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. References Bal, D, H.M. Beije, Y.R. Hoogeveen, S.R.J. Jansen & P.J. vander Reest 1995. Handboek natuurdoeltypen in Nederland. EC-LNV, Wageningen. Bartelink, H. H., H. F. van Dobben, J. M., Klap & Th. W. Kuyper 2001. Maatregelen om effecten van eutrofiering en verzuring in bossen met bijzondere natuurwaarden tegen te gaan: synthese. OBNRapport 13. ECLNV, Wageningen. Beck, J.P., L. van Bree, M. van Esbroek, J. Freijer, A. van Hinsberg, M. Marra, K. van Velze, H.A. Vissenberg en W.A.J. van Pul. (2001) Evaluatie van de Verzuringsdoelstellingen: de emissievarianten. RIVM-rapport 725501002. RIVM, Bilthoven. Bobbink, R., M. Hornung & J.G.M. Roelofs 1998. The effect of air-borne nitrogen pollutants on species diversity in natural and semi-natural European vegetation. Journal of Ecology 86: 717-738. Ellenberg. H., H.E. Weber, R. Düll, V.Wirth, W. Werner & D. Pauliβen 1991. Zeigerwerte von Pflanzen in Mitteleuropa. Scripta Geobotanica 18. IMAG 2001. Het Groene Boek. Tijdnormen aanleg en onderhoud van natuur, groen en recreatieve voorzieningen ingedeeld volgens de RAW-systematiek. Wageningen, IMAG, IMAG-rapport 2001-05, 363 p. Kros, J., G.J. Reinds, W. de Vries, J.B. Latour, & M. Bollen, 1995. Modelling of soil acidity and nitrogen availability in natural ecosystems in response to changes in acid deposition and hydrology. DLO Winand Staring Centre, Report 95, Wageningen, the Netherlands. Kros, J. 2002. Evaluation of biogeochemical models at local and regional scale. Thesis. Alterra, Wageningen. Latour, J.B., I.G. Staritsky, J.R.M. Alkemade & J. Wiertz 1997. De Natuurplanner. Decision Support Systeem natuur en milieu. Versie 1.1. Rapport 711901019. RIVM, Bilthoven. Riem Vis, F. 1985. Composteren van materialen die vrijkomen bij het beheer van heidevelden. With a summary: composting of materials resulting from heathland management. Haren, Instituut voor Bodemvruchtbaarheid, Rapport 6-85, 33 p. RIVM, 2001. Natuurbalans 2001. Kluwer, Alphen aan de Rijn. RIVM, 2002. Natuurverkenningen 2 2000 – 2030. Kluwer, Alphen aan de Rijn. 15 Additional costs of nature management caused by deposition, Wamelink et al. Schouwenberg, E.P.A.G, H. Houweling, M.J.W. Jansen, J. Kros & J.P. Mol-Dijkstra 2000. Uncertainty propagation in model chains: a case study in nature conservancy. Alterra-report 001. Alterra, Wageningen. Staatsbosbeheer 2000. Normenboek Staatsbosbeheer 2000 - 2001. Normen voor de uitvoering van werkzaamheden in Bosbouw, Natuurbeheer en Landschapsverzorging. Driebergen, Staatsbosbeheer, 141 p. Wamelink, G.W.W., J.P. Mol-Dijkstra, H.F. van Dobben, J. Kros & F. Berendse 2000. Eerste fase van de ontwikkeling van het Successie Model SUMO 1. Verbetering van de vegetatiemodellering in de Nature Planner. Rapport 045. Alterra, Wageningen. Wamelink, G.W.W. , V. Joosten, H.F. van Dobben1 & F. Berendse. Validity of Ellenberg indicator values judged from physico-chemical field measurements. 2002. Journal of vegetation science 13: 269-278. Wamelink, G.W.W., H.F. van Dobben, E.P.A.G. Schouwenberg & J.P. Mol-Dijkstra 2002. Haalbaarheid van natuurdoeltypen in arme bossen en droge heide op de hogere zandgronden: een modelstudie. Rapport 562. Alterra, Wageningen. 16