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Landscape and Urban Planning 203 (2020) 103905 Contents lists available at ScienceDirect Landscape and Urban Planning journal homepage: www.elsevier.com/locate/landurbplan Assessing the sustainability of contrasting land use scenarios through the T Socioecological Integrated Analysis (SIA) of the metropolitan green infrastructure in Barcelona Roc Padróa, María José La Rota-Aguileraa,c, Annalisa Giocolib, Jacob Cirerab, Francesc Colla, ⁎ Manel Ponsa, Joan Pinoc, Silvia Pilia, Tarik Serranoa, Gara Villalbad,e, Joan Marulla, a Barcelona Institute of Regional and Metropolitan Studies, Autonomous University of Barcelona, E-08193 Bellaterra, Spain b Redaction Service of the Barcelona Metropolitan Area Master Plan, Barcelona, Spain c Center for Ecological Research and Forestry Applications, Autonomous University of Barcelona, E-08193 Bellaterra, Spain d Department of Chemical, Biological and Environmental Engineering, Autonomous University of Barcelona, E-08193 Bellaterra, Spain e Institute of Environmental Science and Technology, Autonomous University of Barcelona, E-08193 Bellaterra, Spain A R T I C LE I N FO A B S T R A C T Keywords: Urban development and the sprawl of transport infrastructures have disregarded the crucial function of me- Land use policy tropolitan landscape in provisioning human well-being and biodiversity. This research aims to contribute to the Socioecological transition challenges of Planning for Sustainability by proposing a Socioecological Integrated Analysis (SIA) to support the Social metabolism Land Use Master Plan in the Barcelona Metropolitan Area, to conciliate urban development with the perfor- Ecosystem services mance of surrounding open spaces. The paper evaluates four different land cover scenarios (current, trending, Multi-criteria analysis Organic agriculture alternative and potential), and two kinds of agricultural management (conventional and a socioecological transition towards organic agriculture). The results suggest that although there are significant improvements on job provisioning and nutrient-cycling closures (circular economy), certified organic agriculture is not enough to overcome some trends of industrialized agrarian systems such as low energy efficiency or poor improvements in greenhouse gas emissions. The results also show a crossed effect between social metabolism and landscape ecology where changes in the management could affect the landscape functioning while changes in the land covers are particularly affecting the resource use. Then, deeper changes that consider together land use and metabolic flows are required to promote more sustainable agroecological transitions. The SIA model is an im- portant conceptual and methodological step forward that facilitates the transition towards sustainable land use policies. 1. Introduction 2007). Simultaneously, this metropolitan growth has often increased administration costs in order to maintain basic functions of the open Creating metropolitan areas capable of conciliating population rise spaces for the provisioning of ecosystem services required by society and the landscape ecological functioning should be a priority for (Benedict and McMahon, 2002, Tzoulas et al., 2007, Sandifer et al., planning cities and communities, in accordance to the 2030 UN 2015). Sustainable Development Goals (SDG). Building sustainable cities re- In order to overcome these trends towards a more sustainable quires achieving the targeted objectives of participatory, integrated and economy, one of the main challenges of future cities and their me- sustainable human settlement planning and management (UUNN, tropolitan communities is how to provide close, sustainable and safe 2015). However, up to now urban development has mainly gone by food for their population while contribute to a more circular economy hand with the disconnection of cities from the surrounding territories (FAO, 2011). Along the decades of the green revolution, western due to globalized markets, the loss of natural areas, landscape frag- agrarian activities simplified their complex socioecological functioning mentation, natural resources and ecosystem services degradation, and a resulting in a loss in territorial and resource use efficiency (Gingrich reduction on nature's capacity to respond to anthropogenic global et al., 2018, Marull et al., 2019). This affected both landscape func- changes (Antrop, 2004, Calvo-Iglesias et al., 2006, Tratalos et al., tioning and metabolism in open spaces. Hence, although there is a ⁎ Corresponding author. E-mail address: joan.marull@uab.cat (J. Marull). https://doi.org/10.1016/j.landurbplan.2020.103905 Received 29 April 2020; Received in revised form 8 July 2020; Accepted 23 July 2020 Available online 30 July 2020 0169-2046/ © 2020 Elsevier B.V. All rights reserved. R. Padró, et al. Landscape and Urban Planning 203 (2020) 103905 growing trend advocating for the need of an agro-ecological transition towards a Planning for Sustainability. However, despite the develop- (Aguilera et al., 2020, Gliessman, 1998), it is necessary to develop ments of a new socioecological approach, currently there is a lack of methodologies aiming to understand its feasibility and impacts from a models to assess the land planning on the multifunctionality of the multi-criterial perspective to better understand its potentials and green infrastructure (Maruani and Amit-Cohen, 2007). In order to shortcomings beyond its economic viability (Marull et al., 2020). In this guarantee a meaningful land Planning for Sustainability and advance in sense, planning towards this socio-ecological transition of agriculture the knowledge of the metropolitan systems and the complexity of the towards more sustainable management should aim, at least, at four decisions making processes, multi-criteria and multi-scale analysis are objectives. The first one would imply to reduce the external inputs needed to facilitate the necessary deliberative processes (European needed for agriculture (i.e. fertilizers, animal feed, seeds) (Tello et al., Commission, 2013). This strategy is also an imperative by current 2016). The second, to optimize material and energy flows between food policy roadmaps in order to identify the role of the green infrastructure production and animal husbandry (i.e. closing energy and material in providing ecosystem services, nature-based solutions, climate change cycles at landscape scale (Tello and González de Molina, 2017). The mitigation and adaptation, and maintaining natural capital (European third, to improve the autonomy of farms by promoting functional di- Commission, 2013; Hansen and Pauleit, 2014). versification and biodiversity by implementing more integrated and In this paper, we use an improved version of the Socioecological complex types of farming (Marull et al., 2016). And the last but not Integrated Analysis (SIA) (Marull et al., 2020), a particularly compre- least, to strengthen climate change adaptations and contributing to net- hensive model of the landscape-scale social metabolism that includes its zero emissions policies (Aguilera et al., 2015). Accordingly, a quanti- main structural, functional and managerial dimensions, to integrate fication of energy and matter flows inside agricultural systems is es- social metabolism variables into land planning, through the quantifi- sential to understand how socio-metabolic exchange configures land cation of the metabolic flows of the green infrastructure land uses. The uses, and landscapes that must provide vital food security and eco- work has two specific objectives. First, it aims to explore alternative but system services for cities. feasible horizons of the Barcelona Metropolitan Area (BMA) by ap- Nowadays, multidimensional and multiscale governance ap- plying the SIA to different theoretical land use scenarios defined by the proaches have become important decision-making tools for land plan- Land Use Master Plan (PDU for its acronym in Catalan) of the BMA. ning, particularly in metropolitan areas. However, many of these Second, it aims to particularly assess the socioecological implications of models remain superimposing an environmental economics approach a transition in the agrarian system from the current conventional over an ecological economics, through cost-benefit methodologies, management to an organic one. leading to a prioritization of economic growth as a key criterion for decision-makers (Thomas and Littlewood, 2010, Martínez-Alier et al., 2. Methodology 1998). Then, only when the biophysical benefits to the metropolis are valued with a multi-criterial perspective, the socioeconomic pressures 2.1. Case study to the green infrastructure can be reduced (Thomas and Littlewood, 2010). Also, this process would allow understanding some issues that The Barcelona Metropolitan Area (BMA) is comprised of 36 muni- often remain out of focus with the classical cost-benefit analysis: the cipalities in a total area of 63,611 ha (Fig. 1) and has a population of 3.3 environmental externalities, the asymmetry of information, and the of million people (Idescat, 2020). According to the newest Land Cover open spaces as public goods in a wider perspective (Weimer and Vining, Map of the BMA (CREAF, 2015), open spaces are still the predominant 1992). land covers (55%) distributed among forests and scrublands (42%), As a response to these challenges, over the last years four conceptual croplands (8%), pastures (3%) and other open spaces (2% water cor- developments have enriched territorial development and land planning ridors and bare soil). The remaining 45% of the surface are built-up debates by interaction with other disciplines such as ecological eco- areas including compact and spread urban areas, urban parks, roads nomics or landscape ecology. The first one is social metabolism as a and other infrastructures. Agriculture is concentrated along the lower methodological and theoretical framework from ecological economics valley and the Delta of the Llobregat River, although some patches of to understand and quantify nature-society interactions (Fischer- arable land, vineyards and arboriculture still form mosaic patterns with Kowalski, 1997). This approach allows the adoption of a reproductive forests in the Vallès plain and the slopes between sparsely populated point of view, fundamental to identify what are the system’s biophysical areas. requirements to maintain the ecological functioning of renewable re- The BMA has a metropolitan institution that seeks to integrate and source sources (Padró et al., 2019). Second, ecosystem services provide a create flexible, efficient and democratic governing tools to decide crucial approach that recognizes the non-economic values of the nature strategic policies for the correct management and development of the and the human activities as key elements for the sustainability of the metropolis (Martí-Costa, 2018). This is fundamental for planning po- urban areas (Martínez-Alier et al., 1998; MEA, 2005). This concept has licies to harmonize and frame a consensus to achieve sustainable cities proved to be particularly useful at highlighting all the non-commodified (11th goal of the SDG; UUNN, 2015). The General Metropolitan Plan values of nature and the impact that human activity generates on these from 1976 set the foundations of land use planning basis for the urban values (Bastian et al., 2012). Third, acknowledging green infrastructures expansion up to 2014. After 38 years a new process was launched to as socioecological systems allows land planners to overcome the his- achieve a new consensus under the Urban Master Plan (PDU). The torical limitation of focusing urban planning to built-up spaces Action Plan for the PDU considers 3 structural elements that constitute (Benedict and McMahon, 2002). The role of green infrastructure is the socioecological system: i) urban and social structure; ii) mobility gaining importance as the definitions of a landscape are becoming more and utilities infrastructures; and iii) the green infrastructure (BMA, complex (Fischer and Lindenmayer, 2007), drifting away from a clas- 2019). The current study focuses on the green infrastructure in order to sical landscape ecology view of discrete elements such as patches, provide tools and evidence on the priority and strategic areas of in- corridors and matrix (Forman, 1995). Finally, the notion of cultural terest, the potentials and challenges of different types of management landscape where its different elements (both social and natural) interact, and planning and on the most relevant synergies and trade-offs among through innumerable processes that characterize the functioning of the dimensions of the role of green infrastructure in the socioecological territory as a system as a result of a relation between nature and society system. To this aim, the SIA model can be an effective tool. in a given site-specific context (Marull et al., 2010, Agnoletti, 2006). Together, the above-mentioned frameworks provide the conceptual 2.2. Socioecological Integrated assessment bases for a paradigm shift towards an updated approach for land planning, redirecting the focus onto processes rather than just land uses The Socioecological Integrated Assessment (SIA) (Marull et al., 2 R. Padró, et al. Landscape and Urban Planning 203 (2020) 103905 Fig. 1. Land cover map (2015) of the Barcelona Metropolitan Area (BMA). Source: CREAF, 2015. Fig. 2. Conceptual framework (a) and experimental design (b) for the evaluation of land cover scenarios and agricultural practices (conventional vs organic) with the Socioecological Integrated Analysis (SIA). Source: Our own modified from Marull et al. 2020. 2020) is a metabolic-territorial model that evaluates the contribution of indicators (Table 1): energy efficiency (A1), energy-landscape integra- the green infrastructure to the whole socioecological system of the BMA tion (B1), landscape complexity (C1), non-renewable energy input (D1), considering six interrelated dimensions (Fig. 2a): A. Metabolic effi- nutrient recirculation (E1A), carbon stock (E1B), agricultural produc- ciency, B. Biodiversity conservation, C. Landscape functioning, D. tion (E1C), and, finally, agricultural jobs (F1). Indicators C1 and E1B Global change, E. Ecosystem services and D. Social cohesion. Each of depend directly and only on the land cover arrangement of each sce- these six dimensions is assessed through one or more principal nario, hence they will only present differences among land cover 3 R. Padró, et al. Landscape and Urban Planning 203 (2020) 103905 Table 1 Socioecological Integrated Analysis (SIA) of the Metropolitan Green Infrastructure. Dimensions, indicators, methodological description and references. Dimension Indicator Description A. Metabolic efficiency A1. Energy efficiency Evaluates in energy terms the relation between the returned biomass obtained by the agricultural activities and the external inputs used by measuring the External Final Energy Return On Investment (EFEROI; Tello et al. 2016) B. Biodiversity conservation B1. Energy – landscape Simultaneously evaluates the landscape complexity (C1) and the agricultural metabolic flows (A1) as a proxy integration for the conditions to host biodiversity (ELIA; Marull et al. 2016) C. Landscape functionality C1. Landscape complexity Simultaneously evaluates the landscape heterogeneity and the ecological connectivity (Marull and Mallarach, 2005) D. Global change D1. Non-renewable energy Evaluates the input of external non-renewable energy (Tello et al. 2015) as a proxy of greenhouse gas emissions. E. Ecosystem services Support E1A. Nutrient recirculation Estimates the amount of phosphorus that return to the agricultural system taking into account the rest of land use and the livestock system (Marco et al. 2018). This work used phosphorus as the reference nutrient after checking that it is the limiting one in nutrient cycling of nitrogen, phosphorus and potassium. Regulation E1B. Carbon stock Measures the stock of carbon that is present in soil, roots and woody aerial structures of the open spaces (Doblas-Miranda et al. 2013) by integrating several different territorial sources. Supply E1C. Agricultural production Evaluates the agricultural production of each land use available that exits the agroecosystem (orchards, greenhouses, dry grassland and irrigated land, fruit trees of dry land and irrigation, olive trees of dry land and irrigation and vineyard) F. Social cohesion F1. Agricultural jobs Characterizes the potential of Agrarian Workers Units required to maintain agrarian activities in open spaces (Padró et al. 2017) scenarios and not between agricultural management scenarios. areas and urban parks and leading to a decrease in forests, scrublands The selection of socioecological indicators has been done according and agricultural areas. In the alternative scenario (S2), change from to the main objectives for the green infrastructures’ planning in the PDU planned urban parks to productive agricultural areas is proposed. Fi- Action Plan. The conceptual definition of these indicators was done nally in the potential scenario (S3) an important recovery of the pre- through a semantic categorisation together the technicians in charge of existing agricultural areas in the BMA is set (identified through an the redaction of the PDU so as to ensure its usefulness of the multi- historical land cover map of 1956). Land uses, specifically crop surface criteria assessment in the deliberative processes (Giampietro et al., and structure, were adjusted accordingly to the land cover distribution 2009). The model is fed with land use digital maps and regional sta- changes between scenarios (i.e. when herbaceous crop surface in- tistical data on inputs and products of agricultural systems. It considers creased in S3, specific crop surface increased depending on the original the whole relevant biophysical fluxes that circulate within the agroe- distribution). cosystems and assesses its functioning based on four balances: phyto- The trending scenario (S1) , supposes an increase in the built-up areas mass, energy, animal feeding and biogeochemical cycles (Marco et al., of 5500 ha (considering as well the urban parks) (Fig. 3). The most 2018). This means the model accounts whether nutrients or the feed affected categories are the forest and the scrublands (1500 ha and flows circulating through the case study are enough to ensure re- 1330 ha respectively), but it is also relevant the loss of around 25% of production of soil fertility and livestock. If not, it is estimated the current agricultural surface (1150 ha). The effect of the urban devel- amount of feed or soil amendments that has to be imported from out- opment in S1 is partially reverted in the alternative scenario (S2) where a side and all the corresponding implications on the indicators. This large part of the urban park area considered in S1 is transformed into biophysical framework is also related to a set of landscape ecology agroforestry activities (more than 80%). Also, around 520 ha and models that account for patterns and processes considering the green 600 ha, respectively, of compact and lax urban areas are reconsidered, infrastructure as a system (Marull et al., 2008). All together make up a increasing agricultural areas in the BMA from 4200 ha in S1 to 6950 ha set of interrelated models which allow to calculate the set of socio- in S2. In the potential scenario (S3), the increase in the agricultural ecological indicators. Thus, changes on management or on land use surface is very important: up to 12,600 ha as all the agricultural areas composition, would result in different values for the eight principal SIA from 1956 are recovered except for those already built-up areas indicators. (Giocoli, 2017). New transport infrastructures, which heavily impact on the fragmentation processes, increase in more than 720 ha in S1, 430 ha in S2 and few more than 320 ha in S3. 2.3. Land planning scenarios Each land cover scenario was analysed under two different agri- cultural management practices: conventional and organic (Fig. 2b). The The present analysis of land planning strategies is based on four first corresponds to the current agrarian management activities, and is theoretical land cover scenarios (current, trending, alternative and mainly based on the 2009 agricultural census and updated with the potential) provided by the PDU, and two management practices (con- statistical sources using the year 2015 as reference. This allows esti- ventional and organic) that consider changes in the metabolic fluxes mating the metabolic fluxes of the current agrarian activities and, by that take place in agricultural systems. The study was carried out at two extension, of the complete green infrastructure (for more details see different scales: a landscape scale, with 500x500m cells (n = 2,764) Marull et al., 2020). proposed by the PDU methodology (Fig. 2b) and a regional scale that To simulate organic agricultural management scenarios, we fol- will provide an overview of the land planning scenarios for the entire lowed the guidelines for certified organic animal and food production BMA. stablished by the European Commission legislation (834/2007, 889/ The current distribution of land covers for the BMA was considered 2008, and 1235/2008) and the Catalan Council of Ecological Agri- as the reference or current scenario (S0) and was obtained from the latest cultural Production (CCPAE, 2017). Given the many possible crop available Land Cover Map (Fig. 1). Land cover composition for each management practices under the official certification of CCPAE (i.e. scenario is detailed in Table 2 and changes from the current to the fertilizing techniques, pest control management, crop rotations), for the trending (S1), alternative (S2) and potential (S3) scenarios are shown in specific purpose of this study, we defined organic agriculture manage- Fig. 3. The trending scenario (S1) corresponds to business-as-usual si- ment as: i) the complete removal of chemical non-mineral fertilizer use; tuation, with the full implementation of the current municipal urba- ii) the complete removal of chemical pesticides and herbicides use; and nistic land plans, characterized by a general increase in the built-up 4 R. Padró, et al. Landscape and Urban Planning 203 (2020) 103905 Table 2 Land planning scenarios of the Land Use Master Plan of the Barcelona Metropolitan Area (BMA) considered in the Socioecological Integrated Analysis (SIA) of the Green Infrastructure. Land-planning scenario Description Land-cover Urban* Forest** Agriculture Pastures Other*** S0. Current 2015 Land-cover map (CREAF) 45% 42% 8% 3% 2% S1. Trending Current urbanistic land plan of each municipality, considering the metropolitan land reserves 52% 38% 6% 2% 2% and sectors defined in the General Metropolitan plan from 1976. S2. Alternative S1 with recovery of open spaces in some areas expected to be urban parks, as well as in other 46% 38% 12% 2% 2% reserves for metropolitan services S3. Potential Based on S2, but with a recovery of agricultural uses outside built-up areas. The existing 45% 32% 20% 2% 2% agricultural area in 1956 was joined to the new agricultural areas considered in S2 Notes: * Includes low and high-density urban areas, urban parks and roads. ** Includes forests and scrubland. *** Includes fluvial corridors, wetlands and bare soils. iii) the limited and regulated use of external inputs (i.e. animal feed and Analysis (PCA) was performed to assess the synergies and trade-offs seeds). Under those definitions, organic agricultural practices were as- among SIA dimensions through a statistical Exploratory Factorial sumed to comply with the minimum CCPAE certifying criteria (Table Analysis (EFA). Finally, we used results at cell level to identify how the A1 in Supplementary Material). relation among dimensions and scenarios shifts and how changes in the Additionally, a shift towards organic management would alter other landscape structure are associated with changes in the metabolism agricultural fluxes such as yields (of both crops and animals), labour (Section 3.3). requirements and unharvested biomass and manure management. Consequently, based on the conventional scenarios’ values set by the empirical statistical sources, these fluxes were modified using adjust- 3. Results and discussion ment factors from a literature review (Table A1). In summary, three main assumptions were made: i) crop and animal yields decrease (De 3.1. Contrasting land planning scenarios and management practices Ponti et al., 2012, Seufert et al., 2012); ii) labour requirements per product unit increase, as well as the intensity of machinery use (DAAR, Our study analysed how contrasting land planning strategies might 2007); iii) all biomass and manure are properly reused (nutrient cycles result in different structural patterns of the green infrastructure in the are closed) and there is no waste flow (biomass discard); and iv) crop BMA and how these patterns might contribute to the functioning of the species composition and crop structure remained the same between metropolitan socioecological system, through pair-wise comparisons of organic and conventional managements. SIA values per 500 × 500 m cell between alternative land planning scenarios, This is the first time that SIA is applied to assess different land cover scenarios and management practices so that associations 2.4. Cartographic and statistical analyses among dimensions of the socioecological system can be assessed in terms of their contribution for a sustainable development. To assess the implications of a potential territorial (land cover Results show that, in general, the energy efficiency indicator (A1) is scenarios) or/and metabolic (management scenarios) transition in the higher for all conventional scenarios compared with the same scenarios BMA, each SIA indicator was calculated for each scenario at 500x500m with organic agricultural practices, with the lowest A1 value found in sample cell and metropolitan (aggregated) scope. First, the SIA assess- the organic trending scenario (S1), although it is not statistically sig- ment at cell level allow a pairwise comparison of the indicators for each nificant (Table 3). Scenarios of conventional management with larger scenario and their statistically significant differences based on a bi- agricultural land cover (S2 and S3), have significantly higher A1 values lateral test-t for each cell (n = 2467). This allows to find how strategies than S0 and S1 scenarios of the same management type. on land use changes or shifting management can suppose different The energy-landscape integration indicator (B1), has an overall green infrastructure’s performances for each SIA dimension (Section higher and significant values when the agroforestry mosaic is recovered 3.1). Then, in order to compare the overall impact of scenarios, a multi- (S2 and S3) and when there is a transition towards organic management criterial assessment is performed through aggregate values (this is, the in each land cover planning scenario, despite those effects remain absolute value for the whole BMA), which allow to have the big picture around 5% (Table 3). Thus, despite a greater energy efficiency of on the overall functioning (Section 3.2). Finally, a Principal Component conventional scenarios, the lesser reliance on external inputs favours Fig. 3. Land cover changes among land planning scenarios (S0 = current scenario, S1 = trending scenario, S2 = alternative scenario, S3 = potential scenario) in the Barcelona Metropolitan Area (BMA). Changes from one land cover category to another are shown, from the current to the planning scenarios. Source: Our own from CREAF, 2015. 5 R. Padró, et al. Landscape and Urban Planning 203 (2020) 103905 Table 3 Socioecological Integrated Analysis (SIA) of the Barcelona Metropolitan Area (BMA) Green Infrastructure. Indicators comparison between land-planning scenarios (S0 – S3), and conventional (C) and organic (O) management scenarios. Data based on result indicators for each 500x500m cells. SIA Scenarios Indicator Current (S0) Trending (S1) Alternative (S2) Potential (S3) C O C O C O C O (a) (b) (c) (d) (e) (f) (g) (h) A1 3.53 b,d 3.24 3.31 3.15 3.59 b,d 3.53 b,d 3.73 b,c,d 3.58 b,c,d B1 0.41 c,d 0.43 a,c,d,e 0.35 0.37 0.40 0.42 c,d,e 0.41 0.44 a,c,d,e,g C1 0.31 c,d 0.31 c,d 0.26 0.26 0.30 0.30 0.31 0.31 D1 97.99 d 86.45 91.09 77.82 116.01 b,c,d 101.54 d 186.92 a,b,c,d,e,f 174.41 a,b,c,d,e,f E1A 27.42 g 47.82 a,c,e,g,h 29.60 e,g 49.99 a,c,e,g,h 26.13 g 45.83 a,c,e,g,h 21.95 34.06 E1B 1,642 c,d,g,h 1,642 c,d,g,h 1,502 1,502 1,597 c,d 1,597 c,d, 1,537 1,537 E1C 1,421 b,d,f 926 1,315 b,d 803 1,487 b,d,f 1,067 d 2,210 a,b,c,d,e,f,h 1,743 a,b,c,d F1 0.89 1.16 a,c,e 0.82 1.07 a,c 0.93 1.22 a,c,e 1.39 a,b,c,d,e 1.80 a,b,c,d,e,f Note: Indicators: energy efficiency (A1), energy-landscape integration (B1), landscape complexity (C1), non-renewable energy input (D1), nutrient recirculation (E1A), carbon stock (E1B), agricultural production (E1C), and agricultural jobs (F1). Letters (a, b, c, d, e, f, g, h) indicate statistically significant differences among scenarios for each indicator based on that bilateral test-t (n = 2,467) and with alpha value of 0.05. Fig. 4. Results of the Multi-criteria Analysis of the evaluated land planning scenarios (S0 = current scenario, S1 = trending scenario, S2 = alternative scenario, S3 = potential scenario), under conventional (C) and organic (O) managements, in the Barcelona Metropolitan Area (BMA). Note: Socioecological Integrated Analysis (SIA) indicators: energy efficiency (A1), energy-landscape integration (B1), landscape complexity (C1), non-renewable energy input (D1), nutrient recirculation (E1A), carbon stock (E1B), agricultural production (E1C), and agricultural jobs (F1). better conditions to host biodiversity in organic scenarios. significant (Table 3). As organic farming maintains machinery or The indicator of landscape complexity (C1), a proxy for the land- greenhouses, which are an important part of external energy inputs, the scape functioning, shows small differences among land cover scenarios, exclusion of pesticides, herbicides and chemical fertilizers is not enough only a significant decrease between the current (S0C and S0O) and the to significantly affect total external inputs. However, like A1, the in- trending (S1C and S1O) scenarios (Table 3). There are no significant dicator was especially sensitive to the substantial agricultural area in- changes between the alternative and potential scenarios, but they both crease of the potential scenario (S3). present relatively low differences compared to changes in other di- In terms of nutrient recirculation (E1A), regardless of the land mensions. planning scenario, mean indicator values under conventional manage- Regarding the non-renewable energy inputs (D1), the transitions ment were always lower than under organic management (Table 3). from conventional into organic management generally resulted in lower These differences are significant for the current (S0), trending (S1) and non-renewable energy inputs, although these differences were not alternative (S2) scenarios. However, the greater the agricultural surface 6 R. Padró, et al. Landscape and Urban Planning 203 (2020) 103905 the lower the system’s ability to provide enough nutrients to close the agricultural yields was expected considering the yield factors estimated nutrient cycles at local level. The carbon stock indicator (E1B) reveals in the model (De Ponti et al., 2012, Seufert et al., 2012). Despite the higher values in the current scenario (S0). With respect to agricultural decrease of external fertilizers use and the complete elimination of production (E1C), values are always significantly higher for conven- herbicides and pesticides, a significant decrease on energy efficiency tional management mainly due to the lower yields considered for or- under organic practices could be explained by the elevated use of ex- ganic management. These sustained differences (an overall drop in ternal inputs: in this particular case the feed, imported from regional production of 17%), are also affected by the increase in agricultural organic sources when the local production did not satisfy the require- area that makes the average value of production per cell increase sig- ments, as well as machinery use also slightly increased. nificantly in the potential scenario (S3) in relation to the current sce- The effect of an organic transition would significantly reduce ag- nario (S0). gregate agricultural production (E1C), with an average drop of 17% Finally, the agricultural jobs indicator (F1) showed for all land cover (Fig. 4). Indeed, this decline in productivity per hectare is not as much scenarios higher labour intensities in organic production (Table 3). This as the decline in productivity, even though the total amount of inputs difference was significant for the current, trending and alternative per hectare decrease. Thus, energy efficiency of agriculture falls be- scenarios (S0, S1 and S2 respectively). Additionally, the shift from the tween 9% and 20% at the aggregate level. On the contrary, the average current scenario into the potential scenario (S3), where agricultural difference among agricultural practices in terms of nutrient recircula- land cover considerably increased, would imply an increase in the tion (E1A) is a relevant 30% increase between the conventional and the average amount of work in relation to any of the other scenarios. organic management, as following the legal criteria livestock is mainly feed with local sources trying to maximize the circular functioning and 3.2. Multi-criteria assessment of the scenarios and practices limiting external imports of grains and hay. A similar effect is observed with the slight reduction in the depen- 3.2.1. Land cover planning scenarios, metropolitan landscapes on change dence on external inputs (D1) or the energy-landscape interaction (B1), Changing from current to the trending scenario result in a loss of but in this case the increase is much more restrained as they only im- landscape complexity (C1) given the increase of urban sprawl, and the prove on average between 10 and 5% respectively when compared to subsequent loss of forest, scrublands and agricultural areas (Fig. 4). This the conventional production (Fig. 4). Those two aspects are probably loss of complexity, together with the increase of urban sprawl, would showing the biophysical limits of an organic management versus an also worsen the conditions for biodiversity conservation (B1). In gen- agroecological one (Tello and González de Molina, 2017), challenging eral, all fluxes are reduced in the trending scenario, resulting in less the transition and the goals of a sustainable management. production (E1C), lower job provision (F1) but less external entries as Finally, the average agricultural job provisioning (F1) increased well (D1), as a counter-effect. 24% Agrarian Working Units (AWU) (Fig. 4). An ecological transition The high values of the carbon stock (E1B) indicator found in the would increase the current estimated 640 to almost 2,400 AWU in the current scenario, might be explained because in the short to medium potential land cover scenario (S3). This increase of 3.7 times in the term, changes in land covers mean the loss of an important part of the volume of workers is explained mainly by the increase of surface, but by accumulated biomass (both aerial and belowground) (Fig. 4). This the shift to organic farming as well as by the agricultural expansion means that S0 has more stock than the trending scenario (S1) but also towards cropping areas with productivities below the average. compared to the potential scenario (S3). In terms of the alternative (S2) and potential (S3) scenarios, re- 3.3. Trade-offs and synergies on the socioecological functioning garding the soil nutrients recycling (E1A), an increase in the agri- cultural surface causes a drop in the ability to close the nutrient cycles, The Principal Component Analysis (PCA) results in the identifica- because nutrients are lost through sewage sludge and are not recycled tion of 2 components with eigen values over 1 that represent around to agricultural areas (Padró et al., 2017) (Fig. 4). This makes difficult to 66.9% of the total variance in the case study and have very different close the nutrient cycles, increasing the heavy reliance on imports as composition (Table 4). The first component mostly includes energy- seen in the D1 results, regardless of the type of fertilizer imported landscape integration (B1), landscape complexity (C1) and carbon stock (manure or chemical). (E1B). Then, it is more related to the landscape structure and func- The transition between S1 to S2, where the agroforestry land re- tioning, reflecting a classical perspective on the land covers from a covered, shows the potential to mitigate the impacts of the trending landscape ecology viewpoint. On the contrary, the second component is scenario (S1), although its effects would not be even equal to the si- a good proxy of the biophysical flows circulating through the land- tuation in 2015 (S0) (Fig. 4). This agroforestry recovering in the al- scape. The variables of agricultural production (E1C), use of non-re- ternative and potential scenarios, has also potential benefits for biodi- newable inputs (D1), and energy efficiency (A1) or agricultural labour versity conservation (B1), which can go hand in hand with the increase (F1) to a lesser extent, represent the material flows that occur in the of total agricultural production (E1C), the later with a 2.2-fold increase green infrastructure. This gives prominence to the agricultural meta- from the current (S0) to the potential scenario (S3). This synergy found bolic dimensions when considering the approach that must be con- in the SIA indicators supposes an interesting trend that should be cor- sidered for a land Planning for Sustainability. It is worth noting that roborated in further studies, supported under the hypothesis of the so- while component 1 explain 42% of the total variance, component 2 called land sharing strategy (Fischer et al., 2014, Marull et al., 2019), so accounts for the 25%. This means that while land use planning for that increasing agricultural production by increasing cropland cover sustainability cannot set aside the metabolic flows, the landscape pat- while maintaining intermediate levels of human disturbance can hold terns and processes play a fundamental role to understand variability greater levels of biodiversity than intensifying the already existing along the territory. cropped surface. It is also relevant to bring to light the shared contribution of the E1A indicator (soil nutrient recycling) to both components, suggesting that 3.2.2. Management practices, a socioecological transition towards organic this is an important aspect to be considered in land planning given its production ability to integrate metabolic and territorial aspects of the socio-eco- A transition to organic farming (Fig. 4) meeting the CCPAE criteria logical system (Table 4). From a conceptual perspective means that this (Table A1) is particularly favourable facilitating a greater degree of indicator is affected by both the landscape funds and the metabolic autonomy closing the nutrient cycles (E1A) and providing agricultural flows and gives relevance to the reproductive processes needed by the jobs (F1). But this process is associated with a decrease of agricultural green infrastructure to keep its socioecological functioning. In this production (E1C) and energy efficiency (A1). A reduction on sense, the recirculation of nutrients, as a fundamental regulating 7 R. Padró, et al. Landscape and Urban Planning 203 (2020) 103905 Table 4 Principal Component Analysis (PCA). Component Eigenvalues Sums of square saturations of the extraction Sums of square saturations after rotation Total Variance (%) Accumulated Variance (%) Total Variance (%) Accumulated Variance (%) Total Variance (%) Accumulated Variance (%) 1 3.36 41.95 41.95 3.36 41.9 41.9 2.77 34.6 34.6 2 1.99 24.92 66.86 1.99 24.9 66.9 2.58 32.3 66.9 3 0.98 12.19 79.05 4 0.71 8.92 87.97 5 0.47 5.93 93.90 6 0.29 3.63 97.53 7 0.14 1.77 99.30 8 0.06 0.70 100.00 Composition of the Principal Components after rotation Indicator Component 1 Component 2 A1 0.2469 0.7248 B1 0.9407 0.2132 C1 0.9327 0.1414 D1 0.0138 0.8356 E1A 0.4191 0.4023 E1B 0.8673 −0.0717 E1C −0.0511 0.8657 F1 0.1463 0.6129 Note: Indicators: energy efficiency (A1), energy-landscape integration (B1), landscape complexity (C1), non-renewable energy input (D1), nutrient recirculation (E1A), carbon stock (E1B), agricultural production (E1C), and agricultural jobs (F1). ecosystem service, represents the paradigm of the reproductive man- agement of the landscape funds (soil fertility, livestock, farming com- munity and associated biodiversity). However, this hypothesis could be extended to other reproductive processes such as the integration of li- vestock breeding and land uses or other practices that maintain the cultural landscape capital (such as terraces or the selective management of forests). The Exploratory Factor Analysis (EFA) allows assessing the con- tribution of landscape structure (component 1) and socio-metabolic processes (component 2) in each land planning scenario and agri- cultural practices (Fig. 5). As can be seen, scenarios are much more affected by changes in component 2 (‘metabolic flows’) than component 1 (‘landscape ecology’). For this case study, the trending scenario is the only land use scenario that supposes a relevant change on the landscape component, with an average loss of 0.31 points in component 1, while for the rest of land use scenarios are practically null with an average change around 0.02 points. On the other hand, the performance of component 2 is much more sensible to land use scenarios, with an average loss of 0.14 points in the trending scenario, a gain of 0.25 for the alternative and a much more greater 0.87 increase in the potential compared with the current one. The observed low and high sensitivity of land cover scenarios to landscape pattern and metabolic flows variables, respectively, lead us to a draw a relevant statement for policy making in this study: land use planning is much more affecting the agricultural metabolic flows than Fig. 5. Exploratory Factor Analysis (EFA). Land planning scenarios* (dots, dark traditionally expected. Finally, organic farming scenarios compete with text) and Socioecological Integrated Analysis (SIA) indicators** (triangles, grey conventional ones in terms of the metabolic flows (component 2) but text) in the Barcelona Metropolitan Area (BMA). Notes: * Land-planning sce- also result in a better performance in relation to sustainability objec- narios: (S0 = current scenario, S1 = trending scenario, S2 = alternative sce- tives of the landscape in an average increase of 0.11 points (Fig. 5). nario, S3 = potential scenario), under conventional (C) and organic (O) man- Something that, again, reinforces this crossed effect of land use plan- agements, in the Barcelona Metropolitan Area (BMA). ** Indicators: energy ning on metabolic performance and viceversa (the effect of metabolic efficiency (A1), energy-landscape integration (B1), landscape complexity (C1), changes on landscape performance). non-renewable energy input (D1), nutrient recirculation (E1A), carbon stock (E1B), agricultural production (E1C), and agricultural jobs (F1). 3.4. Strengths and limitations of the model strategic land-use planning to improve its operation as a green infra- structure to help move them towards more sustainable agro-futures. The SIA assessment is focused on the multiple dimensions of the The SIA approach highlights the society-nature interactions that take contribution provided to social welfare by the joint operation of the place through agroecosystems within metropolitan areas from a re- metropolitan agricultural landscapes through its functioning as agroe- productive point of view. SIA is a socio-metabolic-territorial assessment cosystems. The set of integrated indicators generated will inform the 8 R. Padró, et al. Landscape and Urban Planning 203 (2020) 103905 designed to be applied to land-use planning. Its nodal point is con- such as scaling up organic farming into agroecological territories. sidering that society invest through farming a set of biophysical flows in the agricultural system in order to obtain ecosystem services. These 4. Conclusions ecosystem services can only be ensured by keeping those metabolic flows that reproduce a set of vital live funds, such as agrarian com- The proposed Socioecological Integrated Analysis (SIA) model has munity, livestock, soil fertility and functional landscape structure. The proven its ability to inform about the territorial effects of changing the closer the functioning of these funds to natural processes, the more land covers and the agrarian metabolism through modifying the man- sustainable the agroecosystem will be. agement practices in metropolitan landscapes in order to facilitate the The SIA model is innovative because brings a set of indicators and policymaking decision processes, in this case applied to the Barcelona maps on the ecosystem services they currently provide to city dwellers, Urban Master Plan. Using this multi-criterial perspective, integrating and how to improve them by changing the interaction between the ecological economics and landscape ecology could enable and enrich biophysical flows of agricultural, livestock and forestry activities with informed debates on circular economy and land planning. The SIA the land use and cover patterns of those landscapes planned as green model is an important conceptual and methodological step forward that infrastructures. It is important, because it becomes a useful tool for a facilitates the transition towards Planning for Sustainability. This sustainability-oriented land-use planning that seeks to integrate urban- planning strategy aims to reconcile urban development with the bio- industrial and green infrastructures as complementary components of physical limits of territories, as well as to improve the socioecological metropolitan areas, acknowledging that the continuous expansion of functioning of green infrastructures. the former at the expense of the latter means degrading or even su- Regarding the land cover scenarios considered, the increase in pressing the provision of the ecosystem services these horticultural and urban areas of the business as usual scenario would severely affect di- agroforest landscapes provide to the citizens living on the metropolis. mensions directly related to landscape patterns and processes. It would And it is relevant, because the indicators and maps here presented are also affect the ability of the green infrastructure to close nutrient cycles, currently being applied in the approach of land-use planning adopted improve food provisioning, maintain agricultural jobs and increase its by the new Master Urban Plan of the Metropolitan Area of Barcelona, in metabolic efficiency as well, calling for imminent revision on the pro- line with the SDG of the United Nations 2030 Agenda and the Milan jected land planning scenario. Planning land covers to restore agri- Urban Food Policy Pact. cultural areas lost during these past decades would allow to mitigate Metropolitan agricultural landscapes can become the greenbelts some of the negative socioecological impacts of past urban growth, needed for a closer agri-food supply in line with the Milan Urban Food increasing the diversity of the ecosystem services provisioned by the Policy Pact (Moragues-Faus and Morgan, 2014), as well as for the de- metropolitan green infrastructure, specially food security, and dimin- livery of many ecosystem services (Haines-Young and Potschin, 2010). ishing its reliance on massive external imports. Despite that, some in- The proposed SIA model has proven to be a useful assessing tool for this dicators such as the total carbon stock or the expected emissions from new sustainability-driven approaches to urban planning, remarking the agrarian activities would be negatively affected in total, as measured at need to redirect and take care of the biophysical flows that shape these the local level. However, this requires an additional assessment con- horticultural and agroforest landscapes within metropolitan areas. It sidering the net global effect considering the food provisioning re- confirms the relevance of the FAO’s 2018 Scaling Up Agroecology In- placed. itiative that claim to leap forward from current organic farming to more With respect to an organic transition in agricultural management, integrated agroecology territories able to ensure the provision of all considering the minimum criteria to be certified following the CCPAE, kinds of ecosystem services to society. Land-use planning can enhance the results show how this would suppose improving significantly nu- all the ecosystem services delivered to citizens from the metropolitan trients recirculation and job provisioning at the cost of decreasing the green infrastructures by driving towards socially desired scenarios these overall production. However, the contribution of the green infra- farming matter-energy flow that shape the agroforest landscape mo- structure to the socioecological functioning on metropolitan areas saics. Thus, land-use policy can do it through incentives and regulations during a possible organic transition should be carefully accounted. which set in motion positive synergies with farmers. Strict compliance with ecological regulations might not necessarily However, in this current version, the SIA model has certain limita- translate into overall improvements, and might not be enough to face tions that should be addressed in future research. Some indicators could challenges such as the decrease on the use of external inputs or on the be improved (for example, nitrogen flows in nutrient recycling, carbon increase on the energy efficiency improvement. balance of all agricultural activity, or agroecological EROIs), and ad- The results reinforce that, when considering transitions towards ditional indicators could be added in order to highlight certain di- more sustainable functioning of agrarian systems, models must take mensions that have not been prioritised in the first SIA assessment (for into account a proper optimization of metabolic flows and land uses to example, in relation to water cycle, greenhouse gas emissions, or the satisfy specific social goals (i.e. food provisioning, biodiversity con- impact of green infrastructure on health -a relevant aspect in the cur- servation). This means that those organic practices must also consider, rent context of COVID-19 crisis). The model is not considering the dy- for example, the type of crops needed to promote synergies among food namic synergies and trade-offs involved in changing the pattern of demand, livestock functioning, food provisioning and the other eco- energy and material flows interlinking the agroecosystem funds in- system services and socioecological functions. From our results arises a volved (i.e. livestock and feed coming from local crops). It does not new hypothesis relevant for this new paradigm of Planning for allow to connect land and livestock uses with dietary changes in the Sustainability: it seems to be a crossed effect on the changes in land consumers' food baskets. We are then considering the average most covers and agricultural management and the impact on dimensions of unfavourable scenario for organic production yields, based on the es- landscape ecology and social metabolism. This means that land cover timations of a literature review (De Ponti et al., 2012, Seufert et al., changes would be more related to changes on metabolic flows, while 2012). The proposed organic production model only takes into account management changes could affect also dimensions of landscape func- the food supply service, but it does not explain dependency from the tioning. outside. The SIA should be put in relation to the territorial scale that In summary, the challenge of sustainable land planning and circular makes the functioning of the BMA sustainable, beyond its adminis- economy in metropolitan areas could be addressed by adopting an in- trative limits. All these limitations mean that, while being a useful tool tegrated view that allows for the identification of both land uses and to help land-use planers to make better decisions aimed at improving metabolic flows changes. 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