynamics exist for terrestrial soils (for example, see review by Poeplau et al.
2011), but none have been applied to coastal wetlands. Key criteria in developing an appropriate model for these
purposes include its capability of representing belowground production, soil organic matter turnover, and verticalsoil accumulation rates that are compatible with the availability of country-wide input data, but more research isneeded; and that the model sufficiently represents stock changes based on comparisons with experimental data.

816
TABLE 4.11. EMISSION FACTORS FOR COASTAL WETLAND SOILS CHANGED THROUGH AQUACULTURE, SALT PRODUCTION OR
EXTRACTION

Mean (Mg C ha-1 yr-1)

Range (Mg C ha-1 yr-1)

Climate Zone

Ecosystem

Boreal and Temperate

Tidal Marshes

8.75

1.18-47.50

Tropical and Sub tropicalMangroves

12.13

3.88-28.75

Sources: Chmura et al . 2003, Silfleet et al., 2011, Donato et al., 2011; Lovelock et al. 2011; Fourqurean et al., 2012.

817

Biomass

818

4.3.4

819
820
821
822
823
824
825
826

This section provides guidance for estimating carbon stock changes in biomass for Management Changes in
Coastal Wetlands including changing cover in vegetation, effects of nutrient additions and the effects ofmanagement. The concepts underlying carbon stock changes in biomass of Management Changes in Coastal
Wetlands are tied to management practices. Larger amounts can accumulate in the woody component ofvegetation in mangroves, and in root biomass and in soils of all three coastal wetland ecosystems. In mangroves
gains include total (aboveground and belowground) biomass growth, but additional losses are incurred due tofuelwood removal/harvest and gathering. When such losses occur, belowground biomass is also reduced andtransformed to dead organic matter (DOM).

4.24

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

827
828
829
830
831

The decision tree in Figure 4.1 provides guidance on the choice of Tiers for reporting changes in biomass C
stocks. Because data on below-ground biomass are often lacking for specific ecosystems, a simplified approachbased upon below-ground to above-ground biomass ratios is used. With this approach, estimates of belowground biomass are closely tied to estimates of above-ground biomass. Hence, for simplicity, above-ground andbelowground biomasses are combined for estimation and reporting.

832
833
834
835
836

Although the methods for estimating biomass changes are conceptually similar among the ecosystems that
constitute Management Changes in Coastal Wetlands, there are some aspects that are unique to each of theecosystems. In particular, mangrove stands allometric relationships differ from those used in Forest Land andconsideration must also be taken of differences between mangrove species growing in different geographic
regions.

837

4.3.4.1

838
839
840
841
842

General considerations relevant to, and the generic equations that can be used for, the estimation of biomasschanges for are provided in Chapters 2 and 4 of Volume 4. These generic equations can be used but more
specific consideration needs to be taken when estimating biomass stocks in association with Management
Changes in Coastal Wetlands. Depending on the Tier used and data availability, coastal wetlands can be
disaggregated by ecosystem, climate, salinity level and management system.

843

TIER 1

844
845
846
847
848
849
850
851
852
853
854

A Tier 1 approach generally assumes no change in biomass in Management Changes in Coastal Wetlands except
those ecosystems where woody vegetation is prevalent. In any coastal wetland ecosystem, where there is nochange in either type or intensity of management, biomass will be in an approximate steady-state (i.e. carbon
accumulation through plant/tree growth is roughly balanced by losses through herbivory and decomposition).
However, where management changes are occurring over time (e.g., through introduction of aquaculture,physical disturbance, soil removal, nutrient enrichment or other practices) carbon stock changes can besignificant. If it is reasonable to assume that any of the coastal wetland ecosystems are not a key source, acountry may apply the Tier 1 assumption of no change in biomass. However, if information is available todevelop reliable estimates of rates of change in biomass in Management Changes in Coastal Wetlands, a country
may use a higher Tier, even if Management Changes in Coastal Wetlands is not a key source, particularly ifmanagement changes are likely, in which case default data in Tables 4.5-4.8 can be applied.

855

TIER 2

856
857
858

Tier 2 allows for estimation of changes in biomass when Management Changes in Coastal Wetlands is a key
category. Two methods are suggested for estimating the carbon stock change in biomass. Gain-Loss and StockDifference Methods.

859

TIER 3

860
861
862
863
864

Tier 3 methods are used where countries have country-specific emission factors, and substantial national data.
Country-defined methodology may be based on detailed inventories of permanent sample plots for their Coastal
ecosystems, and/or models. For Tier 3, countries should develop their own methodologies and parameters for
estimating changes in biomass. These methodologies may be derived from equations specified above, or may bebased on other approaches. The method used needs to be clearly documented.

865

4.3.4.2

866
867

Emission and removal factors that are required to estimate the changes in biomass resulting from management
include biomass growth rate, loss of biomass, and expansion factor for below-ground biomass.

868

TIER 1

869
870
871

Default factors in Table 4.4-4.8 can be used to estimate change in woody biomass at Tier 1 level. If managementchanges are significant, but management changes are not a key category, then non woody biomass can be
estimated using default data in Tables 4.4-4.8

872

TIER 2

873
874
875
876
877

It is good practice to use country-specific data on biomass C stocks for different mangrove, seagrass and salt
marsh species that constitute a particular biogeographic region. Country-specific values for net biomass
increment as well as losses from harvested mangroves and decomposition rates, in the case of the Gain-Loss
Method, or the net change in biomass stocks, in the case of the Stock-Difference Method can be derived fromcountry-specific data, taking into account the ecosystem type. Estimating below-ground biomass is also an

CHOICE OF METHODCHOICE OF EMISSION / REMOVAL FACTORSDRAFT 2013 Wetlands Supplement

4.25

Chapter 4

DO NOT CITE OR QUOTE

878
879
880
881
882
883

important component of biomass surveys of coastal wetland ecosystems and expansion factors are provided toestimate belowground biomass from aboveground biomass. Table 4.4 provides default root-to-shoot ratios (allvegetation) for mangrove, seagrass and salt marsh ecosystems in the major climate zones of the world (IPCC
climate zones are the same as those reported in Annex 3A.5, 2006 GL as well as the classification of climate
zones more appropriate for seagrass species). These values can be used as defaults when countries do not havemore specific information to develop country-specific ratios.

884

TIER 3

885
886
887
888
889
890

Tier 3 approaches consist of using a combination of dynamic models and inventory measurements of biomass
stock changes. This approach does not employ simple stock changes or emission factors per se. Estimates ofemissions/removals using model-based approaches are derived from the interaction of multiple equations that
estimate the net change of biomass stocks within the models. Models, jointly with periodic sampling-based stock
estimates could be applied to estimate stock changes or inputs and outputs as in Tier 2 to make spatial
extrapolations for coastal wetland areas.

891

4.3.5

892
893
894
895
896
897
898
899
900
901

Changes in dead organic matter resulting from land-use conversion or management activities that occur inforested coastal wetlands are estimated at the Tier 1 level because they represent potentially large C emissions toor removals from the atmosphere. Dead organic matter pools under conditions of low soil oxidation-reduction
potential under saturated conditions, especially at high latitudes, can be large. Conversions that result inpreviously forested coastal wetlands shifting to non-forested wetlands can have large implications for C
estimates. In non-forested coastal wetlands, the default assumption is that no changes in stocks occur at the Tier
1 level of estimation. For key categories or extensive management activities occurring in either forested or nonforested coastal wetlands, Tier 2 and higher estimation methods should be used and these values reported. In
these cases, stock changes should be disaggregated relative to climate, vegetation type and salinity whereapplicable.

902

4.3.5.1

903

TIERS 1, 2 AND 3

904
905
906
907
908
909
910
911
912
913
914

The method for estimating changes in dead organic matter stocks are presented in Equations 2.18 and 2.19
(Volume 4, Chapter 2). The method estimates the change in dead organic matter stocks applying the StockDifference Method where the change in dead organic matter stocks are estimated at two points in time relative tothe period before and after the land-use conversion or management activity. This method can be applied forforested coastal wetlands at a Tier 1 level or at a Tier 2 level using country estimates where changes occur ineither forested or non-forested coastal wetlands. Tier 1 default stocks for forested coastal wetlands are provided
in Table 4.9. The default for changes in dead organic matter stocks at the Tier 1 level of estimation is 0 for nonforested coastal wetlands. Tier 2 level of estimation should be used when extensive management activities leadto key category land-use conversions. The Gain-Loss Method and better estimates of transition times may also be
more appropriate for Tier 2 or higher level of estimation to reduce uncertainties. Estimates of dead wood andlitter exports due to tidal advection should also be considered.

915

4.3.5.2

916

TIER 1

917
918
919
920
921
922
923
924
925

Countries using a Tier 1 method require data on the default dead wood and litter carbon stocks as defined inTable 4.8. The Tier 1 assumption is that carbon stocks in litter and dead wood pools in all non-forested coastal
wetlands and conversion among non-forest land-use categories are zero. The use of equation 2.18 isrecommended for Tier 1 level estimation. For lands converted to forested coastal wetland, the carbon stocks indead wood and litter pools are assumed to increase linearly over the transition period T (default is 20 years forboth litter and dead wood C stocks). Thus, the annual rate of increase is estimated as the ratio between the
difference in carbon stocks in the DOM pools in the non-forest and forest categories, and the numbers of years in
the transition period T. Conversions from forested coastal wetland to non-forested coastal wetland are assumed
to be emitted in the year of conversion.

926

TIERS 2 AND 3

927
928

The higher Tier methods described above (Equation 4.18) and in Chapter 2 will allow for more robust estimateswhen applied to national data. Additional requirements may arise if the assumption that carbon stocks in dead

4.26

Dead Organic Matter

CHOICE OF METHODCHOICE OF EMISSION / REMOVAL FACTORSDRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4929
930

wood and litter pools of non-forest land-use categories are zero cannot be justified, such as in some agro-forestry
systems or other circumstances where intensive management activities have occurred.

931

4.3.6

932
933
934
935
936
937
938
939

This section provides methods for estimating the emissions of two non-CO2 gases from coastal wetlands under

940
941
942
943
944

Some management activities, such as shrimp/fish culturing, nutrient enrichment and nutrient management, resultin nutrient/organic enrichment in the water and soil, and affect the microbiological mechanisms responsible forCH4 and N2O production. But for some other activities, such as salt production, no reports are available on N2Oemissions. Despite notable levels of sulfate reduction, methanogenesis occurs in the saltern pond sediments but
no significant methane oxidation has been measured (Conrad et al. 1995).

945
946
947

Coastal wetlands subject to intensive nutrient loading may also be sources of CH4 emissions. However, in theabsence of intensive nutrient loading only coastal wetlands with salinity of soil porewater <15 are likely to besources of CH4 emissions.

948

4.3.6.1

949
950
951
952

Emissions of non-CO2 greenhouse gases from coastal wetlands with altered Hydrology are associated with data

953

TIER 1954
955

The default method to estimate the non-CO2 gases emissions from coastal wetlands is to multiply the area ofthese wetlands by the gases emission rates.

956
957
958

MethaneNon-CO 2 emissions

different management schemes, but with altered Hydrology. Non-CO2 gas emissions from seagrass are not taken
into account due to limited data. Management activities include: construction of canals for transportation,
ditching for vector control, harvesting, grazing, and construction and maintenance of solar salterns (saltproduction facilities), nutrient management and nutrient enrichment. Although the wetland hydrology remains
unchanged (or the characteristics of the hydrological regime that maintain its wetland status), the management
activities alter the environmental factors that regulating the non-CO2 gas productions and emissions, e.g. thesubstrate availability, hence leading to changes in gas emissions.

C HOICE OF ME THOD AND EMISSION FA CTOR

on specific activities within this land-use category, and are calculated as the sum of these wetlands with different
management activities. A generic method for estimating the emission of non-CO2 gas is provided in Equation 2.6,
Vol. 4, Chapter 2.

In Tier 1 method, the CH4 emissions due to activities associated with partial drainage are not considered and theemission factors are assumed to be zero. Default emission factors for Tier 1 method are provided in Table 4.12.
TABLE 4.12 EMISSION FACTORS FOR CH4 FROM COASTAL WETLANDS WITH ALTERED HYDROLOGY
WetlandDefault EF(tonnes CH4C ha-1 y-1)

Nfertilized
wetlandTo becompleted

Nutrientenrichedwetland11.5

Impounded
wetlands

To becompleted

EF Range(tonnes CH4C ha-1 y-1)

0-54

Error

Reference

Sotomayor et al., 1994, Purvaja and Ramesh 2001, Ye
and Lu, 2001, Allen et al., 2007, Chauhan et al., 2008,
Krithika et al., 2008, Liikanen et al., 2009, Allen et al.,2010, Chen et al., 2010, Tong et al., 2010, Adams et al.,2011, Ramesh et al., 2011

959
960
961
962
963

Nitrous oxide
Tier 1 method estimates N2O emissions from coastal wetlands with altered Hydrology based on the assumptionthat the N2O gas was negligible from those wetlands without nutrient loading. Default N2O emission factors forTier 1 method are provided in Table 4.13.

964

DRAFT 2013 Wetlands Supplement

4.27

Chapter 4

DO NOT CITE OR QUOTETABLE 4.13 EMISSION FACTORS FOR N2O EMISSION FROM COASTAL WETLANDS
WetlandDefault EF(kg ha-1 y-1)

EF Range(kg ha-1 yr-1)

N-fertilized
wetland

49.89

0.77~200.43

Nutrientenrichedwetland10.52−0.35~91.85

Impounded
wetlands

To becompleted

Error

Reference
Muñoz-Hincapié et al., 2002, Kreuzwieser et al., 2003,
Moseman-Valtierra et al., 2011, Kenny et al., 2004,
Lindau and DeLaune, 1991
Kreuzwieser et al., 2003, Corredor et al., 1999,
Liikanen et al., 2009, Adams et al., 2011, Bauza et al.,2002, Krithika et al., 2008, Alongi et al., 2005, Chen etal., 2010, Allen et al., 2007, Wang et al., 2007

965
966

TIER 2967
968

The Tier 2 method requires country-specific emission factors that account for climate, vegetation type, andintensity of nutrient input.

969
970
971

For nutrient management, emissions of non-CO2 gases from nutrient-managed wetlands could also be estimatedbased on the annual amount of fertilizer N (activity data) applied to wetland soils and the emission factor(transfer rate of fertilizer N to non-CO2 gases by weight).

972

TIER 3

973
974
975
976
977

The Tier 3 method involves a comprehensive understanding and representation of the dynamics of non-CO2 gasemission factors, taking account of parameters such as season, soil texture, fertilizer composition (for Nutrient
management), tidal elevation and tidal cycle (high tide vs. low tide). Field research should be carefully carriedout at representative sites for emission factors estimation. The countries are encouraged to setup own
methodology or model based on the N input amount for estimation of emission factors.

978

4.4

DRAINAGE OF COASTAL WETLANDS

979

4.4.1

Description of Activities

980
981
982
983
984
985
986
987

Tidal wetlands have been diked and drained to create land for agriculture (pasture and croplands) and settlement
since before the eleventh century (Gedan et al. 2009). The practice, sometimes referred to as "reclamation",continues today on many of the world’s coastlines, for example countries such as Korea (e.g., Byun et al. 2004)
and China (e.g., Sun et al. 2003) where drained wetlands may be used for modern industrial complexes. On
some diked coasts groundwater below reclaimed former-wetlands is pumped out to maintain the water table at an
optimum level below a dry soil surface while on other coasts drainage is achieved through a system of ditches
and tidal gates (opening only at low tide). A third means to deal with high water tables is to increase the surface
soil elevation with fill, a practice most common when wetlands are transformed to settled lands.

988
989
990
991
992
993
994

Rates of organic matter decomposition in soil below the water table are lower than in aerated soils above,
because anaerobic decomposition is less efficient (e.g., Reddy and Patrick 1975; Kristensen et al. 1995). Thus,
reduction in the degree of soil saturation during drainage should increase rates of decomposition, resulting in lossof soil carbon stored as a result of wetland plant production (Armentano and Menges, 1986). This response willvary regionally with climate (Pozo and Colino 1992) and locally with soil salinity, soil texture, and the quantityof labile organic matter available in the drained soil (e.g., Heminga et al. 1998, Setia et al. 2011), the latter canbe related to varied chemical composition tissues of plant species (e.g., Buth 1987).

995

4.4.2

996
997
998
999
1000
1001

This section deals with anthropogenic impacts to wetland soil organic C stocks, primarily C emissions from soil
and soil C storage, by activities affecting soil drainage through modification of the water table,. This section
provides guidelines for estimating carbon stock changes in soils of coastal wetlands due to drainage which canincrease rates of decomposition. Land conversions following Coastal Wetland drainage (e.g., agriculture,settlement, aquaculture), will impact soil carbon stocks and these must be considered in calculation of overall
carbon stocks.

4.28

Soil carbon

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 41002

4.4.2.1

C HOICE OF METHOD

1003
1004
1005
1006
1007

Inventories can be developed using a Tier 1, 2 or 3 approaches, with each successive Tier requiring more details
and resources than the previous one. It is also possible that countries will use different tiers to prepare estimates
for the separate sub-categories of soil C (i.e., soil organic C stocks changes in mineral and organic soils; andstock changes associated with soil inorganic C pools). A decision trees is provided (Figure 4.1) to assist
inventory compilers with the selection of the appropriate tier for their soil C inventory.

1008

4.4.2.2

1009

MINERAL /ORGANIC SOILS

1010
1011
1012
1013
1014
1015

Tier 1

1016
1017
1018
1019

Equation 4.3 (Chapter 2) is used to estimate change in soil organic C stocks. Note that area of exposed bedrockin wetlands and open water channels are not included. In practice, country-specific data on land management
activity should be obtained and classified into appropriate land management systems, and then stratified byecosystem type. Table 4.14 provides annual rates of C emission for soils of drained coastal wetlands.

1020
1021

If land area data disaggregated by ecosystem type is not available, countries can employ Equation 4.4, using
stock change factor data provided in Table 4.15.

1022
1023
1024
1025
1026
1027
1028
1029
1030
1031

Tier 21032
1033

A tier 2 method might also utilize the emission factor approach if country-specific data, disaggregated by soil
type, climate, ecosystem type, and/or salinity level, are available.

1034
1035
1036
1037
1038

Tier 3

C HOICE OF EMISSION AN D STOCK CHANGE FACTORS

For all soils, the estimation method is based on emission of C from soil (with mineral and organic soils
aggregated) over a finite (40 yr) period following changes in management that impact soil organic C storage.
After a finite transition period, one can assume a steady state change in stock assuming no change in water levelthat may result in a net accumulation of soil C after the transition period. The method assumes that land area
data is available to disaggregate coastal wetlands by ecosystem type to estimate losses due to drainage activities.

Equation 4.4 is used to estimate change in soil organic C stocks, disaggregated by soil type (mineral and organic)
in coastal wetland soils by subtracting the C stock in the last year of an inventory time period (SOC0) from the C
stock at the beginning of the inventory time period (SOCO/M,b) and dividing by the time dependence of the stockchange factors (D). Note that area of exposed bedrock in wetlands and open water channels are not included in
the soil C stock calculation (assume a stock of 0). In practice, country-specific data on land management activity
should be obtained and classified into appropriate land management systems, and then stratified by IPCC climate
regions and soil types. Soil organic C stocks (SOC) are estimated for each time period in the inventory using
default reference carbon stocks (SOCref) and default stock change factors (FLU, FMG). If country-specific stockchange factors are not available, countries-specific stocks can be used with stock change factors in Table 4.15.

Tier 3 approaches do not employ simple stock change factor per se, but rather use dynamic models and/or
detailed soil C inventory measurements as the basis for estimating annual stock changes. Estimates of stockchanges using model-based approaches are computed from the coupled equations that estimate the net change ofsoil carbon as described in section 4.2.2.2.

1039
TABLE 4.14 ANNUAL EMISSION FACTORS (EF) FOR DRAINED SOILS FOR TIER 1 ESTIMATION
Climate Zone

Wetland TypeDefault(Mg C ha-1 yr-1)

Range(Mg C ha-1 yr-1)

Boreal andTemperate

Tidal Marshes

8.75

1.18-47.50

Tropical and
SubtropicalMangrove

12.13

3.88-28.75

Review sources: Chmura et al . 2003, Silfleet et al., 2011, Donato et al., 2011; Fourqurean et al., 2012.

1040
1041

DRAFT 2013 Wetlands Supplement

4.29

Chapter 4

DO NOT CITE OR QUOTETABLE 4.15 RELATIVE STOCK CHANGE FACTORS FOR DRAINED COASTAL WETLANDS FOR TIER 1 LEVEL ESTIMATION(WHERE DISAGGREGATION BY SOIL TYPE IS POSSIBLE OR TO SUPPLEMENT TIER 2 ESTIMATION)
Soil Type

Wetland Type

Organic

Tidal Marsh0Mangrove0

Tidal Marsh

0.5

Mangrove

0.5

MineralDefault Stock Change
Factor (unitless)

Reference

Lovelock et al 2011

Lovelock et al 2011

Note: Stock change factors for mineral soils are assumed based on a value of 50% C stock of coastal wetland soil i.e. (0.5 * 351)/40 Mg C
ha-1 yr-1 over a 40 year period where 0.5 = 50% C stock of coastal wetland soil.

1042

1043

4.4.3

1044
1045
1046
1047
1048
1049

This section provides guidelines for estimating carbon stock changes in biomass due to the conversion of coastal
wetlands, mostly mangroves and tidal salt marshes, due to drainage. During drainage of coastal wetlands,changes in the carbon stock of biomass can result from the loss of existing vegetation and replacement withvegetation that is more characteristic of the dried soils. This scenario is different than that described in Coastal
wetlands with unaltered or partly modified hydrology, where the vegetation of the existing wetland remains thesame but generally experiences changes in biomass due to different management activities.

1050
1051
1052
1053
1054

Conversion of coastal wetlands during drainage often results in the transfer of carbon from one pool to another.
All transfers must be accounted during the transition to a new steady state. For example, when converting
mangroves via drainage, trees can be felled and a portion of the above-ground biomass is transferred to harvested
wood products and/or the dead organic matter pool. In addition, a portion of the below-ground biomass istransferred to the soil organic matter pool, etc.

1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078

Estimating changes in carbon stocks in biomass for coastal wetlands, converted by drainage, can require a twophase approach if there are different time-scales for vegetation loss from existing wetlands and replacement by
new, different vegetation in the drained soils. There can be an abrupt change in biomass, if say mangrove trees
are felled prior to or concurrent with drainage. This abrupt change can be treated as phase 1 and in-line with the2006 guidelines be estimated at the year of conversion. The second phase accounts for a gradual biomass loss
and gain during a transition period to a new steady state system. At some time after drainage the new vegetationthat develops on the drained coastal wetland should be comparable to that in the natural setting and should thenbe considered under, and accounted for in this new category of land-use. The transition period following
conversion by drainage will not be the same for different coastal ecosystems, Default values of 10 years are to be
used for drained mangroves and tidal salt marshes respectively for remaining in the transitional category.
Countries can determine more appropriate transition periods, at their discretion, that more specifically quantify
the particular type of drainage and ecosystem that is affected. The values of coefficients determining the rate ofemissions may depend on the transition period used. In-line with the 2006 guidelines, wetlands converted bydrainage should be accounted for with Phase 1 methods in the year that they are converted, with Phase 2
methods being used for all subsequent transitional years until the new vegetation achieves steady state. At theend of the transitional period, the land area currently being accounted for now comes under consideration of the
new category, which has resulted from the drainage of the particular coastal wetland. If there is no abrupt change
in biomass associated with the conversion, and a gradual transition occurs between the two different vegetation
types, Phase 1 accounting would not be appropriate and the whole conversion accounting can be undertakenusing Phase 2 methods. Conversely there may be a rapid conversion with little or no opportunity available forsubsequent re-vegetation on drained soils. This usually occurs when there is partial drainage of wetland soils,
such as when excavation of water-logged soils is piled onto the existing soil surface during ditching andcanalisation. If the excavation is more frequent than the time taken for new vegetation to colonize the soil, thewhole accounting for biomass change can be treated with Phase 1 methods.

1079
1080
1081
1082
1083
1084
1085
1086

When the Phase 1 method is implemented, it is good practice to apportion transfers of carbon between pools.
The immediate impacts of drained coastal wetland conversion activities on the five carbon stocks can besummarized in a “disturbance matrix”. The disturbance matrix describes the retention, transfers and releases ofcarbon in the pools in the original ecosystem following conversion due to drainage. A disturbance matrix defines
for each pool the proportion that remains in that pool and the proportion that is transferred to other pools. A
small number of transfers are possible, and are outlined in the disturbance matrix in Table 2.1 of Chapter 2 in the2006 guidelines. If the rate of conversion of coastal wetland by drainage is more or less constant, the assumptionthat all carbon in theses pools was lost at the time of conversion would be a reasonable first approximation.

4.30

Biomass

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

1087
1088
1089
1090
1091
1092
1093
1094
1095

Where the rate of conversion of coastal wetland by drainage varies over time, it is good practice to account for
the transfer and release of carbon among the different carbon pools and ensure that all carbon is accounted. In
cases where there is an immediate and abrupt carbon stock change in biomass due to conversion of coastal
wetlands, the effect of this conversion will be estimated using Equation 2.16 in Chapter 2 of the 2006 guidelines,
with the default assumption that BAfter=0. During the transition period, pools that gain or lose C often have a nonlinear loss or accumulation curve that can be represented through successive transition matrices. If the true
shapes of the curves are known, these curves can be applied to each cohort that is under transition during thereporting year to estimate the annual emission or removal by the specific pool. If the shape of the curve isunknown, countries may simplify and use a linear decay function to estimate pool changes.

1096

4.4.3.1

1097
1098
1099
1100
1101
1102

The decision tree (Figure 1) provides guidance for selecting the appropriate tier level for the implementation of
estimation procedures for biomass associated with the drainage of coastal wetlands. Estimation of changes inbiomass requires an estimate of changes in above-ground vegetation and changes in below-ground biomass.
Countries should use the highest tier possible given national circumstances. It is good practice to use a Tier 2 orTier 3 approach if carbon emissions and removals in coastal wetlands converted by drainage is a key category
and if the sub-category of biomass is considered significant, based on principles outlined in Volume 1, Chapter 4.

1103

TIER 1

1104
1105
1106
1107
1108
1109
1110
1111

The change in biomass carbon stock on Drainage of Coastal Wetlands under Tier 1 should be estimated using
Equation 2.15 of the 2006 guidelines. The average carbon stock change is equal to the sum of increase in carbon
stock due to biomass growth following conversion, changes due to actual conversion (difference between
biomass stocks before and after conversion), and decrease in carbon stocks due to losses after conversion. As asimplification for Tier 1, it is assumed that all biomass is lost immediately from the previous coastal wetland
ecosystem after conversion (Equation 2.16) , even when there is no abrupt change, and residual biomass (BAFTER)
is thus assumed to be zero (i.e., the wetland ecosystem is cleared of all vegetation before a new category of landis established).

1112
1113
1114

In this case there is no transfer of biomass from the biomass pool to the dead wood pool, for example. Default
values for mangrove, seagrass and tidal salt marsh biomass prior to conversion can be found in this chapter,
Tables 4.6 and 4.7).

1115
1116
1117
1118
1119
1120
1121
1122
1123

Additionally, it is assumed that each new category of land use established after drainage of coastal wetlands
achieves its steady-state biomass during the first year following conversion. Thus, for Tier 1, there are no stockchanges associated with Phase 2, though the drained coastal wetlands that are converted to a new category
should be retained in the conversion category for the 20 year transition period because the soil stocks will takelonger to reach equilibrium. Emissions and uptakes from biomass during Phase 2 of the calculation are therefore
zero. If there are significant management changes during the transition phase, countries can account for the
impacts of this on C stocks in biomass using the appropriate Tier 2 methods for any category remaining in thesame category. It is good practice to account for all ecosystems within coastal wetlands converted by drainage toanother category. Thus, a separate calculation must be done for each ecosystem conversion.

1124

TIER 2

1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142

The Tier 2 calculations differ structurally in a number of ways from Tier 1. First, Tier 2 estimates use the twophase approach described earlier. Tier 2 relies on some country-specific estimates of the biomass in initial andfinal land uses rather than the defaults, as in Tier 1. Area estimates for Drainage of Coastal Wetlands are
disaggregated at higher resolution spatial scales than in Tier 1 to capture regional variations within and between
the different coastal ecosystems of the country. Second, for Tier 2 countries may modify the assumption thatbiomass immediately following conversion is zero. This enables countries to take into account land-use
transitions where some, but not all, vegetation from the original land use is removed. In addition, under Tier 2, itis possible to account for biomass accumulation following establishment of a new land use category over aseveral year period (rather than accounting all biomass stock change in the year of conversion) if data are
available to estimate the time to full biomass establishment and the annual stock changes. Third, under Tier 2, itis good practice to apportion transfers of carbon between pools. Some of the land categories developed after
coastal wetland drainage do not contain significant carbon in the dead wood or litter pools, but dead wood may
persist for a number of years in land that is replacing mangroves or woody biomass may persist that had
previously accumulated in salt marshes. If the rate of land conversion is more or less constant, the assumptionthat all carbon in theses pools was lost at the time of conversion would be a reasonable first approximation.
Where the rate of land conversion varies over time, it is appropriate to try to account for the transfer and releaseof carbon from litter, dead wood, and soil carbon pools. It is therefore necessary to distinguish immediate losses
due to the conversion activities from the losses that occur in the years following the land conversion.

C HOICE OF METHOD

DRAFT 2013 Wetlands Supplement

4.31

Chapter 4

DO NOT CITE OR QUOTE

1143
1144
1145
1146
1147
1148
1149
1150
1151
1152

The immediate and abrupt carbon stock change in biomass due to drainage of coastal wetlands under Tiers 2 and3 will be estimated using Equation 2.16 in Chapter 2, where BAFTER is assumed to be zero. During the transition
period, pools that gain or lose C often have a non-linear loss or accumulation curve that can be represented
through successive transition matrices. For Tier 2, a linear change function can be assumed. For a Tier 3
approach based upon these methods, it is good practice to use the true shapes of the curves. These curves are tobe applied to each cohort that is under transition during the reporting year to estimate the annual change in thebiomass carbon pools. For the estimation of changes in biomass carbon during the transition phase, two methods
are suggested. The equations, related to the Gain-Loss Method and Stock-Difference Method are the same as
those used in Chapter 2 of the 2006 guidelines. The equations have also been presented in this chapter (Eqs 4.9
and 4.10 respectively).

1153

TIER 3

1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165

Tier 3 methods are used where countries have country-specific emission factors, and substantial national data.
Country-defined methodology may be based on detailed inventories of permanent sample plots for teach coastal
wetland ecosystem and/or models. For Tier 3, countries should develop their own methodologies and parameters
for estimating changes in biomass. These methodologies may be derived from methods specified above, or may
be based on other approaches. The method used needs to be clearly documented. Tier 3 involves inventory
systems using statistically-based sampling of biomass over time and/or process models, stratified by what type ofland use the coastal wetlands have been converted to, changes in vegetation type within each land use, climate,and management regime. For example, if the drained coastal wetland was converted to grassland, validated
species-specific growth models that incorporate management effects such as grazing intensity, fire, liming, andfertilization, with corresponding data on management activities, could be used to estimate net changes ingrassland biomass overtime. Models, together with periodic sampling-based biomass estimates, could be applied
to estimate stock changes to make spatial extrapolations for areas of drained coastal wetland.

1166
1167
1168
1169
1170

Key criteria in selecting appropriate models include the ability to represent all of the ecosystem conversions andmanagement practices that are represented in the activity data. It is critical that the model be validated withindependent observations from country-specific or region-specific field locations that are representative of thevariability of local environmental change as well as climate, soil and vegetation management systems in the
country.

1171
1172
1173
1174

If possible, spatially explicit area estimates should be used to facilitate complete coverage of the converted areaof coastal wetland and ensure that areas are not over- or underestimated. Furthermore, spatially explicit area
estimates can be related to locally relevant carbon accumulation and removal rates, and restocking andmanagement impacts, improving the accuracy of estimates.

1175

4.4.3.2

1176

TIER 1

1177
1178
1179
1180
1181

Tier 1 methods require estimates of the biomass of the land use before conversion and after conversion. It is
assumed that all biomass is cleared when preparing a coastal wetland site for drainage and alternative land use,
thus, the default for biomass immediately after conversion is 0 tonne ha-1. Default values for biomass before
conversion can be found in this Chapter (Tables 4.6 and 4.7). For biomass following (not immediately after)
conversion can be found in the appropriate chapter of the 2006 guidelines.

1182

TIER 2

1183
1184
1185
1186
1187

It is good practice to use country-specific estimates for biomass stocks and emissions/removals due to land
conversion, and also include estimates of on-site and off-site losses due to burning and decay following land
conversion due to drainage of coastal wetlands. These improvements can take the form of systematic studies ofcarbon content and emissions and removals associated with land uses and land-use conversions within the
country or region and are-examination of default assumptions in light of country-specific conditions.

1188
1189
1190
1191
1192
1193
1194

Region-specific or country-specific data on biomass for growth in the vegetation that characterises the drained
wetland are needed for a Tier 2 approach. These can be obtained from the existing description of conversion to
Grassland, Cropland and Forest Land in the 2006 guidelines. General guidance on survey and samplingtechniques for biomass inventories is given in Chapter 3 in Annex 3A.3. If possible accurate knowledge of the
dynamics of below-ground biomass should be obtained for accounting for carbon stockchanges when coastal
wetlands are drained to provide land for other uses. Estimation of below-ground biomass in the converted landshould be available in Grassland, Cropland and Forest Land Chapters in the 2006 guidelines.

1195
1196
1197

Estimation of below-ground biomass in the pre-existing coastal wetland can be an important component of thecalculated stock change. Field measurements are laborious and difficult and thus expansion factors to estimate
below-ground biomass from above-ground biomass are often used. Below-ground biomass to above-ground

4.32

C HOICE OF E MISSION /R EMOVAL F ACTORSDRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

1198
1199
1200
1201
1202
1203

biomass ratios appropriate to each coastal wetland ecosystem should be used. Even within a coastal ecosystem,
below-ground biomass to above-ground biomass ratios vary at both individual species and community scales.
Thus, it is recommended to use, as far as possible, empirically-derived root-to-shoot ratios specific to eachecosystem type and region. Tables 4.4 provide default root-to-shoot ratios for mangroves, tidal salt marsh andseagrass meadows for different regions. These data can be used as defaults when countries do not have moreregionally specific information to develop country specific values.

1204

TIER 3

1205
1206
1207
1208

Tier 3 approaches consist of using a combination of dynamic models and inventory measurements of biomass
stock changes. This approach does not employ simple stock changes or emission factors per se. Estimates ofemissions/removals using model-based approaches are derived from the interaction of multiple equations that
estimate the net change of biomass stocks within the models. Models can be used, together with periodic

1209
1210
1211

sampling-based stock estimates, to estimate stock changes or inputs and outputs. For example, validated speciesspecific growth models that incorporate management effects in the drained coastal wetland with corresponding
data on management activities, could be used to estimate net changes in biomass in the converted land over time.

1212

4.4.4

1213
1214
1215
1216
1217
1218
1219

Changes in dead organic matter resulting from drainage activities that occur in forested coastal wetlands are
estimated at the tier 1 level because they represent potentially large C emissions to or removals from theatmosphere. Drainage can increase the oxidation rate of dead wood and litter that occurred in the pre-drainage
condition. In non-forested coastal wetlands, the default assumption is that no changes in stocks occur at the tier 1
level of estimation. When drainage of coastal wetlands is a key category in both forested or non-forested coastal
wetlands, tier 2 and higher estimation methods should be used and these values reported. In all cases, stockchanges should be disaggregated relative to climate and vegetation type where applicable.

1220

4.4.4.1

1221

TIERS 1, 2 AND 3

1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233

The method for estimating changes in dead organic matter stocks are presented in Equation 4.15. The method
estimates the change in dead organic matter stocks applying the Stock-Difference Method where the change indead organic matter stocks are estimated at two points in time relative to the period before and after the land-use
conversion or management activity. This method can be applied for forested coastal wetlands at a Tier 1 level orat a tier 2 level using country estimates where changes occur in either forested or non-forested coastal wetlands.
For drainage of forested coastal wetlands, the Gain-Loss Method may also be applied as decay rates in a drained
condition are readily estimated. Tier 1 default stocks for forested coastal wetlands are provided in Table 4.6.
The default for changes in dead organic matter stocks at the Tier 1 level of estimation is 0 for non-forested
coastal wetlands. Tier 2 level of estimation should be used when extensive management activities lead to key
category land-use conversions. Better estimates of transition times may also be more appropriate for Tier 2 orhigher levels to reduce uncertainties. Estimates of dead wood and litter exports due to tidal advection would beconsidered negligible under a drained condition.

1234

4.4.4.2

1235

TIER 1

1236
1237
1238
1239
1240
1241
1242
1243

Countries using a Tier 1 method require data on the default dead wood and litter carbon stocks as defined inTable 4.8. The Tier 1 assumption is that carbon stocks in litter and dead wood pools in all non-forested coastal
wetlands and conversion among non-forest land-use categories are zero. For lands converted to forested coastal
wetland, the carbon stocks in dead wood and litter pools are assumed to increase linearly over the transition
period T (default is 20 yr for both litter and dead wood C stocks). Thus, the annual rate of increase is estimatedas the ratio between the difference in carbon stocks in the DOM pools in the non-forest and forest categories, andthe numbers of years in the transition period T. Conversions from forested coastal wetland to non-forested
coastal wetland are assumed to be emitted in the year of conversion.

1244

TIERS 2 AND 3

1245
1246

The higher Tier methods described above (Equation 4.8) and in Chapter 2 will allow for more robust estimateswhen applied to national data. Additional requirements may arise if the assumption that carbon stocks in dead

Dead Organic Matter

CHOICE OF METHODCHOICE OF EMISSION / REMOVAL FACTORSDRAFT 2013 Wetlands Supplement

4.33

Chapter 4

DO NOT CITE OR QUOTE

1247
1248

wood and litter pools of non-forest land-use categories are zero cannot be justified, such as in some agro-forestry
systems or other circumstances where intensive management activities have occurred.

1249

4.4.5

1250
1251
1252
1253
1254
1255

This section provides guidelines for estimating non-CO2 gas emissions from coastal wetlands, mostly mangroves
and tidal marshes, being drained by way of conversing them to other dry land uses. The land use following
Coastal Wetland drainage (e.g., agriculture, settlement, aquaculture), will have a major impact on emissions of
non-CO2 greenhouse gases from drained Coastal Wetlands. Non-CO2 emissions from these dry land uses are
dependent upon the type of management that follows drainage of coastal wetlands, and are covered in GL2006(e.g. Chapter 11 of Volume 4).

1256
1257
1258
1259
1260

Conversely to rewetting of coastal wetlands, drainage of coastal wetlands increases the surface area for aerobic
respiration and chemical oxidation of organic matter, resulting in a reduction of CH4 production but enhanced
CH4 oxidation by methanotrophic bacteria in the top aerated soil layer. CH4 emissions from aerobic soils are
negligible. Under this aerobic soil, N2O production was attributed mainly to nitrification, and the production andemission rate of N2O is largely controlled by the provision of nitrogen by mineralization.

1261
1262
1263
1264
1265

Tier 1 method for estimation of the gas emissions from drained wetlands assumes that the emissions could be
ignored, and the emission factors for CH4 and N2O from drained wetland is assigned to be zero. Tier 2 method
requires country specific data that account for climate, vegetation type and soil texture. A comprehensive
understanding and representation of the dynamics of non-CO2 gas emission factors during the drainage, based onfield measurement, is involved in higher Tier method (Tier 3).

1266

4.4.5.1

1267

Non-CO2 emissions are dependent upon the type of management that follows drainage of coastal wetlands.

1268
1269

Methods described in Chapter 11 of Volume 4 of the 2006 supplement should be consulted for when land use ofdrained coastal wetlands includes application of:

1270



synthetic N fertilisers;

1271



organic N applied as fertiliser (e.g., animal manure, compost, sewage sludge, rendering waste);

1272



urine and dung N deposited on pasture, range and paddock by grazing animals;

1273



N in crop residues (above-ground and below-ground), including from N-fixing crops and from forages

1274
1275
1276
1277

Livestock production on drained coastal wetlands can result in methane emissions from enteric fermentation andboth CH4 and N2O emissions from livestock manure management systems. The methods for estimating CH4 andN2O emissions from these activities are provided in Chapter 10 Emissions from Livestock and Manure
Management of Volume 4.

1278

TIER 1

1279
1280

Tier 1 method for estimation of the gas emissions from drained wetlands assumes that the emissions could be
ignored, and the emission factors for CH4 and N2O from drained wetland is assigned to be zero.

1281

TIER 2 AND TIER 3

1282
1283
1284
1285

Country-specific emission factors should be used in Tier 2 methods. Tier 2 method requires country specific datathat account for climate, vegetation type. a comprehensive understanding and representation of the dynamics of
non-CO2 gas emission factors, based on field measurement, is involved in higher Tier method (Tier 3), taking
account of parameters such as season, soil texture, tidal elevation and tidal cycle (high tide vs. low tide).

Non-CO 2 emissions

C HOICE OF METHOD AND EMISSION FACTOR

1286

4.5

REWETTING AND RESTORATION OF
COASTAL WETLANDS

1289

4.5.1

Description of activities

1290
1291

Rewetting. Rewetting of coastal wetlands occurs where hydrology has been altered but the soil is at an
appropriate elevation for the establishment of functioning vegetation. Wetland restoration through reconnection

1287
1288

4.34

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

1292
1293
1294
1295
1296
1297
1298

of hydrology halts any ongoing emissions of soil carbon and upon the reestablishment of vegetation reinitiatedautochthenous carbon sequestration. Once vegetated is reestablished rates of removals are comparable withnatural marsh reference sites (Craft et al., 2003). Restored hydrological connectivity, through actions thatremove tidal restrictions or otherwise modify water delivery or discharge, can also result in increased soil storage
and productivity of coastal wetland plant species (Harris et al 2010). The rewetted condition covered in thissection results where off-site hydrologic modifications reverse drainage or impoundments or other obstructions
to hydrologic flow are removed (i.e. levee breach).

1299
1300

Restoration (vegetation and soils). Restoration generally refers to re-creating habitat that was present prior tothe current land use within recorded time, but here we also include afforestation in this definition.

1301
1302
1303
1304
1305
1306
1307
1308
1309
1310

1.Afforestation/reforestation. Afforestation and reforestation are common restoration activities in coastal regions
to conserve biodiversity and to mitigate disasters from tsunami and cyclones. Improved estimates of C storage inmangroves have recently been obtained at global/regional (Donato et al. 2011) and local (Fujimoto et al. 1999;
Ren et al. 2009; Kauffman et al. 2011; Donato et al. 2012; Zhang et al. 2012) scales, which makes it possible toquantify carbon gain due to mangrove afforestation and reforestation. It has been shown that mangroves contain
2-3 times higher carbon pools than in nearby upland forests in tropical Pacific regions (Donato et al. 2012).
Similarly, the sediments of mangrove forests in southern China sequester large quantities of soil organic C
during mangrove restoration (Zhang et al. 2012). Recognition of the C sequestration value of mangrove forestsand other vegetated coastal wetlands provides a strong argument for their protection and restoration (Chmura etal. 2003; Irving et al. 2010; Crooks et al. 2011).

1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322

2.Revegetation. Seagrasses are known as ‘ecosystem engineers’. For example, they reduce current velocity andattenuate wave activity, promote soil stabilization and as a result enhance sediment trapping, reduce
resuspension that cause accumulation of fine sediments and organic matter in seagrass beds relative to adjacentbare areas. Loss of seagrass cover due to a range of anthropogenic activities leads to de-stabilisation of thesediment, reduction in C sequestration and soil carbon content. Restoration of seagrass meadows can restore
these functions, but before recolonization of bare sediment can occur certain habitat conditions must be met,
including adequate light levels and the availability of donor material. Donor material can be provided via
transplantation or from seed banks or can occur naturally with donor material supplied from adjacent vegetatedareas. Restoration occurs slowly, for example a 3-5 yr time lag between nutrient load reduction and initiation ofseagrass recolonization has been observed (Vaudrey et al. 2010), with a further 12-15 yr time lag before seagrassbiomass attains a relatively stable distribution. Over larger spatial scales, C accumulation rates in seagrassmeadows are significant (Duarte et al. 2011; Kennedy et al. 2012).

1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336

Creation and restoration with sediment modifications including sediment resupply. These activities include
restoration that results from sediment removal or ditch filling or other modifications of the soil and vegetation(hydrology is unaltered), sediment/soil elevation or vegetation that is modified). These activities include: a)sediment removal and b) sediment enhancement including active sediment amendments. A recent synthesis ofwetland restoration studies suggests that wetlands with a higher degree of connectivity with allochthonous inputs
is an important factor driving high rates of recovery after restoration in coastal systems such as riverine and tidal
marshes (Ballantine and Schneider 2009). In these systems, wetland restoration may be accelerated by inputs ofmineral sediment and organic particles (Fennessy et al. 1994, Morgan and Short 2002, Anderson et al. 2005).
Examples of sediment modification include the use of sediment slurries of dredge material to fill containment
levees, water ponds and deteriorating brackish marshes (LaPeyre et al 2009; Llewellyn and LaPeyre 2011).
Deteriorating marshes in tidal systems often result as a function of sediment diversions or embankments that
restrict sediment supply that are replaced by shallow ponds (Barras et al 2003). Other factors have been
implicated that cause coastal erosion and subsidence (Dahl 2011), but the result can be decreased plant
productivity and plant mortality (Baumann et al. 1984; McKee and Mendelssohn 1988).

1337

4.5.2

1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348

This section deals with anthropogenic impacts to wetland soil organic C stocks, primarily C emissions from soil
and soil C storage, by activities affecting soil drainage through rewetting by modification of the water table or
restoration of natural hydrology and restoration of vegetation and soils. Guidelines are provided for estimating
carbon stock changes in soils of drained coastal wetlands where the hydrological regime has been restored.
Restoration of the soil water table and tidal flooding regime in coastal wetlands are assumed, over the long term,
to increase rates of soil organic C and increase the net stock of C through return of vertical soil accretion (e.g.
Connor et al. 2001). Rates of organic matter decomposition in soil below the restored water table will be lower
than that in the previously aerated soil, because anaerobic decomposition will dominate below the water table,
and this process is less efficient than aerobic decomposition (e.g., Reddy and Patrick 1975; Kristensen et al.
1995). Belowground biomass is a major contributor to soil carbon stocks, and this production generally occurs
within the upper 15 cm of soil in tidal marshes. There may be a lag time until maximum belowground biomass

Soil Carbon

DRAFT 2013 Wetlands Supplement

4.35

Chapter 4

DO NOT CITE OR QUOTE

1349
1350
1351
1352
1353

and soil carbon concentrations are reached. It is likely that reference carbon stocks of will be representative ofcarbon stocks obtained after native wetland vegetation has been reestablished under restored conditions. These
responses will vary locally within a wetland and may vary regionally with climate, but as yet there evidence fordifferences in magnitude of these responses is inadequate. Where this information is available it can be used forrefined calculations in upper tiers.

1354
1355
1356

General information and guidance for estimating changes in soil C stocks are provided in Section 4.2 (including
generic equations), and this section should be read before proceeding with a consideration of specific guidelines
dealing with coastal wetland soil C stocks.

1357
1358
1359
1360
1361

Total change in soil C stocks for Rewetting and Restoration of Coastal Wetlands is estimated using Equation 4.2,
which combines the change in soil organic C stocks for mineral soils and organic soils (including C gains); andstock changes associated with soil inorganic C pools (if estimated at Tier 3). Changes in stock may also be
calculated by input-output approaches though requires additional balancing of dissolved organic carbon
emissions along with balancing atmospheric fluxes.

1362
1363
1364
1365
1366

For Rewetting and Restoration of Coastal Wetlands, soils are maintained wet (or dry periodically in response tonatural hydrological cycles). Rewetting and Restoration of Coastal Wetlands may occur through managed
activities (such as rewetting of soils in areas disconnected from natural flows by structures) or the removal of
barriers to allow for natural natural hydrological connections. . As the water table is maintained at or above thegraded soil surface further emissions of soil carbon are assumed to be zero.

1367

4.5.2.1

1368
1369
1370
1371
1372

Inventories can be developed using a Tier 1, 2 or 3 approaches with each successive Tier requiring more details
and resources than the previous one. It is also possible that countries will use different tiers to prepare estimates
for the separate sub-categories of soil C (i.e., soil organic C stocks changes in mineral and organic soils; andstock changes associated with soil inorganic C pools). A decision tree is provided in Figure 4.1 to assist
inventory compilers with the selection of the appropriate tier for their soil C inventory.

1373

4.5.2.2

1374

MINERAL /ORGANIC SOILS

1375
1376
1377
1378

Tier 1

1379
1380
1381
1382

Equation 4.3 is used to estimate change in soil organic C stocks. Note that area of exposed bedrock in wetlands
and open water channels are not included. In practice, country-specific data on land management activity should
be obtained and classified into appropriate land management systems, and then stratified by ecosystem type.
Table 4.16 provides annual rates of C removal for soils of rewetted and hydrologically restored coastal wetlands.

1383
1384
1385
1386
1387

Tier 2

1388
1389
1390
1391

Tier 3

C HOICE OF METHODC HOICE OF E MISSION /R EMOVAL F ACTORS

For all soils, the estimation method is based on changes in soil organic C stocks over a finite (40 yr) period
following changes in management that impact soil organic C storage. After a finite transition period, one canassume a steady state change in stock at Tier 1 level of estimation assuming no change in water level.

The Tier 2 method for soils also uses Equation 4.3 but the inventory approach is further developed with countryspecific information to better specify emission/removal factors for climate regions, soil types, and/or the land
management activities. Tier 2 also employs models to better approximate accumulation or decay rates over time,
beyond the linear assumptions made in application of Tier 1 methods.
Tier 3 approaches use dynamic models and/or detailed soil C inventory measurements as the basis for estimating
annual stock changes. Estimates of stock changes using model-based approaches are computed from the coupledequations that estimate the net change of soil carbon as described in section 4.3.2.2.

1392

4.36

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

TABLE 4.16 ANNUAL REMOVAL FACTORS FOR REWETTED AND RESTORED SOILS FOR TIER 1 ESTIMATION
Climate Zone

Ecosystem

Number of
Observations

Mean(Mg C ha-1 yr-1)

Boreal andTemperate

Tidal Marshes

126

2.06

TropicalMangroves

39

1.32

GlobalSeagrass*

17

0.5±0.5

Range(Mg C ha-1 yr-1)

0.04 - 2

Source: Chmura et al . 2003, ,Silfleet et al., 2011, Duarte et al., 2011; *Data only includes measurements representative of ≥1 yr sedimentaccumulation
Data for tidal marsh soil stocks is derived from the following locations (with number of observations): Louisiana (34), Northeast Canada(31), New England (20), Continental Europe (9), Chesapeake Bay (8), UK, (6), California (5), North Carolina (5), Florida (4), Honk Kong,
China (1)
Data for mangrove soil stocks is derived from the following locations (with number of observations), Florida Keys, USA (15), Queensland,
Australia (12), Estero Pargo, Mexico (4), Hong Kong, China (2), Pohnpei Island, Micronesia (2), Victoria, Australia (1), Malaysia (1), Puerto
Rico (1), South Africa (1).

1393

1394

4.5.3

Biomass

1395
1396
1397
1398
1399
1400
1401
1402
1403
1404

This section provides guidelines for estimating carbon stock changes in biomass due to the reversion frompreviously drained coastal wetlands, through hydrological change, back to an ecosystem with fully saturated soil
and restoration through revegetation or reforestation. These conversions are relevant to mangrove and salt marsh
coastal ecosystems. Vegetation that characterizes for example agricultural land, protected by dikes will be lostwhen the land is inundated by seawater. Over a period of time new vegetation will colonise and expand within
the coastal wetland or, in the case of mangroves, re-vegetation may be accelerated through replanting. This
scenario is similar to that described during drainage of coastal wetlands in as far as they both should beconsidered as a two process conversion. If rewetting or restoration of previously drained coastal wetlands resultsin the transfer of carbon from one pool to another, all transfers must be accounted for during the transition to a
new steady state.

1405

4.5.3.1

1406

TIER 1

1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417

A Tier 1 approach generally assumes no change in biomass in Rewetting and Restoration of Coastal Wetlands
except those ecosystems where woody vegetation is prevalent. In any coastal wetland ecosystem, where there is
no change in either type or intensity of management, biomass will be in an approximate steady-state (i.e. carbon
accumulation through plant/tree growth is roughly balanced by losses through herbivory and decomposition).
However, where management changes are occurring over time (e.g., through introduction of aquaculture,physical disturbance, soil removal, nutrient enrichment or other practices) carbon stock changes can besignificant. If it is reasonable to assume that any of the coastal wetland ecosystems are not a key source, acountry may apply the Tier 1 assumption of no change in biomass. However, if information is available todevelop reliable estimates of rates of change in biomass in Rewetting and Restoration of Coastal Wetlands, acountry may use a higher Tier, even if Rewetting and Restoration of Coastal Wetlands is not a key source,
particularly if management changes are likely, in which case default data in Tables 4.5-4.8 can be applied.

C HOICE OF METHOD

1418
1419

TIER 2

1420
1421
1422
1423
1424
1425
1426
1427
1428
1429

Estimating changes in carbon stocks in biomass for any rewetted coastal wetland ecosystem can require a twophase approach if there are different time-scales for vegetation loss associated with the drained coastal wetland
land use and replacement by vegetation tolerant of the saline, waterlogged conditions in the rewetted soil orrestored ecosystem. There can be an abrupt change in biomass, which can be treated as phase 1 and in-line withthe 2006 guidelines be estimated at the year of conversion. The second phase accounts for a gradual biomass loss
and gain during a transition period to a new steady state system. At some time after rewetting the new vegetationthat develops on the coastal wetland ecosystem should be comparable to that found in its natural setting and thenshould be considered under, and accounted for under Rewetting and Restoration of Coastal Wetlands. The
transition period following rewetting and conversion to coastal wetland will vary depending on the how therestoration of the hydrology is managed and countries should determine transition periods that specifically relate

DRAFT 2013 Wetlands Supplement

4.37

Chapter 4

DO NOT CITE OR QUOTE

1430
1431
1432
1433
1434
1435
1436
1437
1438

to the particular type of rewetting and ecosystem that is affected. The values of coefficients determining the rateof emissions may depend on the transition period used. In line with the 2006 guidelines, rewetted coastal
wetlands should be accounted for with Phase 1 methods in the year that they are converted, with Phase 2
methods being used for all subsequent transitional years until the new vegetation in the rewetted coastal
ecosystem achieves steady state. At the end of the transitional period, the land area should be accounted forunder Rewetting and Restoration of Coastal Wetlands. If there is no abrupt change in biomass associated withthe conversion, for example if hydrology is restored to existing tilled fields or abandoned shrimp ponds or a
gradual transition occurs between two different vegetation types, Phase 1 accounting would not be appropriate
and the whole conversion accounting can be undertaken using Phase 2 methods.

1439
1440
1441
1442
1443
1444
1445
1446

In cases where there is an immediate and abrupt carbon stock change in biomass on the land that is being
rewetted the effect of this conversion will be estimated using Equation 2.16 in Chapter 2 of the 2006 guidelines,
with the default assumption that BAfter=0. During the transition period, pools that gain or lose C often have a nonlinear loss or accumulation curve that can be represented through successive transition matrices. If the true
shapes of the curves are known, these curves can be applied to each cohort that is under transition during thereporting year to estimate the annual emission or removal by the specific pool. If the shape of the curve isunknown, countries may simplify and use a linear decay function to estimate pool changes. A disturbance matrix
as described in section 4.3.3.1 is a useful tool for good practice implementation.

1447

4.5.3.2

1448

TIER 1

1449
1450
1451
1452
1453
1454

Tier 1 methods require estimates of the biomass of the land use before conversion and after conversion. It is
assumed that there is no biomass (as in abandoned shrimp ponds) or that all biomass is cleared when preparing
land for rewetting and restore a coastal wetland. Thus, the default for biomass immediately after conversion is 0
tonne ha-1. Default values for biomass before conversion can be found in the appropriate chapters (e.g. Croplands,
Grasslands) of the 2006 guidelines. Default values for biomass and net growth, following (not immediately after)
rewetting and conversion back to a coastal ecosystem, can be found in Table 4.6 and 4.7.

1455

TIER 2

1456
1457
1458
1459
1460
1461

It is good practice to use country-specific estimates for biomass stocks and emissions/removals due to land
conversion, and also include estimates of on-site and off-site losses due to burning and decay following land
conversion by rewetting of previously drained coastal wetlands. These improvements can take the form ofsystematic studies of carbon content and emissions and removals associated with land uses and land-use
conversions within the country or region and a re-examination of default assumptions in light of country-specificconditions.

1462
1463
1464

Region-specific or country-specific data on biomass for growth in the vegetation that characterises the rewetted
coastal ecosystem are needed for a Tier 2 approach. These can be obtained from Table 4.6. General guidance on
survey and sampling techniques for biomass inventories is given in Volume 4, Chapter 3 (Annex 3A.3).

1465
1466
1467
1468
1469
1470

If possible accurate knowledge of the dynamics of below-ground biomass should be obtained for accounting forcarbon stock changes when land is rewetted and converted to a coastal wetland. Estimation of changes in belowground biomass during conversion from the land use in the previously drained coastal wetland to rewetted
coastal ecosystem can be an important component of the calculated stock change. Field measurements arelaborious and difficult and thus expansion factors to estimate below-ground biomass from above-ground biomass
are often used. Default ratios can be found in Table 4.4.

1471
1472
1473
1474
1475
1476

Below-ground biomass to above-ground biomass ratios can vary at both individual species and community
scales. Thus, it is recommended to use, as far as possible, empirically-derived root-to-shoot ratios specific toeach land use type, ecosystem and region are used and can be found in the appropriate chapters (e.g. Croplands,
Grasslands) of the 2006 guidelines or in this chapter for the rewetted coastal ecosystems (state location).. These
data can be used as defaults when countries do not have more regionally specific information to develop country
specific values.

1477

TIER 3

1478
1479
1480
1481
1482
1483
1484

Tier 3 approaches consist of using a combination of dynamic models and inventory measurements of biomass
stock changes. This approach does not employ simple stock changes or emission factors per se. Estimates ofemissions/removals using model-based approaches are derived from the interaction of multiple equations that
estimate the net change of biomass stocks within the models. Models can be used, together with periodic
sampling-based stock estimates, to estimate stock changes or inputs and outputs. For example, validated speciesspecific growth models that incorporate management effects in the drained coastal wetland with corresponding
data on management activities, could be used to estimate net changes in biomass in the converted land over time.

4.38

C HOICE OF EMISSION / REMOVAL FACTORSDRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

1485

4.5.4

Dead Organic matter

1486
1487
1488
1489
1490
1491

Changes in dead organic matter resulting from rewetting of forested coastal wetlands are estimated at the Tier 1
level because they represent potentially large C emissions to or removals from the atmosphere. In non-forested
coastal wetlands, the default assumption is that no changes in stocks occur at the Tier 1 level of estimation. For
key categories or extensive management activities occurring in either forested or non-forested coastal wetlands,
Tier 2 and higher estimation methods should be used and these values reported. In these cases, stock changes
should be disaggregated relative to climate, vegetation type and salinity where applicable.

1492

4.5.4.1

1493

TIERS 1, 2 & 3

1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504

The method for estimating changes in dead organic matter stocks are presented in Equations 2.18 and 2.19 (Vol.
4, Chapter 2). The method estimates the change in dead organic matter stocks applying the Stock-Difference
Method where the change in dead organic matter stocks are estimated at two points in time relative to the period
before and after the land-use conversion or management activity. This method can be applied for forested coastal
wetlands at a Tier 1 level or at a Tier 2 level using country estimates where changes occur in either forested or
non-forested coastal wetlands. Tier 1 default stocks for forested coastal wetlands are provided in Table 4.9. The
default for changes in dead organic matter stocks at the tier 1 level of estimation is 0 for non-forested coastal
wetlands. Tier 2 level of estimation should be used when extensive management activities lead to key categoryland-use conversions. The Gain-Loss Method and better estimates of transition times may also be more
appropriate for Tier 2 or higher level of estimation to reduce uncertainties. Estimates of dead wood and litter
exports due to tidal advection should also be considered.

1505

4.5.4.2

1506

TIER 1

1507
1508
1509
1510
1511
1512
1513
1514
1515

Countries using a Tier 1 method require data on the default dead wood and litter carbon stocks as defined inTable 4.9. The Tier 1 assumption is that carbon stocks in litter and dead wood pools in all non-forested coastal
wetlands and conversion among non-forest land-use categories are zero. The use of equation 4.17 isrecommended for Tier 1 estimation. For lands converted to forested coastal wetland, the carbon stocks in deadwood and litter pools are assumed to increase linearly over the transition period T (default is 20 yr for both litterand dead wood C stocks). Thus, the annual rate of increase is estimated as the ratio between the difference incarbon stocks in the DOM pools in the non-forest and forest categories, and the numbers of years in thetransition period T. Conversions from forested coastal wetland to non-forested coastal wetland are assumed to be
emitted in the year of conversion.

1516

TIERS 2 AND 3

1517
1518
1519
1520

The higher Tier methods described above (Equation 4.18) and in Chapter 2 will allow for more robust estimateswhen applied to national data. Additional requirements may arise if the assumption that carbon stocks in deadwood and litter pools of non-forest land-use categories are zero cannot be justified, such as in some agro-forestry
systems or other circumstances where intensive management activities have occurred.

1521

4.5.5

1522
1523
1524
1525

These saturated conditions also enable methanogens, sulfate-reducers, and other bacteria to decompose part ofthe organic matter with CH4 as a by-product. Nitrous oxide results mainly from microbial denitrification under
this reduced environment, with rates depending mostly on the availability of nitrate. The degree of water
saturation is one of the key factors controlling CH4 and N2O emissions.

1526
1527
1528
1529
1530
1531

Rewetting of Coastal Wetland soils shifts microbial decomposition from aerobic to anaerobic (responsible forCH4 emissions) regimes, generally reducing the potential for CH4 emissions from rewetted coastal wetlands. If
soil conditions prior to rewetting were aerobic, then it is likely that CH4 emissions will increase where tidal
water salinities are <15 ppt. However, coastal wetlands subject to intensive nutrient loading may be sources ofCH4 emissions. If tidal waters rewetting coastal wetlands are nutrient-enriched, then wetlands with salinities>15 ppt also are likely to be sources of CH4 emissions.

1532
1533
1534

One of the main controlling factors in this reaction is the availability of inorganic N in the soil. If, prior to
rewetting, the area of coastal wetland was subject to increased N supply (e.g. in fertilized land) it may be asource of N2O emissions during the rewetting. However, experimental studies have shown that the substrate N is

CHOICE OF METHODCHOICE OF EMISSION / REMOVAL FACTORS

Non-CO 2 emissions

DRAFT 2013 Wetlands Supplement

4.39

Chapter 4

DO NOT CITE OR QUOTE

1535
1536
1537

rapidly depleted (Moseman-Valtierra et al. 2011), thus N2O is likely to be negligible after the N is depleted andno continuous N is supplied. Contrarily, flooded coastal wetlands subjected to increased N supplies throughground water or tidal water may become sources of N2O emissions.

1538
1539
1540
1541

This section provide methods for estimations of non-CO2 emission from rewetted wetlands at the first conversion
process, i.e. initial conversion from some other land use to a rewetted coastal wetlands ecosystem and transition
to a new steady state. The estimations of non-CO2 emissions from the second process, subsequent managementof the rewetted coastal wetlands, are addressed in section 4.4.4 in this chapter.

1542

4.5.5.1

1543

TIER 1

1544
1545

Tier 1 method in this section estimates the non-CO2 emissions by taking no account of the land use prior to
rewetting. The emissions of N2O and CH4 depend on the nutrient/organic matter available in the tidal water.

1546
1547

If the rewetted lands are subjected to nutrient-enriched condition, N2O and CH4 emissions could be estimatedusing default emission factor similar to those in section 4.4.4 (Nutrient-enriched Wetlands).

1548
1549
1550
1551
1552

In those lands rewetted by ‘pristine’ water, N2O emission is assumed to be negligible, and the emission factors
are assigned to be zero. For CH4, its flux depends on salinity level in tidal marshes (Table 4.17), but polyhaline
marshes approximate an average CH4 flux of a 1 g m-2 yr-1 and thus assumed to be negligible at Tier 1 level of
estimation (Poffenbarger et al 2011). In mangrove wetlands, average CH4 emissions are around 3 (g m-2 y-1) andare also considered negligible at Tier 1 estimation level.

C HOICE OF METHOD AND EMISSION FACTOR S

1553
TABLE 4.17 EMISSION FACTORS FOR CH4 FROM “INTACT” COASTAL WETLANDS FOR TIER 1 ESTIMATION
WetlandType

Salinity
type

Default EF(tonnes CH4C ha-1 y-1)

EF Range(tonnes CH4C ha-1 y-1)

Tidal
Marsh

FreshBrackish

0.28

Polyhaline(>18ppt)

0

Saline0Mangrove

Error(95%CI)

Reference

0.02-1.6±78%

Poffenbarger et al 2011

0-0.04±94%

Poffenbarger et al 2011

±87%

Page and Dal 2010

1554
1555

TIER 2 AND TIER 3

1556
1557
1558
1559

Country-specific emission factors should be used in Tier 2 methods. In tier 3 method, the land use prior to
rewetting, climate and vegetation type should be taken into account. A comprehensive understanding andrepresentation of the dynamics of non-CO2 gas emission factors, based on field measurement, is involved in Tier
3.

1560

4.6

COMPLETENESS, TIMES SERIESCONSISTENCY, QUALITY ASSURANCE ANDQUALITY CONTROL

1563

4.6.1

Completeness

1564
1565
1566
1567
1568
1569
1570
1571

Completeness is a requirement for greenhouse gas inventories, and it is good practice to address all wetland
carbon gain and losses. For completeness, it is good practice to include all carbon pools and non-CO2 gases. The
wetland area used for calculation for different carbon pools must be the same, and emissions from organic soils
and emissions or removals attributed to land-use change on mineral soils should be estimated. Country-specificinformation should be incorporated into higher tier methodologies. A complete accounting of emissions andremovals of CO2 associated with Management Changes in Coastal Wetlands, Drainage of Coastal Wetlands and
Re-Wetting of Coastal Wetlands is necessary. It is good practice that all losses from biomass carbon pools that
result in transfers to dead organic matter pools are first accounted for as changes to biomass carbon stocks.

1561
1562

4.40

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

1572

4.6.2

Developing a consistent time series

1573
1574
1575
1576

It is good practice to develop a consistent time series of inventories of anthropogenic emissions and removals ofgreenhouse gases for all wetland conversion categories using the guidance in Chapter 8 in this volume.
Achieving time series data may require extrapolation or interpolation from longer time series data or from longterm trends, as few long-term data for available for most coastal wetlands.

1577
1578
1579
1580
1581
1582

Consistent accounting over time of wetland areas included in biomass and soil C emissions and removals
inventory requires that activity data be stratified by the common definitions of wetland type/ soil type. Wetlands
subject to land-use change will not be lost or double-counted due to accounting errors resulting from inconsistent
stratification of wetland types/ soil types. Ideally, the same protocol should be applied consistently every year in
the time series, at the same level of disaggregation and where country-specific data are used, it is good practiceto use the same values and methods for equivalent calculations throughout the time series.

1583
1584
1585
1586
1587

New values should be included if the inventory capacity and information and data sources improve over time. It
is good practice in these circumstances to consistently recalculate the earlier emissions and removals. Otherchanges during the time series need to be consistent to take account of new data or methods and their consistency
with the earlier data. It is good practice to recalculate the entire time series of data if either the default values arechanged; changes in wetland types need to be tracked for long periods of time.

1588
1589
1590

It is good practice to use the same model parameter values for the entire time series and to recalculate the entire
dataset if one of more of the parameters has changed. Failure to do so may result in either under-or overestimates of the true changes in carbon and non-CO2 gas emissions or removals.

1591

4.6.3

1592
1593
1594
1595

Different levels of precision and accuracy, and as a result, bias will invariably apply to a number of the values
used to assess greenhouse gas inventories. Estimates are influenced by the quality and consistency of data andinformation available as well as knowledge gaps, all of which will vary among countries. Depending on the tierlevel used, estimates will be affected by different sources and degrees of error, such as sampling error.

1596
1597
1598
1599
1600
1601
1602

It is good practice to execute quality control checks through Quality Assurance (QA) and Quality Control (QC)
procedures as detailed in Chapter 8, and review the emission estimation procedures by experts. Additional
quality control checks as outlined in Chapter 8 and quality assurance procedures may also be applicable. This isespecially so if higher tier methods are used. It is good practice to supplement the general QA/QC related to dataprocessing, handling, and reporting and documenting, with source-specific procedures. QA/QC proceduresshould be documented separately for Management Changes in Coastal Wetlands, Drainage of Coastal Wetlands
and Re-Wetting of Coastal Wetlands.

1603
1604
1605
1606
1607

Organizations and institutions which collect the data are responsible for reviewing data collection methods andall aspects of the data handling and analysis procedures, and ensure that they are done correctly, and arecomplete and consistent over time. It is important to document all procedures and processes as it enables
reviewers to identify inaccuracy, gaps and to suggest improvements. Transparency is most important in other toensure consistency and clarity of the processes and procedures over time.

1608
1609
1610
1611
1612
1613

All data should be checked against other reliable sources of information that are independent. Any differences ordiscrepancies must be documented, and consistency must be applied to total areas involved in the inventory toensure that wetland area are neither ‘created’ or ‘lost’ overtime. When using country-specific data, the inventory
compiler should compare these data to the IPCC default values or the Emissions Factor Database (EFDB) anddetail any differences. These country-specific data must be of high quality, adequately described, anddocumented.

1614
1615
1616
1617

If factors are based on direct measurements (i.e., soil C content) the inventory agency should review themeasurements to ensure that they are representative of the actual range of environmental conditions. It is goodpractice to review and, if necessary, revise the default assumptions and to compare model estimates with fieldmeasurements and other data sources.

1618

4.6.4

1619
1620
1621
1622

General requirements for reporting and documentation are set out in Chapter 8. It is good practice to archive anddocument all data and information applied to produce the national emissions/removals inventory. Definitions of
all carbon pools should be included in the inventory, including evidence that these definitions have been appliedconsistently over time.

Quality assurance and quality control

Reporting and documentation

DRAFT 2013 Wetlands Supplement

4.41

Chapter 4

DO NOT CITE OR QUOTE

1623
1624
1625
1626
1627
1628
1629

Documentation is necessary for demonstrating transparency, completeness, consistency of all data and methods
for interpolating between samples, methods and years, and for recalculating and avoidance of possible double
accounting or ‘loss’ of C inventory. Regardless of Tier methodology used, explanations are required for
decisions regarding choice of methodology, approaches and use of default or other data. This is necessary tofacilitate examination by independent third parties; inventories should include summaries of approaches andmethods used and references to data sources so that the reported emissions estimates are transparent and can beretraced or recalculated.

1630
1631
1632
1633

All data sources, including default values, must be quoted. The scientific basis for any country-specific data andmethods must be completely described and justified, as well as describing sources and magnitudes of uncertainty.
This is especially so for any large-scale estimates as in these cases the statistical procedures should be described
and well as the level of uncertainty

1634
1635

Differences between years in emissions should be explained and the possible reasons for these differences
documented as much as possible.

1636

4.7

1637

TBD

FUTURE METHODOLOGICAL DEVELOPMENT

1638
1639

Annex 4.1

1640
1641
1642
1643

Mangrove soils

1644
1645
1646
1647
1648
1649
1650

It has been shown that mangroves contain 2-3 times higher carbon pools than in nearby upland forests (830-1218
vs. 357-486 Mg C ha-1) in tropical Pacific regions (Donato et al. 2012). Similarly, the sediments of mangrove
forests in southern China sequester large quantities of soil organic C during mangrove restoration, with sediment
total organic carbon densities of 90, 170 and 288 Mg C ha-1, respectively, for barren sites, mangrove plantations,and natural mangrove forests (Zhang et al. 2012). In afforested Sonneratia apetala plantations, the averageannual rate of total carbon storage accumulation at 4, 5, 8, and 10-year age was 5.0, 7.9, 8.7, and 8.4 Mg C ha-1
yr-1, respectively (Ren et al. 2009).

1651
1652
1653
1654
1655
1656
1657
1658
1659

Seagrass soils

Lovelock et al., 2011 measured CO2 efflux from mangrove soils that had been cleared for up to 20 years on theislands of Twin Cays, Belize. Rates of emissions from disturbed soils display exponential decay. At years 1 and
20 Lovelock et al., 2011, document rates of emissions of 28.9 Mg C ha-1 yr-1 and 8.2 Mg C ha-1 yr-1, respectively.

Changes in carbon stocks during meadow recolonization have been assessed over different time scales (Pedersen
et al. 2003; Barron et al. 2004; McGlathery et al. 2012). In general, no increase in sediment carbon pools can bediscerned during early years (0-6 yr) of meadow development. There has only been one study over an extended
period (9 yr), after which time there were quantifiable changes in the sediment carbon pool. The carbon stock inunvegetated sediment (1.4 Mg C ha-1) was almost half that found in the restored meadow (2 Mg C ha-1). Overlarger spatial scales, C accumulation rates in seagrass meadows vary from 0.03 to 2 Mg C ha-1 yr-1 (range of
which 50% can be attributed to seagrass organic matter (Kennedy et al. 2012) resulting 0.02 to 1 Mg C ha -1yr-1(mean 0.54±0.5 Mg C ha-1, N=16) accumulation of seagrass C ( Duarte et al. 2011).

1660
1661
1662
1663
1664
1665
1666
1667
1668

4.42

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

1669

References

1670
1671

Adams, C.A., Andrews, J.E., Jickells, T. (2011). Nitrous oxide and methane fluxes vs. carbon, nitrogen andphosphorous burial in new intertidal and saltmarsh sediments. Science of the Total Environment (in press)

1672
1673
1674

Allen D.E., Dalal R.C., Rennenberg H., Meyer R.L., Reeves S. and Schmidt S. 2007. Spatial and temporalvariation of nitrous oxide and methane flux between subtropical mangrove soils and the atmosphere. Soil
Biology and Biochemistry 39: 622–631.

1675
1676

Allen, D., Dalal, RC, Rennenberg, H, Schmidt, S. 2011. Seasonal variation in nitrous oxide and methane
emissions from subtropical estuary and coastal mangrove sediments, Australia. Plant Biology 13: 126-133.

1677

Alongi, DM. 2010. The Energetics of Mangrove Forests. Springer Science.

1678
1679
1680

Alongi, DM, Pfitzner, J, Trott, LA, Tirendi, F, Dixon, P, Klumpp, DW. 2005. Rapid sediment accumulation andmicrobial mineralization in forests of the mangrove Kandelia candel in the Jiulongjiang Estuary, China.
Estuarine Coastal and Shelf Science 63: 605-618.

1681
1682

Anderson, C. J., W. J. Mitsch, and R. W. Nairn. 2005. Temporal and spatial development of surface soil
conditions at two created riverine marshes. Journal of Environmental Quality 34:2072–2081.

1683
1684

Apostolaki ET, Holmer M, Marbà N, Karakassis I. 2010. Metabolic imbalance in coastal vegetated (Posidonia
oceanica) and unvegetated benthic ecosystems. Ecosystems 13:459−471

1685
1686
1687

Apostolaki ET, Holmer M, Marbà N, Karakassis I. 2011. Reduced carbon sequestration in a Mediterranean
seagrass (Posidonia oceanica) ecosystem impactedby fish farming. Aquaculture Environment Interactions 2:
49-59.

1688
1689

Armentano, T. V. and Menges, E. S.: Patterns of change in the carbon balance of organic soil wetlands of thetemperate zone, Journal of Ecology 74:755–774.

1690
1691

Badalamenti F, Alagna A., D’Anna G.a, Terlizzi A., Di Carlo G. 2011 The impact of dredge-fill on Posidonia
oceanica seagrass meadows: Regression and patterns of recovery Marine Pollution Bulletin 62: 483–489.

1692
1693

Ballantine K. and Schneider R. 2009. Fifty-five years of soil development in restored freshwater depressional
wetlands. Ecological Applications 19: 1467-1480.

1694
1695
1696

Barras, J.A., S. Vebille, D. Britsch, S. Hartley, S. Hawes, J. Johnston, P. Kemp, Q. Kinler, A. Martucci, J.
Porthouse, D. Reed, K. Roy, S. Sapkota, and, J. Suhayda. 2003. Historical and projected coastal Louisiana
land changes: 1978–2050: USGS Open File Report 03-334, 29 pp.

1697
1698

Barron, C., Marbaa, N, Terrados, J, Kennedy, H, Duarte, CM. 2004. Community metabolism and carbon budget
along a gradient of seagrass (Cymodocea nodosa) colonization. Limnology and Oceanography 49: 1642-1651.

1699
1700

Baumann, R.H., J.W. Day Jr., and C.A. Miller. 1984. Mississippi deltaic wetland survival: Sedimentation versus
coastal submergence. Science 224: 1093–1095.

1701
1702

Baustian, J., Mendelssohn, I., Lin, Q. and Rapp J. 2011. In situ burning restores the ecological function andstructure of an oil-impacted coastal marsh. Environmental Management 46: 781-789.

1703
1704

Bauza, J., Morell, J.M, Corredor, J.E. (2002). Biogeochemistry of nitrous oxide production in the red mangrove(Rhizophora mangle) forest soils. Estuarine, Coastal and Shelf Science 55: 697-704.

1705
1706

Bridgham, SD, Megonigal, JP, Keller, JK, Bliss, NB, Trettin, C. 2006. The carbon balance of north American
wetlands. Wetlands 26:889-916.

1707
1708

Buresh, RJ, DeLaune, RD, Patrick, WH. 1980. Nitrogen and phosphorus distribution and utilization by Spartina
alterniflora in a Louisiana Gulf Coast Marsh. Estuaries 3: 111-121.

1709
1710
1711

Burnside N.G., Joyce C.B., Puurmann E. and Scott D.M. 2007. Use of vegetation classification and plant
indicators to assess grazing abandonment in Estonian coastal wetlands. Journal of Vegetation Science 18:645-654.

1712
1713

Buth, G.J.C. 1987. Decomposition of roots of three plant communities in a Dutch salt marsh. Aquatic Botany
29: 123-138.

1714
1715

Byun, D.S., Wanga, X.H. and Holloway, P.E. (2004) Tidal characteristic adjustment due to dyke and seawall
construction in the Mokpo Coastal Zone, Korea Estuarine, Coastal and Shelf Science 59:185-196.

1716
1717

Chauhan, R, Ramanathan, AL, Adhya, TK. 2008. Assessment of methane and nitrous oxide flux frommangroves along the Eastern coast of India. Geofluids 8: 321-332.

DRAFT 2013 Wetlands Supplement

4.43

Chapter 4

DO NOT CITE OR QUOTE

1718
1719

Chen G.C., Tam N.F.Y. and Ye Y. 2010. Summer fluxes of atmospheric greenhouse gases N2O, CH4 and CO2
from mangrove soil in South China. Science of the Total Environment 408: 2761–2767.

1720
1721

Chen G..C., Tam N.F.Y., Wong Y.S. and Ye Y. 2011. Effect of wastewater discharge on greenhouse gas fluxes
from mangrove soils. Atmospheric Environment 45: 1110-1115.

1722
1723

Chen G.C., Ye Y., Lu C.Y. 2008. Seasonal variability of leaf litter removal by crabs in a Kandelia candelmangrove forest in Jiulongjiang Estuary, China. Estuarine, Coastal and Shelf Science 79: 701-706.

1724
1725

Cheng X., Peng R. Chen J., Luo Y., Zhang Q., An S., Chen J., and Li B. 2007. CH4 and N2O emissions from
Spartina alterniflora and Phragmites australis in experimental mesocosms, Chemosphere 68:420-427.

1726
1727

Chmura G..L., Anisfeld S., Cahoon D. and Lynch J. 2003. Global carbon sequestration in tidal, saline wetland
soils. Global Biogeochemical Cycles 17: 1111 (1-12).

1728
1729

Connor, R.F., Chmura, G.L. and Beecher, C.B. 2001. Carbon accumulation in Bay of Fundy salt marshes:
implications for restoration of reclaimed marshes. Global Biogeochemical Cycles 15(4): 943-954.

1730
1731

Corredor, JE, Morell, JM, Bauza, J. 1999. Atmospheric nitrous oxide fluxes from mangrove sediments. Marine
Pollution Bulletin 38: 473-478.

1732
1733

Craft, C., Megongial, P, Broome, S., Stevenson, J. Freese, R., Cornell, J, Zheng, L, Sacco, J. 2003. The pace of
ecosystem development of constructed Spartina alterniflora marshes. Ecological Applications 13: 1417-1432.

1734
1735
1736

Crooks S. and others. 2011. Mitigating Climate Change through Restoration and Management of Coastal
Wetlands and Near-shore Marine Ecosystems: Challenges and Opportunities. Environment Department Paper
121. Washington, DC: World Bank.

1737
1738

Curcό, A, Ibanez, C, Day, JW, Prat, N. 2002. Net primary production and decomposition of salt marshes of theEbre Delta. Estuaries 25: 309-324.

1739
1740

Daby D. 2003 Effects of seagrass bed removal for tourism purposes in a Mauritian bay . Environmetal Pollution
125: 313-324.

1741
1742

Dahl, T.E. 2011. Status and trends of wetlands in the conterminous United States 2004 to 2009. U.S. Departmentof the Interior; Fish and Wildlife Service, Washington, D.C. 108 pp.

1743
1744

Dai M. and others. 2008. Nitrification and inorganic nitrogen distribution in a large perturbed river/estuarine
system: the Pearl River Estuary, China. Biogeosciences 5: 1545–1585.

1745
1746

Da Silva J.F., Duck R.W., Catarino J.B. 2004. Seagrasses and sediment response to changing physical forcing ina coastal lagoon. Hydrology and Earth System Sciences 8: 151–159.

1747
1748

Darby, FQ and Turner, RE. 2008. Below- and aboveground Spartina alterniflora production in a Louisiana salt
marsh. Estuaries and Coasts 31: 223-231.

1749
1750

Ding W., Zhang,Y., and Cai Z. 2010. Impact of permanent inundation on methane emissions from a Spartina
alterniflora coastal salt marsh. Atmospheric Environment 44: 3894-3900.

1751
1752

Donato D, JB Kauffman, D Murdiyarso, S Kumianto, M Stidham, M Kanninen. 2011. Mangroves among themost carbon-rich forests in the tropics. Nature Geoscience 4: 293-297.

1753
1754

Donato D. and others. 2012. Whole-island carbon stocks in the tropical Pacific: Implications for mangrove
conservation and upland restoration. Journal of Environmental Management 97:89-96.

1755
1756

Duarte C.M. and Chiscano C.L. 1999 Seagrass biomass and production: a reassessment. Aquatic Botany, 65,
159-174

1757
1758
1759

Duarte, CM, Marba, N, Gacia, E, Fourqurean, JW, Beggins, J, Barron, C, Apostolaki, ET. 2011. Seagrass
community metabolism: assessing the carbon sink capacity of seagrass meadows. Global Biogeochemical
Cycles 24

1760
1761
1762

Dumbauld B.R., Ruesink J.L., Rumrill S.S. 2009 The ecological role of bivalve shellfish aquaculture in theestuarine environment: A review with application to oyster and clam culture in West Coast (USA) estuaries.
Aquaculture 290: 196–223.

1763
1764

Dunton, KH, Hardegree, B, Whitledge, TE. Response of estuarine marsh vegetation to interannual variation inprecipitation. Estuaries 24: 851-861.

1765
1766

Edwards, KR and Mills, KP. 2005. Aboveground and belowground productivity of Spartina alterniflora (smooth
cordgrass) in natural and created Louisiana salt marshes. Estuaries 28: 252-265.

4.44

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

1767
1768

Ellison, AM and Farnsworth, EJ. 1996. Anthropogenic disturbance of Caribbean mangrove ecosystems: past
impacts, present trends, and future predictions. Biotropica 28: 549-565.

1769
1770

Erftemeijer P.L.A. and Lewis III, R.R. 2006 Environmental impacts of dredging on seagrasses: A review.
Marine Pollution Bulletin 52:1553–1572.

1771
1772

Fennessy, M. S., C. C. Brueske, and W. J. Mitsch. 1994. Sediment deposition patterns in restored freshwater
wetlands using sediment traps. Ecological Engineering 3:409–428.

1773
1774

Food and Agriculture Organization of the United Nations (FAO). 2003. Status and trends in mangrove area
extent worldwide, FAO, Paris, 2003.

1775
1776

Food and Agriculture Organization of the United Nations. 2007. The World's Mangroves 1980-2005. FAO
Forestry Paper 153.

1777
1778
1779

Flores-Verdugo FJ, Day JW, Briseño-Dueñas R. 1987. Structure, litter fall, decomposition, and detritus
dynamics of mangroves in a Mexican coastal lagoon with an ephemeral inlet. Marine Ecology Progress
Series 35: 83-90.

1780
1781

Fujimoto, K and others. 1999. Below-ground carbon storage of Micronesian mangrove forests. EcologicalResearch 14:409-413.

1782
1783
1784

Gabrey S.W. and Afton A.D. 2001. Plant community composition and biomass in Gulf Coast Chenier Plain
marshes: Responses to winter burning and structural marsh management. Environmental Management 27:
281-293.

1785
1786

Gedan, K.B., Silliman, B. and Bertness, M.D. 2009. Centuries of Human-Driven Change in Salt Marsh
Ecosystems. Annual Review of Marine Science 1:117–41.

1787
1788

Giri, R and others. 2010. Status and distribution of mangrove forests of the world using earth observation
satellite data. Global Ecology and Biogeography 20: 154-159.

1789
1790
1791

Guimarães H.M.E., Cunha A.H., Nzinga R.L., Marques J.F. 2012 The distribution of seagrass (Zostera noltii) in
the Ria Formosa lagoon system and the implications of clam farming on its conservation. Journal for Nature
Conservation 20: 30– 40

1792
1793
1794

Hammerstrom K.K., Kenworthy W.J., Whitfield P.E. and Merello M.F. 2007 Response and recovery dynamics
of seagrasses Thalassia testudinum and Syringodium filiforme and macroalgae in experimental motor vessel
disturbances. Marine Ecology Progress Series 345: 83–92,

1795
1796

Harris R.J, Mildbrandt E.C., Everham E.M. and Bovard B.D. 2010. The effects of reduced tidal flushing on
mangrove structure and function across a disturbance gradient. Estuaries and Coasts 33:1176-1185.

1797
1798

Hemminga, M.A., Kok, C.J. and de Munck, W. 1988. Decompostion of Spartina anglica roots and rhizomes ina salt marsh of the Westerschelde Estuary. Marine Ecology Progress Series 48:175-184.

1799
1800

Huang B., Yu K. and Gambrell R.P. 2009. Effects of ferric iron reduction and regeneration on nitrous oxide andmethane emissions in a rice soil. Chemosphere 74: 481-486.

1801
1802

Imgraben S. and Dittmann S. 2008. Leaf litter dynamics and litter consumption in two temperate South
Australian mangrove forests. Journal of Sea Research 59: 83-93.

1803
1804

Kauffman, J.B. C Heider & T G. Cole &K A. Dwire & Dl C. Donato. 2011. Ecosystem carbon stocks ofMicronesian mangrove forests. Wetlands 31:343-352.

1805

Kennedy et al 2012

1806
1807
1808

Kenny, C., Yamulki, S., Blackwell, M., Maltby, E., French, P., Birgand, F. (2004). The release of nitrous oxidefrom the intertidal zones of two european estuaries in response to increased ammonium and nitrate loading.
Water, Air and Soil Pollution: Focus 4: 61–66.

1809
1810

Krauss KW, TW Doyle, RR Twilley, TJ Smith, KT Whelan, JK Sullivan. 2005. Woody debris in the mangrove
forests of south Florida. Biotropica 37: 9-15

1811
1812

Kreuzwieser J, Buchholz J, and Rennenberg H. 2003. Emission of methane and nitrous oxide by Australian
Krithika, mangrove ecosystems. Plant Biology 5: 423–431

1813
1814

Kreuzwieser J., Purvaja, R. and Ramesh, R. 2008. Fluxes of methane and nitrous oxide from an Indian mangrove.
Current Science 94: 218-224.

1815
1816

Kristensen, E., Bouillon, S. Dittmar, T. and Marchand, C. 1995. Organic carbon dynamics in mangrove
ecosystems: a review. Aquatic Botany 89:201-219.

DRAFT 2013 Wetlands Supplement

4.45

Chapter 4

DO NOT CITE OR QUOTE

1817
1818

Krithika, K, Purvaja, R, Ramesh, R. 2008. Fluxes of methane and nitrous oxide from an Indian mangrove.
Current Science 94: 218-224.

1819
1820
1821

La Peyre MK, Gossman B, Piazza BR. 2009. Short- and Long-Term Response of Deteriorating Brackish
Marshes and Open-Water Ponds to Sediment Enhancement by Thin-Layer Dredge Disposal. Estuaries andCoasts 32: 390-402.

1822

Landsat TM. 2009. Photogrammetric Engineering and Remote Sensing 59: 415–421.

1823
1824

Larkum, A.W.D. and West R.J. 1990 Long-term changes of seagrass meadows in Botany Bay, Australia.
Aquatic Botany 37: 55-70.

1825
1826
1827

Latimer J.S. and Rego S.A. 2010. Empirical relationship between eelgrass extent and predicted watershedderived nitrogen loading for shallow New England estuaries. Estuarine, Coastal and Shelf Science 90: 231240.

1828
1829

Leendertse P.C., Rozema J. and Andrea A. 1997. Effects of nitrogen addition on the growth of the salt marsh
grass Elymus athericus. Estuarine, Coastal and Shelf Science 3: 35-40.

1830
1831

Leonard C.A., Ahn C. and Birch D. 2010. Above- and below-ground vegetative responses to prescribed fire
regimes in a Chesapeake Bay tidal brackish marsh. Journal of Ecology and Field Biology 33: 351-361.

1832
1833

Liao B.W., Zheng D.Z. and Zheng S.F. 1998. Biomass and Productivity of Bruguiera gymnorrhiza stand. Forest
Research 4: 22-29 (in Chinese with English abstract).

1834
1835

Liikanen, A, Silvennoinen, H. Karvo, A, Rantakokko, P, Martikainen, PJ. 2009. Boreal Environment Research
14: 351-368.

1836
1837

Lin G.H. and Lin P. 1988. Study of energy in two mangrove communities, Bruguera sexangula and Kandelia
candel, in China. Acta Phytoecologica et Geobotanica Sinica, 12: 31-39. (in Chinese with English abstract).

1838
1839

Lin P. and Lu C.Y. 1990. Biomass and productivity of Bruguera sexangula mangrove forest in Hainan Island,
China. Journal of Xiamen University (Natural Science) 29: 209-213 (In Chinese with English abstract)

1840
1841
1842

Lindau, CW, Delaune, RD. 1991. Dinitrogen and nitrous-oxide emission and entrapment in Spartina alterniflora
salt marsh soils following addition of N-15 labelled ammonium and nitrate. Estuarine Coastal and Shelf
Science 32: 161-172.

1843
1844
1845

Llewellyn C and La Peyre M. 2011. Evaluating Ecological Equivalence of Created Marshes: Comparing
Structural Indicators with Stable Isotope Indicators of Blue Crab Trophic Support. Estuaries and Coasts 34:
172-184.

1846
1847

Loveland D.G. and Ungar I.A. 1983. The effect of nitrogen fertilization on the production of halophytes in an
inland salt marsh. American Midland Naturalist 109: 346-354.

1848

Lovelock, CE, Ruess, RW, Feller, IC. CO2 efflux from cleared mangrove peat. PLOS One 6: 1-4.

1849
1850

Martin S.R., Onuf C.P.and Dunton K.H. 2008. Assessment of propeller and off-road vehicle scarring in seagrassbeds and wind-tidal flats of the southwestern Gulf of Mexico. Botanica Marina 51: 79–91.

1851
1852

McGlathery, KJ, Reynolds, LK, Cole, LW, Orth, RJ, Marion, SR, Schwarzschild, A. 2012. Recovery trajectories
during state change from bare sediment to eelgrass dominance. Marine Ecology Progress Series 448: 209-221.

1853
1854

McKee, K.L., and I.A. Mendelssohn. 1988. Spartina alterniflora dieback in Louisiana: Time-course investigationof soil waterlogging effects. Journal of Ecology 76: 509–521.

1855
1856

Mesléard F., Lepart J., Grillas P. and Mauchamp A. 1991. Effects of seasonal flooding and grazing on thevegetation of former ricefields in the Rhône delta (Southern France). Plant Ecology 145:101-114

1857
1858
1859
1860

Mitchell L.R., Gabrey S., Marra P.P. and Erwin R.M. 2006. Impacts of marsh management on coastal-marsh
bird habitats. In R. Greenberg, J. Malonado and S. Droege (Eds.), Terrestrial Vertebrates of Tidal Marshes:
Evolution, Ecology, and Conservation; Studies in Avian Biology (No.32). Cooper Ornithological Society. p.
155-175.

1861
1862

Morgan, P. A., and F. T. Short. 2002. Using functional trajectories to track constructed salt marsh developmentin the Great Bay Estuary, Maine/New Hampshire, USA. Restoration Ecology 10:461–473.

1863
1864
1865

Moseman-Valtierra S., Gonzalez R., Kroeger K., Tang J., Chun W., Crusius J., Br atton J., Green A. and
Shelton J. 2011. Short-term nitrogen additions can shift a coastal wetland from a sink to a source ofN2O. Atmospheric Environment 45: 4390-4397.

1866
1867

Muñoz-Hincapié, M., Morell, J.M., Corredor, J.E. (2002). Increase of nitrous oxide flux to the atmosphere upon
nitrogen addition to red mangroves sediments. Marine Pollution Bulletin 44: 992–996.

4.46

DRAFT 2013 Wetlands Supplement

DO NOT CITE OR QUOTE

Chapter 4

1868
1869
1870
1871

Neves, JP, Ferreira, Simoes, MP, Gazarini, LC. 2007. Primary production and nutrient content in two salt
marsh species, Atriplex portulacoides L. and Limoniastrum monopetalum L. in southern Portugal.
Estuaries and Coasts 30: 459-468.

1872
1873

Olsen Y.S., Dausse A., Garbutt A., Ford H., Thoman, D.N. and Jones, D.L. 2011. Cattle grazing drives nitrogenand carbon cycling in a temperate salt marsh. Soil Biology and Biochemistry 43:531-541.

1874
1875

Onuf C.P., 1994. Seagrasses, dredging and light in Laguna Madre, Texas, USA. Estuarine Coastal and Shelf
Science 39: 75–91.

1876
1877

Owens A.B., Proffitt C.E. and Grace J.B. 2007. Prescribed fire and cutting as tools for reducing woody plant
succession in a created salt marsh. Wetlands Ecology and Management 15: 405-416.

1878
1879
1880

Pedersen, MF, Duarte, CM, Cebrian, J. 1997. Rates of changes in organic matter and nutrient stocks during
seagrass Cymodocea nodosa colonization and stand development. Marine Ecology Progress Series 159: 2936.

1881
1882

Penn,N., 1981. The environmental consequences and management of coral sand dredging from seagrass beds in
the Suva region, Fiji Islands. Bulletin of Marine Science 31:814-824.

1883
1884

Pennings S.C., Stanton L.E. and Stephen Brewer J. 2002. Nutrient effects on the composition of salt marsh plantcommunities along the southern Atlantic and Gulf coasts of the United States. Estuaries 25: 1164–1173.

1885
1886

Perillo G.M.E., Wolanski E., Cahoon D.R., Brinson M.M. 2009. Coastal Wetlands: An Integrated Ecosystem
Approach. Elsevier, Amsterdam, 941 pp.

1887
1888
1889

Poeplau, C., Axel, D., Vesterdal, L., Leifeld, J., Van Wesemael, B,. Schumacher, J. and Gensior, A. 2011.
Temporal dynamics of soil organic carbon after land-use change in the temperate zone – carbon response
functions as a model approach. Global Change Biology 17:2415-2427.

1890
1891

Poffenbarger, H.J, Needelman, B.A, and Megonigal, J.P. (2011). Salinity influence on methane emissions fromtidal marshes. Wetlands 31(5):831-842.

1892
1893

Pozo, J. and Colino, R. 1992. Decomposition processes of Spartina maritima in a salt marsh of the BasqueCountry. Hydrobiologia 231:165-175.

1894
1895

Purvaja R. and Ramesh R. 2001. Natural and anthropogenic methane emission from coastal wetlands of South
India. Environmental Management 27: 547-557.

1896
1897

Rajendran N. and Kathiresan K. 1996. Effect of effluent from a shrimp pond on shoot biomass of mangrove
seedlings. Aquaculture Research 27: 745-747.

1898
1899

Ramesh, R., Purvaja, G. R., Parashar, D. C., Gupta, P. K., Mitra, A.P., 2011. Anthropogenic Forcing on Methane
Efflux from Polluted Wetlands (Adyar River) of Madras City, India. Ambio 6: 369-374.

1900
1901

Ramos e Silva, CA, Oliveira SR, Rȇgo RDP, Mozeto AA. 2007. Dynamics of phosphorus and nitrogen throughlitter fall and decomposition in a tropical mangrove forest. Marine Environmental Research 64: 425-534.

1902
1903
1904

Reddy, K.R. and Patrick, W.H., Jr. (1975). Effect of alternate aerobic and anaerobic conditions on redox
potential, organic matter decomposition and nitrogen loss in a flooded soil. Soil Biology Biochemistry 7:8794.

1905
1906

Ren H., Chen H., Li Z.A., Han W.D. 2009. Biomass accumulation and carbon storage of four different aged
Sonneratia apetala plantations in Southern China. Plant and Soil 327:279-291.

1907
1908

Robertson A.I. and Daniel P.A. 1989. Decomposition and the annual flux of detritus from fallen timber intropical mangrove forests. Limnology and Oceanography 34: 640-646.

1909
1910

Setia, R., Marschner, P., Baldock, J., Chittleborough, D. and Verma, V. 2011. Relationships between carbon
dioxide emission and soil properties in salt-affected landscapes. Soil Biology and Biochemistry 43:667-674.

1911
1912

Silva CAR, Mozeto AA, Ovalle ARC. 1998. Distribution and fluxes as macrodetritus of phosphorus in red
mangroves, Sepetiba Bay, Brazil. Mangroves and Salt Marshes 2:37-42.

1913
1914

Sotomayor, D, Corredor JE, Morell, JM. 1994. Methane flux from sediments along the southwestern coast of
Puerto-Rico. Estuaries 140-147.

1915
1916

Steward J.S.., and Green W.C.G. 2007. Setting load limits for nutrients and suspended solids based upon
seagrass depth-limit targets. Estuaries and Coasts 30: 657–670

DRAFT 2013 Wetlands Supplement

4.47

Chapter 4

DO NOT CITE OR QUOTE

1917
1918

Strauss E.A. and Lamberti G.A. 2000. Regulation of nitrification in aquatic sediments by organic carbon.
Limnology and Oceanography 45: 1854-1859.

1919
1920

Sukardjo, S. 1993. The present status of the mangrove forests in the northern coast of West Java with specialreference to the recent utilization. Southeast Asian Studies 31: 141-157.

1921
1922

Sun S, Cai Y, Tian X. 2003. Salt marsh vegetation change after a short-term tidal restriction in the Changjiang
Estuary. Wetlands 23:257–66.

1923
1924
1925

Thiery A. and Puente L. 2002. Crustacean assemblage and environmental characteristics of a man-made solar
saltwork in southern France, with emphasis on anostracan (Branchiopoda) population dynamics.
Hydrobiologia 486: 191-200.

1926
1927
1928

Tong, C, Wang, WQ, Zeng, CS, Marrs, R. 2010. Methane (CH(4)) emission from a tidal marsh in the Min Riverestuary, southeast China. Journal of Environmental Science and Health Part a-Toxic/Hazardous Substances &Environmental Engineering 45: 506-516.

1929
1930

Twilley R.W., Lugo A.E., Patterson-Zucca C. 1986. Litter Production and Turnover in Basin Mangrove Forests
in Southwest Florida. Ecology 67: 670-683

1931
1932

Twilley R.R, Pozo M., Garcia VH, Rivera-Monroy VH, Zambrano R, Bodero A. 1997. Litter dynamics inriverine mangrove forests in the Guayas River estuary, Ecuador. Oecologia 111: 109-122.

1933

Vaudrey, JMP, Kemer, JN, Branco, BF, Short FT. 2010. Aquatic Botany 93: 237-243.

1934
1935
1936

Walters, BB, Ronnback, P, Kovacs, JM, Crona, B, Hussain, SA, Badola, R, Primavera, JH, Barbier, E, DahdouhGuebas, F. 2008. Ethnobiology, socio-economics and management of mangrove forests: A review. Aquatic
Botany 89: 220-236.

1937
1938
1939

Wang, DQ, Chen, ZL, Wang, J, Xu, SY, Yang, HX, Chen, H, Yang, LY, Hu, L. 2007. Summer-timedenitrification and nitrous oxide exchange in the intertidal zone of the Yangtze Estuary. Estuarine Coastal
and Shelf Science 73: 43-53.

1940
1941
1942

Wang, J., Dodla, S., DeLaune R., and Cook, R. L. (2010). Organic carbon transformation along a salinity
gradient in Louisiana wetland soils. 2010 19th World Congress of Soil Science, Soil Solutions for a
Changing World 1 – 6 August 2010, Brisbane, Australia.

1943
1944
1945

West, RC. 1977. Tidal Salt-Marsh and Mangal Formations of Middle and South America
Ecosystems of the World 1: Wet Coastal Ecosystems, Elsevier Scientific Publishing Co., New York 1977, p.
193-213. 16 fig, 1 tab, 92 ref.

1946
1947
1948

Windham L. 2001. Comparison of biomass production and decomposition between Phragmites australis(common reed) and Spartina patens (salt hay grass) in brackish tidal marshes of New Jersey, USA. Wetlands
21: 179-188.

1949
1950

Yang D, and Yang C. 2009 Detection of seagrass distribution changes from 1991 to 2006 in Xincun Bay,
Hainan, with satellite remote sensing. Sensors 2: 830-844.

1951
1952

Yu, O. and Chmura, G.L. 2010. Soil carbon is maintained under grazing in a St. Lawrence Estuary tidal marsh.
Environmental Conservation 36: 312-320.

1953
1954

Zainal A.J.M., Dalby D.H. and Robinson, I.S., 1993. Monitoring marine ecological changes on the east coast of
Bahrain with

1955
1956

Zhang, J.P. and others. 2012. Estimating change in sedimentary organic carbon content during mangrove
restoration in southern China using carbon isotopic measurements. Pedosphere 22:58-66.

1957
1958

Zhang Y., Ding W., Cai Z., Valerie P., and Han F. 2010. Response of methane emission to invasion of Spartina
alterniflora and exogenous N deposition in the coastal salt marsh. Atmospheric Environment 44: 4588-4594

1959
1960
1961
1962

4.48

DRAFT 2013 Wetlands Supplement