Integrated Valuation of Ecosystem Services: A Systematic Review of Socio-Biophysical Valuation Research

Abstract

Integrated Valuation of Ecosystem Services (IVES) has emerged as a pluralistic framework for bringing multiple forms of ecosystem service value into relation for environmental decision-making. Within this literature, socio-biophysical approaches have become especially prominent, most often comparing biophysical estimates of ecosystem service supply with social measures of demand-as-use. However, recent studies increasingly move beyond this supply–demand framing by operationalizing alternative social value constructs. This study conducts a scoping review of this emerging literature following PRISMA-ScR procedures. We identify 18 empirical socio-biophysical studies that compare biophysical supply with social value constructs other than demand-as-use. Across these studies, we identify three recurring constructs: perceived importance, perceived supply and recognition of ecosystem services. We examine how each construct is operationalized and how it is compared with biophysical supply. Our synthesis shows that social construct choice shapes the basis of socio-biophysical comparison, the spatial and analytical strategies available and the governance insights that can be drawn from integrated valuation. Perceived importance is most useful for identifying social priorities and anticipating public reception of management interventions. Perceived supply better supports spatial targeting, hotspot-based planning and comparison with modeled ecological supply. Recognition reveals awareness gaps and under-recognized services that can inform communication, education and participatory planning. By clarifying these construct-specific contributions, this review supports more targeted construct selection in future socio-biophysical IVES research.

1. Introduction

To inform environmental decision-making, ecosystem service valuation has developed across three broad approaches: economic, biophysical and social valuation [1,2,3]. Economic valuation estimates ecosystem service value in monetary terms, often through stated and revealed preference methods [4,5,6]. Biophysical valuation estimates the ecological supply of services based on landscape features, ecological functions and spatial processes [7,8,9]. Social valuation examines how people perceive, prioritize and appraise ecosystem services, often through surveys, interviews and participatory methods [10,11,12]. Grounded in distinct epistemological traditions, these approaches each capture a different dimension of value and generate a distinct form of evidence for environmental decision-making [13].

Accordingly, scholars have long argued that environmental decision-making is strengthened through the integration of evidence across multiple valuation approaches [14,15,16]. This argument rests on the premise that valuation approaches function as value-articulating institutions, each foregrounding particular dimensions of ecosystem service value while delimiting the forms of value that are recognized, formalized and made available for decision-making [13]. Economic valuation is often praised for advancing utilitarian arguments for conservation by making ecosystem services legible within monetary, market and cost–benefit frameworks [5,7,17,18]. Yet, it is less suited to examining non-market and relational values, including those associated with cultural services [19,20,21,22,23]. Biophysical approaches, including specialized modeling tools such as InVEST, are useful for estimating the ecological supply of services across landscapes, identifying spatial patterns of service provision and modeling potential trade-offs under alternative land-use or management scenarios [8,24,25]. However, modeled supply does not necessarily indicate service delivery, beneficiary experience, social importance or governance relevance. Social valuation helps address this limitation by capturing how ecosystem services are perceived, prioritized and interpreted by stakeholders within specific social and institutional contexts. However, it is also best used alongside biophysical approaches because perceptions and priorities do not, on their own, establish whether valued services correspond to ecological supply, ecological condition or the landscape processes that sustain service provision [26,27].

Building from the premise that different valuation approaches generate complementary forms of decision-relevant evidence, prominent science–policy organizations, including the Millennium Ecosystem Assessment (MEA) and the Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services (IPBES), have called for greater value pluralism in ecosystem service valuation [28,29,30]. In response, a growing body of empirical scholarship has demonstrated the feasibility and conceptual utility of integrated valuation approaches across diverse socio-ecological contexts [14,31]. Recently, these efforts have been formalized through the Integrated Valuation of Ecosystem Services (IVES) framework, which has emerged as an organizing science–policy process for interpreting the relationship between diverse forms of evidence [16]. In its simplest form, IVES can reveal whether particular ecosystem services are valued consistently across domains, indicating potential priorities for conservation, restoration or other forms of intervention. Its broader conceptual contribution, however, lies in its capacity to interpret divergence across valuation approaches. By comparing how different approaches assess the same services, IVES can clarify which dimensions of value are foregrounded or obscured by particular methods and identify trade-offs among value domains that would remain difficult to discern through any single valuation approach [16]. Integration, in this sense, rejects value monism (the aggregation of values into a singular measure) and embraces value pluralism, the idea that multiple valid measures of value can exist, each contributing a distinct lens through which to view the human–ecosystem wellbeing relationship [13,32].

Socio-Biophysical Integration

As the IVES agenda has rapidly gained traction, the integration of social and biophysical valuation approaches (known as socio-biophysical valuation) has emerged as a particularly promising direction. A sizable body of this work has developed through the Integrated Assessment of Ecosystem Service Supply and Demand (IAESSD) framework, which compares biophysical measures of ecological supply with social measures of demand for the same services [31,33]. In this framework, supply is conceptualized as the biophysical capacity of ecosystems to generate services based on underlying structures, processes and functions in each place and time, irrespective of whether those services are used or consumed [8,34]. Demand, by contrast, captures the social dimension of ecosystem services and conventionally has been operationalized as the actual use or consumption of services among beneficiaries [24,35]. By weighing supply and demand, IAESSD can diagnose where social demand is met or unmet and thereby guide ecosystem management and policy intervention [31].

Increasingly, however, the IAESSD framework has become conceptually stretched. A review of 38 IAESSD studies found that while research consistently examined supply as the biophysical construct, there exists growing variation in how studies operationalize social value, with many studies straying from demand-as-use [31]. These findings can be traced to the uneven methodological development of the two valuation approaches. The biophysical approach is considerably better defined [10], supported by an established agenda of ecological supply modeling [36,37]. By contrast, the social approach reflects a relatively younger body of scholarship, with fewer methodological norms established for defining what, precisely, is being valued [10]. Although demand-as-use was prominent in early social valuation research, more recent studies have operationalized alternative social value constructs, including ecosystem service recognition [11,38], the relative importance of services for societal and personal wellbeing [39,40] and the perceived supply of services [41,42]. As alternative social value constructs move into socio-biophysical IVES research, they expand the kinds of relationships that can be examined between ecological conditions and social valuation (Figure 1).

This represents an important opportunity for IVES because it moves the field beyond a relatively narrow supply–demand model and allows researchers to ask a wider range of decision-relevant questions about how people recognize, prioritize, perceive and respond to ecosystem services. However, this opportunity also creates a need for greater conceptual clarity. Different social value constructs do not simply provide interchangeable measures of the same social dimension [10]. Rather, they shape what is being studied, what kind of knowledge is generated and how social evidence can be meaningfully compared with biophysical supply. Construct selection can therefore change the basis of comparison, including the spatial scale of analysis, the analytical strategy used and the type of alignment or misalignment that can be interpreted. As a result, different constructs may generate different governance insights from the same general act of socio-biophysical comparison, shaping whether integrated evidence is used to identify social priorities, diagnose mismatches between ecological conditions and public perceptions, reveal under-recognized services, anticipate conflict or inform communication and management strategies. A clearer synthesis of this emerging literature is therefore needed to clarify the role of different social value constructs and guide more deliberate construct selection in future socio-biophysical IVES research. Such guidance is especially important for place-based environmental decision-making, where the most appropriate construct should be selected in relation to the ecological conditions, stakeholder concerns and governance challenges at hand.

To address this gap, this study presents a scoping review of socio-biophysical IVES research that compares biophysical supply with social value constructs other than demand-as-use. Through a review of empirical case studies, we identify three emergent social value constructs and examine how each is operationalized, compared with biophysical supply and interpreted as decision-relevant evidence. In doing so, we clarify how social construct selection shapes the form of socio-biophysical comparison and the governance insights that can be drawn from integrated valuation. We further assess the strengths, limitations and opportunities associated with these evolving research practices and situate our findings within broader socio-ecological system (SES) theories of plural valuation and knowledge integration.

2. Methods

We conducted a scoping review following the PRISMA Extension approach for Scoping Reviews (PRISMA-ScR) [43]. We selected this method because it is well suited to mapping the breadth of research activity in an emerging area, clarifying how studies have been conducted and identifying key concepts and knowledge gaps [44]. Unlike systematic reviews, which address narrowly specified questions and typically include critical appraisal of evidence quality, scoping reviews are designed to characterize the extent, range and nature of research and to summarize patterns across a heterogeneous evidence base [44]. This aligns with our objective of synthesizing emerging approaches to integrated socio-biophysical valuation of ecosystem services. A PRISMA-ScR checklist is provided in the Supplementary Materials.

2.1. Data Collection

We searched for empirical articles on the Clarivate Web of Science Core Collection (WoSCC) and on Google Scholar. To do this, we carefully considered which search terms were most appropriate. Recognizing that IVES terminology has been inconsistently applied through the literature, we opted to avoid search terms related to integration and instead structured our searches around “social” and “biophysical” terms to best reflect the value domains of interest. As the terms “valuation” and “assessment” are used synonymously in the literature, we implemented both as search terms.

Although this domain-based search strategy was intended to avoid privileging particular approaches to socio-biophysical integration, the ecosystem services literature remains terminologically diffuse. Adjacent terms such as “socio-cultural valuation,” “participatory mapping” and “cultural ecosystem services” may therefore capture relevant social valuation studies, but they also refer to broader methodological and conceptual traditions that do not necessarily involve comparison with biophysical values. For this reason, we did not include these terms in the primary search string, as doing so would have shifted the review toward social valuation more generally rather than the specific socio-biophysical comparison that defines the scope of this review.

Across all the stages, we restricted the results to original research articles and excluded review articles, proceedings papers, book chapters, early access publications, editorial material, data papers, letters and publications with an expression of concern. We applied no time restrictions.

The four search stages and their terms were as follows:

• WoSCC: “social” AND “biophysical” AND “ecosystem service assessment” (topic fields). This search returned 244 articles.
• WoSCC: “social” AND “biophysical” AND “ecosystem service valuation” (topic fields). This search returned 158 articles.
• WoSCC: “social” AND “biophysical” AND “ecosystem service” (topic fields). This search returned 760 articles.
• Google Scholar: “social” AND “biophysical” AND “ecosystem service valuation”. We screened the first 20 pages of results (200 articles).

Regarding the Google Scholar search, this stage was intended to function as a supplementary search. The threshold of the first 20 pages of results, corresponding to 10 articles per page and 200 records total, was used because Google Scholar ranks results by relevance and because precision declined substantially across successive results pages. To assess whether this threshold provided a defensible stopping point, we conducted a saturation check by screening an additional five pages of results using the same inclusion criteria. No additional articles meeting the inclusion criteria were identified in these additional results, suggesting that the first 200 records provided a defensible stopping point for this supplementary search.

2.2. Screening and Eligibility Criteria

Figure 2 presents the PRISMA-ScR flow diagram for article identification, screening and inclusion. Across the four search stages, 1362 records were identified, including 1162 from Web of Science and 200 from Google Scholar. Duplicate records were identified and removed after consolidating the results from the four search stages, with duplicates determined by matching article title, author information and publication metadata. After removing 217 duplicate records, 1145 articles were screened by title and abstract against the five inclusion criteria: (i) the article presented an ecosystem services valuation, (ii) the article examined value from both the biophysical and social domains, (iii) the article examined biophysical value as ecological supply, (iv) the article examined social value as other than demand-as-use or consumption, and (v) the article examined the same set of ecosystem services across both domains. This screening process excluded 1080 articles, leaving 65 full-text articles to be assessed for eligibility.

Of the 65 full-text articles assessed, 47 were excluded. Five articles were excluded because they did not examine value from both the biophysical and social domains. Twenty-five articles were excluded because they examined social value as demand-as-use or consumption. Seventeen articles were excluded because they did not examine an identical set of ecosystem services across the biophysical and social domains. The remaining 18 articles met all the inclusion criteria and were retained for review.

In applying criterion four, we defined social demand-as-use using the Burkhard et al. (2012) [24] definition of demand as the ecosystem services currently consumed or used in a particular area over a given period. Given the conceptual ambiguity surrounding the demand construct [31], we carefully evaluated both how social value was defined and operationalized. Articles were excluded only when social value was operationalized as the use or consumption of ecosystem services. Articles that labeled the construct as “demand” but operationalized it using terms conceptually distinct from use or consumption were retained. In several cases, this required consulting Supplementary Materials to verify the exact wording of survey items or prompts.

2.3. Data Extraction

For each retained article, we first extracted descriptive information including title, publication year, authors, journal, study region (continent), study site size (km²), and site characteristics (for example, national park, biosphere reserve, or World Heritage status) and the ecosystem services examined. Next, we characterized the social value construct(s) operationalized in each article, organizing them by thematic categories that reflect shared underlying meaning.

We then characterized the methodological approaches employed, recording each article’s respective social and biophysical approaches to valuation. Regarding the biophysical methods, we examined whether specialist ecosystem service modeling tools, such as InVEST, were used. We also examined if field measurements of ecological functions or structures were used. Regarding the social valuation methods, we recorded whether studies used questionnaires (surveys), qualitative interviews or observational approaches, participatory mapping, or mixed-method designs. We also extracted the social sample size (number of participants) and whether valuations were elicited from a general public sample or from defined stakeholder groups (for example, farmers, local residents, natural resource managers).

Next, we sought to characterize each article’s comparative analytical approach, defined as the primary mechanism used to compare social and biophysical values. Building from the reported social and biophysical methods, we documented whether comparisons relied on basic statistical techniques (for example, correlations, regressions, or cross-tabulations) and whether these were extended through spatial overlays or hotspot–coldspot analyses. We also recorded the spatial unit of analysis used for comparison (for example, land-use classes, grid cells or broader landscape units). In studies reporting social valuations across multiple stakeholder groups, we noted whether socio-biophysical comparisons were conducted separately by group or only in aggregate.

Finally, we summarized each article’s comparative socio-biophysical findings by classifying studies as showing either partial alignment or misalignment between social and biophysical values. This classification was conducted at the article level and was intended to capture how each article interpreted the relationship between value domains, rather than to impose a standardized numerical threshold across heterogeneous cases. Fixed empirical cut-offs were not appropriate for this review because the retained articles varied substantially in the number and type of ecosystem services assessed, the social constructs used, the biophysical indicators selected, the spatial units of comparison and the degree to which findings were reported at the service, stakeholder-group or landscape level. In many cases, articles did not report results in a form that would allow each ecosystem service, spatial unit or stakeholder comparison to be recoded independently into a common proportional metric. For this reason, our coding prioritized the authors’ reported interpretation of the socio-biophysical relationship while also recording the analytical basis on which that interpretation was made.

Studies were classified as showing partial alignment when the authors interpreted social and biophysical values as corresponding in at least part of the comparison. This included cases where alignment was service-specific, spatially uneven, limited to particular stakeholder groups or accompanied by divergence in other parts of the analysis. In spatial studies, we considered whether authors interpreted social and biophysical values for the same ecosystem services as overlapping in similar areas, diverging across priority areas or producing mixed spatial relationships. Studies were classified as showing misalignment when the authors interpreted the two domains as broadly divergent. This included cases where social and biophysical values showed limited spatial overlap, contrasting spatial patterns or substantially different priority areas. Because no retained study reported consistent correspondence across all the examined services, stakeholder groups and spatial units, no study was classified as showing full alignment. These categories therefore should be understood as interpretive summaries of each article’s reported comparative findings, rather than objective service-level classifications.

Finally, we assessed how each article characterized the implications of its findings for policy or decision-making. In the process, we focused on how articles connected the (mis)alignment between value domains to any aspect of environmental management, planning, governance or decision support.

3. Results

3.1. Study Characteristics

Our scoping review identified 18 articles that met all the inclusion criteria. This section summarizes the main characteristics of the included articles.

Articles were published across a diverse set of journals, including four in Ecological Indicators, three in Landscape Ecology, two in Ecosystem Services, two in AMBIO, and one in each Regional Environmental Change, Scientific Reports, Water Research, Journal of Arid Environments, Land Use Policy, Landscape and Urban Planning, and Applied Geography.

As described in

Table 1. Descriptive characteristics of 18 articles, including number of ecosystem services examined, region of study, site size, and site special characteristics.

Source	Number of ES Included	Region	Site Size (km2)	Site Special Characteristics
Martín-López et al., 2014 [15]	11	Europe	2201	European Biodiversity Hotspot, International Biosphere Reserve, World Heritage Site, National Park
Schwartz et al., 2022 [45]	5	Europe	481	Maerkische Schweiz Nature Park
Bagstad et al., 2016 [46]	3	North America	9011	Pike–San Isabel National Forest
Cebrián-Piqueras et al., 2017 [47]	5	Europe	Undefined	Wadden Sea National Park
Quintas-Soriano et al., 2019 [48]	7	Europe	Undefined	NA
De Vreese et al., 2016 [41]	25	Europe	164	European-wide Natura 2000 network area
Castillo-Eguskitza et al., 2018 [49]	12	Europe	220	Urdaibai Biosphere Reserve
Quintas-Soriano et al., 2014 [50]	1	Europe	12,207	New national park area under consideration
Minayeva et al., 2021 [51]	29	Asia	6000	Numto Nature Park
Chen et al., 2024 [26]	9	Asia	46,744	Contiguous special economic hardship area of Yanshan-Taihangshan Mountains
David et al., 2024 [32]	8	Europe	89,105	NA
Rooney et al., 2015 [52]	8	North America	Undefined	NA
Rodríguez-Caballero et al., 2018 [53]	8	Europe	Undefined	Cabo de Gata Nijar Natural Park and Special Protection Area
Cusens et al., 2024 [54]	6	Europe	Undefined	Nordhordland UNESCO Biosphere Reserve
Castro et al., 2014 [55]	5	Europe	2459	Sierra Nevada National Park
Xia et al., 2024 [42]	4	Asia	669	Qingpu District, the water conservation area for Shanghai
Bai et al., 2025 [56]	9	Asia	46,744	NA
Wei et al., 2018 [57]	6	Asia	22,900	NA

, the 18 included studies were geographically concentrated in Europe (11), followed by Asia (5) and North America (2). The number of ecosystem services examined varied substantially across studies, ranging from one to 29. Reported study site sizes also varied widely, from 164 km² to 89,105 km², although five articles did not report site size. Most studies were conducted in landscapes with notable conservation, cultural, or governance significance, including national parks, biosphere reserves, Natura 2000 sites, UNESCO-designated areas, and national forests.

3.2. Ecosystem Services

Across the 18 articles, the aggregate coding identified a total of 161 ecosystem service mentions (

Table 2. Description of the ecosystem services examined across the 18 articles included in this study.

Ecosystem Services	Frequency
Food and agriculture (incl. agriculture, traditional and intensive agriculture, crops, cultivated crops, food supply, food production, food provisioning, livestock, cattle, fishing, wild food, and yield)	20
Habitat and biodiversity (incl. habitat quality, habitat provision, habitat maintenance, habitats for species, biodiversity, habitat biodiversity, local species presence, maintenance of global biodiversity, and net primary productivity)	18
Climate regulation (incl. global climate regulation, climate adaptation, climate mitigation, air quality, and air purification)	12
Soil conservation and stabilization (incl. soil formation, soil fertility, soil protection, soil conservation, wind-breaking and soil-fixing, sand fixing, sand fixation, and landscape stability)	10
Recreation, leisure and tourism (incl. recreation, leisure, active recreation, tourism and recreation, tourism, ecotourism, nature tourism, and environmental tourism)	10
Subsistence products (incl. forage production, forage provision, haymaking for winter fodder, berry picking, mushroom picking, medical plant harvesting, and pine nut harvesting)	8
Erosion control (incl. erosion control and erosion prevention)	7
Aesthetics (incl. aesthetics, viewsheds, aesthetic experiences, aesthetic appreciation, and aesthetic enjoyment)	7
Water regulation (incl. water regulation, water flow maintenance, and water regulation and purification)	7
Flood regulation (incl. flood regulation, flood protection, flood control, and drought regulation)	6
Freshwater provision (incl. fresh water, freshwater provision, freshwater supply, water availability, local water supply, and groundwater recharge)	5
Water purification and quality (incl. water quality, water quality improvement, water purification, and local water purification)	5
Carbon sequestration (incl. carbon sequestration)	5
Timber and wood products (incl. timber, timber harvesting, wood production, timber and firewood, and birch bark harvesting)	5
Hunting (incl. hunting large herbivores, hunting large predator mammals, and game for fur hunting)	5
Sense of place and identity (incl. sense of place, regional belonging, local identity, and maintaining a traditional lifestyle)	4
Cultural heritage and sacred sites (incl. historical landscape protection, historical and cultural places, holy and sacred sites, and cultural heritage)	4
Existence and conservation value (incl. existence, value for conservation, and satisfaction for conserving biodiversity)	3
Education (incl. education and environmental education)	2
Scientific knowledge and research (incl. scientific knowledge and research opportunities)	2
Pollination	2
Other (incl. biological control, life-sustaining regulating services, nature conservation, social relations, therapeutic recovery, employment in agriculture, employment in nature and landscape management, regional products production, noise protection, nutrient regulation, infrastructure security, oil and gas production capacity, environmental capacities, and cultural services)	14
Total	161

). Food and agriculture was the most frequently identified ecosystem service category (20), followed closely by habitat and biodiversity (18). Climate regulation (12) was the next most commonly represented service, while soil conservation and stabilization (10) and recreation, leisure and tourism (10) were also frequently identified. Subsistence products appeared 8 times. Several services were represented at moderate levels, including erosion control (7), aesthetics (7) and water regulation (7), while flood regulation appeared slightly less often (6). Freshwater provision (5), water purification and quality (5), carbon sequestration (5), timber and wood products (5) and hunting (5) were each identified with the same frequency. Less commonly represented services included sense of place and identity (4), cultural heritage and sacred sites (4) and existence and conservation value (3).

3.3. Methods and Social Value Constructs

Among social valuation methods, quantitative surveys were the most common approach (13), followed by participatory mapping (6) (

Table 3. Description of the social value construct(s), social methodology, and biophysical methodology used in the 18 articles included in this study.

Source	Social Value Construct(s)	Social Method (Sample Size)	Biophysical Method (Model)
Martín-López et al., 2014 [15]	Perceived importance	Quantitative Survey (796)	Direct Measurement
Schwartz et al., 2022 [45]	Perceived supply	Participatory Mapping (30)	Direct Measurement
Bagstad et al., 2016 [46]	Perceived supply	Participatory Mapping (684)	Model (ARIES)
Cebrián-Piqueras et al., 2017 [47]	Perceived supply and perceived importance	Mixed, qualitative focus group discussion, supported by quantitative survey (11)	Direct Measurement
Quintas-Soriano et al., 2019 [48]	Recognition and perceived importance	Quantitative Survey and Participatory Mapping (411)	Model and Direct Measurement (InVEST, APLIS, and USLE)
De Vreese et al., 2016 [41]	Perceived importance	Participatory Mapping (38) with survey.	Direct Measurement
Castillo-Eguskitza et al., 2018 [49]	Perceived importance	Quantitative Survey (334)	Model (RUSLE and ESTIMAP)
Quintas-Soriano et al., 2014 [50]	Perceived supply and perceived importance	Quantitative Survey (465)	Model (APLIS)
Minayeva et al., 2021 [51]	Recognition	Interviews (54)	Landscape divided into 19 land classes. Biophysical traits assigned to these classes.
Chen et al., 2024 [26]	Perceived supply	Quantitative Survey (25)	Model (InVEST)
David et al., 2024 [32]	Perceived supply	Quantitative Survey (30)	Model and Direct Measurement (InVEST)
Rooney et al., 2015 [52]	Perceived importance	Quantitative Survey (73)	Direct Measurement
Rodríguez-Caballero et al., 2018 [53]	Recognition and perceived importance	Quantitative Survey (228)	Direct Measurement
Cusens et al., 2024 [54]	Perceived supply	Participatory Mapping (433)	Direct Measurement
Castro et al., 2014 [55]	Perceived importance	Quantitative Survey (340)	Model and Direct Measurement (APLIS, BCI, and USLE)
Xia et al., 2024 [42]	Perceived supply	Participatory Mapping (223)	Model (InVEST)
Bai et al., 2025 [56]	Perceived supply	Quantitative Survey (675)	Model
Wei et al., 2018 [57]	Perceived importance	Quantitative Survey (815)	Models (CASA, RUSLE, Budyko, RWEQ, and InVEST)

). Interviews appeared in one article and focus group discussions in one article, while mixed-method designs were used in three articles. Biophysical approaches were similarly varied, with articles relying on direct measurement (8), ecosystem service models (7), or combinations of both (3). Among the model-based approaches, InVEST was the most frequently used tool (5), followed by APLIS (3) and RUSLE (2), while ARIES, ESTIMAP, CASA, Budyko, RWEQ, and BCI each appeared once (1) (Table 3).

Across the 18 articles, three social value constructs were commonly used: perceived importance, perceived supply, and recognition of ecosystem services. Four articles examined more than one of these constructs, while the remaining 14 examined only one. Perceived importance was the most frequently used construct, appearing in 10 articles, followed by perceived supply in nine studies, while recognition appeared in three articles.

3.4. Socio-Biophysical Findings

Across the 18 articles, we characterized 11 as exhibiting a partial alignment between social and biophysical values. The remaining seven articles were characterized by misalignment (

Table 4. Description of the socio-biophysical findings, analytical focus, and relevance to policymaking described in each of the 18 articles included in this study.

Source	Summary of Socio-Biophysical Findings	Analytical Focus	Relevance to Policymaking
Martín-López et al., 2014 [15]	Partial alignment. General alignment for services such as climate regulation, biological control, and agriculture. General misalignment for services such as soil formation, biodiversity conservation, water quality, and ecotourism.	No spatial comparison. Examines how ecosystem service trade-offs appear or disappear depending on the chosen assessment approach.	Suggests misalignment is a problem of value pluralism and advocates for multi-domain approaches to support more democratic and ecologically informed decision-making.
Schwartz et al., 2022 [45]	Partial alignment. General alignment for water supply, carbon sequestration and biodiversity supply. General misalignment for erosion control and water availability.	Spatial comparison, including hotspot–coldspot analyses. Degree of alignment is presented using visual outputs, including side-by-side hotspot and coldspot maps.	Suggests that coldspot alignment can be used to prioritize areas for management intervention, while misalignment can highlight method-specific perspectives that are important for negotiation and conflict awareness.
Bagstad et al., 2016 [46]	Partial alignment. In general, aggregated biophysical and social values are disproportionately concentrated around designated wilderness areas and high-elevation landscapes, indicating broad-scale spatial alignment. General alignment for services such as water yield and carbon sequestration. General misalignment for services such as biodiversity and species richness.	Spatial comparison, including hotspot–coldspot analyses. Degree of alignment between social values and biophysical values is presented with visuals and regression analysis.	Suggests that overlaying (aggregated) social and biophysical values on one map is a useful tool to help resource managers visualize human–landscape relationships and areas of potential management synergies or conflicts. Suggests that hotspots are priorities for management actions and public engagement.
Cebrián-Piqueras et al., 2017 [47]	Partial alignment. The article compares social values to measured biophysical ecosystem properties. In general, significant links are identified; however, these relationships differed between the two stakeholder groups (farmers and conservationists) examined.	No spatial comparison. Comparative stakeholder analysis. Examines how farmers and conservationists differently value services, before comparing both groups’ social valuations to biophysical valuations.	Suggests social valuation to include comparative stakeholder analysis. Suggests that when integrating social–biophysical values, multiple stakeholders should be consulted to investigate how they may differentially attribute value.
Quintas-Soriano et al., 2019 [48]	Misalignment. General misalignment for services such as water regulation, climate regulation, and soil protection. Most misalignments are characterized by high biophysical valuation and low social valuation.	Spatial comparison. The study delineates a large study area into 160 subunits, reflecting local governance municipalities. These municipalities are grouped into bundles based on the services they provide—and socio-biophysical alignment is presented for each bundle.	By creating typologies of social–biophysical (mis)alignment, authors suggest various management or outreach interventions; for example, where social valuation is low relative to biophysical, they suggest incorporating public awareness into conservation and land-use strategies, promoting public participation in environmental planning, and reconnecting with landscapes.
De Vreese et al., 2016 [41]	Misalignment. Large misalignment between provision of wood, food, and regional products, and flood protection services, and moderate misalignment between carbon storage and erosion control services.	Spatial comparison, including hotspot–coldspot analyses. Additional variables such as landscape designations are also examined.	Suggest that participatory mapping can help identify areas that are important to local people and avoid conflicts when designing management measures that affect these services.
Castillo-Eguskitza et al., 2018 [49]	Partial alignment. Some alignment between habitat for species, fishing, and water purification. General misalignment for services such as agriculture, food from livestock, timber, freshwater, erosion control, recreation, nutrient regulation, and aesthetics.	Limited spatial comparison. The study region is divided into four contiguous units that reflect socio-economic characteristics. Therefore, four socio-biophysical comparisons are presented, one for each unit.	Suggests that identifying misalignment is important for sustainable ecosystem service management and for anticipating or resolving conflicts. Authors propose that these mismatch patterns can help policymakers and managers identify priority services and units where management efforts should be adjusted to better align ecosystem capacity with social expectations.
Quintas-Soriano et al., 2014 [50]	Misalignment. General misalignment for the service of water regulation, with social valuation higher than biophysical. No other services were examined.	Limited spatial comparison. The study divides the region into five landscape units. Therefore, five socio-biophysical comparisons are presented, one for each unit. For each landscape unit, a ratio of biophysical to social valuation is presented.	Regarding water regulation, it suggests that where social values far outweigh biophysical values, this is a useful indicator of unsustainability and potential social conflict.
Minayeva et al., 2021 [51]	Misalignment. General misalignment for services such as water and soil regulation and biota functions.	No spatial comparison. While biophysical values are calculated spatially, social values are not. Social valuations are generated from qualitative interviews and transformed (via service presence/absence) to support empirical comparison.	Suggests that misalignments can signal social vulnerabilities and guide land-use negotiations and management actions.
Chen et al., 2024 [26]	Partial alignment. General alignment for services such as food supply, habitat quality, and aesthetic appreciation. General misalignment for services such as freshwater provision, soil conservation, recreation and leisure, and carbon sequestration.	No spatial comparison. While biophysical values are calculated spatially, social values are not. Comparative analysis includes social subgroups defined by region (urban/rural), gender, age, income and education.	Suggests that when integrating social–biophysical values, multiple socio-demographic subgroups should be considered because these groups understand and value the same services in different ways.
David et al., 2024 [32]	Misalignment. General misalignment for services such as drought regulation, climate regulation, pollination, and habitat quality. Social values are consistently higher than biophysical values.	Spatial comparison. Two levels of spatial comparison are presented. First, an aggregate socio-biophysical comparison combining all eight services. Second, service-specific comparisons, with one spatial comparison for each of the eight services.	Suggests that, given the limitations inherent in each approach, relying solely on either biophysical or social valuation can mislead land-use planning. Suggests integrating both approaches to identify ecological realities alongside societal needs, in order to contribute to more balanced and inclusive policies.
Rooney et al., 2015 [52]	Misalignment. General misalignment for services such as biodiversity and ecological integrity.	Limited spatial comparison. The article compares social–biophysical valuation for four types of wetlands (natural reference sites, natural wetlands impacted by agriculture, created stormwater wetlands, and created stormwater ponds). Therefore, four socio-biophysical comparisons are presented, one for each type of wetland.	Suggest that, because stormwater management facilities provide much lower biophysical value than natural wetlands yet are highly valued by the public, they caution that combining biophysical and social scores into a single wetland “grade” may mask important trade-offs and allow continued loss of high-value natural wetlands. Author recommendations are tied directly to ongoing local-level wetland policies. They recommend using social values at broader planning scales, improving public understanding of wetland functions, and offering only partial compensation credit for stormwater facilities to incentivize better designs while avoiding net losses of wetland value.
Rodríguez-Caballero et al., 2018 [53]	Misalignment. General misalignment for regulating services, including soil regulation, erosion control, carbon sequestration, and air quality, and provisioning services including agriculture and tourism.	No spatial comparison. With a focus on biocrusts in two sites, both social and biophysical values are aggregated to the site level.	Suggests that the analysis reveals a critical misalignment: biophysical valuation highlights the importance of biocrusts for delivering regulating services, whereas social values prioritize agricultural and grazing outputs that threaten those same services. Authors call for management and conservation policies that explicitly recognize the biophysical capacity of biocrusts, address trade-offs between extractive land uses and biocrust health, and invest in environmental education and science–policy interfaces so that biocrust protection becomes a clearer priority in dryland planning.
Cusens et al., 2024 [54]	Partial alignment. General alignment for services such as biodiversity, agricultural products, wild food, and aesthetic value. General misalignment for services such as climate regulation, timber, and firewood.	No spatial comparison. The article compares social–biophysical valuation for four vegetation types (open heathland, broadleaved forest, pine forest, spruce plantation). Alignment is examined at both the level of the four vegetation types and overall, for each service.	Suggests that land-use decisions about abandonment versus afforestation should account for both biophysical and social values. Suggests that, in stewarding cultural landscapes, planners should recognize that different stakeholder groups (e.g., older farmers vs. non-farmers) value ES differently and calls for agri-environment schemes and broader public participation to maintain mosaic landscapes that balance provisioning, cultural, and regulating services.
Castro et al., 2014 [55]	Partial alignment. General alignment for climate regulation. General misalignment for services of cultivated crops, maintaining habitats, control of erosion, and water flow maintenance.	Limited spatial comparison. The study divides the region into six landscape units (sedimentary mountains, metamorphic mountain, sedimentary valley, coastal platform, high mountain, and saline marshland). Alignment is examined at the level of the six landscape units.	Suggests that areas of high value across domains are priority areas for conservation.
Xia et al., 2024 [42]	Partial alignment. General alignment for services of environmental capacities and cultural impacts. General misalignment for habitat maintenance and food production.	Spatial comparison. For each of the four ecosystem services examined, a separate spatial comparison is presented, with both graphical and statistical analysis.	Suggest that the relationships between socio-biophysical values can be conceptualized as: (1) low/low, (2) low/high, (3) high/low, (4) high/high. They discuss the implications of each orientation for management. For instance, high/high zones are a priority for conservation action, and low/low zones indicate where environmental management could be reduced.
Bai et al., 2025 [56]	Partial alignment. General alignment for services of food supply and freshwater supply. General misalignment for all supporting, regulating and cultural services.	Limited spatial comparison. The article presents social and biophysical values for each of the 11 counties in the study area. However, socio-biophysical comparison focuses on aggregated scores across all counties.	Suggests that, owing to consistent findings between this and other socio-biophysical research, specifically regarding the alignment for provisioning services, decision-making can be based on biophysical values alone. Additionally, the authors suggest that for regulating and supporting services, decision-making should be grounded in biophysical values as they are most reliable. Whereas the authors suggest that for cultural services, social values are useful for decision-making.
Wei et al., 2018 [57]	Partial alignment. General alignment for the services of water regulation and habitat. General misalignment for the services of cultivated crops, soil conservation, sand fixation, and climate regulation.	Limited spatial comparison. The article divides the region into four landscape units (high mountain, low hills, oasis, desert). Socio-biophysical comparison is presented for each of the four landscape units.	From the socio-biophysical findings, the authors make suggestions for local land planning and decision-making.

).

The articles employed a diversity of comparative analytical approaches to generate evidence through the comparison of socio-biophysical values. Eleven articles conducted spatially explicit comparisons. Of these, six employed high-granularity spatial analyses, using mapped overlays to visualize areas of convergence and divergence. Five articles conducted more limited spatial comparisons, relying on large spatial units such as municipalities, counties, or socio-economic regions. The remaining seven articles relied on aggregate, study-area-level comparisons and did not explicitly map socio-biophysical relationships. Only two articles conducted separate socio-biophysical comparisons for distinct stakeholder groups.

All articles described some link between the observed extent of (mis)alignment and the implication for policy and decision-making contexts. These links ranged from broad conceptual arguments about the importance of value pluralism and inclusive planning to more applied recommendations. Common themes included using extent of alignment to identify priority areas for management or conservation, to anticipate social conflict or sustainability risks, and outreach and communication strategies.

4. Discussion

This scoping review examined socio-biophysical IVES studies that compare biophysical estimates of ecosystem service supply with social value constructs other than demand-as-use. Across 18 empirical case studies, we identified three recurring social value constructs within this emerging body of scholarship: perceived importance, perceived supply, and recognition of ecosystem services. Although modest in size, this literature reflects an important shift in integrated valuation research away from a narrower demand-as-use framing of the social domain. That shift has introduced growing conceptual and methodological heterogeneity into socio-biophysical IVES, with limited clarity regarding how alternative social constructs shape comparison with biophysical supply and the forms of decision-relevant knowledge such comparisons produce. Our synthesis addresses this gap by showing that these constructs represent different ways of articulating the social dimension of ecosystem services and, in turn, influence the kinds of socio-biophysical evidence that are ultimately generated. We consider how these differences shape the interpretation of findings for environmental policymaking. From the patterns we identify, we offer guidance for selecting social constructs based on specific research and governance questions and situate these emerging practices within broader SES concepts and theory that can strengthen future applications of socio-biophysical IVES.

4.1. Social Value Constructs

4.1.1. Perceived Importance of Ecosystem Services

We found that ten of the 18 case studies examined perceived importance. It was most often elicited via a questionnaire (8), with two studies embedding importance scoring within qualitative designs (

Table 5. Description of the social elicitation method and associated operationalization of “perceived importance”.

Source	Elicitation Method	Operationalization
Martín-López et al., 2014 [15]	Survey questionnaire	Respondents selected which ecosystem services they perceived as most important (relative to others) for human wellbeing from a provided list of ecosystem services in the study area.
Cebrián-Piqueras et al., 2017 [47]	Focus group discussion followed by individual questionnaire	Farmers and conservationists rated the importance of ecosystem services associated with four vegetation units on a 0–100 scale.
Quintas-Soriano et al., 2019 [48]	Survey questionnaire	Respondents selected the four ecosystem services they considered most important for maintaining wellbeing or quality of life for residents or visitors, then ranked the selected services.
De Vreese et al., 2016 [41]	Interview, followed by survey and participatory mapping	Following the interview discussion, respondents scored the importance of ecosystem services at the local scale using a structured scoring table and then mapped them using PGIS.
Castillo-Eguskitza et al., 2018 [49]	Survey questionnaire	After being introduced to ecosystem services provided by the area, respondents identified their five most important ecosystem services for personal wellbeing and rated the importance of each selected service on a 1–5 Likert scale.
Quintas-Soriano et al., 2014 [50]	Survey questionnaire	Respondents assessed the importance of water regulation relative to other listed ecosystem services supplied in the study area, supported by visual aids (maps, panels, photographs).
Rooney et al., 2015 [52]	Survey questionnaire	Respondents rated which ecosystem services they felt were most important using a 4-point Likert scale—the survey was administered during a physical visit to each landscape type.
Rodríguez-Caballero et al., 2018 [53]	Survey questionnaire	Respondents selected the four ecosystem services they considered most important for maintaining wellbeing or quality of life for residents or visitors, then ranked the selected services.
Castro et al., 2014 [55]	Survey questionnaire	Respondents rated the relative importance of provisioning, regulating, and cultural ecosystem services to their lifestyle.
Wei et al., 2018 [57]	Survey questionnaire	Respondents selected up to four ecosystem services (from six) that they considered most important for their own wellbeing or the population’s wellbeing; importance was quantified as the percentage of respondents selecting each ecosystem service. Responses given relative to four landscape units.

).

As presented in Table 5, the “importance” construct was operationalized differently across articles. Several articles relied on terms related to social wellbeing; however, these varied in their referents, including general human wellbeing [15], personal wellbeing [49], the broader population’s wellbeing [57], and the wellbeing or quality of life of people living in or visiting the area [41,48,53]; one study framed importance relative to “lifestyle” [55]. As previously identified in Table 4, we found that perceived importance was rarely elicited with much spatial specificity (i.e., how the landscape spatially connected to each ecosystem service). One article examined importance without any spatial dimension [15], while others used landscape subunits such as contiguous socio-economic subregions [49], landscape-unit typologies [55,57], and ecosystem-type categories [52]. De Vreese et al. (2016) is the principal exception, using a participatory mapping workflow in which stakeholders scored services and then mapped locally important locations, which were aggregated into social “hotspots” comparable to biophysical and ecological hotspots for planning applications [41].

Despite variation in operationalization and spatial specificity, we found general trends in how studies interpreted their socio-biophysical findings. Misalignment between social and biophysical domains was treated as a warning that interventions grounded primarily in biophysical supply may conflict with what people prioritize, signaling where outreach or management adjustments may be needed to better align ecosystem capacity with social expectations [49,55,57]. Conversely, where values aligned, this was framed as suggestive of social support for conservation or protective actions [55]. De Vreese et al. (2016) extended this logic by using mapped importance hotspots as a practical planning input, explicitly positioning spatialized importance to identify socially salient areas and anticipate where management interventions may generate support or contestation [41].

4.1.2. Perceived Supply of Ecosystem Services

Across the 18 case studies, perceived supply was the second most frequently examined social value construct, appearing in nine articles. In contrast to perceived importance, which varied in how importance was framed, perceived supply was operationalized more consistently, with studies using language tied to ecosystem service supply and provision (

Table 6. Description of the social elicitation method and associated operationalization of “perceived supply”.

Source	Elicitation Method	Operationalization
Schwartz et al., 2022 [45]	Participatory mapping	Respondents mapped up to three areas they considered relevant for the supply of each ecosystem service and estimated perceived current supply levels for those areas as a percentage of an optimal state (0–100%).
Bagstad et al., 2016 [46]	Participatory mapping	Respondents marked locations on a paper map corresponding to ecosystem-related value types; mapped locations were used as a spatial proxy for perceived ecosystem service supply.
Cebrián-Piqueras et al., 2017 [47]	Mixed methods: focus group discussion supported by survey	Stakeholders ranked spatial units according to their perceived provision or support of ecosystem services using a 0–5 scale.
Quintas-Soriano et al., 2014 [50]	Survey questionnaire	Respondents assessed the perceived capacity of regional ecosystems to supply ecosystem services, expressed as generalized judgments of ecosystem service provision.
Chen et al., 2024 [26]	Survey questionnaire	Respondents rated the extent to which they felt they were receiving services or benefits from regional ecosystems using a 1–5 Likert scale.
David et al., 2024 [32]	Survey questionnaire	Respondents scored the potential of each land-cover class to deliver each ecosystem service on a 0–5 scale, where higher scores indicated greater perceived supply potential.
Cusens et al., 2024 [54]	Participatory mapping	Respondents placed spatial markers indicating locations where they perceived ecosystem services to be supplied, using a web-based PGIS platform.
Xia et al., 2024 [42]	Participatory mapping	Respondents marked up to five locations on a satellite image map indicating areas of perceived ecosystem service supply.
Bai et al., 2025 [56]	Survey questionnaire	Respondents rated the extent to which they felt they had received ecosystem services or benefits over the previous year using a 1–5 Likert scale.

).

Methodologically, perceived supply was often elicited via participatory mapping approaches. While some participatory mapping approaches relied on emerging digital technologies [45,54], others used paper-based approaches that involved respondents marking locations directly on hard-copy landscape maps [42,46]. Designs also varied in whether mapping captured location only or paired locations with an intensity layer. For example, Schwartz et al. (2022) elicited both the spatial location of each service and perceived supply magnitude at those locations using a 0–100 scale [45].

Where examined, spatially explicit comparisons between biophysical supply and perceived supply were framed as a core contribution to environmental policymaking. For instance, Schwartz et al. (2022) argue that when biophysical and perceived supply converge at high levels, those places provide clear candidates for targeted management, while divergence between the two measures identifies places where stakeholders and models point to different priorities, increasing the need for negotiation and conflict awareness [45]. Bagstad et al. (2016) similarly position overlays of aggregated biophysical and perceived supply as practical decision-support layers that help managers visualize human–landscape relationships, anticipate synergies or tensions and prioritize hotspots for management action and public engagement [46].

4.1.3. Ecosystem Service Recognition

Ecosystem service recognition was the third most frequently examined social value construct, appearing in three articles. Notably, given this small evidence base, we are cautious in discussing the generalizability of our associated findings.

As presented in

Table 7. Description of the social elicitation method and associated operationalization of ecosystem service “recognition”.

Source	Elicitation Method	Operationalization
Quintas-Soriano et al., 2019 [48]	Survey questionnaire	Respondents completed a free-listing task identifying all ecosystem-related benefits they considered relevant; recognition was operationalized as the spontaneous mention of ecosystem service benefits.
Minayeva et al., 2021 [51]	Interviews	Semi-structured interviews elicited stakeholders’ perceived connections to ecosystem services; recognition was operationalized as the frequency and type of ecosystem services mentioned in relation to specific land uses in the study area.
Rodríguez-Caballero et al., 2018 [53]	Survey questionnaire	Respondents completed a free-listing task identifying all ecosystem-related benefits they considered relevant; recognition was operationalized as the spontaneous mention of ecosystem service benefits.

, recognition was elicited through two approaches, including an open-ended questionnaire and interview prompts.

Both questionnaire approaches asked respondents to describe ecosystem-related benefits provided by the study region in their own words, without any prompts or predefined options. These open-ended responses were then thematically coded to the most applicable ecosystem service [48,53]. The interview approach operationalized recognition as the frequency of ecosystem services mentioned during a semi-structured interview [51]. Both approaches intentionally avoid predefining which services should be evaluated, in contrast to importance and perceived-supply designs that typically elicit perceptions across a predetermined service list. As a result, recognition-based assessments reveal which services are cognitively visible and readily articulated, and where socially salient benefits diverge from biophysically supplied functions.

4.2. Selecting a Social Value Construct

Our synthesis indicates that social construct choice shapes socio-biophysical integration by determining spatial comparability, the type of evidence produced, and the subsequent governance inferences derivable.

Among the articles that examined perceived importance, socio-biophysical comparisons often focused on whether areas of high ecological supply also corresponded with elevated perceptions of importance. Our synthesis suggests that this relationship was uncommon. Services in relatively low biophysical supply were often still assigned high social importance. Consistent with prior research, one explanation is that respondents may rank services as important because they are perceived to be scarce, limited, or insufficiently available [38]. In this sense, perceived importance may capture judgments of scarcity as much as, or more than, comparative judgments about the relative importance of one service against others [58,59]. This tendency should be considered when interpreting related findings. We also found that because perceived importance is typically elicited as a generalized judgment about a landscape, place, or region, it offers only limited support for fine-scale spatial assessment. Consequently, the policy-relevant inferences it generates tend to remain broad.

Perceived supply, by contrast, reduces the conceptual asymmetry between the focal social and biophysical constructs by positioning both around supply. This provides a more direct basis for cross-domain comparison and, because perceived supply is often elicited through participatory mapping, it more readily supports spatial overlay with biophysical supply. These comparisons can then be extended through hotspot–coldspot diagnostics, offering a particularly useful basis for prioritization and targeted intervention in applied policymaking contexts [46,60].

Recognition appears to capture a different social dimension, namely the cognitive visibility of ecosystem services. However, because only three reviewed studies examined recognition, the findings associated with this construct should be read as exploratory. In the articles reviewed here, recognition-based comparisons suggested that integrating recognition with biophysical supply may help reveal epistemic blind spots by identifying services that are strongly supplied but only weakly recognized across landscapes. Recognition was typically elicited through free-listing or other open-ended prompts. These approaches avoid predefined response categories and are often valued for reducing framing effects by limiting the degree to which external information is embedded in the instrument [11]. At the same time, open-ended elicitation is sensitive to variation in ecosystem service knowledge and can produce systematically uneven responses across participants. Regulating services, in particular, may be less likely to be recognized because they are linked to less visible and more complex ecological functions [11].

4.3. Considerations for Future Research

Across the 18 articles reviewed, authors drew a wide range of decision-relevant inferences from socio-biophysical comparison. However, relatively few studies situated those inferences within a broader conceptual framework capable of explaining why alignment or misalignment between social and biophysical values matters for environmental decision-making. This creates an important opportunity for future IVES research. If socio-biophysical valuation is to move beyond documenting whether social and biophysical values correspond, future studies need clearer conceptual tools for interpreting what different forms of alignment or misalignment reveal, how they matter for governance and how they can inform planning under changing environmental conditions.

One useful interpretive framework is PΔI, proposed by Williams et al. (2018), which conceptualizes the relationship between perceptions (P) and instrumented measures (I) of environmental conditions [27]. The difference between these domains is represented as delta (Δ), capturing the degree of alignment or divergence between what people perceive and what is measured. Although PΔI was not developed for ecosystem service valuation specifically, it offers a useful way to interpret socio-biophysical (mis)alignment in IVES. In this context, social value constructs such as perceived importance, perceived supply, or recognition can be understood as perception-based representations of ecosystem services, while biophysical models or field-based indicators provide an instrumented representation of ecosystem service supply.

This is significant because PΔI links the size of Δ to the likelihood of adaptive or maladaptive responses [27]. Since environmental decisions often begin from perception, smaller deltas may indicate circumstances where social judgments are more closely aligned with underlying ecological conditions. Larger deltas, by contrast, may indicate circumstances where actions guided primarily by social perceptions risk overlooking ecological dynamics, thereby increasing the possibility of maladaptive management. This logic is consistent with Rooney et al. (2015), one of the studies reviewed here, who found that social perceptions of wetland ecosystems corresponded poorly with biophysical supply [52]. In particular, respondents attributed important regulating services to artificial wetland systems that were not capable of delivering those services [52]. Read through PΔI, such findings do not diminish the relevance of social values. Rather, they clarify why social and biophysical evidence need to be interpreted together. Perceptions remain decision-relevant because they often shape how environmental problems are recognized, prioritized and acted upon, while instrumented measures provide a complementary means of assessing how well those perceptions correspond to ecological conditions.

A second opportunity for future IVES research is to extend socio-biophysical comparison into forward-looking planning contexts. Much of the reviewed literature treats integration as a static, point-in-time comparison between current social values and current biophysical supply. However, environmental decision-making often requires anticipating how land-use change, climate pressures or management interventions may alter both ecological supply and social priorities over time. Alternative future methodologies provide one way to address this need [61]. Notably, consideration of alternative futures is already present in the respective biophysical [61,62] and social ecosystem service valuation studies [11], indicating the viability of this research direction for socio-biophysical research designs.

Together, the PΔI framework and alternative futures methodologies point toward a more explicitly interpretive and planning-oriented agenda for socio-biophysical IVES. PΔI helps clarify why alignment and misalignment matter, while alternative futures provide methods for examining how those relationships may change under different management scenarios.

4.4. Limitations

This review should be interpreted in light of several limitations. First, the ecosystem services literature remains conceptually and terminologically diffuse [63], particularly in how studies describe integration, social value, and socio-biophysical comparison. As a result, some relevant studies meeting the inclusion criteria were likely difficult to identify through standardized search terms alone. Second, the evidence base remains modest and geographically uneven, with the included studies concentrated primarily in Europe, which may limit the broader generalizability of the patterns identified here. In addition, while recognition of ecosystem services emerged as one of the three social value constructs identified, it appeared in only a small number of studies. Findings related to recognition should therefore be interpreted as exploratory, rather than as providing construct-selection guidance comparable to perceived importance or perceived supply. Future work should further examine recognition as an emerging social value construct, including whether and how it produces distinct forms of decision-relevant evidence when compared with more established constructs in socio-biophysical IVES. Third, our classification of social value constructs and socio-biophysical alignment necessarily involved interpretive judgment and some compression of place-based variation. This simplification was necessary to support cross-study comparison in an initial review of an emerging and conceptually heterogeneous body of scholarship. At the same time, it reduces some of the differences in how individual studies define, measure, and interpret socio-biophysical relationships. Future research could build on this foundation by developing more fine-grained typologies of social value constructs, analytical strategies, and forms of socio-biophysical (mis)alignment.

5. Conclusions

Across 18 empirical case studies, we identify three recurring social value constructs, perceived importance, perceived supply, and recognition, and show that these constructs are not interchangeable because they enable different forms of socio-biophysical comparison, support different spatial inferences, and produce different kinds of decision-relevant evidence. Importance-based comparisons are most useful for diagnosing priorities and anticipating public reception of management options, perceived supply is especially useful for spatially explicit prioritization and conflict-aware planning, and recognition reveals which services are cognitively visible or under-recognized relative to biophysical supply. Social construct selection, therefore, should be treated as a design choice tied to the governance question at hand.