Research

INTRODUCTION

Human societies face a polycrisis of interconnected challenges, including biodiversity loss, climate change, pandemics, economic inequality, and financial system instability (Homer-Dixon et al. 2021). Resilience is an increasingly popular concept (Lade and Peterson 2019) describing capacities to deal with such threats. Research on social-ecological systems defines resilience as “a system’s capacity to cope with shocks and undergo change while retaining essentially the same structure and function” (Walker et al. 2009). Here, we focus on the resilience of livelihoods, which is “the issue of highest normative priority” in response to environmental change (Tanner et al. 2015). As the polycrisis deepens, it is critical to understand what factors affect resilience and how resilience can be built.

A recent advancement in resilience thinking is conceptualizing resilience as pathway diversity (Lade et al. 2020). According to the framework of pathway diversity, resilience is greater if more pathways are available to an actor, where a pathway is defined as a sequence of actions over time. In short, “resilience is greater if more actions are currently available and can be maintained or enhanced into the future” (Lade et al. 2020). This approach to resilience combines strengths of individual-based perspectives on resilience in terms of options available to an actor or responses available to species in an ecosystem (Elmqvist et al. 2003) and systems-based perspectives on resilience that incorporate feedbacks triggered by actions. It complements other approaches to assessing resilience (e.g., Enfors-Kautsky et al. 2021) by providing quantifiable, but context-sensitive, guidance for decision making. Pathway diversity is a promising new approach to understanding and operationalizing resilience, but so far has only been applied to idealized cases such as a farmer making stylized decisions on a farm (Lade et al. 2020).

Here, we apply the pathway diversity approach to the mosaic landscape surrounding Västra Harg, Sweden with the goals to (a) further develop and test the pathway approach for understanding resilience and, through that, (b) better understand how multiple actors and their strategies shape livelihood resilience in a mosaic landscape. Our analysis combines output from a knowledge co-production process that produced qualitative data from meetings, interviews, surveys, workshops, and webinars with semi-quantitative coding of these data and mathematical modeling to calculate pathway diversity. Our work is intended as an illustration of how pathway diversity could be applied to an empirical case and the insights it could bring and to trigger further discussion and refinement.

Cultural landscapes with mosaics of different land uses have long been recognized for hosting a wide range of values for people and biodiversity (Forman 1995), but their governance is complex. Through a patchy structure of different land uses, they provide renewable resources, such as food and timber, recreational and regulating services, as well as habitats for different species (Raudsepp-Hearne et al. 2010). Mosaic-type landscapes have often been portrayed as supportive of biodiversity and ecosystem services to a higher degree than landscapes shaped by spatial segregation of ecosystem functions and processes (e.g., Hölting et al. 2019). Cultural landscapes may also offer a broader suite of ways of relating to the landscape and tend to provide a more diverse set of ecosystem services (e.g., Foley et al. 2005). Sustaining mosaic landscapes thus aligns with calls for sustainable agricultural landscapes made in international agreements such as the EU Biodiversity Strategy for 2030 (European Commission (EC) 2020) and the Kunming–Montreal Global Biodiversity Framework (Convention on Biological Diversity (CBD) 2022). Land-use consolidation and intensification and changes in climate, national and international policy, and consumer demand, however, are threatening small-scale mosaic landscapes across the world (Bengtsson et al. 2003, Hanspach et al. 2014, Takeuchi et al. 2016).

The hypothesis that a more diversified mosaic of land uses produces a greater overall level of livelihood resilience (Speranza et al. 2014) has not been thoroughly tested. There is some evidence that dispersed governance among multiple actors in mosaic landscapes, including local governments, regional agencies, and landowners, provides redundancy and polycentricity (Biggs et al. 2015, Grêt-Regamey et al. 2019). Although positioned as a feature providing resilience (Biggs et al. 2015), this evidence also generates challenges for coordination and collective action and may complicate the development of a shared regional identity (Pouwels et al. 2011). The presence of extensive edges may also lead to fragmented landscapes and changing land uses, thereby reconfiguring spatial assemblages of different habitat resources, which will have implications for biodiversity (Forman 1995).

Set in this context, this paper investigates livelihood resilience as the ability to change between alternative uses of land to cushion stresses and disturbances (Speranza et al. 2014) and continue to make a meaningful living. Taking one step beyond diversification and safe-to-fail land-use portfolios, the pathways approach examines the relative ease of over time switching between alternative uses of the same land-use unit. We recognize and want to emphasize that livelihood resilience is but one way of assessing the resilience of different qualities of mosaic landscapes.

METHODS

To explore livelihood resilience as pathway diversity in the mosaic landscape of Västra Harg and its surroundings, we combine qualitative material from an empirical case study with conceptual modeling. Developing the methodology and results was a process of testing and refining in several iterations. Here, we present a linear narrative of the final set of methods: first, the study site; second, the knowledge co-production process that was conducted in this study site; third, coding and interpretation of these data to identify strategies, ease of transitions between strategies (accessibilities), and supporting interactions between strategies; fourth, using these outputs to calculate pathway diversity; and fifth, sensitivity analysis of the quantitative pathway diversity results.

To make pathway diversity suitable for the multi-actor and polycentric conditions of mosaic landscapes, methodological advances are needed to include multiple land-use strategies interacting with each other and to differentiate between strategies at different levels of organization, such as individual actor strategies vs. more collective strategies.

Study site: Västra Harg and its surrounding mosaic landscape

The core of the study area is Västra Harg nature reserve, a relatively small protected area (extent: 345 ha, category iv of the International Union for the Conservation of Nature (IUCN)) and Natura 2000 site managed by the Östergötland County Administrative Board (Länsstyrelsen Östergötland 2009). It is situated close to the village Västra Harg in Mjölby municipality (557.2 km²; 27,758 inhabitants) in southern Sweden (Fig. 1). Västra Harg is located in a transition landscape between agricultural plains in northern Östergötland County and primarily forests in the south (Länsstyrelsen Östergötland 2016, Zaman et al. 2022). Nature and people have interacted for millennia, shaping this area into a patchy landscape mosaic of oak woodlands, mixed forests, open fields, lakes, and wetlands (Garrido et al. 2017, Torralba et al. 2018). The case study area is also a mosaic in terms of landowners and users. Some of the landscape is owned by the local municipality; much is owned by private actors (mostly farmers or small-scale forest owners, but also homeowners); and some is owned by the Swedish church. Hence, individual actions and strategies are always embedded in a larger context where multiple actors pursue the same or different paths in parallel. Private landowners focus on farming, mainly meat and dairy production, hay-making and grains, or coniferous production forestry (Norway spruce (Picea abies (L.) Karst.) or Scots pine (Pinus sylvestris L.)) (Garrido et al. 2017, Milberg et al. 2019). Cultural ecosystem services are important across different stakeholder types, including recreation, tourism, hunting, and the aesthetic values connected to maintaining the open landscape (Garrido et al. 2017), and the landscape hosts a rich diversity of traditional grassland species and is part of Sweden’s largest area of oak wood–pasture landscapes, unique to Northern Europe (Fig. 2; Garrido et al. 2017).

On a county level, municipalities, the County Administrative Board, the regional authority, and the forestry agency have different, and sometimes overlapping, roles related to landscape management. The County Administrative Board developed a green infrastructure strategy in collaboration with different actors (Länsstyrelsen Östergötland 2018). It suggests implementing a mix of commercial oak forestry practices, voluntary set-aside, nature reserves, habitat protection areas, and nature conservation agreements. This is aligned with the integrated Swedish approach to conservation, which relies on voluntary measures across all land uses, and acknowledges that landscape governance is inherently shared across many stakeholders and levels of decision making (Appelstrand 2012).

Despite these efforts, the mosaic landscape surrounding Västra Harg is threatened by degradation, afforestation, and abandonment of species-rich oak woodlands, pastures, and meadows, similar to extensive agricultural landscapes in other parts of Sweden (Björklund et al. 2009, Andersson et al. 2015, Garrido et al. 2017). Climate change is increasing risks of droughts and wildfires, and species such as the spruce bark beetle and wild boars cause problems for forestry and agriculture (Andersson et al. 2020a). In times of unprecedented changes, management strategies need not only to accommodate plural interests but also to be flexible and resilient enough to navigate novel circumstances of climate change, market fluctuations, and policy changes.

Knowledge co-production process

A participatory, predominantly web-based knowledge co-production process was conducted from 2019–2021, focusing on how to maintain and develop the mosaic landscape surrounding Västra Harg. The process was one of four international case studies in ENVISION, an international research project on inclusive conservation (Raymond et al. 2022), and built on previous work in Västra Harg that mapped values in the landscape (Zaman et al. 2022).

Our two main partners were the green infrastructure team at Östergötland County Administrative Board and a local resident representing multiple village associations in Västra Harg. Through a series of conversations, meetings, and joint field-visits, they informed us about the case, provided contacts to study participants, and contributed to the design of the research process.

The co-production process aimed to foster inclusive stakeholder interaction and joint reflection and learning for managing the interconnections and tensions between interests and land uses across scales. An important objective was to build the capacity of local actors and stakeholders for developing resilient strategies for inclusive conservation (Andersson et al. 2020b).

The approach was adapted from a participatory resilience assessment (Enfors-Kautsky et al. 2021). Due to the COVID-19 pandemic, we primarily worked through online platforms. Participants included representatives from regional authorities, local landowners, businesses, and interest organizations. They were selected to represent a diversity of actors and interests in the landscape, including recreation and tourism, nature conservation, education and rural development, climate adaptation, and agriculture and forest production. The process included a series of consequent engagements, starting with interviewing 14 key participants, documented through note taking. The emerging outputs fed into a two-step online questionnaire-based survey on how to preserve the mosaic landscape surrounding Västra Harg. The first step (N = 61) focused on challenges and key issues. The second step (N = 45) focused on solutions, agency, and barriers. The outputs of these surveys fed into a webinar and an in-person workshop with 14 participants to discuss potential strategies at the individual and collective level, ranging from certification schemes to ecotourism initiatives. The process concluded with a webinar with 29 participants to present the outcomes and receive feedback. Although the ENVISION project is completed, knowledge co-production in Västra Harg continues through a local management council hosted by the County Administrative Board. This council, which was established following the participatory process, reflects the ongoing commitment to collaborative landscape management. More information on the process can be found in two ENVISION fact sheets (Andersson 2020a, b) and the appendices of this manuscript (Appends. 1, 2: Fig. A2.1, Table A2.1).

In this paper, we use qualitative data from the empirical case study as input and evidence for mapping strategies and for the parameterization of the conceptual modeling of pathway diversity. The data also helped us to interpret and discuss the results of calculating pathway diversity and performing the sensitivity analysis.

Coding and interpretation of qualitative data

We analyzed the qualitative outputs from the knowledge co-production process in the software NVivo (Bazeley and Richards 2000). The qualitative data used were primarily the results from the open survey questions, supported by notes from meetings, interviews, and workshops. Using these data, we coded information on collective and local actors’ strategies, as well as factors enabling change (such as good relations between landowners and authorities), factors hindering change (such as grazing damage from wild ungulates hindering planting of deciduous trees), and conflicting interests (mainly between production, conservation, and recreation interests). Within each of these categories we analyzed the data thematically (Patton 2002). Enabling and hindering factors particularly helped to address transitions and interactions between strategies. The qualitative data were triangulated and complemented by existing agricultural statistics of Östergötland county (Jordbruksverket 2020).

From the coded data, we:

1. Identified the strategies pursued by different actors, both current strategies and potential future strategies. These strategies are the key units of analysis in a pathway diversity approach to resilience, as they allow actors to respond to changing situations. As the complexity of analysis increases rapidly with the number of strategies, we identified a small number of general strategies for the initial analysis. We focused on strategies that are directly linked to land use and are currently active in Västra Harg or in nearby areas (e.g., the UNESCO Biosphere reserve in Östra Vätternbranterna).
2. Assessed the relative ease of switching between strategies in an “accessibility matrix.” For example, switching may be difficult if there are large costs or other obstacles associated with the switch. Alternatively, switching may be facilitated if there are large costs involved with maintaining the current strategy. In this paper, we focus on a semi-quantitative assessment of strategy accessibility. A deeper analysis of the many factors that influence the capacity or willingness to switch is important for management but beyond the scope of this work.
3. Explored interactions between two simultaneous strategies, that is, the extent to which pursuing one strategy supports another strategy, in a “supporting matrix.” For example, a supporting interaction may occur when spending to support one strategy supports the costs of another strategy. We considered these interactions important to include because they emerged as a frequent theme in our interview data.

The accessibility and supporting matrices are semi-quantitative interpretations of qualitative data. We continually checked to ensure the relative magnitudes of these matrix entries were consistent with the data. All interpretations of the data were reviewed through an expert assessment by three of the co-authors who have expertise in landscape management and actor perspectives in southern Sweden, including food system innovation, conservation, forestry, and agriculture (e.g., Andersson et al. 2015, Sellberg et al. 2020, Malmborg et al. 2022). See Append. 1 for examples of our process for coding the data.

To calculate the accessibility of abandoning an agricultural strategy (last column in Table 1), we used data on the rate of exit from farming (Jordbruksverket 2020; Append. 2: Table A2.2). These data provide transition rates as defined in Eq. (5); per that equation, we set the accessibility matrix entry so that its value divided by all entries for the same row gives the reported rate of exit from farming. Furthermore, the data reported the rate of exiting farming altogether, instead of the rate of abandoning a specific strategy on a plot, as needed for our model, which is likely a higher rate. In the absence of data on the relationship between these rates, we multiplied the resulting entries by a further factor of two to convert from rate of farm abandonment to rate of strategy abandonment.

Calculating pathway diversity

To make the pathway diversity approach suitable for the multi-actor and polycentric conditions of mosaic landscapes, we advanced pathway diversity methods in several ways: (1) to calculate pathway diversity more efficiently than the “brute force” approaches that have been used previously; (2) to differentiate between strategies at different levels of organization, i.e., individual actor strategies vs. more collective strategies; (3) to include multiple land-use strategies interacting with each other.

To simplify the calculation of pathway diversity, we considered a series of scenarios in which actors switch strategies at a rate proportional to the accessibility of the other strategy. Lade et al. (2020) used this assumption to measure pathway diversity in a simulation that repeatedly modeled an individual actor taking decisions, but this approach was computationally slow, due to every possible pathway having to be identified separately. We derived an alternative method (Append. 1) that improves the efficiency of this computation. This method shifts from stochastically modeling the decision pathway of a single actor to deterministically modeling the probability distribution of an actor over time.

We used a quantitative definition of pathway diversity (Lade et al. 2020), in which the pathway diversity S_i of an initial strategy i calculated to time horizon τ is

(1)

Here, P_ij(τ) is the viability of each pathway j that starts with strategy i and continues until time horizon τ. This formulation was inspired by the concept of causal entropy from physics (Wissner-Gross and Freer 2013), which is one of many entropy measures of diversity (Stirling 2007) that have theoretical foundations in information theory and statistical thermodynamics. Advantages of this mathematical definition of pathway diversity include: (a) it can account for weightings of transitions between strategies, rather than a binary “accessible” or “not accessible”; and (b) under this definition, pathway diversity is “additive” or “extensive,” in that the total pathway diversity of two independent sets of strategies is the sum of the pathway diversities of the two sets (we demonstrate this in Append. 1). The natural logarithm in Eq. (1) is needed to make pathway diversity, and entropy more generally, extensive (Wehrl 1978). The minus sign makes pathway diversity, and entropy more generally: (a) positive, as generally 0 < P_ij(τ) < 1 and the logarithm of a number in that range is negative; (b) increase with an increasing diversity of components.

In our new method, rather than computationally enumerating each possible pathway, pathway diversity at successive time steps can be iteratively calculated using the formula:

(2)

where

(3)

 

(4)

Here, the vector X(t) encodes the probability distribution of the actor’s strategy at time t, the matrix T(t) encodes the transition probabilities of each strategy from each other strategy at time t, and the vector S̃_i(t) represents the option diversities (that is, pathway diversity over a single time step) from each strategy at time t. Equation (3) states how to update the probability distribution in the next time step based on the probability distribution at the previous time step and the transition matrix T. Equation (2) states that the pathway diversity increases at each time step by the option diversity of that step weighted by the probability distribution of current strategies.

To implement these equations, we used the following calculation procedure.

1. Choose some starting strategy i.
2. Initialize the pathway diversity S to zero. Initialize the vector X to have value 1 in its ith element and all other elements to have value zero.
3. Calculate the probability distribution of strategies at the next time step with Eq. (3).
4. Update the pathway diversity value according to Eq. (2).
5. Repeat steps (c) and (d) until t reaches the desired time horizon τ.
6. Repeat all above steps for other starting strategies i.

We assumed that all actors can switch strategies once a year, and therefore, used a time step in the mathematical analysis above of 1 yr.

We first analyze pathway diversity for single local actor strategies. Therefore, we assume that one strategy is being pursued by a local actor and no landscape-scale strategies are active. Supporting interactions are, therefore, not relevant, and we set the transition matrix to:

(5)

where ||A(t)|| denotes the accessibility matrix A(t) with its rows normalized so that each row sums to 1. This normalization ensures that we maintain probability distributions X(t) that sum to 1.

We next examined the effect of supporting interactions by examining the pathway diversity resulting from two strategies being undertaken simultaneously. We used a transition matrix of the form TX(1 + UY), where U is the supporting interaction matrix and X and Y are the probability distributions of the two strategies. The precise implementation requires a generalization of Eqs. (2–4) to a higher dimension (Append. 1). As the pathway diversity of single strategies was already studied above, we focused on the changes to pathway diversity introduced by supporting interactions between strategies. To simplify our analysis, we examined pathway diversity results for multiple strategies only at a time horizon of τ = 30 yrs.

Sensitivity analysis

Finally, we performed sensitivity analyses of pathway diversity to individual entries in the accessibility and supporting matrices. Sensitivity analysis checks how much changes in these entries affects results, providing both a test of the robustness of our results to assumptions on specific quantifications and a priority order for future research. We performed a “one by one” sensitivity analysis, where we vary each matrix entry separately and measure how pathway diversity is affected. More sophisticated sensitivity analyses (Saltelli et al. 2008) are beyond the scope of this study.

We performed sensitivity analysis for both single strategies and strategy pairs. Examining the sensitivity of pathway diversity to supporting matrix entries (Append. 2: Fig A2.4) requires modeling pairs of strategies. Calculating the sensitivity of every strategy pair to every supporting matrix entry would produce a set of results too large to easily visualize and analyze. Instead, we calculated the sensitivity of the total pathway diversity, summed across all strategies except abandonment, to each entry in the supporting matrix.

RESULTS

Mapping strategies

In Västra Harg, we identified two levels of strategies: (a) Actor (e.g., user or manager) strategies on a specific plot of land (Table 2), and (b) Collective landscape-level strategies (Table 3). Of the actor strategies, we identified three main groups: forestry strategies, tourism and conservation strategies, and agricultural strategies. To limit the complexity of analysis, we only considered actors pursuing one strategy on each plot of land. We also include an “abandonment” strategy corresponding to the farmer or forester abandoning the strategy, for example, due to the cost of maintaining that strategy.

Assessing transitions and interactions

Our results show that most strategies can be accessed from other strategies (accessibilities arranged in matrix form in Table 1, supported by evidence described in Append. 2: Table A2.2). The only block of transitions that we found to be inaccessible in Västra Harg were moving from forestry strategies (except conservation) to agriculture, due to the large changes in technology, land cover, and farming practices required. Transitions between continuous cover forestry and ecotourism were the most accessible. Transitions from commercial forestry or conservation to continuous cover forestry were difficult due to the long time scales needed for returns on commercial forestry and the regulatory lock-in of conservation. Transitions between agricultural strategies were feasible, with transitions between fodder and food cropping easiest due to their similarity. We only analyzed transitions between local strategies for individual actors (Table 2), not for landscape-scale strategies, which would require a larger study incorporating the factors that influence landscape-scale resilience.

We also found a dense network of supporting interactions between two simultaneous strategies (arranged in matrix form in Table 4, supported by evidence described in Append. 2: Table A2.3). We analyzed two types of supporting interactions: the supporting effect of collective strategies (Table 3) on local actor strategies (Table 2) and the supporting effect of a local actor strategy on another strategy pursued by the same local actor. We found that strategies support each other in different ways (Append. 2: Table A2.3). Direct support, such as practical support of shared infrastructure, competence, and machinery among strategies, is generally stronger. For example, the strongest supporting interactions are where fodder crops provide food for cattle in milk and meat production. Indirect support is generally weaker, such as decreased vulnerability through economic diversification and maintaining a landscape that supports another strategy. For example, conservation can provide land for limited grazing dairy cattle (Append. 2: Table A2.3). Only two supporting interactions were negative, indicating that one strategy obstructs the other strategy: the effects of commercial forestry and food production on conservation (Table 4).

Pathway diversity: single strategies

Our results for single local actor strategies show different patterns on short and long time horizons (Fig. 3). If evaluated on a time horizon of less than about 10 yrs, all strategies show similar pathway diversity. This similarity is reasonable, as the strategies form two groups with similar structures for the accessibility of transitions. Specifically, (a) the forestry, tourism, and conservation strategies and (b) the agricultural strategies each have four strategies in total, of which two strategies can be relatively easily switched between (continuous cover forestry and ecotourism, and fodder and food production for agriculture, respectively) and two that are less accessible. Commercial forestry has slightly lower pathway diversity over these short time horizons due to the relative inaccessibility of other strategies from commercial forestry.

At time horizons longer than approximately 10 yrs, the forestry, tourism, and conservation strategies have higher pathway diversity than the agricultural strategies, especially compared with milk and meat production. We conjecture this relative decline in the pathway diversity of agricultural strategies is due to the risk of these actors, especially milk and meat producers, abandoning farming (see last column in Table 1). This assumption is tested in our sensitivity analysis below. The pathway diversities of all strategies increase at longer time horizons, which is as expected as a longer time horizon means more opportunities to switch strategies.

The transition time horizon at which the pathway diversity of different strategies begins to diverge is approximately 10 ys (Fig. 3). We expect that this transition time depends on how accessible strategies are from each other. We confirmed this hypothesis by showing that halving all accessibilities between strategies (all non-diagonal entries in Table 1) leads to doubling the transition time horizon to approximately 20 yrs (Append. 2: Fig A2.2).

We conclude that on short decision-making horizons, most of the strategies considered have similar resilience. Agricultural strategies may have decreased resilience due to the risk of abandoning a strategy on longer decision-making horizons, reinforcing the importance of examining long-term pathway diversity rather than only initial option diversity.

Pathway diversity: two strategies

Our results for two strategies show that supporting interactions increase the pathway diversity of all strategy pairs in Västra Harg (Fig. 4). This result is as expected, as supporting interactions generally increase the viability of other strategies. Among the strongest fractional increases were for local agricultural strategies supported by collective strategies (top right block of Fig. 4), especially milk production. This result may be due to these single strategies having the lowest pathway diversity (Fig. 3) and, therefore, being more sensitive to increased accessibility from supporting interactions.

The average strength of supporting interactions (Table 4) is 0.17, but supporting interactions increase pathway diversity by no more than 10%. This reduction (from 0.17 to 0.10) may be because the causal entropy formula used to calculate pathway diversity has a sublinear relationship between pathway viability and pathway diversity (Pij and S, respectively, in Eq. 1).

Sensitivity analysis

Accessibility of abandonment stands out as the accessibility matrix entries that most strongly affect the pathway diversity of single strategies. This result confirms the hypothesis introduced in the section “Pathway diversity: single strategies.” To increase farmer and forester resilience, therefore, it is most important to ensure they are not forced to abandon a strategy.

The pathway diversity of single forestry, tourism, and conservation strategies is also highly sensitive to the accessibility of agricultural strategies from commercial forestry (Append. 2: Fig. A2.3), which on short time horizons was the forestry strategy of least pathway diversity (Fig. 4). We note that in the baseline version of the model, switches from forestry, tourism, or conservation to agriculture are difficult (only conservation to fodder or food is allowed). The same sensitivity was not observed for the accessibility of agriculture from other forestry, tourism, or conservation strategies. We conclude that, when there are two modular sets of strategies, making one set accessible from the least resilient strategy of the other set can improve resilience overall.

Similarly, the diversity of pathways available when pursuing an agricultural strategy is sensitive to the accessibility of forestry, tourism, and conservation from agriculture. This result can be explained by noting that all forestry, tourism, and conservation strategies have higher pathway diversity than agricultural strategies.

We found that interactions that support commercial forestry decrease pathway diversity overall, with mixed results for supporting conservation (Append. 2: Fig. A2.4). We hypothesize that this result is due to commercial forestry and conservation having lower pathway diversity than the tourism and continuous cover forestry strategies. Therefore, these supporting interactions encourage, on average, switching to commercial forestry, which has a lower pathway diversity. This specific result is subject to the assumptions and quantifications made in this model. We can conclude, however, that an unintended consequence of some policies, such as land-based entrepreneurship, that support strategies of lower pathway diversity, such as commercial forestry, can decrease resilience overall.

The supporting interactions that most strongly influence total pathway diversity are the support of food and fodder production on continuous cover forestry and fodder and food production. These strategies have the highest pathway diversity within the agricultural and the forestry/tourism/conservation strategy groups, which presumably magnifies the effects of supporting interactions. Pathway diversity was not as sensitive to collective strategies (Table 3) as these actor strategies.

DISCUSSION

The mixed methods in this paper, combining the results of qualitative knowledge co-production and semi-quantitative modeling, contribute to the further operationalization of the pathways diversity approach to resilience studies. We have made several advances in using the pathway diversity approach for conceptualizing and measuring resilience, including: (1) applying the approach to a case with rich empirical data; (2) developing computational methods for pathway diversity, allowing pathway diversity to be calculated through iterative deterministic manipulation of matrices, rather than ensemble stochastic simulation as in previous work (Lade et al. 2020); (3) complementing “individual” with “collective” strategies; and (4) incorporating supporting interactions between pairs of strategies.

We will first discuss emerging insights from the analysis of actor strategies in the Västra Harg landscape for understanding livelihood resilience in mosaic landscapes in general. We then reflect on how we achieved those insights by discussing the methodological advancements and remaining limitations of the pathway diversity approach, along with possible future developments.

Lessons from a pathway diversity approach for understanding livelihood resilience in mosaic landscapes

Options to switch between strategies promote livelihood resilience

According to a pathway diversity view of resilience, access to more alternative (livelihood) strategies makes an actor more resilient. Previous studies have focused on actors and strategies within a specific sector, meaning that livelihood resilience can be understood also as “sector” resilience, e.g., more alternative farming styles increases the likelihood that farming continues (e.g., Darnhofer 2010, Lade et al. 2020). We focused instead on actor strategies within a specific landscape. In our case, an actor’s ability to switch between sectors on a given plot enhances the resilience of that actor’s livelihood. Owning and managing both farmland and forests has been a long-standing strategy in the region for building livelihood resilience, but one made less common by industrialization and upscaling (Ingemarson et al. 2006). Maintaining a mosaic landscape means ensuring that all existing land uses are maintained to some extent. More generally, land-sharing strategies (Sidemo-Holm et al. 2021), of which mosaic landscapes are an example, are likely to have higher livelihood resilience from a pathway diversity perspective than land-sparing strategies. However, we also found a potential trade-off between livelihood and landscape-level resilience (see section “Managing trade-offs across scales”).

Specifically, our analysis showed that some of the greatest improvements in livelihood resilience came with possibilities to switch between groups of strategies such as agriculture and forestry, or tourism/conservation. In Västra Harg, like in many other European landscapes (Plieninger et al. 2016), transitions from agriculture to forestry are more frequent than from forestry to agriculture. Intermediary steps between clusters of strategies could serve as bridges, or alternative opportunities. For example, the possibility of harvesting foliage (in Swedish “hamling”) for fodder was raised in the Västra Harg knowledge co-production process. However, as a less established strategy nationally, it would require continuous effort by local actors.

We recommend that landscape managers and national and EU governments build resilience from a pathway diversity perspective by promoting policies that make it easier for actors to switch strategies when needed. Actors encounter several barriers for switching strategies, including social, economic, and biophysical ones. Transitioning from commercial forestry to continuous cover forestry, for example, is hindered by norms of desirable ways of conducting forestry, the loss of investment from early felling, together with the time it takes for trees to reach maturity (Hertog et al. 2022). These barriers are likely worsened by agricultural and forestry policies, which often have focused on making single strategies more efficient (Winkel et al. 2022). Including collective strategies in a pathway diversity analysis helps to explore how to create an enabling context for switching strategies, which often is perceived as outside the scope of individual landowners and other local actors (e.g., Borgström et al. 2021).

Reducing the risk of abandonment

Our analysis showed that the risk of abandoning a strategy was particularly influential for pathway diversity, which explained why cattle farming with the highest risk of abandonment also had the lowest pathway diversity in the long-term (see section “Pathway diversity: single strategies”). The assumptions regarding abandonment were based on data on the number of farms decreasing over time (Jordbruksverket 2020), as well as, for example, the requirement to keep forested land under active management (or conservation) by law (Skogsstyrelsen 2022). The latter shows how the ability to avoid abandonment is, at least partly, shaped by the institutional context. Similar to the situation in other European agricultural landscapes of high biological value (Plieninger and Bieling 2013), further assistance for farmers to avoid abandoning livestock husbandry may be needed to increase the resilience of these individual actors and maintain landscape biodiversity. In Västra Harg nature reserve, grazing to preserve traditional grassland species currently relies on one large cattle farm, highlighting the vulnerability of this landscape function. We recommend that landscape managers and national and EU governments pay particular attention to policies that reduce the risk of abandonment.

Our analysis also showed that the possibility of coming back from abandonment is important for pathway diversity. However, finding and implementing alternative development pathways for abandoned land is notoriously difficult (Munroe et al. 2013) and has to build on strategies that require low investment, such as ecotourism (Lomba et al. 2020). Ecotourism was discussed in our knowledge co-production process as an unused potential to diversify landowners’ and users’ activities (Append. 2: Table A2.3).

Managing trade-offs across scales

In this analysis, we included interactions across scales, which raised potential trade-offs and considerations. First, pathway diversity of strategies changed over time (Fig. 3), which meant that there can be trade-offs between choosing a strategy with many options in the short-term, compared with one that has high pathway diversity in the long term. Second, there can be trade-offs between supporting a particular strategy and enhancing overall livelihood resilience. Policies that support one actor strategy more than others, can decrease overall livelihood resilience if that strategy has lower pathway diversity than alternative strategies. Such was the case for commercial forestry in our analysis, which had a lower pathway diversity than the tourism and continuous cover forestry strategies but is supported by policies such as land-based entrepreneurship. Third, our results indicate a trade-off between livelihood resilience and the resilience of the mosaic landscape. Our analysis showed that transitioning from agriculture into commercial forestry might increase pathway diversity in the long term for the individual actor by decreasing risk of abandonment. This study did not model landscape-level biophysical changes, but if several actors chose this transition, it would imply a continued afforestation on a landscape level, thereby threatening the maintenance of the patchy mosaic structure, its biodiversity, and other ecosystem services (Tuvendal and Elmqvist 2011, Malmborg et al. 2022).

For landscape managers and national and EU governments, it is important to consider multiple scales, as well as the full range of strategies in a landscape and assess how collective strategies affect them, e.g., by favoring some over others. This study considered a few collective-level strategies that arose from the knowledge co-production process (Table 3), but this is an area that needs further studies. Collective strategies, such as integrated landscape initiatives (García-Martín et al. 2016), could be key to balance between land-use strategies and coordinate individual actors toward a common aspiration of maintaining a mosaic landscape as a way to manage trade-offs.

Our results give general insights on the importance of considering multiple pathways, trade-offs, and unexpected consequences of supporting strategies with lower pathway diversity. Our analysis also obtained specific insights regarding the resilience of strategies in the Västra Harg region, e.g., that agricultural strategies have low resilience on long time scales due to the risk of abandonment. We caution against designing national or international policies based on these insights regarding specific strategies, because (a) our study was limited to one case, with no evidence to support generalization; (b) our decisions on system boundaries omit factors such as landscape-scale feedbacks; and (c) our modeling has currently unquantified uncertainties associated with pathway identification, model parameterization, and calculation of pathway diversity. Further research is needed to overcome these limitations, which we now describe.

Reflections on the pathway diversity approach

This article demonstrates that pathway diversity can be operationalized in an empirical case and that it yields results that are plausible, uncover unexpected patterns, and could potentially guide stakeholder actions. There are, however, many elements that could be developed in future research using pathway diversity, including:

(1) a co-production approach to studying pathway diversity. In this article, we applied a pathway diversity lens once data from the ENVISION project had already been collected through a participatory research process. Future research could explore how to engage actors in knowledge co-production and apply pathway diversity together, for example, as part of a participatory resilience assessment process (e.g., Enfors-Kautsky et al. 2021). In this way, assumptions could be further iterated and grounded, and the potential for social learning and capacity building among participants would increase.

(2) Incorporating social and environmental feedbacks. In this article, feedbacks are implicit through the viability of particular strategies, e.g., when we assume that continuous cover forestry is less accessible as fewer landowners have adopted this strategy, or that there is a strong identity of being a milk farmer as was apparent in one of the landowner interviews. A more detailed approach would explicitly include (i) biophysical feedbacks, such as changes in tree density or soil organic matter over time, (ii) feedbacks through social networks, such as influence on farmers by a critical mass of adoption by close relations in their social network (e.g., Centola et al. 2018) or by traditions and social identity (Marshall et al. 2012), and (iii) actor feedbacks, e.g., how levels of capitals such as financial capital or social capital change over time. Upcoming work on pathway diversity in the context of water management will explore feedbacks between actor decision making and water availability.

(3) Testing the pathway diversity approach in more contested contexts to explore if it helps shed light on issues of conflicts and power (e.g., López-Rodríguez et al. 2020). The difference in pathway diversity between the strategies of different actor groups could highlight their different resilience and vulnerability in the face of change.

(4) Optimizing for pathway diversity. Possible optimization methods include dynamic programming and its variants.

(5) Although the ambition of pathway diversity is to measure general resilience (Carpenter et al. 2012), it could be informative to model the response of our pathways and their diversity to specific drivers relevant to Västra Harg, such as land degradation, afforestation, droughts, wildfires, pests, market fluctuations, and policy changes.

(6) Systematic analysis of the uncertainties associated with estimation of the entries in the accessibility and supporting matrices, which were in turn used to parameterize our model. Such analysis would be important if a pathway diversity were to move beyond the exploratory study performed here into a tool to inform decision making.

(7) Exploring other diversity metrics. Causal entropy is based on a Shannon entropy definition of diversity, but there are many other metrics one could use to measure diversity (Stirling 2007). First, these other metrics could affect quantitative results and thereby interpretation of pathway diversity. Second, other metrics could incorporate other features of pathway diversity, such as characteristics of “disparity” (Stirling 2007) that could capture how similar in character different options are (Lade et al. 2020).

Our work includes an analysis of the sensitivity of pathway diversity to the accessibility and supporting matrix entries that we estimated from data. These results are useful to identify features of actor decision making in Västra Harg that should be the subject of focused future research or that are potential leverage points for policy making. However, many assumptions were made about switching strategies and interactions between strategies that could be refined and verified with additional data (Append. 2: Tables A2.2, A2.3). Our work included neither a parameter uncertainty analysis, which is appropriate for an exploratory modeling study (Kwakkel and Pruyt 2013), nor a structural uncertainty analysis of how results depend on the choice of strategies included in the analysis. Future work aiming to develop a more precise model of livelihood resilience in Västra Harg could use these analyses.

CONCLUSIONS

In a world of accelerating rates of changes, actor options and alternative strategies are essential attributes of livelihood resilience in mosaic landscapes. In this study, we adapted a pathway diversity approach to resilience analysis and applied it to the mosaic landscape of Västra Harg in southern Sweden. Pathway diversity complemented existing approaches to social-ecological resilience assessment by using an actor perspective, identifying tangible actor strategies, and letting a more systemic picture emerge from the analysis. The resulting multi-level perspective meant that the approach captured trade-offs, e.g., that increased resilience at the actor level could come at the cost of decreased resilience at the landscape level by accelerating afforestation. Policies often try to optimize a certain strategy within forestry and agriculture, whereas this approach instead promotes policies that make it easier for actors to switch strategies when needed and reduce the risk of abandoning strategies. Thus, it highlights the need for flexible and multifunctional land-use strategies, which generate several different ecosystem services and are less locked in by regulations, long-term decision cycles, or high investments. We conclude that pathway diversity complements existing approaches to resilience assessment to provide a more holistic understanding of resilience in mosaic landscapes. We think it is promising also for analyzing and managing other complex social-ecological systems with multiple actor strategies, such as coastal fisheries, watershed management, and urban green areas.

LITERATURE CITED

Albrektson, A., B. Elfving, L. Lundqvist, E. Valinger and Skogsstyrelsen. 2012. Skogsskötsel grunder och samband. Skogsskötselserien nr 1, Skogsstyrelsens förlag. https://www.skogsstyrelsen.se/globalassets/mer-om-skog/skogsskotselserien/skogsskotsel-serien-1-skogsskotselns-grunder-och-samband.pdf

Andersson, E., J. J. Kuiper, and M. M. Sellberg. 2020a. Promoting inclusive conservation in protected areas. ENVISION fact sheet. https://doi.org/10.5281/zenodo.4304053

Andersson, E., B. Nykvist, R. Malinga, F. Jaramillo, and R. Lindborg. 2015. A social-ecological analysis of ecosystem services in two different farming systems. Ambio 44:102-112. https://doi.org/10.1007/s13280-014-0603-y

Andersson, E., M. M. Sellberg, and J. J. Kuiper. 2020b. Building capacity for resilient and inclusive conservation of cultural landscapes. ENVISION fact sheet. https://doi.org/10.5281/zenodo.4386500

Appelstrand, M. 2012. Developments in Swedish forest policy and administration—from a “policy of restriction” toward a “policy of cooperation.” Scandinavian Journal of Forest Research 27(2):186-199. https://doi.org/10.1080/02827581.2011.635069

Bazeley, P., and L. Richards. 2000. The NVivo qualitative project book. Sage, London, UK. https://doi.org/10.4135/9780857020079

Bengtsson, J., P. Angelstam, T. Elmqvist, U. Emanuelsson, C. Folke, M. Ihse, F. Moberg, and M. Nyström. 2003. Reserves, resilience and dynamic landscapes. Ambio 32:389-396. https://doi.org/10.1579/0044-7447-32.6.389

Biggs, R., M. Schlüter, and M. L. Schoon, editors. 2015. Principles for building resilience: sustaining ecosystem services in social-ecological systems. Cambridge University Press, Cambridge, UK. https://doi.org/10.1017/CBO9781316014240

Björklund, J., L. Westberg, U. Geber, R. Milestad, and J. Ahnström. 2009. Local selling as a driving force for increased on-farm biodiversity. Journal of Sustainable Agriculture 33:885-902. https://doi.org/10.1080/10440040903303694

Borgström, S., E. Andersson, and T. Björklund. 2021. Retaining multi-functionality in a rapidly changing urban landscape: insights from a participatory, resilience thinking process in Stockholm, Sweden. Ecology and Society 26(4): 17. https://doi.org/10.5751/ES-12432-260417

Carpenter, S. R., K. J. Arrow, S. Barrett, R. Biggs, W. A. Brock, A. S. Crépin, G. Engström, C. Folke, T. P. Hughes, N. Kautsky, C.-Z. Li, G. McCarney, K. Meng, K.-G. Mäler, S. Polasky, M. Scheffer1, J. Shogren, T. Sterner, J. R. Vincent, B. Walker, A. Xepapadeas, and A. De Zeeuw. 2012. General resilience to cope with extreme events. Sustainability, 4(12):3248-3259. https://doi.org/10.3390/su4123248

Ceballos-Lascuráin, H. 1996. Tourism, ecotourism, and protected areas: the state of nature-based tourism around the world and guidelines for its development. International Union for the Conservation of Nature (IUCN) Protected Areas Programme. https://doi.org/10.2305/IUCN.CH.1996.7.en

Centola, D., J. Becker, D. Brackbill, and A. Baronchelli. 2018. Experimental evidence for tipping points in social convention. Science 360(6393):1116-1119. https://doi.org/10.1126/science.aas8827

Convention on Biological Diversity (CBD). 2022. The Kunming–Montreal global biodiversity framework. Convention on Biological Diversity, Montreal, Quebec, Canada. https://www.cbd.int/doc/c/e6d3/cd1d/daf663719a03902a9b116c34/cop-15-l-25-en.pdf

Darnhofer, I. 2010. Strategies of family farms to strengthen their resilience. Environmental Policy and Governance 20(4):212-222. https://doi.org/10.1002/eet.547

Djurskyddsförordning. 2019. Landsbygds- och infrastrukturdepartementet RSL. https://www.riksdagen.se/sv/dokument-lagar/dokument/svensk-forfattningssamling/djurskyddsforordning-201966_sfs-2019-66

Elmqvist, T., C. Folke, M. Nyström, G. Peterson, J. Bengtsson, B. Walker, and J. Norberg. 2003. Response diversity, ecosystem change, and resilience. Frontiers in Ecology and the Environment 1(9):488-494. https://doi.org/10.1890/1540-9295(2003)001[0488:RDECAR]2.0.CO;2

Enfors-Kautsky, E., L. Järnberg, A. Quinlan, and P. Ryan. 2021. Wayfinder: a new generation of resilience practice. Ecology and Society 26(2): 39. https://doi.org/10.5751/ES-12176-260239

European Commission (EC). 2020. EU biodiversity strategy for 2030. European Commission, Brussels, Belgium. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52020DC0380

Foley, J. A., R. DeFries, G. P. Asner, C. Barford, G. Bonan, S. R. Carpenter, F. S. Chapin, M. T. Coe, G. C. Daily, H. K. Gibbs, J. H. Helkowski, T. Holloway, E. A. Howard, C. J. Kucharik, C. Monfreda, J. A. Patz, I. C. Prentice, N. Ramankutty, and P. K. Snyder. 2005. Global consequences of land use. Science 309(5734): 570-574. https://doi.org/10.1126/science.1111772

Forman, R. T. T. 1995. Land mosaics: the ecology of landscapes and regions. Cambridge University Press, Cambridge, UK. https://doi.org/10.1017/9781107050327

García-Martín, M., C. Bieling, A. Hart, and T. Plieninger. 2016. Integrated landscape initiatives in Europe: multi-sector collaboration in multi-functional landscapes. Land Use Policy 58:43-53. https://doi.org/10.1016/j.landusepol.2016.07.001

Garrido, P., M. Elbakidze, and P. Angelstam. 2017. Stakeholders’ perceptions on ecosystem services in Östergötland’s (Sweden) threatened oak wood-pasture landscapes. Landscape and Urban Planning 158:96-104. https://doi.org/10.1016/j.landurbplan.2016.08.018

Grêt-Regamey, A., S. H. Huber, and R. Huber. 2019. Actors’ diversity and the resilience of social-ecological systems to global change. Nature Sustainability 2:290-297. https://doi.org/10.1038/s41893-019-0236-z

Hannerz, M., A. Nordin, and T. Saksa, editors. 2017. Hyggesfritt skogsbruk-en kunskapssammanställning från Sverige och Finland. Future Forests Rapport 2017: 1. https://www.slu.se/globalassets/ew/org/centrb/f-for/pdf/ff-rapport_hyggesfritt_skogsbruk_en_kunskapssammanstallning-2017-04-02.pdf

Hanspach, J., T. Hartel, A. I. Milcu, F. Mikulcak, I. Dorresteijn, J. Loos, H. von Wehrden, T. Kuemmerle, D. Abson, A. Kovács-Hostyánszki, A. Báldi, and J. Fischer. 2014. A holistic approach to studying social-ecological systems and its application to southern Transylvania. Ecology and Society 19(4): 32. https://doi.org/10.5751/ES-06915-190432

Hertog, I. M., S. Brogaard, and T. Krause. 2022. Barriers to expanding continuous cover forestry in Sweden for delivering multiple ecosystem services. Ecosystem Services 53: 101392. https://doi.org/10.1016/j.ecoser.2021.101392

Hölting, L., S. Jacobs, M. R. Felipe-Lucia, J. Maes, A. V. Norström, T. Plieninger, and A. F. Cord. 2019. Measuring ecosystem multifunctionality across scales. Environmental Research Letters 14(12): 124083. https://doi.org/10.1088/1748-9326/ab5ccb

Homer-Dixon, T., O. Renn, J Rockström, J. F. Donges, and S. Janzwood. 2021. A call for an international research program on the risk of a global polycrisis. SSRN preprint. http://dx.doi.org/10.2139/ssrn.4058592

Ingemarson, F., A. Lindhagen, and L. Eriksson. 2006. A typology of small-scale private forest owners in Sweden. Scandinavian Journal of Forest Research 21:249-259. https://doi.org/10.1080/02827580600662256

Jordbruksverket. 2020. Livsmedelskedjan i Östergötlands län: Fakta och statistik om produktion och konsumtion, Sammanställning maj 2020. https://jordbruksverket.se/download/18.2aaadab117518b8e8b0d6ae0/1602683799403/Regional-statistik-ostergotland.pptx

Jordbruksverket. 2021. Skötsel och stallmiljö för nötkreatur. https://jordbruketisiffror.files.wordpress.com/2020/12/regional-statistik-ostergotland-1.pptx

Kwakkel, J. H., and E. Pruyt. 2013. Exploratory modeling and analysis, an approach for model-based foresight under deep uncertainty. Technological Forecasting and Social Change 80(3):419-431. https://doi.org/10.1016/j.techfore.2012.10.005

Lade, S. J., and G. D. Peterson. 2019. Comment on “Resilience of complex systems: state of the art and directions for future research.” Complexity 2019:6343545. https://doi.org/10.1155/2019/6343545

Lade, S. J., B. H. Walker, and L. J. Haider. 2020. Resilience as pathway diversity: linking systems, individual, and temporal perspectives on resilience. Ecology and Society 25(3): 19. https://doi.org/10.5751/ES-11760-250319

Länsstyrelsen Östergötland. 2009. Skötselplan för naturreservatet Västra Hargs lö¨vskogar. https://www.lansstyrelsen.se/ostergotland/besoksmal/naturreservat/vastra-hargs-lovskogar-naturreservat.html?sv.target=12.382c024b1800285d5863a8b8&sv.12.382c024b1800285d5863a8b8.route=/&searchString=&counties=&municipalities=&reserveTypes=&natureTypes=&accessibility=&facilities=&sort=none

Länsstyrelsen Östergötland. 2016. Regional landskapsanalys för Östergötland. http://ext-dokument.lansstyrelsen.se/Ostergotland/Planeringskatalogen/Regionallandskapsanalysforostergotland.pdf

Länsstyrelsen Östergötland. 2018. Handlingsplan för grön infrastruktur i Östergötland. https://www.lansstyrelsen.se/download/18.2887c5dd16488fe880d67555/1538574250720/1%20Intro%20Övergripande.pdf

Lomba, A., F. Moreira, S. Klimek, R. H. Jongman, C. Sullivan, J. Moran, X. Poux, J. P. Honrado, T. Pinto-Correia, T. Plieninger, and D. I. McCracken. 2020. Back to the future: rethinking socioecological systems underlying high nature value farmlands. Frontiers in Ecology and the Environment 18:36-42. https://doi.org/10.1002/fee.2116

López-Rodríguez, M. D., I. Ruiz-Mallén, E. Oteros-Rozas, H. March, R. Keller, V. B. Lo, M. A. Cebrián-Piqueras, and R. Andrade. 2020. Delineating participation in conservation governance: insights from the Sierra de Guadarrama National Park (Spain). Environmental Science and Policy 114:486-496. https://doi.org/10.1016/j.envsci.2020.09.019

Malmborg, K., E. Enfors-Kautsky, L. Schultz, and A. V. Norström. 2022. Embracing complexity in landscape management: learning and impacts of a participatory resilience assessment. Ecosystems and People 18(1):241-257. https://doi.org/10.1080/26395916.2022.2061596

Marshall, N. A., S. E. Park, W. N. Adger, K. Brown, and S. M. Howden. 2012. Transformational capacity and the influence of place and identity. Environmental Research Letters 7(3): 034022. https://doi.org/10.1088/1748-9326/7/3/034022

Milberg, P., K.-O. Bergman, D. Jonason, J. Karlsson, and L. Westerberg. 2019. Land-use history influence the vegetation in coniferous production forests in southern Sweden. Forest Ecology and Management 440: 23-30. https://doi.org/10.1016/j.foreco.2019.03.005

Mukherjee, N., J. Huge, W. J. Sutherland, J. McNeill, M. van Opstal, F. Dahdouh-Guebas, and N. Koedam. 2015. The Delphi technique in ecology and biological conservation: applications and guidelines. Methods in Ecology and Evolution 6:1097-1109. https://doi.org/10.1111/2041-210X.12387

Munroe, D. K., D. B. van Berkel, P. H. Verburg, and J. L. Olson. 2013. Alternative trajectories of land abandonment: causes, consequences and research challenges. Current Opinion in Environmental Sustainability 5:471-476. https://doi.org/10.1016/j.cosust.2013.06.010

Patton, M. Q. 2002. Qualitative analysis and interpretation. Pages 431-534 in M. Q. Patton, editor. Qualitative research and evaluation methods. Sage, Thousand Oaks, California, USA.

Plieninger, T., and C. Bieling. 2013. Resilience-based perspectives to guiding high-nature-value farmland through socioeconomic change. Ecology and Society 18(4): 20. https://doi.org/10.5751/ES-05877-180420

Plieninger, T., H. Draux, N. Fagerholm, C. Bieling, M. Bürgi, T. Kizos, T. Kuemmerle, J. Primdahl, and P. H. Verburg. 2016. The driving forces of landscape change in Europe: a systematic review of the evidence. Land Use Policy 57:204-214. https://doi.org/10.1016/j.landusepol.2016.04.040

Pouwels, R., P. Opdam, and R. Jochem. 2011. Reconsidering the effectiveness of scientific tools for negotiating local solutions to conflicts between recreation and conservation with stakeholders. Ecology and Society 16(4): 17. http://doi.org/10.5751/ES-04191-160417

Raudsepp-Hearne, C., G. D. Peterson, and E. M. Bennett. 2010. Ecosystem service bundles for analyzing tradeoffs in diverse landscapes. Proceedings of the National Academy of Sciences 107:5242-5247. https://doi.org/10.1073/pnas.090728410

Raymond, C. M., M. A. Cebrián-Piqueras, E. Andersson, R. Andrade, A. A. Schnell, B. Battioni Romanelli, A. Filyushkina, D. J. Goodson, A. Horcea-Milcu, D. N. Johnson, R. Keller, J. J. Kuiper, V. Lo, M. D. López-Rodríguez, H. March, M. Metzger, E. Oteros-Rozas, E. Salcido, M. Sellberg, W. Stewart, I. Ruiz-Mallén, T. Plieninger, C. J. van Riper, P. H. Verburg, and M. M. Wiedermann. 2022. Inclusive conservation and the post-2020 Global Biodiversity Framework: tensions and prospects. One Earth 5:252-264. https://doi.org/10.1016/j.oneear.2022.02.008

Saltelli, A., M. Ratto, T. Andres, F. Campolongo, J. Cariboni, D. Gatelli, M. Saisana, and S. Tarantola. 2008. Global sensitivity analysis: the primer. Wiley, Chichester, UK. https://doi.org/10.1002/9780470725184

Sellberg, M. M., A. V. Norström, G. D. Peterson, and L. J. Gordon. 2020. Using local initiatives to envision sustainable and resilient food systems in the Stockholm city-region. Global Food Security 24: 100334. https://doi.org/10.1016/j.gfs.2019.100334

Sidemo-Holm, W., J. Ekroos, and H. G. Smith. 2021. Land sharing versus land sparing—what outcomes are compared between which land uses? Conservation Science and Practice 3(11): e530. https://doi.org/10.1111/csp2.530

Skogsstyrelsen. 2021. Hyggesfritt skogsbruk: Skogsstyrelsens definition. Rapport 2021/8. Norwegian Forestry Agency, Oslo, Norway. https://www.skogsstyrelsen.se/globalassets/om-oss/rapporter/rapporter-2021/rapport-2021-8-hyggesfritt-skogsbruk---skogsstyrelsens-definition.pdf

Skogsstyrelsen. 2022. Skogsvårdslagen. Norwegian Forestry Agency, Oslo, Norway. https://www.skogsstyrelsen.se/lag-och-tillsyn/skogsvardslagen/

Speranza, C. I., U. Wiesmann, and S. Rist. 2014. An indicator framework for assessing livelihood resilience in the context of social-ecological dynamics. Global Environmental Change 28:109-119. https://doi.org/10.1016/j.gloenvcha.2014.06.005

Statistics Sweden. 2020. Skyddad natur. MI 41 2020A01. Statistics Sweden and Swedish Environmental Protection Agency, Stockholm, Sweden. https://www.scb.se/contentassets/969d343fd8c648529810769f0542f35c/mi0603_2020a01_br_mi41br2101.pdf

Stirling, A. 2007. A general framework for analysing diversity in science, technology and society. Journal of the Royal Society Interface 4(15):707-719. https://doi.org/10.1098/rsif.2007.0213

Takeuchi, K., K. Ichikawa, and T. Elmqvist. 2016. Satoyama landscape as social-ecological system: historical changes and future perspective. Current Opinion in Environmental Sustainability 19:30-39. https://doi.org/10.1016/j.cosust.2015.11.001

Tanner, T., D. Lewis, D. Wrathall, R. Bronen, N. Cradock-Henry, N., S. Huq, C. Lawless, R. Nawrotzki, V. Prasad, M. A. Rahman, R. Alaniz, K. King, K. McNamara, M. Nadiruzzaman, S. Henly-Shepard, and F. Thomalla. 2015. Livelihood resilience in the face of climate change. Nature Climate Change 5(1):23-26. https://doi.org/10.1038/nclimate2431

Torralba M., N. Fagerholm, T. Hartel, G. Moreno, and T. Plieninger. 2018. A social-ecological analysis of ecosystem services supply and trade-offs in European wood-pastures. Science Advances 4:eaar2176. https://doi.org/10.1126/sciadv.aar2176

Tuvendal, M., and T. Elmqvist. 2011. Ecosystem services linking social and ecological systems: river brownification and the response of downstream stakeholders. Ecology and Society 16(4):21. http://doi.org/10.5751/ES-04456-160421

Walker, B. H., N. Abel, J. M. Anderies, and P. Ryan. 2009. Resilience, adaptability, and transformability in the Goulburn-Broken Catchment, Australia. Ecology and Society 14(1):12. https://doi.org/10.5751/ES-02824-140112

Wehrl, A. 1978. General properties of entropy. Reviews of Modern Physics 50(2):221-260. http://dx.doi.org/10.1103/RevModPhys.50.221

Winkel, G., M. Lovrić, B. Muys, P. Katila, T. Lundhede, M. Pecurul, D. Pettenella, N. Pipart, T. Plieninger, I. Prokofieva, C. Parra, H. Pülzl, D. Roitsch, J.-L. Roux, B. Jellesmark Thorsen, L. Tyrväinen, M. Torralba, H. Vacik, and G. Weiss. 2022. Governing Europe’s forests for multiple ecosystem services: opportunities, challenges, and policy options. Forest Policy and Economics 145: 102849. https://doi.org/10.1016/j.forpol.2022.102849

Wissner-Gross, A. D., and C. E. Freer. 2013. Causal entropic forces. Physical Review Letters 110(16):168702. https://doi.org/10.1103/PhysRevLett.110.168702

Zaman, S., S. Korpilo, A.-I. Horcea-Milcu, and C. Raymond. 2022. Associations between landscape values, self-reported knowledge, and land-use: a public participation GIS assessment. Ecosystems and People 18(1):212-225. https://doi.org/10.1080/26395916.2022.2052749