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Production in peatlands: comparing ecosystem services of different land
use options for intensive dairy farms
Weier Liu1, Christian Fritz2,1, Jasper van Belle3, Sanderine Nonhebel1
1 Integrated Research on Energy, Environment and Society (IREES), University of Groningen
2 Institute for Water and Wetland Research, Radboud University Nijmegen
3 Van Hall Larenstein University of Applied Sciences
Graphical abstract
Electronic copy available at: https://ssrn.com/abstract=4122062
Highlight
Six theoretical productive peatland systems were designed under a gradient of water level.
High water level leads to co-benefit of carbon-water-biodiversity related services.
Market value of paludiculture production is not comparable with Dutch dairy production.
Organic dairy farming does not lead to higher carbon-water-biodiversity related services.
Sustainable peatland use needs fundamental management change and financial support.
Electronic copy available at: https://ssrn.com/abstract=4122062
1Production in peatlands: comparing ecosystem services of different land
2use options for intensive dairy farms
3 Weier Liu1, Christian Fritz2,1, Jasper van Belle3, Sanderine Nonhebel1
41 Integrated Research on Energy, Environment and Society (IREES), University of Groningen
52 Institute for Water and Wetland Research, Radboud University Nijmegen
63 Van Hall Larenstein University of Applied Sciences
7Graphical abstract
8
Electronic copy available at: https://ssrn.com/abstract=4122062
9Highlight
10 Six theoretical productive peatland systems were designed under a gradient of water level.
11 High water level leads to co-benefit of carbon-water-biodiversity related services.
12 Market value of paludiculture production is not comparable with Dutch dairy production.
13 Organic dairy farming does not lead to higher carbon-water-biodiversity related services.
14 Sustainable peatland use needs fundamental management change and financial support.
15 Abstract
16 The majority of Dutch peatlands are drained and used intensively as grasslands for dairy farming. This
17 delivers high productivity but causes severe damage to the provisioning of ecosystem services. Peatland
18 rewetting is the best way to reverse the damage, but high water levels do not fit with intensive dairy
19 production. Paludiculture, defined as crop production under wet conditions, provides viable land use
20 alternatives, but these alternatives are rarely compared to conventional drainage-based systems. Here,
21 we compare ecosystem services of six theoretical production systems on peatland following a gradient
22 of low, medium, and high water levels. This includes conventional and organic drainage-based dairy
23 farming, low-input grasslands for grazing and mowing, and high-input paludiculture systems with reed
24 and Sphagnum cultivation. For each production system, a theoretical 1 ha unit was designed using data
25 from literature. Four aspects of ecosystem services were quantified and monetized, including
26 agricultural productivity, reduction of greenhouse gas emissions, water storage, and biodiversity
27 potential. Results show that drainage-based dairy farming systems only support high milk production
28 without any of the other ecosystem services included, even with organic farming practices. Biomass
29 producing paludiculture systems have high ecosystem services value, but do not lead to production
30 values comparable to the present dairy farming. Capitalizing GHG reduction and other ecosystem
31 services from peatland rewetting with carbon credits or other payment schemes would close this
32 production and income gap. However, standard practice to monetize provision of ecosystem service is
33 currently unavailable. Sustainable use of peatlands urges more fundamental changes in land and water
34 management along with the financial and policy support required.
35 Keyword
36 Peatland, drainage, dairy farming, paludiculture, Sphagnum farming, ecosystem services
37 1 Introduction
38 Peatlands are valuable ecosystems providing a wide range of goods and services to human society.
39 Pristine peatlands provide climate regulation services as the largest natural terrestrial carbon store with
40 global total C pool of over 600 Gt C (Leifeld et al., 2019; Yu et al., 2010); water regulation services
41 regarding water retention, quality as well as flood and drought mitigation (Joosten and Clarke, 2002;
42 Parish et al., 2008); and supporting services of peat soil formation and biodiversity of specialized
43 endemic species (Minayeva et al., 2017; Parish et al., 2008). These important ecosystem services related
44 to carbon, water and biodiversity are characterized and supported by the unique function of natural
45 peatlands that features high water level and moisture content (Minayeva et al., 2017).
46 Peatlands also provide substantial provisioning services of food and fiber in the form of intensive
47 agriculture. The majority of peatlands in The Netherlands are drained for grassland use (Joosten and
48 Clarke, 2002). However, such services rely heavily on intensive drainage, causing severe degradation and
49 diminishing the above-mentioned ecosystem services. Intensively drained peat meadows are a
Electronic copy available at: https://ssrn.com/abstract=4122062
50 substantial source of greenhouse gas (GHG) emissions (Schrier-Uijl et al., 2014; Tiemeyer et al., 2016). In
51 the Netherlands, peatlands make up 15% of the total agricultural land but (disproportionally) emit 35%
52 of all GHG emissions from the agricultural sector (Greifswald Mire Centre, 2020), which is associated
53 with soil subsidence and subsequently increased flood risk and damage to infrastructure (Erkens et al.,
54 2016). Intensive agriculture on peatlands is also one of the major causes of deteriorating water quality,
55 eutrophication and biodiversity losses (Bonn et al., 2014; Tanneberger et al., 2021).
56 Water level is an important driver of the provisioning of ecosystem services in peatlands. Rewetting
57 peatland to its natural hydrology is the best way to mitigate or even reverse the degradation, leading to
58 long-term benefits of GHG emissions reduction (Günther et al., 2020), flood and drought mitigation
59 (Ahmad et al., 2021, 2020), and biodiversity restoration (Strobl et al., 2020; Tuittila et al., 2000).
60 However, current agricultural land uses cannot be easily combined with high water levels (Tanneberger
61 et al., 2021), while the large area of agriculturally used peatlands cannot be taken out of production and
62 rewetted solely on nature restoration purposes. Meanwhile, evidence from peatland ecological
63 monitoring studies proved that the climate benefit from raising water level in agricultural peatlands can
64 be achieved without necessarily halting the productive use (Evans et al., 2021). ‘Paludiculture’, defined
65 as productive land use of peatlands under rewetted condition (Wichtmann et al., 2016), presents a wide
66 range of alternative production options at a gradient of higher water levels (Tanneberger et al., 2021)
67 that could achieve these benefits. A variety of wet crops were identified, with management guidelines
68 developed and farm-level feasibility evaluated (Geurts et al., 2019; Wichmann, 2017; Wichmann et al.,
69 2020). On the other hand, agricultural sciences put great effort on the optimization of conventional
70 dairy production systems which would lead to the continuation of the intensive drainage. Research on
71 improving sustainability of dairy farming often focuses on organic farming practices with regard to
72 optimizing feed and manure management (Baldini et al., 2018; Van Middelaar et al., 2014), but
73 disregards peatland degradation and associated effects on soil carbon dynamics, water, and biodiversity.
74 Integration of existing knowledge on peatland uses from both ecological and agricultural perspectives is
75 urgently needed to support a transition to sustainable peatland use. However, drainage-based dairy
76 systems and the paludiculture alternatives are rarely compared, despite availability of field-based
77 research. Direct comparison of both types of system is difficult, because field experiments are carried
78 out at different locations, under different groundwater fluctuation and management regimes, and at
79 different time scales. Setting up new field experiment to make direct comparisons is time and money-
80 consuming. Effects of peatland rewetting projects need to be evaluated by continuous monitoring
81 covering at least two to three years when the vegetation succession has stabilized (Günther et al., 2017).
82 Hypothetical land use system analysis, on the other hand, has the potential to provide evidence on the
83 environmental impacts from different systems without need of large investment. For example, a recent
84 study from (de Jong et al., 2021) compared emissions and revenues on a 1 ha unit of Dutch peat soil
85 used for dairy production and cattail paludiculture. Such analyses can provide insights on the differences
86 between systems and the causes by adopting field-based data when necessary, without need of a site-
87 specific ‘true-value’. However, for most land use options no comparisons are available.
88 Here, the question addressed is how land use options at different groundwater levels perform on
89 production, carbon, water, and biodiversity related ecosystem services. To answer this question, we
90 defined theoretical peatland production systems under a gradient of groundwater levels, starting from
91 drainage-based dairy farming, with low-intensity grassland systems at medium water levels and high-
92 intensity paludiculture at high water levels as alternatives. The analysis focuses on the most important
93 and well-studied ecosystem services, which includes agricultural production, GHG emission reduction,
94 water storage, and biodiversity value.
Electronic copy available at: https://ssrn.com/abstract=4122062
95 2 Methods
96 2.1 System design
97 We designed six production system on peat soils at three ranges of groundwater levels based on the
98 summary of land use options on different ranges of annual mean water level from Tanneberger et al.
99 (2021). Three drainage categories were define: 50 cm below surface or dryer supports conventional
100 drainage-based dairy farming systems. 50 to 10 cm below surface supports low-input production on
101 grasslands where biomass from spontaneously established vegetation is harvested. High water level
102 around or above surface level supports high-input paludiculture of deliberately established and selected
103 wetland crops. These categories were defined to represent all the typical land use options not only in
104 the Netherlands but also across western Europe.
105 Two systems were designed in each of the three categories that resulted in total of six production
106 systems, on a functional unit of 1 ha utilized peatland. Existing land use systems from field trails and
107 pilot studies were adopted and conceptualized into theoretical systems to represent each of the
108 productive land uses. Vegetation cover and farm management were the main components of the system
109 design to serve as the basis of the ecosystem services quantification (Table 1). Vegetation cover was at
110 the center of the of the system design due to its role as bioindication for environmental conditions (e.g.
111 groundwater regime, nutrient availability) and carbon exchanges (Couwenberg et al., 2011; W. Liu et al.,
112 2020). More specifically, main crop cover was decided to indicate production type. Natural reference
113 vegetation type was selected from the Dutch vegetation classification system (Schaminee et al., 1995),
114 as it is interrelated with groundwater fluctuation and could specify the vegetation composition (Everts
115 and de Vries, 1991; Schaminée et al., 2012) (Table S1). Besides vegetation cover, assumptions on farm
116 structure were made to specify the production function of the systems. Soil properties, structure of
117 animal production, fuel consumption during management, and the final productivity of the system were
118 assumed based on literature and online databases.
119 2.1.1 Drainage-based dairy farming – Conventional / Organic
120 The first system is the drainage-based dairy farming system. The Conventional system is the business-as-
121 usual option in the Netherlands (de Jong et al., 2021; Joosten, 2010), and was proven to emit large
122 amount of CO2 through peat oxidation (Tiemeyer et al., 2020, 2016) and CH4 from ruminant cows
123 (Olesen et al., 2006). A low annual mean groundwater level of -50 cm and high nutrient input via
124 artificial and manure fertilization supports species poor grassland dominated by perennial ryegrass as
125 main crop. A share of the land is used as arable land to produce maize as feed for the cows. The
126 resulting high grass yield of over 10 t DM yr-1 (Weideveld et al., 2021) allows intensive dairy production
127 with high stock density and milk productivity.
128 The second system is the Organic dairy farming system, which is applied on the same vegetation cover
129 as Conventional system with deep drainage and monocultural perennial grassland cover. It is assumed
130 to be free of artificial fertilization, have more grassland and less arable land and allow more grazing
131 hours for the cows. Grass and crop yield is lower than in the Conventional system (Olesen et al., 2006;
132 Thomassen et al., 2008). Lower number of cows and milk productivity is supported as a consequence.
133 For both conventional and organic dairy farming, detailed data on farm structure and field management
134 is retrieved from an online database agrimatie (Wageningen Economic Research, 2020). The amount of
135 manure excretion and application as well as artificial fertilizer use were adopted at the highest level
136 from the Dutch regulation (RVO, 2021a, 2021b). Diesel consumption on farm was adopted from
137 (Thomassen et al., 2008).
Electronic copy available at: https://ssrn.com/abstract=4122062
138 2.1.2 Low-intensity grassland – Grazing / Mowing
139 Low-intensity grassland systems involve two different biomass uses on grasslands under extensive
140 management. One is a grazing system that aims at producing milk, the other is a mowing system that
141 produces biomass as bioenergy feedstock for direct combustion. Both are not yet widely applied as
142 farming practices, but sufficient case studies in western Europe exist (Wichtmann et al., 2016) to base
143 the assumptions on. Both systems do not have the intensive water management required to maintain
144 deep or very high water levels. Input of extra nutrients is also absent. Grazing use of the grasslands
145 requires shallow-drained conditions with annual mean water level at around -30 cm to allow animal
146 activities and avoid water-borne diseases. Vegetation of grazed nutrient rich grassland type develops
147 under such water level and management regimes, with presence of ryegrass (Lolium perenne) as high
148 quality fodder, bentgrass (Agrostis spp.) and fescues (Festuca spp.) species with lower fodder quality.
149 The overall lower energy content of the fodder leads to lower number of cows, while the milk
150 productivity was assumed to be at the same level with the Organic system according to the case study of
151 (Bakker and Ter Heerdt, 2005). No fertilization is allowed, with only manure excretion as nitrogen input
152 also at the same amount as the Organic system. Diesel consumption was assumed to be proportional to
153 Organic based on animal density.
154 Without needs for animal production, higher water level at -20 cm is allowed on the Mowing system,
155 leading to a vegetation cover of marshy hay meadows. Mixed folder is produced with reed canary grass
156 dominance and presence of sedges (Carex spp.), rushes (Juncus spp.) and marsh-marigold (Caltha
157 palustris). The presence of rushes were frequently observed on rewetted agricultural peatlands (Lamers
158 et al., 2015), which are ‘shunt species’ that have aerenchyma that would provide an extra pathway for
159 CH4 effluxes (Couwenberg and Fritz, 2012). This system involves no grazing animal or fertilization.
160 Biomass yield of 6 t DM ha-1 was adopted from case studies (Wichtmann et al., 2016). Diesel
161 consumption was calculated based on the average fuel consumption of mowing and transporting in L h-1
162 and the operation time in h ha-1 (Wichmann, 2017).
163 2.1.3 High-intensity paludiculture – Reed / Sphagnum
164 High-intensity paludiculture systems aim to produce wetland crops since the very high groundwater
165 level do not allow animal related production. Reed and Sphagnum mosses were selected as
166 representative crops as they have been proven viable according to pilot studies (Geurts and Fritz, 2018;
167 Wichmann et al., 2020), and the products have demonstrated economic potential (Müller and Glatzel,
168 2021; Wichmann, 2017). The Reed system needs high water level at 20 cm above surface for best crop
169 performance. The most profitable product was selected, which is reed bundles for roof thatching at a
170 yield of 500 bundles ha-1 (approximately 8 t DM ha-1) (Wichmann, 2017). Growth of peat mosses in the
171 Sphagnum system requires water levels close to surface at an annual mean of -10 cm. The Sphagnum
172 mosses are harvested once in five years, with an annual average yield of 110.3 m3 ha-1 yr-1 in volume
173 (approximately 3.2 t DM ha-1 yr-1) as horticulture growing media (Wichmann et al., 2020). Both systems
174 do not receive any extra nutrient input. However, the Reed system needs higher nutrient levels from soil
175 or surface water to support the high biomass yield (Geurts et al., 2020). The Sphagnum system requires
176 removal of the nutrient-rich topsoil for the establish of Sphagnum mosses (Huth et al., 2021). Diesel
177 consumption was calculated and divided into annual averages based on the time and fuel consumption
178 factors for harvesting and on-farm transportation provided by (Wichmann, 2017) and (Wichmann et al.,
179 2020).
180 Table 1. Main assumptions for the design of the six production systems in three categories.
Assumption
Drainage-based Dairy
Farming
Low-Intensity Grassland
High-Intensity Paludiculture
Electronic copy available at: https://ssrn.com/abstract=4122062
Conventional
Organic
Grazing
Mowing
Reed
Sphagnum
Annual mean
water level
(cm above
surface)
-50
-50
-30
-20
20
-10
Vegetation
cover
(main crop)
Species poor grassland
(perennial ryegrass)
Grazed
nutrient-rich
grassland
(mixed fodder
with perennial
ryegrass)
Marshy hay
meadow
(mixed
fodder with
reed canary
grass)
Reed
(Phragmites
australis)
Mire
vegetation
(Sphagnum
mosses)
Stocking
density
(animal ha-1)
1.6
1.0
0.6
0
0
0
Share of
grassland
(%)
87
93
100
100
0
0
Manure
excretion
(kg N per
animal)
124
104
104
0
0
0
Artificial
fertilizer
(kg N ha-1)
113
0
0
0
0
0
Manure
application
(kg N ha-1)
167
169
0
0
0
0
Diesel
consumption
(L ha-1)
104
96
57
64
36
229
Yield
(ha-1)
13.2 t Milk
6.2 t Milk
3.6 t Milk
6 t DM
500 bundle
110.3 m3
181
182 2.2 Ecosystem services quantification and valuation
183 2.2.1 GHG emissions
184 GHG emission was calculated on farm scale. Only direct gaseous emissions onsite were included.
185 Emission sources were divided into field emission and farmyard emission.
186 Field emissions
187 Field emission covers all the GHG emissions from the plant–soil interface, which includes CO2 fluxes
188 from net ecosystem exchange (NEE) (Veenendaal et al., 2007), CH4 effluxes via diffusion and ebullition
189 (Couwenberg and Fritz, 2012), and direct N2O emission from peat soil mineralization. The most
190 important driving factors are groundwater level and land cover (Tiemeyer et al., 2020). Peatland field
191 emissions are rarely allocated into agricultural system analysis, but necessary for a complete
192 representation of the environmental impacts from productive peatlands. Earlier studies have included
193 soil carbon change into life cycle assessments of dairy farms on mineral soils, which resulted in lower
194 GHG emissions due to carbon sequestration (Knudsen et al., 2019; Salvador et al., 2017). However,
195 direct measurements of carbon balance on drained peat soils often report strong carbon sources
Electronic copy available at: https://ssrn.com/abstract=4122062
196 (Schrier-Uijl et al., 2014; Weideveld et al., 2021). Therefore, peatland-specific methodology should be
197 incorporated into this system analysis. Currently, the best estimate available for peat soil emissions at
198 project level is the Greenhouse Gas Emission Set Type (GEST) approach (Ekardt et al., 2020). This
199 approach provides CO2 and CH4 emission factors to vegetation types based on meta-analysis of yearly
200 fluxes measurements in relation to groundwater level and vegetation cover (Couwenberg et al., 2011;
201 van Belle and Elferink, 2020). GEST types were selected based on the vegetation cover assumed for each
202 production system (Table 1) and the corresponding emission factors were assigned (Table 2). Field N2O
203 emission factor was adopted from the Dutch national inventory (Lagerwerf et al., 2019) for drained
204 peatlands, from the IPCC Tier 1 emission factors (IPCC, 2013) for the shallow-drained grasslands and
205 from a meta-analysis (Tiemeyer et al., 2020) for rewetted peatlands.
206 Farmyard emissions
207 Farmyard emission covers all the direct emissions from production-related sources including animal,
208 manure management, and energy use, which are determined by farm structure and management as the
209 driving factors. CO2 from animal respiration per cattle was assumed to be 4.6 kg CO2-C d-1 (Felber et al.,
210 2016). CH4 and N2O emission factors were taken from the Dutch national inventory (Lagerwerf et al.,
211 2019; Ruyssenaars et al., 2020). Annual CH4 emission factor for enteric fermentation is 134.6 kg CH4 per
212 dairy cattle per year. Annual emission factors related to manure management, including handling and
213 storage of manure, are 38.8 kg CH4 per dairy cattle and 0.002 kg N2O per kg manure-N excretion. N2O
214 emissions from fertilize use are 0.005 and 0.013 kg N2O-N per kg N applied manure and inorganic N
215 fertilizers, respectively. Emissions from energy uses only included onsite emissions from direct fuel
216 consumption. Off-site emissions from electricity generation and indirect emissions from embedded
217 energy uses of materials were not considered. Emission factor of diesel was 3.23 kg CO2-eq /L.
218 Monetary value
219 GHG emission reduction was accounted as carbon credit. A carbon price of EUR 75 t-1 CO2-eq was
220 adopted from the Dutch Green Deal National Carbon Market (www.nationaleco2markt.nl), where
221 carbon credits from emission reduction in peat meadow areas were successfully sold.
222 Table 2. Emission factors and indicators related to the vegetation cover of the system.
Drainage-based Dairy
Farming
Low-Intensity Grassland
High-Intensity Paludiculture
Conventional
Organic
Grazing
Mowing
Reed
Sphagnum
Natural
reference
vegetation
type
Species poor grassland
(Poa tricialis-Lolium
perenne)
Grazed
nutrient-rich
grassland
(e.g. Lolio-
Cynosurion)
Marshy hay
meadow
(e.g.
Calthion
palustris)
Reed
(Phragmition
australis)
Mire vegetation
(e.g.
Scheuchzerietea)
GEST type[1]
G1 Dry to
moderately
moist
grassland
and arable
land
G1 Dry to
moderately
moist
grassland
and arable
land
G2 Moist
grassland
G4s Very
moist
grassland
with shunt
species
U18 Very
wet
Phragmites
reeds
U13 Wet
Sphagnum lawn
CO2
Emission
factor
(t ha-1 yr-1)
32.77
30.10
19.37
6.45
-12.38
-3.02
Electronic copy available at: https://ssrn.com/abstract=4122062
CH4
Emission
factor
(t CO2-eq
ha-1 yr-1)
0.002
-0.02
0.01
2.1
12.44
5.25
N2O
Emission
factor
(t CO2-eq
ha-1 yr-1)
2.19
2.19
0.75
0.005
0.005
0.005
Annual
maximum
water level
(cm above
surface)
-20[2]
-20[2]
2[3]
10[3]
30[4]
5[3]
Flood
tolerance
(days)
14[5]
14[5]
14[5]
49[6]
Permanent
(365 days
per year)[4]
105 (3.5
months)[7]
223 [1] (van Belle and Elferink, 2020); [2] (Hennekens et al., 2010); [3] (Everts and de Vries, 1991); [4] (Geurts
224 and Fritz, 2018); [5] (McFarlane et al., 2003); [6] (Wrobel et al., 2009); [7] (Rochefort et al., 2002).
225 2.2.2 Water storage
226 Potential water storage of the production systems was determined by water table level and flood
227 tolerance of the vegetation. Water could be stored both below surface as soil pore water and above
228 ground when the system is inundated, with the risk of damaging the productivity of the crops.
229 Below surface water storage
230 Efficiency of below surface water storage was indicated by soil specific yield ( ), which measures the
𝑆
𝑌
231 differences between total porosity and volumetric water content. It was calculated according to its
232 correlation with peat bulk density ( , ) (H. Liu et al., 2020). Bulk density of the
𝐵𝐷
𝑆
𝑌
=
0.003
×
𝐵𝐷
‒
1.4
233 peat soil was adopted from (Lennartz and Liu, 2019; Liu and Lennartz, 2019) according to its correlation
234 to the land use type and the level of degradation. Intensive agricultural peat soil under deep drainage
235 from the drainage-based dairy systems is assumed to be highly degraded with high bulk density
236 (Weideveld et al., 2021) at 0.6 g cm-3. Higher water level in the low-intensity grassland systems was
237 assumed to improve soil conditions and lower bulk density (Ahmad et al., 2020), therefore assumed at
238 0.3 g cm-3. With peat-forming vegetation cover of reed and Sphagnum mosses, high-intensity
239 paludiculture systems were assumed to have the lowest bulk density at 0.2 g cm-3. Annual mean water
240 level (Table 1) represents the volume of subsurface space that could be used for soil water storage. The
241 total below surface water storage potential was therefore calculated as
𝑆
𝑌
(
242 .
𝑐𝑚
3
𝑤𝑎𝑡𝑒𝑟
𝑐𝑚
3
𝑠𝑜𝑖𝑙)
×
𝑊𝐿
𝑚𝑒𝑎𝑛
(
𝑐𝑚 𝑏𝑒𝑙𝑜𝑤 𝑠𝑢𝑟𝑓𝑎𝑐𝑒
)
×
1
ℎ𝑎
243 Above surface water storage
244 Flood tolerance of the production system was considered as the water retention potential, including the
245 amount of water and the duration of inundation. The amount of water was calculated with the
246 maximum water level above surface ( ). Maximum water level was indicated by the
𝑊𝐿
𝑚𝑎𝑥
×
1
ℎ𝑎
247 vegetation cover of the system according to meta-analysis of past measurement records (Everts and de
248 Vries, 1991) and a vegetation bioindication database for the Netherlands (Hennekens et al., 2010;
249 Schaminée et al., 2012) (Table 2, S2). Duration of inundation was represented by the flood tolerance of
Electronic copy available at: https://ssrn.com/abstract=4122062
250 the main crop of the production system retrieved from literature, indicating the vulnerability of the
251 crops against inundation during growing seasons (McFarlane et al., 2003; Rochefort et al., 2002; Wrobel
252 et al., 2009).
253 Monetary value
254 Water retention was accounted with avoided damage approach. Under a hypothetical heavy
255 precipitation event that happens once per year, water stored in the production system was assumed to
256 be able to avoid overflow that would cause damages with a price of EUR 3 m-3 water, according to an
257 analysis from the Dutch water authority (Kanters et al., 2016).
258 2.2.3 Biodiversity
259 Peatland biodiversity is not likely to be quantified with a simple numeric indicator, due to difficulties of
260 covering richness and rarity of the species, considering both flora and fauna, and accounting for the
261 variations of indicators even within the same taxa (Minayeva et al., 2017). Therefore, a qualitative
262 approach was developed considering field management as the major driving factor. The effect of
263 management techniques commonly applied on peatlands was qualitatively evaluated and discussed
264 based on literature (Table S1) and determined as positive or negative. Biodiversity potential of the
265 production systems was therefore judged based on the management practices and presented as ranking
266 scores (Table 3). Monetary value of biodiversity was represented by the subsidies of maintaining a
267 certain type of natural habitat. Prices were adopted from the Dutch Subsidy system of Nature and
268 Landscape (SNL, Subsidiestelsel Natuur en Landschap, www.bij12.nl) (Table S2). In the SNL system, the
269 subsidy levels are allocated based-on the estimated management cost for maintaining a certain
270 vegetation type, which is used to reflect the monetary value of this vegetation. The natural habitat types
271 in the system were related to the production system based on the characteristic vegetation
272 communities and species (Table 3).
273 2.2.4 Production
274 Revenue was decided to be the indicator and monetary value of biomass (and the subsequent dairy
275 products) production in order to reach a comparable indication among different final products such as
276 animal products and green biomass (Table 1, S3). The market price of milk was set at EUR 367.7 and
277 500.1 t-1 Milk for conventional and organic systems (Wageningen Economic Research, 2020). Milk from
278 the low-intensity grazing system was assumed to have the same price as organic milk. Prices of biomass
279 usage were adopted from (Wichmann, 2017) at 46 euro t-1 DM for direct combustion in the low-intensity
280 mowing system, and EUR 2 bundle-1 of reed for roof thatching in the high-intensity reed system. The
281 price of Sphagnum peat as growing media is EUR 25 m-3 (Wichmann et al., 2020).
Electronic copy available at: https://ssrn.com/abstract=4122062
282 3 Results
283 3.1 GHG emissions
284
Conventional
Organic
Grazing
Mowing
Reed
Sphagnum
-20
-10
0
10
20
30
40
50
60
Field-CO2
Field-CH4
Field-N2O
Farmyard-CO2
Farmyard-CH4
Farmyard-N2O
Total emission
GHG Emissions (t CO2-eq ha-1)
285 Figure 1. GHG emissions per category and total emissions per hectare.
286 GHG emissions both per source and in total showed large differences between the systems (Fig. 1). The
287 field CO2 emissions showed the largest differences, caused by the groundwater level differences
288 between systems. Drainage-based systems emit large amount of CO2 due to peat oxidation under low
289 groundwater level, while the higher water level in low-intensity grassland systems led to less CO2
290 emission. In high-intensity paludiculture systems where water level was assumed to be close to or above
291 surface, negative CO2 emissions was achieved with higher photosynthetic CO2 uptake than emission
292 from peat oxidation. Differences in field CH4 emissions were results of the combination of different
293 water levels and vegetation covers. Low-intensity grassland systems showed CH4 emissions due to
294 higher water level and the presence of ‘shunt species’. Water saturated peat soil in high-intensity
295 paludiculture systems led to high CH4 emissions. Field N2O emissions were associated to the land use
296 cover. Drainage-based dairy systems showed N2O emission due to mineralization of soil organic carbon
297 following peat decomposition. The rewetted grassland and high-intensity paludiculture systems emitted
298 negligible N2O. The low-intensity shallow-drained grassland showed lower N2O emission than the
299 drainage-based systems but significantly higher than the wetter systems due to the rich nutrient in the
300 soil and the presence of grazing animals.
301 Farmyard emissions include emissions from dairy cows, storage and application of manure and artificial
302 fertilizer, and consumption of fossil fuel. In the systems involving dairy production (the drainage-based
303 intensive systems and the shallow-drained grazing system), majority of the emissions were from cows
304 and manure of the cows. This emission is linearly related to the number of cows. Therefore, the
305 difference between systems with respect to the farmyard emissions can be primarily explained by
306 stocking density. Conventional had higher farmyard CH4 and N2O emissions also because of the artificial
307 fertilizer application. Non-dairy producing systems (the low-intensity mowing system and high-intensity
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308 paludiculture systems) only had farmyard CO2 emissions from fuel consumption, which is associated to
309 the type of crop produced.
310 In total, emissions from non-livestock systems (the low-intensity mowing system and the high-intensity
311 paludiculture systems) were substantially lower than dairy producing systems (the drainage-based
312 intensive systems and the shallow-drained grazing system), amounting to less than a quarter of the total
313 emissions of the Conventional system (Fig. 1). This is caused by a combination of reductions of both field
314 and livestock related emissions. These sources are interrelated, since higher water level cannot support
315 the same intensity of livestock production as with deep drainage, which means that lower land use
316 intensity and less productivity have to be applied.
317 3.2 Water storage
318
Conventional
Organic
Grazing
Mowing
Reed
Sphagnum
0
200
400
600
800
1000
1200
0
50
100
150
200
250
300
350
400
Above surface
Below surface
Days of inundation
Water Storage (m3)
Days of Inundation
319 Figure 2. GHG emissions per category and total emissions per hectare.
320 Potential of water storage showed substantial differences between above and below surface and
321 between different systems (Fig. 2). Below surface water storage was determined by both soil water
322 holding capacity and the annual mean water level. Rewetted systems (the low-intensity grassland
323 system and high-intensity paludiculture systems) were assumed to have improved peat soil quality,
324 meaning lower bulk density and higher soil water holding capacity. However, the space in the soil
325 available to store water was smaller due to higher water level. Therefore, differences of below surface
326 water storage between systems were small, and the order of magnitude of the potential was in general
327 much smaller comparing to the water storage above surface.
328 Above surface water storage was determined by the maximum water level and the flood tolerance of
329 the crop. Maximum water level is associated with the vegetation type corresponding to the production
330 systems, representing the lower limit of the amount of water each system could withstand. Drainage-
331 based dairy systems with monocultural perennial ryegrass do not get inundated under normal
332 conditions. The wetter meadows with mixed grass species in the low-intensity grassland systems get
333 periodically flooded. However, the main crops perennial ryegrass and reed canary grass can only survive
334 under inundation for two and seven weeks, respectively. Therefore, the grazing activity cannot be
335 sustained under prolonged flooding. The peat moss vegetation representing the Sphagnum system can
336 also be shallowly flooded and for a longer period of time of over 100 days. On the contrary, the reed
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337 dominated system can be permanently flooded with deep water of 30 cm, providing immense potential
338 of water storage.
339 3.3 Biodiversity
340 Table 3. Qualitative scaling of biodiversity potential of the production systems based on common
341 management practices and their effects.
Production System
Management
(Effect: -, negative; +, positive)
Biodiversity Potential (Scale)
Subsidy Type
Subsidy
(euro ha-
1 yr-1 )
Conventional
Deep drainage (-); Tillage (-); Heavy fertilization
(-); Intensive grazing/mowing (-)
Very low (1)
-
0
Organic
Deep drainage (-); Tillage (-); Manure
application (-); Intensive grazing/mowing (-)
Low (2)
Open grassland (A11
Open grasland)
197.93
Grazing
Rewetting (+); No Tillage (+); Grazing manure
(-); Extensive grazing (+)
Medium to high (3.5)
Flora- and fauna- rich
grassland (N12.02
Kruiden- en faunarijk
grasland)
219.08
Mowing
Rewetting (+); No Tillage (+); No fertilization (+);
Extensive mowing (+)
High (4)
Moist meadow
(N10.02 Vochtig
hooiland)
1188.42
Reed
Rewetting (+); No Tillage (+); High nutrient load
(-); Extensive harvest (+)
Moderate (3)
Mowed reedland
(N05.02 Gemaaid
rietland)
575.98
Sphagnum
Rewetting (+); No Tillage (+); No fertilization (+);
Topsoil removal (+); Extensive mowing (+);
Species re-introduction (+)
Very high (5)
Peat moss floating
mat (N06.02 Trilveen)
2082.26
342
343 Biodiversity potential was qualitatively evaluated based on the management practices and their impact
344 on biodiversity (Table S2) that were commonly applied on the production systems (Table 3). Drainage-
345 based dairy systems are characterized by deep drainage, tillage and intensive grazing or mowing,
346 representing the lowest biodiversity. The Organic system does not use artificial fertilizer and pesticide,
347 which primarily reduces effects on flora and fauna populations outside the production system. These
348 effects are outside the scope of this study. Low-intensity grassland systems are characterized by
349 medium groundwater level, low input and extensive management, potentially supporting species-rich
350 meadows with high biodiversity value. However, compared to the Mowing system, grazing requires
351 deeper groundwater level that falls into the shallow-drain category to support animal grazing, while
352 grazing cows produce manure onto the field. This leads to drier and more nutrient rich habitat with
353 lower biodiversity value. High-intensity paludiculture systems represent the highest water level with no
354 extra fertilizer input and lower mowing frequency. These production systems are closer to pristine mires
355 and are therefore more likely to support typical mire species. The Sphagnum system (on former
356 agricultural grounds) which is initiated by topsoil removal can re-introduce bog vegetation through
357 planting of peat mosses. This facilitates the buildup of peat material and creates suitable habitat for a
358 suite of endangered bog species, while the low harvesting frequency limits disturbance to a low level.
359 The Reed system under annual harvest can create opportunities for low-lying flora and support aquatic
360 macrofauna. However, monoculture of reed limits opportunities for other flora, and the system is under
361 eutrophic conditions.
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362 3.4 Ecosystem services value
363
Conventional
Organic
Grazing
Mowing
Reed
Sphagnum
0
2000
4000
6000
8000
10000
12000
Productivity
GHG Emission Reduction
Water Storage
Biodiversity
Ecosystem service value (EUR ha-1)
364 Figure 3. Ecosystem services value in EUR ha-1 per category for the six production systems.
365 The quantification of ecosystem services was translated to a monetary value in order to determine the
366 total ecosystem services value of each production system (Fig. 3). Dairy production from the drainage-
367 based dairy systems has the highest production value, but both drained systems deliver little other
368 ecosystem service value. Sphagnum production generates slightly lower revenue than the organic dairy
369 system, characterized by the high product value of peat mosses while being limited by the low
370 productivity of the system. Biomass from the low-intensity grasslands and Reed paludiculture system
371 have substantially lower revenue. Despite lower revenue from biomass production, all of the low-
372 intensity grassland and high-intensity paludiculture systems have higher total ecosystem services value
373 than the drainage-based dairy systems. The values of regulating ecosystem services make up close or
374 even more than the differences in production values comparing the wetter to the drained systems. GHG
375 emission reduction represents the highest value of these regulating services, closely followed by the
376 avoided damage value of water storage. Biodiversity values are absent in the drainage-based systems,
377 and are highest in the moist meadows.
378 4 Discussion
379 The presented analysis shows substantial differences between the amount and value of ecosystem
380 services from the six land use options. This results from the interrelationship between water level
381 dynamics, vegetation cover, farm structure, field management and ecosystem services provisioning.
382 However, the values presented here are estimates of average values under typical and theoretical
383 conditions, while the actual values in real-life will be subject to site-specific variations. In addition, the
384 monetary values presented are hypothetical values, which do not currently represent economic benefits
385 for farmers. Therefore, interpretation of the results needs to be restricted to the representation of
386 differences in magnitude among land use systems under different water level scenarios. Accuracy of the
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387 indication and monetary values is not the primary goal of this analysis, but some possible variations and
388 uncertainties will be discussed to validate the relationships.
389 4.1 Trade-offs and synergies among ecosystem services
390 Our results show a clear trend of increased total ecosystem services value following higher water levels
391 from the land use systems. Such increases are characterized by a combination of carbon-water-
392 biodiversity co-benefits at the cost of major drops in productivity. Trade-offs between economic value of
393 agricultural production and other ecosystem services have often been observed in peatland ecosystem
394 restoration cases (Law et al., 2015). In our case, this is a result of the elevated water level. Significantly
395 lower amount of milk can be produced in the dairy system at higher water level. The low-intensity
396 shallow-drained grazing system is only able to support around one third of the livestock allowed in the
397 conventional drainage-based dairy system. And the transition into biomass producing paludiculture
398 systems does not yield and revenue from biomass sales comparable with drainage-based dairy
399 production. This difference does not reflect the investment costs for buildings and equipment, which is
400 different in paludiculture than in dairy production, but falls outside the scope of our analysis.
401 Meanwhile, the covariation of emission reduction, water storage, and biodiversity shows synergy
402 between the underlying regulating and supporting services. A number of cases also showed the
403 ecosystem co-benefits from rewetting. For example, (Renou-Wilson et al., 2019) showed rewetting on
404 an Irish cut-away peatland led to the return of net carbon sink function and regeneration of species
405 typical of natural sites. It is clear that current dairy farming systems under intensive drainage sacrifices
406 the multifunctionality of peatland ecosystems for the sole purpose of milk production.
407 Notably, the organic dairy farming system is not providing higher value of on-site carbon-water-
408 biodiversity services compared to the conventional farming system. Organic dairy farming was widely
409 studied as a measure to reduce environmental impact of intensive dairy farming, providing services such
410 as mitigation of emissions (Weiske et al., 2006) and improving biodiversity (Power and Stout, 2011).
411 However, these benefits on mineral soils do not translate directly to peatlands. Emission reduction from
412 less intensive livestock keeping is marginal compared to the huge amount of CO2 emission from peat
413 oxidation under conventional drainage practices. The intensive grassland vegetation type is also
414 unchanged giving limited or no additional benefit in terms of water storage and on-site biodiversity.
415 Restrictions on the application of pesticides and artificial fertilizer and closing biomass loops will
416 probably still have benefits on larger spatial scales, but these are not reflected in our analysis.
417 4.2 Variations in the GHG emissions accounting
418 Emission factors used in this analysis were adopted from literature based-on information on vegetation
419 cover and farm structure. Large variations could emerge under site-specific environmental conditions
420 and management regimes. First of all, CH4 emission poses a major source of uncertainty. In particular,
421 the currently low CH4 emission factors around 1 – 2 t CO2-eq ha-1 yr-1 on LIP systems are comparable to
422 results of a mesocosm study with rewetted peat soils (Karki et al., 2016), which could represent
423 situations under good management practices. However, a poorly managed groundwater level
424 fluctuation or prolonged flooding events on these grassland types could lead to substantially higher CH4
425 emissions. For example, constant flooding of grassland on rewetted agricultural peatland could lead to
426 CH4 emissions up to 30 t CO2-eq ha-1 yr-1 (Huth et al., 2021; Kandel et al., 2020). Taking such extreme
427 situation into account would result in total GHG emissions from low-intensity grassland systems similar
428 to but no larger than drainage-based dairy systems. Such CH4 hotspot could also be prevented by certain
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429 management practices, such as topsoil removal prior to rewetting that could reduce CH4 emissions by
430 factor 30 – 400 (Huth et al., 2020); and sulphate addition into the soil solution that could suppress
431 methane emission via competing microbial activities (Davidson et al., 2021; Dowrick et al., 2006). On the
432 other hand, prolonged flooding could change wet meadow vegetation into reed and cattail cover
433 (Wilcox et al., 1985), which would lead to a different production system. Therefore, the lower total GHG
434 emission from paludiculture options would remain valid even under consideration of higher CH4
435 emission factors.
436 Meanwhile, our analysis only considered direct on-site gaseous emissions. Indirect emissions resulting
437 from biomass utilization were not included for paludiculture options, including low-intensity grassland
438 for mowing and high-intensity paludiculture systems of reed and Sphagnum, while biomass as feed and
439 emitted as CO2 and CH4 through animal was accounted for dairy producing systems. The harvested
440 biomass could be accounted as carbon emissions via export of biomass, or emission reduction via
441 substitution of fossil fuel and materials, based-on the dry matter yield and carbon content of the
442 biomass. Mix fodder and Sphagnum mosses have carbon content of 45% (Adamovics et al., 2018) and
443 51% (Roy et al., 2018), respectively. Therefore, biomass producing paludiculture systems would cause
444 indirect emission of biomass uses around 5 – 10 t CO2-eq ha-1 yr-1, which is relatively small comparing to
445 the potential emission reduction through rewetting of over 20 t CO2-eq ha-1 yr-1 according to our
446 calculations (Figure 1). Meanwhile, uses of paludiculture biomass could substitute fossil-based energy or
447 products, which could provide positive climate effects when considered at a shorter time span.
448 Therefore, the differences between land use options would not be altered by the change of system
449 boundary.
450 4.3 Limitations of the ecosystem services valuation
451 4.3.1 Carbon price
452 The presented monetary values are highly variable due to large regional differences and the possibility
453 of changes over time. The carbon price of EUR 75 /t CO2-eq is adopted from a small-scale peatland
454 restoration-oriented project from the Netherland, which is higher than the price in the European market
455 at around EUR 50 on average for the year 2021 (Sechi et al., 2022). However, a carbon price of one-third
456 less than the currently used level will still separate the paludiculture systems from the drainage-based
457 systems in terms of climate benefits. Meanwhile, the presented price was proven feasible since the
458 German carbon credit scheme from peatland rewetting MoorFutures® has been successfully
459 implemented with carbon prices of up to EUR 67 since 2009 (Günther et al., 2017). And the carbon
460 offset price is expected to increase significantly in the coming decade under the net zero target,
461 potentially providing competitive economic benefits from the climate change mitigation services.
462 4.3.2 Water storage value
463 The values of water storage are likely to change over time. With increasing economic losses from
464 flooding observed under the changing climate (Kundzewicz et al., 2014), one can expect that the value
465 of water storage as flood buffer would also increase. On the other hand, more frequent drought event
466 due to climate Change will also increase the value of groundwater recharge function from the subsoil
467 water storage of peatlands. Water storage value is also regionally specific. Flood prevention will be more
468 valuable in regions with large proportion of built-up areas or intensive agricultural land, such as under
469 the Dutch situation, where flooding will invoke severe damage and high costs. In more extensively used
470 areas the monetary value will be less. The local and regional features strongly determining agriculture
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471 and peatlands stress the need for region-specific studies to improve feasibility and viability (Ziegler et
472 al., 2021). However, the overall differences in the provisioning of ecosystem services from drainage-
473 based and paludiculture systems are fundamental and not likely to shift despite the possible variations
474 in the monetary values assigned.
475 4.3.3 Production value
476 The production value is subject to the system boundary and time scale considered in this study. In
477 reality, revenue from the market values of biomass and subsequent milk products is not equivalent to
478 the gross income of a farm, because the production costs (including long-term investments of
479 infrastructure and machinery) also need to be taken into account. For the dairy systems, high revenue
480 from milk products also incurs high costs to support the level of productivity, such as costs of installation
481 of infrastructures (e.g., stable and machinery), input of resources (e.g., concentrate feed), and costs
482 associated with the whole chain of the dairy industry. Dairy farm accountancy data shows that farm
483 expenditures take up to 79% of the raw incomes of an average Dutch farm (Sechi et al., 2022). This will
484 lead to a much lower net income from intensive dairy systems and make the low-intensity system non-
485 profitable if it solely depends on milk production (assuming the low productive systems have similar cost
486 structures as the high productive systems). Products from the low-intensity mowing system and high-
487 intensity paludiculture systems without dairy production are therefore not benefited from such
488 production inputs. Although conventional dairy system obviously provides the highest revenue and has
489 the best accessible market, differences among gross values of the raw materials (different forms of
490 biomass) are less significant (Table S3). Large investments are also required in some of these systems to
491 provided suitable hydrological conditions for the target wet crop. For example, Sphagnum farming can
492 induce establishment cost of over EUR 100k ha-1 mainly for site preparation and water management
493 (Wichmann et al., 2020) while reed production requires lower costs (Wichmann, 2017). Revenue values
494 presented in this analysis do not represent the true economic values of the production system or the
495 income of a farm. A fair comparison of the production value of all systems would need a more in-depth
496 economic inventory of the land use options.
497 4.3.4 Biodiversity value
498 The biodiversity values used here are proxies adopted from the Dutch subsidy scheme, which is basically
499 the cost of management to preserve the biodiversity on a certain habitat of target. Such a method of
500 valuation of biodiversity based on a production function analogy or cost-based methods is suggested by
501 Farnsworth et al. (2015) to link between economic theory and ecological research, while being
502 empirically practical. However, this will induce large variations and does not represent the intrinsic value
503 of the vegetation biodiversity. The management required for biodiversity conservation and, therefore,
504 the costs will differ regionally depending on the site conditions and land use history (Lamers et al.,
505 2015). Also, subsidies are subject to the production of biomass which is subtracted from the
506 management cost. For example, harvested reed land has much lower subsidy compared to the
507 Sphagnum bog partly due to the revenue from selling the reed bundles. Therefore, biodiversity values
508 presented here are only used for indicative purposes and for the standardized comparison between
509 systems. A more comprehensive valuation methodology is needed for a more general comparison of the
510 biodiversity values among different land uses (e.g. considering threatened species, Díaz et al., 2020)
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511 4.4 Side-effects of the land use systems
512 Not all aspects of the environmental impact of the systems were considered in our analysis. There are
513 strong side-effects that cannot be ignored when implementing the production land uses. Intensive
514 drainage induces large societal costs due to the negative environmental impacts that were not
515 accounted for when considering the economic value of the production at farming system level. Land
516 subsidence, largely caused by intensive peatland drainage, is predicted to cause an accumulated damage
517 cost of over EUR 5 billion for infrastructure alone in the Netherlands till 2050 (Stouthamer et al., 2020).
518 Ammonia vapors from livestock urine and manure, including from dairy farming on peatlands, is one of
519 the major contributor to the Dutch nitrogen crisis, causing excessive airborne nitrogen deposition that
520 harms natural ecosystems and human health (Stokstad, 2019). The Dutch nitrogen crisis has inflicted
521 high economic costs by slowing down building industries. In addition, the current dairy farming practice
522 is economically vulnerable. Business model of current dairy farming is heavily supported by subsidies
523 under the European Common Agriculture Policy (CAP) (Poczta et al., 2020), which hampers the farmers’
524 resilience to technical, climatic and economic risks (Bouttes et al., 2019). The intensive perennial
525 ryegrass on drainage-based dairy farming systems is more likely to suffer from severe drop of yield
526 under extreme weather conditions such as the drought event of 2018 in Europe (Fu et al., 2020).
527 Paludiculture systems combining raised water level and lower land use intensity can reverse the side-
528 effects into even more ecosystem service multifunctionality. For example, the cultivation of wet crop in
529 the high-input paludiculture systems also has the function of nutrient removal, contributing to the
530 mitigation of the nitrogen crisis. Reed cultivation can absorb significant amounts of nitrogen,
531 phosphorus and potassium (Geurts et al., 2020). Sphagnum farming rapidly decreased the ammonium
532 legacy from former drainage-based agriculture and sequestered high loads of nutrients (Vroom et al.,
533 2020). However, besides the large opportunity cost due to the substantially lower productivity,
534 paludiculture systems also present huge transitional cost via the purchase of machinery, site
535 preparation, water management, establishment of crop, etc. (Wichmann, 2017; Wichmann et al., 2020).
536 Such economic side-effect calls for additional policy and financial support to increase the willingness of
537 farmers to implement the alternative systems.
538 5 Conclusions and outlook
539 Our analysis identified the characteristic differences of land use systems under a gradient of water levels
540 despite the variation of indicator values. Drainage-based dairy farming maximizes milk production but
541 hardly provide any other ecosystem services; biomass producing paludiculture systems under both low
542 and high input deliver co-benefits of carbon-water-biodiversity related services but sacrifice economic
543 values of the product. Monitoring and evaluation of multiple ecosystem processes and services presents
544 a number of practical challenges including needs of expertise, labor and investment (Hughes et al.,
545 2016). Our analysis provided a simple approach that integrated existing knowledge to shed light on the
546 order of magnitude of the ecosystem services value from representative land use systems. More field
547 experiment and monitoring are needed to improve understanding of the biological, hydrological, and
548 biogeochemical processes and reduce uncertainties in the underlying indicators of these processes.
549 Conventional agricultural practices are under pressure due to the changing climate and hampering the
550 development of sustainable agriculture (Agovino et al., 2019). It is likely that the economic benefit of
551 milk production under dairy-farming normality will be outweighed by the side-effects from intensively
552 drained peat soils. The synergizing carbon-water-biodiversity benefits from paludiculture systems hint at
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553 potential economic incentives for the transition of systems via payments for ecosystem services (Ziegler
554 et al., 2021). According to the presented ecosystem services evaluation, the values of productivity and
555 emission reduction combined from the low- and high- input paludiculture systems are already
556 compatible with or even higher than the revenue generated by the drainage-based dairy production.
557 Carbon farming, aiming at improving the rate of CO2 removal from atmosphere and conversion into
558 plant biomass and soil organic matter, presents opportunities to combine paludiculture crop production
559 with carbon crediting (Tanneberger et al., 2021). Benefits from a variety of other ecosystem services can
560 be captured and monetized as part of a peatland carbon scheme as well (Bonn et al., 2014). For
561 example, MoorFuture® presented methodologies to combine carbon crediting and accounting of
562 ecosystem services (Joosten et al., 2015).
563 In conclusion, the continuation of current way of dairy farming on peatland under conventional drainage
564 is not likely to achieve major sustainability improvements. The low ecosystem services value, large
565 societal cost and vulnerability under climate change pose significant offsets for the economic value of
566 dairy production. The sustainable benefits of conversion to organic farming does not lead to substantial
567 changes if the system remains intensively drained. Meanwhile, the paludiculture land use systems that
568 transform from animal keeping to biomass utilization provide far larger carbon-water-biodiversity values
569 comparing to the conventional farming systems. However, the economic value of the crop production is
570 not comparable to the conventional dairy farming although individual paludiculture systems were
571 proven profitable and feasible (Wichmann, 2017; Wichmann et al., 2020). Combining insights from both
572 agricultural and peatland ecological perspectives, a clear message is conveyed that more fundamental
573 changes in land and water management are required, while financial and policy support are also needed
574 for the conversion of systems. A far larger step than the optimization of the current system is needed to
575 achieve sustainable transition in the productive use of peatlands.
576 Acknowledgement
577 We would like to thank Winnie Leenes and Abdul Wahab Siyal for their critical comments on the content
578 of this article. We thank Felix Reichelt for providing background information on the vegetation types in
579 the GEST approach. Weier Liu is supported by the China Scholarship Council (201706350201). Christian
580 Fritz is funded by Interreg-NWE Carbon-Connect project and the NWO Dutch Research Council
581 PEATWISE project (ALW.GAS.4).
582 CRediT authorship contribution statement
583 Weier Liu: Conceptualization, Methodology, Writing – original draft. Christian Fritz: Writing – review &
584 editing, Methodology, Validation, Supervision. Jasper van Belle: Writing – review & editing,
585 Methodology, Validation. Sanderine Nonhebel: Writing – review & editing, Supervision.
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