Ecosystem services (ES) are vital for human well-being1. Much attention has been devoted to mapping and quantifying ES to achieve the dual goals of protecting biodiversity and human well-being. A growing number of broad-scale mapping studies aim to identify priority regions for conducting more localised place-based management of ES [e.g.,2–5]. Place-based management requires intensive collection of detailed socio-economic and biophysical data, and close collaboration with stakeholders for effective decision making6,7. Given limited resources and information, and increasing threats to ecosystems, it is not possible to do these comprehensive analyses everywhere in a timely manner. We argue that there is currently an under-appreciated, but vital role for spatial prioritization of locations in which place-based management should occur so that attention is focussed on those locations where resource investment will yield the greatest return for human well-being. Indeed, data are deficient in most locations for informing comprehensive and accurate analyses of trade-offs in ES management, and spatial prioritization is a crucial precursor to attempting such trade-off analyses so that data mining efforts occur in the most critical locations. Moreover, prioritization is essential because much ES management is conducted by government or non-government organizations (NGOs) that could potentially operate in many places.
Given the important role that broad-scale prioritization can play in guiding decisions about where to conduct place-based ES management, a critical assessment of current prioritization approaches is warranted. Some schemes for identifying spatial priorities for managing ES are simple characterizations of biophysical processes and social demand, with little consideration of important information such as the availability of alternatives to ES for meeting human needs, threats to service provision, and the costs of management actions. Although fundamentally different to spatial prioritization for biodiversity conservation, spatial prioritization of ES may be guided by some of the key principles of the former. Spatial prioritization for conservation is well established and may be applied at coarse (e.g., biodiversity hotspots or priority ecoregions;8) or fine scales, identifying locations or actions in locations that are relatively more important for protecting biodiversity than other actions or other locations9. As with spatial prioritization of ES, spatial prioritization for conservation may help to identify locations where more detailed systematic conservation planning should be conducted, and is just one component of the planning process10,11.
Spatial prioritization of ES differs from spatial prioritization for conservation because ES are valued primarily for their worth to humans, can be transferable across space (may not need to be protected at a specific location), are sometimes substitutable by human engineering, and service beneficiaries define the success of management actions. Yet, as with spatial prioritization for conservation, spatial prioritization of ES can guide decsions about local-scale planning and inform the allocation of resources from management agencies (e.g., World Wildlife Fund;12). Moreover, spatial prioritization for conservation is a useful starting framework for ES prioritization because the former is well entrenched in planning discourse13 and yields valuable lessons for ES management14.
Current approaches to identifying spatial priorities for managing ES apply different prioritization methods (see Table 1), and developing more consistent and comprehensive methods is an important goal for future prioritization studies. We review past approaches to spatial prioritization of ES, identifying key aspects that should be considered in future analyses. At appropriate places we discuss the relevance of spatial prioritization for biodiversity conservation to spatial prioritization of ES because certain aspects, such as accounting for costs and threats, are common to both. We then demonstrate the importance of these aspects through a conceptual framework for prioritization that outlines an approach for managing the most vital ES for the least cost where they are most needed15. We illustrate the framework with a worked example using the ES of water provision. Egoh et al.14 reviewed the extent to which ES were included in conservation assessments (≈ identifying spatial priorities). Our work differs from Egoh et al. by assessing how ES priorities have been identified and how methods for prioritization should be improved. It also complements discussions of other aspects of ES management such as how to operationalize ES on the ground16, developing appropriate payments for services schemes (e.g.,17,18) or how to manage service provision at specific sites [e.g.,19,20].
|2 (see also Holland et al. 48[note 1])||Carbon storage||Biophysical quantity[note 2]|
|Agricultural value[note 3]||Gross margin of crops and livestock[note 4]|
|Recreation[note 5]||# of visits[note 6]|
|53||Carbon sequestration||Biophysical quantity[note 7]|
|Water quality||Amount of pollutants removed[note 8]|
|Soil Retention||Biophysical quantity[note 9]|
|Water yield||Biophysical quantity|
|Pollination||Abundance of pollinators[note 10]|
|39||Carbon storage||Biophysical quantity||Target based[note 11]||Area of planning unit[note 12]|
|Flood control||Averted flood risk[note 13]||Target based[note 14]||Area of planning unit|
|Forage production[note 15]||$ value[note 16]||Target based[note 17]||Sum of ‘development’ values[note 18]||Implicit; integrated into benefit values|
|Outdoor recreation[note 19]||Biophysical quantity[note 20]||12 days per person[note 21]||Sum of ‘development’ values|
|Pollination[note 22]||$ value[note 23]||Target based[note 24]||Area of planning unit|
|Water provision[note 25]||Biophysical quantity||A fraction of actual use within each stratification unit[note 26]||Area of planning unit|
|4||Carbon storage||Biophysical quantity and $ value||Target-based and through $ value[note 27]||Road-density proxy and services as added costs/benefits|
|Recreational angling||Biophysical quantity and $ value||Target-based and through $ value[note 27]||Road-density proxy and services as added costs/benefits|
|Timber harvest||$ value (net: benefits – harvest cost)||Target-based and through $ value[note 27]||Flat (costs included in $ value)|
|47||Economic and cultural value of species[note 28]||Binary categories[note 29]||Threats from land use[note 30]|
|24, 54||Surface water supply||Biophysical quantity[note 31]|
|Water flow regulation||Biophysical quantity[note 32]|
|Soil retention||Erosion potential[note 33]|
|Soil accumulation||Biophysical quantity[note 34]|
|Carbon storage||Biophysical quantity|
|3 (see also Egoh et al. 40; Reyers et al. 55)||Carbon storage||Biophysical quantity||Target based[note 35]||Vegetation degradation[note 36]||Conservation of planning unit and opportunity costs[note 37]|
|Fodder provision[note 38]||Biophysical quantity||Target based||Stocking rates[note 39]||Conservation of planning unit and opportunity costs|
|Water recharge||Biophysical quantity[note 40]||Target based||Conservation of planning unit and opportunity costs|
|56 (see also Guo et al. 19)||Water retention[note 41]||Biophysical quantity|
|15||Water provision||Biophysical quantity[note 42]||Supply relative to demand[note 43]||Vegetation cover and loss[note 44]||Proxy of costs per unit area[note 45]||Capacity to pay for alternatives[note 46]|
|Flood mitigation||Biophysical quantity[note 47]||Captured in measures of flood activity and HPD in watershed||Annual change in forest and woodland cover[note 48]||Proxy of costs per unit area||Financial capacity to pay for alternatives (levee banks)|
|Carbon storage||Biophysical quantity||Proxy of costs per unit area|
|28||Carbon sequestration||Biophysical quantity||Land transformation[note 49]|
|Economic value of marketable produce (e.g., timber, rice and non-timber forest produce)||Qualitative ranking[note 50]||Inclusion of stakeholders[note 51]|
|Renewal of soil fertility||Qualitative ranking[note 52]|
|34||Sustainable bushmeat consumption||$ value||Probability of conversion factors in threat||Opportunity costs[note 53]||Market price of beef[note 54]|
|Sustainable timber harvest||$ value||Opportunity costs|
|Bio-prospecting[note 55]||Willingness to pay||Opportunity costs|
|Existence value||Willingness to pay||Opportunity costs|
|Carbon storage||$ value||Deforestation[note 56]||Opportunity costs|
|26||Carbon sequestration||Biophysical quantity[note 57]||Area constraint[note 58]|
|Carbon storage||Biophysical quantity||Area constraint|
|Grassland production of livestock||Biophysical quantity[note 59]||Variation in human population density[note 60]||Area constraint|
|Water provision||Biophysical quantity[note 61]||Area constraint|
|30[note 62]||Water quality||Biophysical quantity||Landscape change[note 63]|
|Storm peak mitigation||Biophysical quantity||Landscape change|
|Soil conservation[note 64]||Biophysical quantity||Landscape change|
|Carbon sequestration||Biophysical quantity and social value (in $)||Landscape change|
|57||Water supply||Biophysical quantity[note 65]||Identified beneficiaries[note 66]|
|Grazing provision||Biophysical quantity[note 67]|
|Tourism||Distance-based aesthetics[note 68]|
|58||Soil and water conservation[note 69]||Landslide, flood and drought prevention7[note 70]||Deforestation potential[note 71]|
|55||Forage production for livestock||Biophysical quantity[note 72]||Land-cover change[note 73]|
|Carbon storage||Biophysical quantity||Land-cover change|
|Erosion control||Vulnerability to erosion[note 74]||Land-cover change|
|Freshwater flow and quality regulation||Biophysical quantity[note 75]||Land-cover change|
|Tourism||Distance-based aesthetics[note 76]||Land-cover change|
|31[note 77]||Hydrological services||Biophysical quantity[note 78]||Human pressure index related to key biodiversity areas[note 79]|
|59||Carbon storage||Biophysical quantity[note 80]|
|29||Various[note 81]||$ value[note 82]||Land transformation[note 83]|
|60||Various[note 84]||$ value||Vulnerability of biodiversity[note 85]|
|41 (see also Bohensky et al. 43).||Freshwater provision||Biophysical quantity[note 86]||Water use and access[note 87]|
|Food provision||Biophysical quantity[note 88]||Dietary intake[note 89]|
|Wood fuel||Biophysical quantity (local production)||Local harvest rate|
|61||Carbon storage||Biophysical quantity||Deforestation rates and cover of protected areas||Opportunity costs|
|18||Carbon storage||Biophysical quantity||Probability of deforestation||Opportunity costs[note 90]|
|Water quality||Proxy[note 91]||Estimated downstream users[note 92]||Probability of deforestation|
Table 1 : Notes
1. Holland et al.48 used four indicators of river status – environmental quality index, taxon richness, habitat quality assessment and habitat modification index – to represent the capacity of river systems and catchments to provide freshwater ecosystem services. The authors argue that changes in the value of these indices reflect changes in the capacity of river systems to provide services such as maintaining water quality, controlling sedimentation and erosion, mitigating floods, cycling nutrients, and filtering pollutants.
2. Carbon stored in soils and vegetation. The authors conducted analyses at different grain sizes (4 km2 and 100 km2) and different spatial extents (Britain/England and 100 × 100 km squares across Britain) and examined variation across regions within Britain.
6. The number of day leisure visits as a measure of the recreational value of particular rural locations (this measure could be interpreted as the demand for recreational services).
10. Combining information on nest sites, floral resources and bee flight ranges to estimate pollinator abundance and likely visitation to agricultural areas.
11. The authors set targets to address the issue of demand (e.g., capturing 50% of total carbon stored in an ecoregion).
12. Costs are represented by the suitability of areas for conservation based on numerical values that reflect the degree of impediments to conservation success. For carbon storage it is a flat cost; the area of the planning unit.
14. The fraction of total flood control value, as a function of the number of housing units in the floodplain.
18. The sum of weighted values associated with developed land, agriculture, road density and length of human-induced patch edges.
21. A baseline target (assumed minimum requirement) of 12 days of outdoor recreation per person per year.
27. The authors pursued two approaches, a target-based approach and incorporating ecosystem services as extra costs or benefits in the cost layer.
28. This is a species-based approach so the priorities are based on species and their distribution across the landscape.
30. The magnitude of threats affecting each species based on major land uses. The loss of a species is equivalent to the loss of the service(s) that species provides.
33. Hotspots mapped as areas with severe erosion potential and vegetation and litter cover of at least 70% where maintaining the cover is essential to prevent erosion.
35. The authors assessed various scenarios for capturing ecosystem services based on incidental protection through the conservation of biodiversity or the inclusion of spatially explicit data on service distribution using Marxan. In Egoh et al.40, the authors set different target thresholds for capturing certain percentages of service provision for surface water supply, water flow regulation, carbon storage, soil retention and soil accumulation.
36. The authors estimated the amount of each ecosystem service provided by vegetation types under intact and degraded conditions. Measuring the difference between the two is indicative of the threat of degradation to service provision.
37. The cost of conserving a planning unit was equivalent to the value of irrigated cropping or grazing. The opportunity costs of conservation were addressed in terms of lost production. The authors included spatial variability in costs because values are per planning unit. In Egoh et al.40, catchment area is used as a cost layer (larger areas = greater cost).
39. The authors examined the relationship between fodder provision and stocking rates to determine the stocking rates that can be implemented without degrading the environment (i.e., sustainable stocking rates). Hence, over-stocking is considered implicitly as a threat to vegetation condition.
41. For example, for flood mitigation. The authors also examined opportunities for service enhancement.
42. Incorporating the density of people who rely on the service (beneficiaries) as density per watershed, and the water–production efficiency as water supply divided by area of watershed.
43. Water supply relative to demand adjusted for the need to redistribute supply within watersheds. Watersheds were supply does not (or only just) meets demand were prioritized.
44. Amount of vegetation cover and rate of vegetation loss with mid-range values designated as priorities.
45. A proxy was used representing resource and maintenance costs (e.g., land acquisition, infrastructure and labour) and considering watershed-level measures of income, population size and area.
46. Financial capacity to pay for alternatives to service provision such as dams and filtration plants.
47. Includes the trade-off between a high level of flood activity (number of floods, duration of floods and area affected) and a high level of impact on human populations (deaths and displacement, and human population density in watershed), and the costs of service protection.
48. As a proportion of all land. The authors examine also the opportunities for service enhancement through landscape restoration.
49. The authors used expert opinion to estimate possible land transformation within the next 5 years. This identified negative and positive changes to service provision.
51. The inclusion of stakeholders in the ranking process addresses to a degree the demand for services and/or the value of services to beneficiaries. This is an explicit incorporation of beneficiaries in the process.
53. The authors compared the ecosystem-service values to the cost of conserving the natural habitat that underlies their provision. The opportunity cost was calculated as the expected agricultural value of each forested parcel of land.
54. To estimate the economic value of bushmeat the authors used the local market price of a kilo of beef since domestic meat is a possible substitute for bushmeat. This approach implicitly recognises alternatives to service provision.
57. Net annual rate of atmospheric carbon added to existing biomass carbon pools (measured using a proxy).
58. The authors’ maximized service provision for a given ecoregion area constraint using optimization methods. Incorporating the issue of area constraints addresses costs, and the maximization goal gets somewhat at demand.
59. Annual production of livestock from grazing on unimproved natural pastures (expressed as tons of meat).
60. Beneficiaries were at the point of production only (where economic benefits are realized). The authors identified production peaks of water provision and grassland production in densely populated biodiversity hotspots, indirectly addressing the issue of spatial variability in demand.
64. Estimated through soil loss. Regions with lower potential soil loss were a priority, which implicitly recognises the importance of threats.
65. Water-supply function and flow regulation (mean annual catchment runoff and mean annual groundwater recharge).
68. Areas that tourists can see within a 10 km buffer surrounding the major tourist driving routes (see Reyers et al.55).
70. Landslide prevention considered in terms of landslide hazard; the more hazardous an area the more important it is to keep forest in place (an alternative perception of ‘demand’). Drought and flood prevention reflects water retention capability of forest.
71. Estimated using the proximity to settlements and roads (measures of access for deforestation), and distribution of the number of commercial species of trees (a measure of forest desirability for logging).
72. Carrying capacities for domestic stock expressed as the number of hectares required per large stock unit (hectares values were determined for pristine examples of habitat types).
73. The authors compared the potential delivery of ecosystem services from ‘pristine’ locations to that provided by degraded locations, estimating how landscape degradation may diminish the capacity of locations to provide a given service (an indirect assessment of threat).
74. The authors mapped areas vulnerable to erosion and classified them as high, medium and low erosion hazard. Habitat types provide erosion control where there is a high threat of erosion owing to factors such as topography, rainfall and soil (indirectly addressing the issue of threat).
78. The authors examined the threats to the biological value of key biodiversity areas (KBAs) based on a ‘human pressure index’ calculated from measures of human population density, road density, fire prevalence and agricultural suitability. They did not directly examine threats to ecosystem-service provision, but did this indirectly by looking at threats to the protection of KBAs, which were ranked based on their hydrological service value.
80. The number (and type) of services is a little ambiguous; it appears to be between 9 and 13 depending on the analysis. The authors also conducted analyses at three different spatial scales.
81. Ecosystem service values were expressed in dollar values of land units based on land cover and the services provided by particular land covers.
82. The authors deal with threat(s) to service provision indirectly by modelling the change in ecosystem service value with two alternative development scenarios.
83. The authors calculated the ecosystem-service values ($ value) for 17 different services and recognised variation in the spatial dependencies of services.
84. The authors assessed the vulnerability of biodiversity (‘threat’) and then determined the ecosystem-service value captured in biodiversity templates where low vulnerability is a priority and high vulnerability is a priority.
85. The authors calculated water availability (total and per person) and mapped supply and demand ratios.
86. Water availability per person was referenced against an accepted minimum target (1000 m3) set by the United Nations (hence, this target represents ‘demand’). The authors also calculated the percentage of the population with access to improved water and improved sanitation, and under five mortality per 1000 births.
87. The percentage contribution of carbohydrate and protein-supplying crops to total dietary intake.
88. Service provision is compared to recommended minimum daily intake (2100 kcal per person) and minimum daily intake of protein.
91. The authors did not calculate water quantity, but used a proxy for the supply of sediment-free water based on population data, land cover and water flow direction.