Additional costs of nature management caused by deposition
G.W.W. Wamelink, J.J. de Jong, H.F. van Dobben & M.N. van Wijk
Alterra, Green World Research
P.O. box 47
6700 AA Wageningen
The Netherlands
fax: +31 317 42 49 88
Corresponding author: g.w.w.wamelink@alterra.wag-ur.nl or m.n.vanwijk@alterra.wag-ur.nl
Abstract
A method was developed to calculate the costs of intensifying nature management to counteract the effects of
atmospheric deposition. The percentages of protected species belonging to 'nature target types' defined for the
Netherlands were used as a measure of the ecological quality resulting from intensified management. Preliminary
results show that the “Nature Planner” set of modelling instruments can be applied with some success to assess these
costs. Model outcomes show clear shifts in nitrogen availability for heaths and grasslands, though no differences
were found for forests. The percentages of protected species in heaths clearly changed. In the present situation, with
sods being removed from heaths every 20 years, the costs of maintaining heaths exceed those in a situation of sodcutting every 60 years by 1.4 m euros per year.
Key words: nitrogen, model, soil, management costs, deposition, heath, grassland, forest
Abbreviations: MSL=mean spring groundwater level, NTT=nature target type, FGR=physico-geographic regions,
F=Ellenberg indicator value for moisture, R=Ellenberg indicator value for acidity, N=Ellenberg indicator value for
nutrient availability
Introduction
A national workshop on the ecological benefits of the current acidification policy was held in early 2002. It
concluded that research should be undertaken to estimate possible savings on nature management costs resulting from
abatement of atmospheric deposition1.
Several reports published by the Dutch National Institute of Public Health and Environmental Protection RIVM over
the last few years (e.g. Natuurbalans, RIVM 2001 and Natuurverkenningen, RIVM 2002) have discussed the relation
between atmospheric deposition and the feasibility of nature target types (NTTs). However, the relation between
atmospheric deposition and the management costs associated with the achievement of nature target types has not yet
been assessed.
Alterra was commissioned by the Dutch Ministry of Housing, Spatial Planning and the Environment (VROM) to
design a method that could estimate the additional costs made by conservation area managers to limit or eliminate the
adverse effects of atmospheric deposition. This study represents a first step towards developing a new perspective on
acidification policy, which would provide the government with information on savings that could be achieved by
reducing atmospheric deposition. In addition, the study could render conservation area managers more fully aware of
the adverse (financial) consequences of atmospheric deposition.
The aim of the study was to describe and test a methodology to estimate the additional management costs required to
counteract the adverse effects of atmospheric deposition. At a later stage, this methodology should allow nationwide
assessment of the relation between atmospheric deposition, ecological quality and management costs.
Estimating the additional management costs necessary to counteract the effects of atmospheric deposition requires
large quantities of data, the most important of which relate to the ecological quality at current deposition levels and
the target ecological quality at a particular site. These data were obtained by combining the Dutch NTT map with the
deposition map. Information is also required on the additional management measures that have to be taken to remove
the excess atmospheric deposition, and on the costs of these measures. The “Nature Planner” set of modelling
instruments (Latour et al. 1997) can be used to calculate what ecological quality can be achieved in a particular NTT
1
In the context of this paper, the term atmospheric deposition includes both acid and eutrophying deposition.
at a particular level of atmospheric deposition with a particular type of management. It is possible to calculate
ecological quality at the natural background level of atmospheric deposition, and to use this as a reference value to be
compared with the value in a situation of increased deposition or altered management.
It is known for each NTT what additional management measures can be used to reduce or eliminate the effects of
deposition. At each deposition level, management options can be varied and the resulting changes in ecological
quality can be calculated. While the present study only used a constant (namely, the current) deposition level, in order
to test the method, follow-up studies can also use scenarios in wich the deposition levels vary over time (e.g.,
decrease as a result of abatement policy). This would allow assessment of the relation between costs of management,
deposition abatement and the likelihood of particular NTTs in the course of the next decades.
Materials and Methods
Level of protection of species
General principles of the study
The costs of increasing deposition – or the benefits of reducing deposition – were calculated from the costs of the
various management scenarios that result in a similar ecological quality. In this context, ecological quality is defined
as the 'species protection level', i.e. the percentage of species belonging to a certain target type that has a probability
of occurrent above a certain threshold. The approach is based on the principle that, for a given deposition level,
increased management effort (which implies increased costs) raises the number of protected species (i.e., the
protection level). It must be kept in mind, however, that there are limits to what can be achieved in terms of
protection levels: a high level of atmospheric deposition limits the protection level that can be attained, whatever the
management effort.
Reference level
Scenario 1
Scenario 2
0
0
C1
C2
Costs for nature management
Figure 1. Theoretical relation between costs of nature management and the species protection level for two
deposition scenarios (deposition in scenario 1 < deposition in scenario 2). The horizontal distance between the two
curves indicates the difference in costs between deposition scenarios 1 and 2. The difference in costs depends on the
intended level of protection. The reference level of protection is the level that has to be achieved for all atmospheric
deposition scenarios. This may be, for instance, the level of protection in a situation with natural (background)
atmospheric deposition.
Figure 1 depicts the theoretical relation between management costs and the species protection level. If the relation
between costs and protection levels is known for various deposition scenarios, the difference in costs between these
deposition scenarios can be calculated as the difference in the costs of nature management between various
deposition scenarios for a fixed reference level of protection. This is indicated in Figure 1 as the difference between
C1 and C2. The reference level of protection is the protection level that serves as the reference for the calculations
and that has to be achieved in the various deposition scenarios, if necessary by intensifying the management effort.
This reference level can be established in various ways, for instance as the level of protection at the natural
background level of deposition.
Alternative methodologies
The principle outlined above largely determined the research methodology used. In addition to this principle, which is
based on additional management costs required to remove the excess atmospheric deposition, the study also
considered other methods to calculate the costs of reducing or eliminating the effects of excess atmospheric
deposition.
One alternative method is to estimate the costs of additional work that is actually being carried out in order to reduce
the effects of atmospheric deposition. While this method of calculation closely reflects actual practice, it is plagued
by a number of practical problems. To begin with, it cannot be known whether the management measures taken did in
all cases lead to an ecological quality equivalent to a situation without increased atmospheric deposition. Also, it is
difficult to separate additional management due to deposition from the regular management that has to be carried out
anyway. Another practical problem is the lack of availability of data and the time required to collect them.
Another alternative method is to calculate the expenses incurred to develop a particular NTT. The general principle is
as follows: managers invest to create or reconstruct particular habitats, on the assumption that a certain level of
ecological quality can be achieved. As a result of high atmospheric deposition levels, however, the intended
ecological quality is not achieved. The ‘damage’ caused by the increased atmospheric deposition can then be
calculated from the development costs and the proportion of the intended ecological quality (i.e., the number of
species) that is not achieved. A variant of this method is based on the view that the ‘damage’ caused by not achieving
the intended quality will have to be compensated for elsewhere by expanding the total acreage of conservation areas.
The costs of this expansion can then be estimated. While the development costs method would seem highly suitable
in the case of new habitat creation or reconstruction schemes, it seems less applicable to situations of existing
conservation areas.
The present study chose to apply the method of additional management costs since we felt hat this methodology was
best suited to the research aims. Using a combination of the methods described above might yield an even more
complete picture, and this might be the subject of a follow-up study.
Nature target types
A range of so-called nature target types (NTT) have been defined for policy and management purposes in the
Netherlands (Bal et al. 1995). Each of these NTTs has its own target species, that is, species which may ‘naturally’
occur in the habitat that belongs to a particular NTT. That does not mean that all of these species actually occur in a
NTT in the present circumstances. Their absence may not only be due to excess atmospheric deposition, but also to a
less than ideal water regime in an area. Calculations made in the present study relate to eleven NTTs, defined on the
basis of the physico-geographic regions (FGRs) distinguished in the Netherlands, largely on the basis of soil types.
The NTTs included in the present study were selected in such a way as to ensure that the main FGRs would be
represented. Only one location for each NTT was assessed. The sites were distributed throughout the country, so that
different deposition levels were included. Figure 2 shows the locations of the NTTs included in the study and the
corresponding atmospheric deposition levels. Box 1 provides brief descriptions of the NTTs.
Figuur. 2. Survey of the locations assessed by means of the Nature Planner set of models. Nature target type codes, soil
types and acid (Sdep) and nitrogen deposition (Ndep) values are indicated for each location. Deposition data in
molc∙m-2∙yr-1. For an explanation of the codes, see table 1.
Additional costs of nature management caused by deposition, Wamelink et all.
Box 1. Description of nature target types. The texts are based on the Handboek natuurdoeltypen (Handbook of nature target types; Bal et al. 1995). The
target species mentioned for each nature target type represent only a selection. Some target types have more than 50 target species, including animals,
which have been omitted here.
Du 3.5 Wet nutrient-poor grassland
These include Cirsio-Molinetum grasslands and other nutrient-poor hay meadows, especially at the inner edge of the coastal dunes. Numbers of plant
species may be very high. These grasslands are rather poor in nutrients and have a fairly high water table; seepage improves the development of this type.
Management usually consists of mowing in summer. In large complexes, certain parts may be mown later in the year or may not be mown in a particular
year. Target species include Dactylorhiza majalis subsp majalis (western marsh orchid), Danthonia decumbens (heath grass), Dactylorhiza incarnata
(marsh orchid) and Fritillaria meleagris (wild fritillary).
Du 3.9 Wet to moist dune valley
This target type is referred to in the present paper as wet dune heaths. It can occur in primary dune valleys as a result of dune formation in primary dunes
near the beach or in secondary dune valleys where the sand has been blown away until the water table is exposed. If no management is applied, it develops
into dune scrub. The vegetation consists of pioneer species or dwarf shrubs. This type is normally not managed, but nitrogen deposition may necessitate
management. This type is also threatened by extraction of drinking water. Target species include Cicendia filiformis (yellow centauri), Radiola linoides
(all-seed), Erica tetralix (cross-leaved heath), Epipactis palustris (marsh helleborine), Cirsium dissectum (marsh plume thistle) and Carex distans (distant
sedge).
Du 3.13 Forest of calcareous dunes
This target type consists of oak and birch woods in calcareous, dry to moist, nutrient-poor to moderately nutrient-rich areas in the central parts or the inner
edges of the coastal dunes. Like the previous type, this type is not being managed, though grazing can be used to achieve a more varied undergrowth. This
type is sensitive to acid deposition, which decalcifies the soil. The target species include Galeobdolon luteum (yellow archangel), Vinca minor (lesser
periwinkle), Corallorhiza trifida (coral-root) and Mycelis muralis (wall lettuce).
Hz 3.5 Dry nutrient-poor grassland
Dry grassland is characterized by mainly grassy, species-rich vegetations. The type occurs on (moderately) nutrient-poor dry soils. It constitutes a
transition between dry heath and extensively grazed agrarian grassland and is mainly found in heathland areas. Management consists of mowing and/or
light grazing. Sod-cutting is sometimes applied to counteract natural succession. The type may also arise as a result of treading. Target species include
Corynephorus canescens (gray hairgrass), Botrychium lunaria (moonwort), Festuca ovina subsp ovina (sheep’s fescue), Scleranthus perennis (perennial
knawel), Genista anglica (needle furze), Arnica montana (leopards bane) and Genista tinctoria (dyer’s greenweed).
Hz 3.9 Dry inland heath
Fairly low vegetation of dwarf shrubs and grasses on dry nutrient-poor soil. Dry heaths can only survive if they are managed, for instance, by sod-cutting,
mowing, grazing, burning and removing tree saplings. A varied structure and the presence of elements like spontaneously seeded pines and juniper bushes
are important for the occurrence of many target species. Dry heaths are under great pressure in the Netherlands, in that they are being overgrown by
grasses due to atmospheric deposition. Target species include Genista germanica (German broom), Ulex europaeus (gorse), Lycopodium clavatum (stag’s
horn moss), Genista pilosa (hairy genista), Genista anglica (needle furze), Arnica montana (leopards bane) and Thymus serpyllum (wild thyme).
Hz 3.13 Forest of nutrient-poor sandy soils
These are forests on nutrient-poor dry sandy soils, including the lichen (Cladina spp.) , Leucobryum (pin cushion moss)and crowberry pine forests and the
forests of birch and common oak. The pine forests often develop into forests of birch and common oak. A striking characteristic of this target type is the
presence of many mosses and lichens; it can be regarded as a peripheral representative of boreal coniferous forests. These forests are normally not
managed, though management measures may be necessary to prevent succession. Extensive grazing can increase the structural variety. These forests are
highly sensitive to deposition. The target species do not include mosses or lichens, and the number of characteristic higher plant species is very limited,
including Lycopodium selago (fir clubmoss), L. annotinum, L. tristachyum (deep root clubmoss) and L. clavatum (Stag’s horn moss), Pyrola minor
(common wintergreen) and Monotropa hypopitys (yellow bird’s nest).
Lv 3.4 Wet, nutrient-poor grassland
This type includes quaking bogs, Cirsio-Molinetum grasslands and other hay meadows, with inflow of good quality ground or surface water. The
vegetation may occur on solid ground but may also be floating (in quaking bogs). It grows on a peat layer. It may be very rich in species, especially plants
and butterflies. Management consists of mowing in summer. This type is highly sensitive to water quality. Target species include Dactylorhiza majalis
subsp majalis (western marsh orchid), Polygala vulgaris (common milkwort), Liparis loeselii (fen orchid), Parnassia palustris (grass of parnassus),
Sagina nodosa (knotted pearlwort), Cirsium dissectum (marsh plume thistle) and Fritillaria meleagris (wild fritillary).
Ri 3.4 Wet nutrient-poor grassland
Wet nutrient-poor grasslands in the area of the main Dutch rivers are characterized by being flooded for a large part of the year and are situated on riverine
clay soils. Management basically consists of letting things take their natural course. If the presence of meadow birds is an objective, some grazing may be
used. Target species include Equisetum variegatum (variegated horsetail), Linum catharticum (purging flax), Pedicularis palustris (marsh lousewort),
Cirsium dissectum (marsh plume thistle), Silaum silaus (pepper saxifrage) and Fritillaria meleagris (wild fritillary).
Ri 3.10 Forest of riverine clay soils
This type includes poplar-elm forests, dry ash-elm forests, ash-elm forests rich in alder, rough alder forests, common alder carr and white willow forests.
These include both softwood and hardwood riverine forests, depending on the inundation frequency, on nutrient-rich, wet to moist riverine clay soils. This
type of forest is normally not managed, though extensive grazing may lead to greater structural variety. The only higher plant species regarded as a target
species is Geranium phaeum (dushy crane’s-bill).
Zk 3.5 Wet nutrient-poor grassland
This type is identical to the previous type (Lv 3.4) in vegetation and management. The main difference is the soil, which is in this type is marine clay.
Target species include Eleocharis quinqueflora (few-flowered spikerush), Radiola linoides (all-seed), Silaum silaus (pepper saxifrage) and Fritillaria
meleagris (wild fritlillary).
Zk 3.10 Forest of marine clay soils
This type includes poplar-elm forests, dry and alder-rich ash-elm forests and white willow forests. This type is currently rare on marine clay soils in the
Netherlands. There is no management, but grazing may be used to increase the structural diversity. The only higher plant species regarded as a target
species is Stellaria nemorum (wood stitchwort).
5
Additional costs of nature management caused by deposition, Wamelink et all.
Models
This study used the “Nature Planner” set of modelling instruments (Latour et al. 1997), an interface
including several models. We used three of these models, SMART2, SUMO2 and MOVE3, which are
briefly described here. For more detailed information, see Kros (2002; for SMART2), Wamelink et al.
(2000; for SUMO2) and Latour et al. (1997; for MOVE3). The SMART2 model is a soil model
simulating processes in the litter and the uppermost mineral layers. The model includes a complete
nutrients cycle, the nitrogen, acid and base cations cycles being the most important ones for the present
study. The resulting nitrogen availability and soil acidity (pH) values were used as input for MOVE3.
The SUMO2 model simulates the nutrient cycle in the vegetation. It uses factors like nitrogen
availability (from SMART2) and light availability to simulate biomass development for five 'functional
plant types': grasses and herbs, dwarf shrubs, shrubs and two different tree species. Biomass
development is affected by management, which may include mowing, sod-cutting and forest
management at various levels of intensity. The management measures remove biomass, and hence
nitrogen (and in the case of sod-cutting also acid) from the system. SUMO2 is fully integrated with
SMART2, exchanging data on nitrogen and litter at each time step of one year. Both SMART2 and
SUMO2 are dynamic process models that produce site-specific output.
The MOVE3 model is based on response curves for individual plant species. Such curves have been
estimated for about 900 plant species on the basis of about 100,000 vegetation relevés. The response
values, expressed as the likelihood of a particular plant species to occur at a given combination of
abiotic factors, are based on Ellenberg's indicator values (Ellenberg et al. 1991) for moisture (F),
acidity (R) and nutrient availability (N). The nitrogen availability and pH values used as input,
however, are provided by SMART2-SUMO2 in physical units, which have to be converted into
Ellenberg indicator values. This conversion is regarded as the main source of uncertainty in the model
chain (Wamelink et al. 2002). In addition to the likelihood of individual plant species being present,
MOVE3 can also calculate the likelihood of particular NTTs, based on the likelihoods of the target
species that constitute a given target type. A threshold value for the likelihood of a species being
present is used to determine whether a species can actually occur. The number of species that can occur
is expressed as a percentage of the total number of species defined for the particular NTT. This
percentage is a measure of the protection level of the NTT, which was used in the present study as an
indicator of the ecological quality of each NTT.
Input for the models
The models discussed above require various types of input, the most important of which are discussed
here. The main input for SMART2 consists of two maps. The first provides data on soil type, water
table and the quantity and quality of seepage. Since these data derive from the soil map of the
Netherlands, they are site-specific. The second map includes data on acid and nitrogen deposition,
which are also site-specific. The soil and deposition maps are standard components of SMART2SUMO2. The soil map is derived from the national soil mapping project (Kros et al. 1995), the
deposition map from Beck et al. (2001). The water table is used to calculate the mean spring
groundwater level (MSL), which is used in both SMART2 and SUMO2 and is also used as input for
MOVE3. The present study worked on the assumption of groundwater and deposition levels that are
constant over time. Spatial variations were allowed, however, yielding site-specific results. The
deposition and groundwater level data used were those for the year 2000.
Input for SUMO2 consists of a map indicating the vegetation type and the type and intensity of
management. In the present study, the type and intensity of management were varied for the NTTs
assessed (see table 1). Management measures include mowing, sod-cutting or forest management, as
appropriate for each NTT.
The main input for MOVE3 is the output of SMART2-SUMO2, that is, nitrogen availability, pH and
spring groundwater level. Regression equations are used to convert these values into the Ellenberg
indicator values for F, R and N respectively.
Output of the models
Vegetation development and soil processes were simulated by SMART2-SUMO2 over a period of 61
years, from 1990 to 2050. The first ten years of this period were used for calibration, and are not
shown. Deposition values were kept constant at the 2000 level during the simulation. The outcome for
2050 was used as the input for MOVE3.
6
Additional costs of nature management caused by deposition, Wamelink et all.
The output of the models is nitrogen availability and the removal of biomass over time. The output
values of the calculations for 2050 include groundwater level, nitrogen availability, acidity and the
amount of biomass removed. The amount of biomass removed was then used to calculate costs. We
also show the protection percentage as calculated by MOVE3 for each NTT and for each type and
intensity of management.
Cost calculations
Assessing the relation between management effort (in terms of costs) and protection level requires that
the costs of various management scenarios are calculated for a range of deposition scenarios. The
present study calculated the costs of management scenarios for the Du 3.5 wet nutrient-poor grassland
and Hz 3.9 dune heath target types at one deposition level.
The cost calculations are based on the Nature Planner output, which produces data on the type and
intensity of management and the amount of biomass removed per simulation year. The calculations are
based on standardized times for various activities and standard rates for labour and materials as used by
the implementing bodies (Staatsbosbeheer, 2000; IMAG, 2001). These standards are based on
measurements in practice situations. The data were supplemented with data from research not
incorporated in the lists of standard rates provided by the implementing bodies, such as the additional
costs of mowing wet grasslands with special equipment, the composition of the biomass (Riem Vis,
1985) and the costs of processing the biomass. A 20% surcharge was added to the management costs
for overheads (work supervision, administration, operational costs, profits and contractors’ financial
risks).
In cases where cost items were calculated on the basis of assumptions, these assumptions were varied
to calculate the possible range of annual costs per hectare. These include the costs of materials
transport, the percentage of dry matter in the biomass removed, the density of the biomass, the average
transport distance for biomass removal and the rates charged for processing the biomass.
Fixed costs, which do not depend on the level of management effort or the level of atmospheric
deposition, were excluded from the calculations, as were costs whose relationship with management
effort or deposition levels was unclear. These include:
- costs of measures not implemented for the direct aim of vegetation development (but for recreation,
fauna development, etc.);
- costs of peripheral management (ditches, fences);
- monitoring and general management planning;
- hydrological measures (providing drainage ditches);
- infrastructure costs.
Costs were calculated on the basis of 2001 rates, over the simulated 51-year period. This was used to
calculate the average cost of a particular management measure for each time it is carried out. Annual
costs were then calculated according to the frequency with which measures are carried out. The
frequency value indicates what percentage of the total acreage is treated per year, a frequency of once
every ten years (f = 0.1) implying that 10% of the acreage is being treated per year. Interest was
disregarded, since the net cash value or annuity of management costs depends closely on the year in
which particular measures were used in the Nature Planner models.
7
Additional costs of nature management caused by deposition, Wamelink et al.
4
1*
biomass removal (ton/ha)
2*
3*
3
4*
2
1
0
2000
2025
2050
year
130
1*
2*
N avail (kg/ha)
3*
4*
120
110
100
2000
2025
2050
year
Figure. 3. Amounts of biomasss removed (upper panel) and nitrogen availability (N avail, lower panel) for the nature target type
Ri 3.4, wet nutrient-poor grassland, at four different levels of management intensity (mowing 1 to 4 times per year). Deposition
over the simulated period equals the 2000 level.
8
Additional costs of nature management caused by deposition, Wamelink et al.
Results
Grassland
The amount of biomass removed was calculated for each combination of a NTT and a particular type of
management. Fig. 3 shows an example of the amount of biomass removed for the Ri 3.4 nature target
type, representing wet, nutrient-poor meadow. Mowing intensities for this type of grassland vary per
year, which means that different amounts of biomass are removed. Intensifying the management results
in larger amounts of biomass being removed, with the greatest difference between annual and bi-annual
mowing regimes. Biomass removal results in changes in nitrogen availability (fig. 3 and table 1), with
intensified mowing regimes clearly leading to lower nitrogen availability. At a constant deposition
level, however, total nitrogen availability increases over time at any mowing intensity, despite the
nitrogen removal. Even mowing four times a year is unable to eliminate the effects of nitrogen
deposition. Table 1 shows the total amount of biomass and the average amount removed annually.
Intensified management effort does in most cases lead to increased protection percentages, although
absolute differences are small and probably not significant.
Annual management costs for the Du 3.5 nature target type increase greatly at increasing mowing
frequencies, from € 873 ha-1yr-1 for mowing once a year to € 2.550 ha-1yr-1 for mowing four times a
year (table 4). At the same time, the costs per mowing round decrease, as less biomass is removed per
round. The range of costs was derived by varying the assumptions about the costs of bringing in
equipment and transporting the biomass, the percentage of dry matter in the biomass, the average
transport distance and rates for biomass processing.
Heath
The costs of sod-cutting were based on the amount of litter removed (table 2). The amount of sand
removed in the sods cannot be shown, as the models fail to take this into account. Large differences
were found for the Hz 3.9 target type, dry heath, where the percentage of protected species is clearly
predicted to rise as management is intensified. Whether sod-cutting is carried out every 60 and 50 or
every 40 and 20 years makes no difference to the percentages, since, relative to the reference year, the
time elapsed since the last cutting is the same for these intensities. This can be prevented by varying the
initial age, that is, the time elapsed before the first sod-cutting. This leads to averaged values per level
of management intensity, resulting in differences between the above levels of intensity. Calculations
for wet dune heath (Du 3.9) yielded no differences between the various levels of management intensity.
The protection level remains fairly low, even if large amounts of biomass and nitrogen are removed
and nitrogen availability changes (table 2). In this case, the MOVE3 model is relatively insensitive to
these fairly large changes in nitrogen availability.
25
Level of protection
20
15
10
5
€-
€20
€40
€60
€80
€100
Costs per ha per year
Figure 4. Relation between nature management costs and level of protection for Hz 3.9 (dry inland
heath).
The annual management costs for the Hz 3.9 target type increase at increasing sod-cutting frequency
(table 5). At the same time, the costs per sod-cutting round decrease as less material is removed. At a
frequency of once every 60 years, the costs of sod-cutting are low compared to those in management
9
Additional costs of nature management caused by deposition, Wamelink et al.
scenarios with higher frequencies, because the amount of biomass and litter in the Nature Planner
models at the first cutting is lower than could be expected on the basis of the sod-cutting frequency.
This means that the first cutting leads to an underestimation of the costs. To a lesser extent, this
problem also arises at frequencies of once every 40 and 50 years. Follow-up studies could eliminate
this problem by varying the moment at which the sod-cutting cycle starts for each management
scenario. Fig. 4 shows the relation between the average costs per hectare per year and the protection
level. The points on the graph represent the outcomes of the calculated scenarios. The line indicates the
trend in the relation between costs and protection levels. If several calculations are made for each
management scenario, using different starting times for the sod-cutting cycle, the resulting points
should be closer to the trend line.
Forests
Biomass is removed from forests five times (data not shown), except in the ‘no action’ management
variant, in which no biomass is removed at all (table 3). Intensifying the forest management did not
lead to a higher protection level, and nitrogen availability could even rise (table 3). This is caused by an
acceleration of the nutrient cycle, more light penetrating to the forest floor and the growth of more
plants with a relatively high nitrogen content in the leaves. Such leaves are more easily mineralized,
leading to greater nitrogen availability. The lack of effect of intensified forest management on the
protection level is in agreement with the results of earlier research (Wamelink et al. 2002), which found
that thinning did not reduce nitrogen availability. Removing nitrogen from forests requires more drastic
interventions, such as sod-cutting, which is currently being applied as an experimental procedure
(Bartelink et al. 2001). It remains to be seen whether this can be introduced on a large scale, since the
trees present in the forest seriously impede cutting activities. Management costs were not calculated,
since the protection level did not change. It must be concluded that application of the method
developed for this study is not useful for the forests included in the present study.
10
Additional costs of nature management caused by deposition, Wamelink et al.
Table 1. Estimated amounts of biomass removed, protection level (%), mean spring grounwater level
(MSL), pH and nitrogen availability (N avail) for the grasslands. Deposition over the simulation period
equals the 2000 level.
code
Du 3.5
Hz 3.5
Lv 3.4
Ri 3.4
Zk 3.5
name
soil type management
Wet nutrient-poor
grassland
sand
Dry nutrient-poor grassland sand
Wet nutrient-poor
grassland
Wet nutrient-poor
grassland
Wet nutrient-poor
grassland
peat
clay
clay
biomass
removed,
total
ton/ha
avg protection in
removal
2050
ton/ha
%
MSL pH (soil)
N avail
1* mowing/yr
79.89
1.57
35
cmsurface
0.48
kmolc/ha/j
7.02
4.76
2* mowing/yr
87.65
1.72
33
0.48
7.02
4.64
3* mowing/yr
90.88
1.78
33
0.48
7.02
4.60
4* mowing/yr
93.79
1.84
33
0.48
7.02
4.57
1* mowing/yr
74.56
1.46
3
1.54
3.90
4.29
2* mowing/yr
81.67
1.60
3
1.54
3.90
4.18
3* mowing/yr
84.64
1.66
3
1.54
3.90
4.14
4* mowing/yr
87.27
1.71
4
1.54
3.90
4.11
1* mowing/yr
57.11
1.12
2
0.24
3.83
3.43
2* mowing/yr
61.81
1.21
4
0.24
3.83
3.33
3* mowing/yr
64.64
1.27
4
0.24
3.83
3.28
4* mowing/yr
67.25
1.32
3
0.24
3.83
3.39
1* mowing/yr
119.2
2.34
0
0.82
6.81
9.25
2* mowing/yr
133.3
2.61
0
0.82
6.81
8.97
3* mowing/yr
139.43
2.73
0
0.82
6.81
8.81
4* mowing/yr
145.45
2.85
1
0.82
6.81
8.74
1* mowing/yr
84.46
1.66
42
0.48
6.82
5.49
2* mowing/yr
93.12
1.83
43
0.48
6.82
5.36
3* mowing/yr
96.68
1.90
43
0.48
6.82
5.30
4* mowing/yr
99.88
1.96
42
0.48
6.82
5.26
Table 2. Estimated amounts of biomass removed, protection level (%), mean spring groundwater level
(MSL), pH and nitrogen availability (N avail) for the heaths. Deposition over the simulation period
equals the 2000 level.
code
name
soil type management
Du 3.9
Wet dune
heath
sand
Hz 3.9
Dry heath
sand
biomass
removed,
total
ton/ha
avg
removal
ton/ha
ton/ha
%
cm-s
sod-cutting every 60 yr
8.53
8.53
76.84
7
0.48
7.00
1.75
sod-cutting every 50 yr
25.36
12.68
103.01
7
0.48
7.00
1.75
sod-cutting every 40 yr
22.22
11.11
94.59
7
0.48
7.00
0.81
sod-cutting every 30 yr
18.65
9.33
85.18
7
0.48
7.00
0.99
sod-cutting every 20 yr
22.07
7.36
77.49
7
0.48
7.00
0.81
sod-cutting every 60 yr
10.42
10.42
25.97
2
1.54
3.79
6.09
sod-cutting every 50 yr
45.53
22.77
62.08
2
1.54
3.75
6.09
sod-cutting every 40 yr
35.14
17.57
55.10
20
1.54
3.85
2.24
sod-cutting every 30 yr
28.32
14.16
47.56
14
1.54
3.84
3.38
sod-cutting every 20 yr
33.31
11.10
50.08
20
1.54
3.85
2.24
11
removal protection in
litter
2050
MSL pH (soil)
N avail
kmolc/ha/j
Additional costs of nature management caused by deposition, Wamelink et al.
Table 3. Estimated amounts of biomass removed, protection level (%), mean spring groundwater level
(MSL), pH and nitrogen availability (N avail) for the forests. Deposition over the simulation period
equals the 2000 level.
code
name
soil type management
Du 3.13
Forest of calcareous
dunes
sand
Hz 3.13
Ri 3.10
Zk 3.10
Forest of nutrient-poor
sandy soils
Forest of marine clay
soils
N avail
%
cm-s
0.00
19
0.48
6.99
4.90
extensive
25.03
5.01
19
0.48
6.99
4.95
intensive
31.59
6.32
19
0.48
6.99
4.98
kmolc/ha/j
0
0.00
13
1.54
3.76
8.34
extensive
23.93
4.79
13
1.54
3.76
8.48
intensive
29.97
5.99
13
1.54
3.75
8.59
0
0.00
28
0.82
6.80
5.89
extensive
26.72
5.34
28
0.82
6.80
5.89
intensive
15.67
3.13
28
0.82
6.80
5.90
no management
clay
MSL pH (soil)
ton/ha
no management
clay
avg protection in
removal
2050
0
no management
sand
Forests of riverine clay
soils
Biomass
removed,
total
ton/ha
no management
0
0.00
28
0.48
6.81
4.85
extensive
24.18
4.84
28
0.48
6.81
4.82
intensive
35.09
7.02
28
0.48
6.81
5.09
Table 4. Results of Du 3.5 nature target type for four management scenarios, calculated over a period
of 51 years. Amounts of biomass removed and total amounts removed (including moisture) indicated
over the entire period.
management
scenario
biomass
removed
Total average cost
amounts of mowing, per
removed
round
(1000kg/ha) (1000kg/ha)
(€/ha)
annual range ofannual
costs
costs
Protection
level
(€/ha)
(€/ha)
Mowing 1x a year
80
399
873
873
755 - 1.032
35
Mowing 2x a year
88
438
722
1.445
1.280 - 1.674
33
Mowing 3x a year
91
454
666
1.998
1.790 - 2.292
33
Mowing 4x a year
94
469
638
2.550
2.299 - 2.907
33
Table 5. Results of Hz 3.9 nature target type for five management scenarios, calculated over a period of
51 years. Amounts of biomass removed and total amounts removed (including moisture and inorganic
material) indicated over the entire period.
management scenario
biomass
removed
total average cost
amounts of sod-cutting,
removed
per round
(1000kg/ha) (1000kg/ha)
(€/ha)
annual
costs
range of
annual costs
Protection
level
(€/ha)
(€/ha)
Sod-cutting every 60 yr
36
162
2.253
38
28 - 56
Sod-cutting every 50 yr
108
478
3.283
66
50 - 98
2
Sod-cutting every 40 yr
90
401
2.769
69
53 - 103
20
Sod-cutting every 30 yr
76
337
2.344
78
59 - 117
14
Sod-cutting every 20 yr
83
371
1.744
87
66 - 131
20
12
2
Additional costs of nature management caused by deposition, Wamelink et al.
Discussion
The aim of the present study was to show that models can be used to estimate the additional costs
required to reduce or eliminate the adverse effects of atmospheric deposition. Preliminary results
indicate that this is indeed possible. However, if we wish to draw useful conclusions, the method must
also be sufficiently sensitive to assess differences in ecological benefits resulting from intensified
management. The results of the present study for grasslands show that management does lead to
nitrogen removal, but that total nitrogen availability still rises as a result of deposition. In this type of
terrain, changes can probably only be expected when deposition levels decrease. The results for heaths
did show overall trends in nitrogen availability, and we expect that this will also turn out to be the case
if the method is applied on a nationwide scale. No effects of forest management were found, in that
thinning alone does not reduce nitrogen availability. It is doubtful whether application on a nationwide
scale would lead to a different outcome. Total removal of all trees might produce an effect, but this
scenario was not included.
The examples (tables 1, 2 and 3) show that the method developed revealed limited differences in
protection levels for different management regimes, a phenomenon for which a number of causes can
be identified. Intensifying management does not necessarily mean that nitrogen availability is reduced,
which means that no improvement in protection levels can be expected. An example is the thinning of
forests. It is also possible that, partly due to deposition, nitrogen availability has now reached such high
levels that intensifying management no longer has any effect. This might imply that intensifying
management could have an influence at sites with lower deposition levels. Groundwater levels may
also represent a limiting factor for the increase in the number of protected species in the Netherlands.
This might limit, or even eliminate, the effect of decreased nitrogen availability. All of these effects are
caused by external factors. On the other hand, the sensitivity of the instruments used also seems to be
insufficient in some cases. This might mean that differences in nitrogen availability as a result of, for
instance, mowing grasslands is incompletely reflected in the percentage of protected species predicted
by the models. Using the models to calculate management costs proved to be useless for the forests
used as an example in the present study, since the various management regimes would not result in
increases in the percentage of protected species. Further research is required to establish whether
changes in protection levels might be achieved at other locations and under different circumstances.
Management strategies mainly affect nitrogen availability. Only in the case of sod-cutting in heaths
was a minor effect on soil acidity predicted (tables 1, 2 and 3). In fact, removing biomass can only be
expected to influence the nitrogen balance, since no acid is removed. This means that the management
measures discussed here can only serve to counteract the effects of atmospheric nitrogen deposition,
not those of acid deposition. The latter might be achieved by spreading lime on vegetations.
Since the calculations in the present study only included one location per NTT, the results are only
valid for that particular location, with its individual conditions and deposition level. At this stage of the
research it is therefore difficult to draw definitive conclusions about the methodology used. Also, it is
not yet possible to present a nationwide overview. Nevertheless, we did make an attempt to do so for
target type Hz 3.9, that of dry heaths, in order to provide a preliminary idea of the costs involved. The
map of NTTs shows that the Netherlands has a total of 28,744 ha. of dry heath (Beck et al. 2001). This
corresponds to total management costs ranging from 1.1 million euros a year if sod-cutting takes place
every 60 years to 2.5 million euros at a frequency of once every 20 years; a difference of 1.4 million
euros a year. If a sod-cuttting frequency of once every 60 years is regarded as standard management
practice, then the additional costs of changing to a frequency of once every 20 years would yield an
increase in the protection level from 2% to 20%. It may be questioned, however, whether such an
intensification of management is ecologically valuable. Intensifying management means that more
nitrogen is removed, which increases the protection percentage. At the same time, however, cutting
sods every 20 years may mean that many species do not have enough time to re-establish themselves in
the areas where sods were cut. Similar limitations can be envisaged for mowing regimes. Plant species
react rather strongly to mowing frequencies, and many species may not survive a frequency of four
times a year.
The fact that our calculations included only one location for each NTT may also have influenced the
outcome in terms of the effectiveness of management measures. It is quite possible that calculations for
a different location with a different deposition level or pH value yields different outcomes. In addition,
our conclusions about the value of the method examined here are based on a selection of target types,
13
Additional costs of nature management caused by deposition, Wamelink et al.
and other target types might respond differently to intensified management. It is to be expected that
target types on sandy soil in particular will show a more pronounced response to variations in
management than the average response predicted by the above calculations.
The present study was based on the assumption of constant acid and nitrogen depositions. Deposition
levels are expected to decrease in the future, a scenario which could yield different results from those
described above. It might mean that effects could be found for locations for which the present study
found that intensifying the management would have no effect.
The results of the present study are based on model calculations. Since the unreliability of conclusions
drawn by MOVE3 is unknown, no confidence intervals can be calculated for the percentages of
protected species.On the whole, the model outcomes tend to be more reliable if model runs are
compared (as was done in the present study) than if they are considered individually. This was made
clear, for instance, in a study by Schouwenberg et al. (2001), which conducted sensitivity and
reliability analyses for SMART2-SUMO2-NTM3.
Estimates have been made of critical loads for the various NTTs in the Netherlands, that is, the nitrogen
and acid deposition ranges within which a specific vegetation type can occur. The objective of
intensifying management is to remove excess deposition of particularly nitrogen. At current deposition
levels, however, it is impossible to counteract its effects for many types in various locations in the
Netherlands to such an extent that they effectively remain within this critical load. The consequence is
that certain NTTs cannot survive (Bobbink et al. 1998). The present study confirms this picture.
Although management of grasslands does have an effect on nitrogen availability, it is unable to prevent
availability levels from rising or to improve protection levels. A similar picture was found for the forest
types included in the study, where management was predicted not to have any effect. Intensified
management of heaths was predicted to have only temporary effects. In the end, long-term survival of
the NTTs can only be ensured by reducing deposition levels. As long as deposition has not been
reduced to acceptable levels, other measures besides those included in the above calculations will be
necessary, including sod-cutting and liming in grasslands or forests.
The mean spring groundwater level (MSL) is a measure of moisture availability, and is used as such in
both SMART2-SUMO2 and MOVE3. The present study assumed MSL to be constant, in order to be
able to distinguish the effects of management alone. Many locations in the Netherlands, however, no
longer have a natural groundwater level, with many areas suffering serious desiccation. It is expected
that groundwater levels will be raised again in the future, at least in conservation areas, which will
result in changes in the percentages of protected species in the NTTs. These changes will probably be
larger than the effects of intensified management. An interaction is expected to occur between raised
groundwater levels and nitrogen availability, in that higher groundwater levels will lead to increased
denitrification, which means that more nitrogen will be released into the atmosphere. This will result in
a lower nitrogen availability, the same effect that is aimed for by mowing and sod-cutting. As a
consequence, the effects of nutrient reduction management may differ from those predicted on the basis
of constant MSL above.
Costs were calculated on the basis of current price and wage levels. These are likely to change in the
near future, however, for instance because processing sods may become more expensive if it is no
longer allowed to dispose of them on agricultural fields or because mown grass, which is currently
composted, may be used for energy production in the future. Such changes will have a clear effect on
costs.
It is hoped that a second stage of the present research project will produce a nationwide overview of the
costs and benefits of intensifying management, by repeating the above calculations for a representative
sample of locations for each NTT and taking into account the different deposition levels at the various
locations. This would allow a more accurate prediction of the spatial distribution of the effects of
deposition and the resulting additional costs of intensified management.. It may reveal that the intensity
of management required may differ for different locations, depending on deposition levels and the
intended protection level at a particular location. The difference between nitrogen availability at
standard management and the availability at intensified management can be regarded as the amount of
nitrogen effectively removed. The intended protection level can be established by running the models
with the natural background levels of deposition. For those target types in which there is no annual
management, the initial age for the various locations will have to be varied in such a way that
14
Additional costs of nature management caused by deposition, Wamelink et al.
management interventions do not take place simultaneously at all locations. This provides a better
reflection of current practice, in which, for instance, sod-cutting is not implemented simultaneously in
all heathland areas, but a certain proportion of them are treated each year.
Although the method described above was developed for the Dutch situation, the principle can also be
applied outside of the Netherlands. With some adjustments, the SMART2-SUMO2 models are able to
make calculations for any temperate climate zone. Such applications will, however, require a new
system to be developed to assess the effect of management on the number of species that can occur,
since the NTTs were only defined for the Netherlands.
Acknowledgements
We would like to thank the members of the supervisory committee for their willingness to assist us,
notwithstanding the extremely tight schedule for the study. This paper was translated into English by
Jan Klerkx, Bèta Vertalingen Maastricht. The study was sponsored by the Dutch Ministry of Housing,
Spatial Planning and the Environment.
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16