Climate-and-Firesmart-Landscape-Scenarios-Redesigning-Protection-Regimes

Journal of Environmental Management 322 2022 116045 Available online 5 September 2022 03014797 2022 The Authors Published by Elsevier Ltd This is an open access article under the CC BYNCND license httpcreativecommonsorglicensesby ncnd40 Research article Climate and firesmart landscape scenarios call for redesigning protection regimes to achieve multiple management goals Miguel Canibe Iglesias abc Virgilio Hermoso de Joao C Campos fg Claudia CarvalhoSantos h Paulo M Fernandes i Teresa R Freitas i Joao P Honrado fjk Joao A Santos i ˆAngelo Sil abfik Adrian Regos cdfk Joao C Azevedo ab a Centro de Investigaçao de Montanha CIMO Instituto Politecnico de Bragança Campus de Santa Apolonia 5300253 Bragança Portugal b Laboratorio Associado para a Sustentabilidade e Tecnologia em Regioes de Montanha SusTEC Instituto Politecnico de Bragança Campus de Santa Apolonia 5300 253 Bragança Portugal c Departamento de Zooloxía Xenetica e Antropoloxía Física Universidade de Santiago de Compostela 15782 Santiago de Compostela Spain d Centre de Ciencia i Tecnologia Forestal de Catalunya CTFC Ctra Sant Llorenç de Morunys km2 25280 Solsona Lleida Spain e Departamento de Biología Vegetal y Ecología Universidad de Sevilla 41012 Sevilla Spain f InBIOCIBIO Centro de Investigacao em Biodiversidade e Recursos Geneticos Campus Agrario de Vairao Rua Padre Armando Quintas nº 7 4485661 Vairao Portugal g CICGE Centro de Investigaçao em Ciˆencias GeoEspaciais Faculty of Sciences University of Porto Alameda do Monte da Virgem 4430146 Vila Nova de Gaia Portugal h Centre of Molecular and Environmental Biology CBMA Institute for BioSustainability IBS University of Minho 4710057 Braga Portugal i CITAB Centro de Investigaçao e de Tecnologias AgroAmbientais e Biologicas Universidade de TrasosMontes e Alto Douro 5001801 Vila Real Portugal j Departamento de Biologia Faculdade de Ciˆencias da Universidade do Porto Rua do Campo Alegre SN Edifício FC4 4169007 Porto Portugal k BIOPOLIS Program in Genomics Biodiversity and Land Planning CIBIO Campus de Vairao 4485661 Vairao Portugal A R T I C L E I N F O Keywords Conservation planning Fire management Biodiversity conservation Ecosystem services Firesmart Climatesmart A B S T R A C T Integrated management of biodiversity and ecosystem services ES in heterogeneous landscapes requires considering the potential tradeoffs between conflicting objectives The UNESCOs Biosphere Reserve zoning scheme is a suitable context to address these tradeoffs by considering multiple management zones that aim to minimise conflicts between management objectives Moreover in Mediterranean ecosystems management and planning also needs to consider drivers of landscape dynamics such as wildfires and traditional farming and forestry practices that have historically shaped landscapes and the biodiversity they host In this study we applied a conservation planning approach to prioritise the allocation of management zones under future land scape and climate scenarios We tested different landscape management scenarios reflecting the outcomes of climatesmart and firesmart policies We projected the expected landscape dynamics and associated changes on the distribution of 207 vertebrate species 4 ES and fire hazard under each scenario We used Marxan with Zones to allocate three management zones replicating the Biosphere Reserves zoning scheme Core area Buffer zone and Transition area to address the various management objectives within the Biosphere Reserve Our results show that to promote ES supply and biodiversity conservation while also minimising fire hazard the reserve will need to i Redefine its zoning especially regarding Core Areas which need a considerable expansion to help mitigate changes in biodiversity and accommodate ES supply under expected changes in climate and species distribution ii Revisit current management policies that will result in encroached landscapes prone to high intensity uncontrollable wildfires with the potential to heavily damage ecosystems and compromise the supply of ES Our results support that both climate and firesmart policies in the Meseta Iberica can help develop multifunctional landscapes that help mitigate and adapt to climate change and ensure the best possible main tenance of biodiversity and ES supply under uncertain future climate conditions Corresponding author Centro de Investigaçao de Montanha Instituto Politecnico de Bragança Campus de Santa Apolonia 5300253 Bragança Portugal Email addresses miglesiasipbpt MC Iglesias virgiliohermosoctfccat V Hermoso jccamposcibiouppt JC Campos ccarvalhosantosbio uminhopt C CarvalhoSantos pfernutadpt PM Fernandes trfreitasutadpt TR Freitas jhonradofcuppt JP Honrado jsantosutadpt JA Santos angelosilcibiouppt ˆA Sil adrianregosctfccat A Regos jazevedoipbpt JC Azevedo Contents lists available at ScienceDirect Journal of Environmental Management journal homepage wwwelseviercomlocatejenvman httpsdoiorg101016jjenvman2022116045 Received 30 May 2022 Received in revised form 22 July 2022 Accepted 17 August 2022 Journal of Environmental Management 322 2022 116045 2 1 Introduction The loss and degradation of ecosystems is leading to a global decline of biodiversity at rates 100 times higher than the background extinction rates for many taxa Ceballos et al 2015 IPBES 2019 Furthermore the increasing demand for food water raw materials and energy mostly driven by an increasing growth of human population is leading to the unsustainable use of renewable and nonrenewable resources further degrading ecosystems Despite the remarkable conservation efforts in the last decades biodiversity and ecosystem condition are still declining due mainly to the impacts of regional landuse and global climate changes that lead to shifts in disturbances regimes IPBES 2019 All these pressures compromise the persistence of biodiversity Habel et al 2019 and consequently the supply of ecosystem services ES Cabral et al 2021 Climatesmart management originated in agricultural systems Scherr et al 2012 and was later extended to forest management Bowditch et al 2020 Climatesmart landscape management aims to help mitigate the effect of climate change by increasing carbon stocks and sequestration rates via measures such as direct afforestation and rewilding initiatives Perino et al 2019 However rewilding and afforestation can reduce landscape heterogeneity and increase fuel load and connectivity in the landscape which in turn reduce ecosystem resilience and adaptability Holl and Brancalion 2020 and conse quently increase wildfire hazard Hermoso et al 2021 This therefore requires the implementation of firesmart management solutions with the goal of building fire resilient landscapes alongside climatesmart policy and practice while maintaining high levels of biodiversity and ecosystem services delivery Hirsch et al 2001 Firesmart management is especially relevant in Mediterranean re gions where wildfires are a key driver of landscape dynamics Lloret et al 2002 These regions are currently experiencing an increased risk of large and highintensity fires due to the combined effect of climate warming longer drought periods and longstanding land abandonment or afforestation processes Moreira et al 2020 that increase fuel load and connectivity at site and landscape levels eg Fernandes et al 2014 Additionally traditional fire management policies based on fire exclusion have increased the risk of catastrophic fires under extreme weather conditions Pausas and FernandezMunoz 2012 Firesmart management can therefore play a key role in reducing fire hazard by promoting firesmart landscapes in Mediterranean regions Pais et al 2020 Under favourable conditions firesmart management can even create opportunities for fire to provide benefits to some species Regos et al 2018 or increase fire resilience by reducing fuel load and con nectivity eg prescribed burning Fernandes et al 2013 Another benefit of firesmart management is its contribution to maintaining landscape heterogeneity minimising the negative impacts of wildfires on biodiversity and ES The integration of ES in landscape management is vital for the development of more integrative conservation frameworks and financing mechanisms such as the Reducing Emissions from Defores tation and forest Degradation REDD or the EU Green Infrastructure Strategy Benedict and McMahon 2002 Despite efforts the amount of land required to fulfil human needs continues to grow Foley et al 2011 whereas the ecosystems ecological integrity continues to decline Plumptre et al 2021 This highlights the need for landscape planning and management approaches that aim to protect land while integrating conservation and development avoiding or at least minimising the conflicts that are likely to arise in the presence of limited resources for different and often conflicting objectives The successful implementation of holistic landscape management approaches relies on our capacity to address tradeoffs and synergies among different ES and between ES and biodiversity conservation CarvalhoSantos et al 2016 MoranOrdonez et al 2017 Sil et al 2016 Studies on the spatial relation between biodiversity and ES supply have shown that synergies between conservation and socioeconomic development objectives exist and are a great opportunity for integrated landscapelevel planning and management Chan et al 2006 Egoh et al 2009 Nelson et al 2009 Ramel et al 2020 How ever the relationship between biodiversity and ES is complex Biodi versity provides and regulates ecosystem processes responsible for the supply of ES or it can be considered as an asset Mace et al 2012 This is also highly dependent on the socioeconomic and biophysical context of the regions of interest as well as on the scale of the analysis Duncan et al 2015 In recent studies spatial tradeoffs and synergies between ES and biodiversity in systematic conservation planning have been addressed using management zones Barbosa et al 2019 Hermoso et al 2018 These zones aim to achieve ES supply and biodiversity conservation goals simultaneously enhancing cobenefits between objectives mini mising potential tradeoffs Some of these management zones can be designed to simultaneously address compatible objectives such as biodiversity conservation and carbon storage and others to allow uses that are not compatible such as conservation and timber production Lanzas et al 2019 or fisheries and conservation Beger et al 2015 This multizoning approach allows for more flexibility in planning securing larger amounts of resources while minimising conflicts be tween objectives when compared to a single management zone Her moso et al 2018 UNESCOs Biosphere Reserves BR offer an innovative and inte grated management model to preserve biodiversity along with the sus tainable use of natural resources and research UNESCO 2021 To efficiently achieve these multiple goals BRs have popularised a flexible multizoning scheme based on three management zones UNESCO 2017a i Core Areas with stricter biodiversity conservation goals usually encompassing areas already included in protected areas with higher conservation value ii Buffer Zones aiming to buffer and connect Core Areas while allowing for traditional activities compatible with conservation and iii Transition Areas where sustainable resource management is promoted Although zoning should be casespecific this scheme presents a good starting point for holistic landscape and con servation management where climate and firesmart policies can be accommodated while avoiding or minimising critical tradeoffs between objectives In this study we aimed to prioritise the allocation of different management zones within the Meseta Iberica Transboundary Biosphere Reserve NW Iberian Peninsula on the PortugalSpain border UNESCO 2017b to achieve multiple objectives for biodiversity conservation and ES supply while minimising wildfire hazard under different landscape management scenarios The area features a Mediterranean landscape affected by land use change and wildfires We assessed contrasting landscape management scenarios from climateto firesmart strategies based on likely outcomes of forestry and agricultural policies and their potential effects on biodiversity ES supply and fire regime 2 Material and methods 21 Study area Our study was conducted in the Meseta Iberica Transboundary Biosphere Reserve Fig 1 located in the northwest Iberian Peninsula This BR designated in 2015 has a total extent of 11326 km2 UNESCO 2017b including territories from both Portugal 58 of the BR and Spain 42 Trillo Santamaría and Paül Carril 2018 The BR comprises 12 Portuguese municipalities in the district of Bragança plus the mu nicipality of Figueira de Castelo Rodrigo in the district of Guarda On the Spanish side the BR includes 75 municipalities 48 in the province of Zamora and 27 in the province of Salamanca all of them in the Castilla y Leon autonomous community ZASNET 2021 The BR follows the conventional Man and Biosphere structure comprised of Core areas areas of higher level of protection within protected areas such as Arribes del Duero Douro International Montesinho and Lago de MC Iglesias et al Journal of Environmental Management 322 2022 116045 3 Sanabria y Sierras de Segundera y Porto natural parks as well as the Regional Natural Park Vale do Tua and the Sierra de la Culebra Site of Community Importance Buffer zones areas of lower level of protection inside protected areas and Natura 2000 sites and Transition areas the remaining areas Santamaría and Carril 2018 Currently 1064 km2 9 are allocated to the Core area 4203 km2 36 to the Buffer zone and 6325 km2 55 to the Transition area Palliwoda et al 2021 The landscape of the BR is diverse and heterogeneous Altitude Fig 1 Map of the Meseta Iberica Transboundary Biosphere Reserve showing the current distribution of management zones Topright corner shows the location of the study area within the Iberian Peninsula Data supplied by ZASNET European Grouping of Territorial Cooperation MC Iglesias et al Journal of Environmental Management 322 2022 116045 4 ranges from 100 to over 2127 m asl Xunta de Galicia 2021 Climate is mostly Mediterranean with drywarm summers and wet winters Mean annual precipitation varies from 500 to 1200 mm following an altitu dinal gradient and presents a strong seasonality Deitch et al 2017 Santos and BeloPereira 2022 Land cover is mainly shrubland farm land and forests Azevedo 2012 Sil et al 2017 The main types of forests are maritime pine Pinus pinaster plantations deciduous wood lands dominated by Pyrenean oak Quercus pyrenaica and evergreen woodlands dominated by holm oak Quercus ilex and cork oak Quercus suber Azevedo 2012 The BR also harbours high levels of species richness including a high number of invertebrates plants and around 250 species of vertebrates among which flagship species such as the Iberian wolf Canis lupus sig natus Egyptian vulture Neophron pernocpterus and iberian endemisms such as Bocages wall lizard Podarcis bocagei or Seoanes viper Vipera seoanei UNESCO 2017b The area hosts a human population of around 300000 inhabitants UNESCO 2017b Depopulation and ageing cause high rates of land abandonment Sil et al 2016 The Mediterranean type of climate in the region characterized by wet mild winters and dry warm summers together with the landscape changes derived from land abandonment vegetation encroachment and affor estation has led to an increased risk for severe wildfires Sil et al 2019 22 Conceptual framework The research followed a systematic conservation planning approach based on spatial modelling of species distribution and supply of ES Fig 2 under historical hereafter 2005 scenario and future conditions 2050 We considered four landscape management options and four climate models projected under two climate change scenarios Repre sentative Concentration Pathways RCP 45 and 85 which were used to evaluate the impact of climate change on species distribution and ES Spatial projections of potential distributions for 207 species and four ES were jointly incorporated into Marxan with Zones Watts et al 2009 a decision support tool that has been successfully used in spatial conser vation planning integrating biodiversity and ES Adams et al 2016 Barbosa et al 2019 Lanzas et al 2019 Marxan with Zones prioritises the allocation of management zones with userdefined roles ie which features are allocated to a management zone and which are not in a flexible way that allows conflicting uses to be managed separately in different zones In addition we used potential fire intensity measured by fireline intensity as a penalty in the spatial prioritisation exercise thus favouring selection of planning units expected to burn with lower intensities to achieve biodiversity and ES supply targets With the resulting distribution of management zones we compared the perfor mance of the different scenarios in regard to species and ES coverage We also compared our zone distributions with the zone distribution in the existing management plan of the BR All Marxan analyses were conducted based on data for features and penalties gathered in a grid of 1 km2 cells hereafter Planning Units covering the BR area Fig 2 Schematic workflow of the study MC Iglesias et al Journal of Environmental Management 322 2022 116045 5 23 Landscape management scenarios We considered four landscape management scenarios projected for the study area for the year 2050 obtained from Campos et al 2022 These scenarios depict future states of the landscape based on the implementation of forest and agricultural management options Afforestation and BAU scenarios and firesmart FarmReturn and AgroforestRe policies supported by climate Scenarios were defined according to the main trends of landscape change identified in 5 periods 19902018 19902000 20002006 20062012 and 20122018 selecting the most representative trend for the storyline of each scenario The landscape management scenarios are defined ac cording to the following storylines see details in Campos et al 2022 Afforestation Defined by forest expansion resulting from afforesta tion as identified in the landscape change trends from 1990 to 2000 This scenario was used to account for changes associated with increasing wood and bioenergy demand as well as for climate change mitigation Main transitions are a strong increase in forest areas through conversion of seminatural areas shrubland and grassland and an increase of deciduousbroadleaved species through natural succession and active planting mainly in shrubland Table S12 Business as usual BAU Defined by land abandonment following historical and current trends of abandonment in the area Azevedo et al 2011 based on 19902018 trends This scenario results in a landscape dominated by shrublands growing in former agropastoral areas FarmReturn Defined by the support of agricultural policies promot ing sustainable low maintenance farming and reverting land aban donment tendencies ie European Unions Common Agricultural Policy contributing to biodiversity conservation and developing low fire hazard landscapes Moreira Peer 2018 based on 20062012 trends It is characterized by an increase in farmland at the expense of seminatural shrubland and grassland areas AgroforestryReturn AgroforestRe A scenario where the support of agricultural and agroforestry policies will create a potentially more fireresilient and fireresistant landscape with lower fuel load and connectivity based on 20062012 and 20122018 data The main trends are a moderate replacement of seminatural areas and conif erous forest by croplands and a strong replacement of deciduous forest shrubland and grassland by agroforestry areas eg sweet chestnut groves Projections of land cover under each landscape management sce nario were built using the Scenario Generator of InVEST Sharp et al 2020 with CORINE Land Cover CLC Copernicus 2020 data for 2018 as the baseline Land Cover CLC data were grouped into 10 broader land cover classes for analysis namely urban agriculture grassland agro forestry forests deciduous coniferous and mixed shrubland water and others Table S11 The trends defined above were used to produce landscape transition matrices for all scenarios To account for the sto chasticity of landscape dynamics 10 simulations were run for each scenario Finally landusecover data projected under each of these scenarios were used as input to predict changes in species distribution ES supply and fire hazard 24 Biodiversity data For biodiversity predictive mapping two sets of species distribution models SDMs were used to account for the joint effects of climate and landuse change 1 SDMs based only on climate predictors obtained from Campos et al 2021 and 2 SDMs based on Land UseLand Cover LULC and topographic variables obtained from Campos et al 2022 Both sets were built from presenceabsence data for 168 birds 24 rep tiles and 15 amphibians from national atlases at 10km resolution for the whole Iberian Peninsula to characterise the ecological niche of the species see Titeux et al 2017 Individual projections were obtained using 6 modelling algorithms and 10 replicates to account for modelling stochasticity and were then used to compute ensemble models consid ering AUC values as model weights for each future management sce nario These ensemble models were then downscaled and projected at 1km resolution to the extent of the BR Bombi DAmen 2012 and reclassified into binary presenceabsence maps using ROC optimised thresholds Thuiller et al 2009 Habitat models projections were obtained for the 2005 scenario and the four landscape management scenarios 2050 To deal with the uncertainty of climate change we considered four widely used models climate models IPSLIPSLC M5AMR ICHECECEARTH MPIMMPIESMLR and CNRMCERFACSCNRMCM5 from the European Coordinated Down scaling Experiment EUROCORDEX Jacob et al 2020 under two climate scenarios RCPs 45 and 85 RCP 45 corresponds to an inter mediate anthropogenic radiative forcing of the climate system with a midcentury peak in greenhouse gas emissions and a subsequent decline thereafter RCP 85 is a fossilfuel emissions intensive scenario commonly considered the worstcase scenario van Vuuren et al 2011 For climate projections we used average predictions of the four climate models under each RCP scenario see Campos et al 2021 All the SDMs procedures were performed using the biomod2 R package Thuiller et al 2009 Only locations where species presence was predicted by both climatic and habitat models were used for this study Complete modelling details are available in Campos et al 2022 25 Ecosystem services Four ES were selected covering the three highest levels of the Com mon International Classification of Ecosystem Services version 51 CICES v51 categories regulation and maintenance provisioning and cultural The selection was limited to those ES potentially affected by landuse changes since the entire research framework relies on land scape change scenarios 251 Provisioning ES cultivated terrestrial plants We used the amount of agricultural surface as a surrogate for pro visioning services that depend on this type of land cover This represents ES in the Cultivated terrestrial plants for nutrition materials or energy group in CICES v51 and it was chosen since CORINE land cover maps do not differentiate between particular end uses of crops ie nutrition materials energy We used 1km resolution LULC maps to identify planning units classified as agriculture 252 Regulation and maintenance ES climate regulation We used the InVEST Carbon Storage and Sequestration module Sharp et al 2020 to assess the dynamics of the climate regulation ecosystem service CRES in the 2005 and 2050 landscape scenarios CRES is the contribution of terrestrial systems to regulate the concen tration of greenhouse gases in the atmosphere HainesYoung and Pot schin 2018 We used carbon sequestration rate Mg C ha1 yr1 as a proxy of the capacity of ecosystems and landscapes to supply CRES The InVEST module was fed with data on carbon stocks based on previous studies in the area see Campos et al 2022 and Sil et al 2017 for a complete description Carbon stocks were estimated for seven major land cover classes agriculture agroforestry deciduous coniferous and mixed forest and seminatural grassland and shrubland and four car bon pools aboveground belowground biomass soil organic carbon and dead organic matter The amount of carbon gain sequestration or loss emission was computed as the difference between stocks in each pixel on two consecutive dates of the two periods 19902020 and 20202050 Raster maps of carbon sequestered or emitted in each period were divided by the number of years in that period to obtain maps of annual estimates to be used as inputs in Marxan with Zones MC Iglesias et al Journal of Environmental Management 322 2022 116045 6 253 Regulation and maintenance ES soil erosion control Soil erosion control was estimated according to Guerra et al 2014 who measured avoided soil erosion due to the effect of vegetation providing the actual ecosystem service The approach is based on the Revised Universal Soil Loss Equation RUSLE which estimates annual soil loss through the product of rainfall erosivity R soil erodibility K slope length and steepness LS covermanagement C and conserva tion practices P factors the latter not considered due to the absence of spatial data Eq 1 A R K LS C 1 It differs from the traditional application of RUSLE in the computa tion of erosion made under two conditions i the structural impact ie the erosion that would occur if vegetation was absent Eq 2 S R K LS 2 and ii the actual soil loss Eq 1 Soil erosion control ES was therefore estimated by subtracting the structural impact Eq 2 from the actual soil loss Eq 1 Control of soil erosion was calculated for the four proposed land management scenarios and respective replicates where the C factor obtained from Pimenta 1998 was used in the reclassification of CORINE land cover map classes Rainfall erosivity R soil erodibility K and slope length and steepness LS were obtained from the Euro pean Soil Data Centre ESDAC Panagos et al 2014 Panagos Ballabio et al 2015 Panagos et al 2015b All rates were normalized in a 0 to 1 scale to be used as input in Marxan with Zones 254 Cultural ES recreation Recreation potential was modelled following the ESTIMAP model for naturebased recreation NBR Zulian et al 2013 This model uses advanced multiple layers lookup tables advanced LUT to assign ES scores to land units based on crosstabulation from different input layers NBR potential combines ecosystembased potential to provide NBR and distance to NBR potential Ecosystembased potential combines three sources of information into a single layer i Suitability of each LULC class to support recreation based on a score from 0 to 1 repre senting the suitability of each LULC class to support these activities Vallecillo et al 2019 Table S21 ii Areabased conservation mea sures according to which we assigned an additional score to Protected Areas and Natura 2000 sites considering their attractiveness to people when deciding where to spend their freetime considering conservation areas World Database of Protected Areas differently Natural and Regional parks were assigned a score of 1 while Natura 2000 sites Special Areas for Conservation Special Protection Areas and Sites of Community Importance were assigned a score of 08 and iii Water masses to which we assigned a score of 1 to include important fluvial beaches and other inland water elements used for recreation collected in the European environmental Agency EEA state of bathing water database The 3 components represented in raster layers were summed up obtaining a 03 layer of scores subsequently normalized to the 01 range representing the Recreation Potential Index RPI RPI was then classified in Low Medium and High classes using the 33 and 66 percentiles Distance to NBR potential indicates accessibility and remoteness of areas with recreation potential Both metrics are based on the Euclidean distance in km from roads OSM contributors 2021 and urban settlements respectively These measures were crosstabulated to obtain the distance matrix Table S22 The NBR provision layer was obtained by crosstabulating ecosystembased potential and distance components according to parameters in Table S23 Final NBR scores ranged from 1 to 9 Table S24 Of these we only used high recreation provision classes 7 8 and 9 as inputs in Marxan with Zones 26 Landscape fire hazard We applied the FlamMap module from the FlamMap5 v5 fire mapping and analysis system model Finney et al 2015 to assess the effect of landscape change on fire behaviour in a spatially explicit manner and derive information on the potential fire hazard in the study area in past using CLC 2006 and in future landscape scenarios 2050 This information was used as costs in Marxan with Zones We assumed fireline intensity kW m1 as the descriptor of potential fire hazard To express the resistance to control of a wildfire fireline intensity outputs were reclassified to be used as inputs in Marxan with Zones according to a standard fire danger classification Alexander and Lanoville 1989 Class 1 Low 500 kWm Class 2 Moderate 5002000 kWm Class 3 High 20004000 kWm Class 4 Very High 400010000 kWm and Class 5 Extreme 10000 kWm In FlamMap raster layers of fuels and topographic conditions and tabular data and several builtin pa rameters were used to set fuel moisture and weather variables Table S31 Fuel models were allocated based on the correspondence between land cover classes and custom fuel models for Portugal Fer nandes et al 2009 Table S32 Canopy cover data for each forest type was based on previous work within the study area Azevedo et al 2011 Table S33 For canopy fuel variables stand height canopy base height and canopy bulk density we used data from Botequim et al 2019 collected data in a Mediterranean climate area of SW Spain for P pinaster and Q pyrenaica in pure and mixed stands Fire behaviour was simulated under severe dry and windy weather conditions expected to be more common under climate change Table S34 The fuel moisture content of surface fuels dead and live and foliar moisture content FMC of canopy fuels was set based on typical conditions Fernandes 2009 Wind speed is representative of wind gusts in active crown fires Cruz and Alexander 2019 Alignment between wind and slope was assumed for all simulations to depict maximum fire behaviour potential All raster files for fuels and terrain were prepared at 100m spatial resolution using GIS functions 27 Spatial prioritisation of management zones We used Marxan with Zones Watts et al 2009 to prioritise the spatial allocation of the three management zones within the BR Marxan with Zones uses data on the spatial distribution of conservation features in our case species and ES and costs in our case fire intensity to identify the most suitable allocation of management zones that allow achieving userdefined representation targets for the features at a min imum cost Marxan with Zones also allows specifying the spatial ag gregation within management zones and the spatial relationship between management zones The mathematical problem that we addressed was therefore minimise m i1 p k1 cikxik b m i11 m i21 p k11 p k21 cvi1i2k1k2xi1 k1xi2k2 3 subject to m i1 p k1 aijxik tjk j 4 where cik is the cost of planning unit i if allocated under zone k xik is a control variable that determines whether planning unit i has been allocated under zone k 1 or not 0 cvi1i2k1k2 is the connectivity penalty for including only one of the pair of planning units i1 i2 xi1 k1 and xi2k2 are control variables that take values of 1 when the planning unit i1 or i2 is included in the solution or 0 otherwise b or boundary length modifier BLM is a weight applied to the connectivity penalty used to aggregate planning units in space or determine the spatial structure of zones aij is the contribution of planning unit i to the achievement of targets for feature j and tjk is the representation target desired for each j feature under their respective zone k MC Iglesias et al Journal of Environmental Management 322 2022 116045 7 271 Representation targets We set an overall representation target of 200 km2 for each species under all planning scenarios and time horizons We selected this rep resentation target to ensure an adequate representation of the rarest species in the study area most in need of conservation action while avoiding overrepresenting the most common ones The target we set represents the full distribution of the 20 about 10 of all species considered rarest species while only a small proportion 23 of the distribution of the most common species For the rare species that do not reach 200 km2 in the area we set their total distribution as the target In the future scenarios we used exactly the same targets although expecting that this would lead to some representation targets being impossible to achieve in the case of species that heavily decline or disappear from the area in the future Last for species that appear in the area only in future scenarios we set new targets following the criteria above We believe that this is a good way to identify species turnover within Marxan with Zones in scenarios of uncertainty Regarding ES we aimed to explore the maintenance of high levels of ES in the future while avoiding conflicts Since higher amounts of ES would make some of the targets impossible to achieve ie asking for more agriculture than is present in a given scenario we set the targets to 70 of 2005 supply Targets for the future scenarios were kept constant according to the absolute amounts of ES demanded for the historic scenario Table 1 We replicated the same types of zones of the UNESCO zoning scheme Transition Buffer and Core areas in our analyses To distribute the abovementioned targets across these three management zones we first evaluated the potential relationships between the different features to look for potential tradeoffs or opportunities to foster cobenefits following recommendations in Hermoso et al 2018 Lanzas et al 2019 and Sil et al 2016 Based on knowledge from the authors in the study area we identified cultivated terrestrial plants as a conflicting ES that can negatively impact carbon sequestration soil erosion and habitat for some species and thus tried to allocate these to different manage ment zones Table 2 For species we distributed the overall targets above according to their distribution ranges to ensure that species with distributions below 200 occurrences achieve their targets within the Core area For species above 200 occurrences we split their targets between the Core area and Buffer zone and for open habitat and generalist species we allowed a portion of their targets to be met in the Transition area For ecosystem services the overall 70 target was partitioned in fractions of 10 25 and 35 and distributed according to their potential impacts on conservation purposes Table 1 We allowed a small proportion of ES targets to be met in zones where they might cause conflicts with other objectives because we assumed that adequate management of the BR can allow for small portions of incompatible ES to coexist within the same management zone 272 Spatial configuration of management zones Marxan with Zones allows specifying the degree of spatial aggrega tion within management zones as well as the spatial arrangement among zones through weighting factors in the objective function the Boundary Length Modifier BLM and the weights in the zoneboundary file We used an overall BLM value of 1 and calibrated the zoneboundary file parameters following Serra et al 2020 to ensure that the Buffer zone buffers the Core area and the Transition and Core areas are not connected 273 Spatial penalties In our research framework we penalised the selection of planning units with a high fire intensity risk assuming that whenever fire sup pression difficulty was rated high or very high potential fire damage is higher e high penalty while in areas where fire suppression difficulty was rated low to moderate fire damage is lower low penalty This cost was equally applied to all zones 274 Feature penalties Failing to achieve representation targets results in penalties As such target achievement is encouraged in the optimisation procedure The feature penalties are weighted by a Feature Penalty Factor FPF in the Marxan objective function so that high SPF results in all targets ach ieved while low SPF can lead to some features not meeting their targets To ensure that representation targets were always met we used a FPF of 10 for all features except for rare species and ES for which we used a FPF of 100 With the specifications detailed above we ran Marxan with Zones 100 times 10 million iterations in each individual run for each of the 81 simulations 4 landscape management scenarios X 10 replicates X 2 RCPs 1 for the 2005 scenario and kept the best solution over those runs for subsequent comparative analyses across scenarios 28 Analysis of Marxan with zones solutions We compared the solutions obtained under each scenario by recording the extent and the mean potential fire intensity within each zone We also compared the amount of ES and species distributions covered within each management zone across landscape management scenarios and RCPs Finally we used the Jaccard index to compare the spatial allocation of management zones derived from Marxan with Zones with the configuration of the zoning currently implemented in Meseta Iberica Eq 5 The Jaccard index measures the spatial overlap be tween the distribution of a given management zone under two alterna tive conditions current and best solution ranging from 0 no planning units in common to 1 all planning units in common Jaccard Best solutions Current zones Best solutions Currentzones 5 3 Results 31 Targets and areas selected The areas selected by Marxan with Zones met representation targets Table 1 Target distribution for ES across management zones Total targets accounted for 70 of the total supply in the 2005 scenario and were distributed according to their compatibility with agricultural practices Zone Agriculture ha Carbon Mg C ha1 yr1 Erosion control normalized rates from t ha 1 yr1 Recreation number of PUs with high value Transition 168386 25463 1079 361 Buffer 120275 63657 2699 1264 Core 48110 89121 3779 632 Total 336772 178243 7558 2529 Table 2 Target distribution for species in number of occurrences across management zones Targets were set according to their total number of occurrences in the study area and distributed according to habitat preferences Rare species are those with 200 or less occurrences across the study area Common Species are those with more than 200 occurrences Habitat Zone Rare Species Common Species Generalist Open Habitat Transition 0 50 Buffer 0 50 Core All occurrences 100 Total All occurrences 200 Forest Wetlands Semiopen habitat Transition 0 0 Buffer 0 75 Core All occurrences 125 Total All occurrences 200 MC Iglesias et al Journal of Environmental Management 322 2022 116045 8 for all species and ES under all management scenarios and RCPs However the number of planning units selected under each manage ment zone differed among scenarios and RCPs Fig 3a In the Farm Return and AgroforestRe scenarios and under both RCPs the Transition area required around 200 km2 less area than the 2005 sce nario BAU especially under RCP 45 required about 200 km2 more area than in 2005 and Afforestation required a similar area under RCP 45 but less area under RCP 85 The Buffer zone remained fairly con stant across future scenarios and RCPs requiring an area only slightly higher in comparison to 2005 The same was observed for the Core area but the increase in extent required in this case was higher In all 3 zones BAU showed a degree of variability between replicates of the same scenario higher than the other scenarios 32 Comparison with the current management plan The Core area in Marxan outputs was almost four times higher than in the actual planning of the BR 38723973 km2 in Marxan vs 1064 km2 currently In contrast Buffer zones and Transition areas in Marxan covered less area compared to their actual extent 27772881 vs 4203 km2 for the Buffer zone and 20202517 vs 6144 km2 for the Transition area Accordingly the spatial overlap of the distribution of manage ment zones in Marxan best solutions and the actual zoning of the BR was low across all management scenarios and RCPs including the 2005 scenario as evidenced by Jaccard index scores ranging between 008 and 026 Fig 3b The Jaccard index was higher in the Transition and Buffer zones than in the Core area for all scenarios and RCPs The Jaccard index for Core areas was highest under FarmReturn and RCP 85 and lowest under Afforestation and RCP 85 For Buffer zones all landscape management scenarios showed Jaccard index scores lower than the 2005 scenario although variation was low Jaccard values were higher for RCP 85 than for RCP 45 For the Transition area only the FarmReturn scenario RCP 85 showed a distribution closer to the current zonation than the 2005 scenario while BAU was the least similar under both RCPs 33 Fire intensity within management zones Average potential fire intensity revealed important differences among management zones Fig 4 The Transition area generally pre sented lower fire intensity across management scenarios in comparison with Buffer and Core areas Among management scenarios BAU showed higher fire intensities in the future compared to 2005 in all management zones but especially in the Core area The other three scenarios showed fire intensities lower than in 2005 with Afforestation showing the lowest fire intensities except for the Core area under RCP 85 for which AgroforestRe presented the lowest value 34 Coverage of ecosystem services There were some scenarios where the representation of ES in areas aiming to secure different ES could lead to conflicts between objectives such as the high representation of agricultural areas in the Core area under future scenarios eg Afforestation and AgroforestRe and 2005 Fig 3 a Area number of 1 km2 planning units allocated to management zones according to landscape management scenarios and RCPs b Similarity represented by the Jaccard index between the zonation of Marxan with Zones best solutions and the zonation currently implemented in the Meseta Iberica Transboundary Biosphere Reserve 2005 scenario is represented by a single line since we used one map only Boxplots aggregate results of 10 runs made for each landscape management scenario Lower and upper hinges of the boxplots correspond to the first and third quartiles Q1 and Q3 while the vertical line inside the box represents the median Lower whisker represents data at Q1 15 IQR and upper whisker represents data at Q3 15 IQR Data beyond that range are called outliers and represented individually with points MC Iglesias et al Journal of Environmental Management 322 2022 116045 9 scenarios Fig 5 Regulating services had high representation in the Transition area under the Afforestation and BAU scenarios for Carbon sequestration and all scenarios for erosion control Naturebased recre ation was highly represented in the Transition and particularly in the Core area Fig 5 35 Temporal turnover of species In the 2005 scenario Marxan with Zones met representation targets for all species However under 2050 scenarios there were some missing targets due to the strong decline in distribution area or local extinction predicted for some species The number of species whose presence is expected to decline below the representation target sought ranged from 20 to 22 under RCP 45 and from 21 to 23 under RCP 85 which is around 10 of the total number of species in both cases Table 3 In addition there were 39 species 188 under RCP 45 and 33 species 159 under RCP 85 that were predicted to completely disappear from the study area by 2050 Table 3 Contrastingly there were species that were not initially in the area but are expected to be present in future scenarios 10 species under RCP 85 and 11 species under RCP 45 rep resenting 5 of total species that always met their representation targets Table 3 All other species met their targets both in 2005 and 2050 Persist species in Table 3 4 Discussion This study illustrates how a flexible approach based on splitting representation targets between different management zones could contribute to harmonising conservation with other management objec tives one of the major challenges of the Meseta Iberica Biosphere Reserve as well as other conservation areas This approach could also contribute to facilitating zoning implementation and securing larger targets Lanzas et al 2019 However the implementation of this ho listic approach would need careful coordination across all local stake holders involved in land management to avoid conflicts between objectives and to identify best management practices Abarca et al 2022 Our simulations indicate that to conciliate biodiversity conservation with the sustainable supply of ES in the upcoming decades changes in the distribution and extent of the zones of the BR would be required To improve the role of Core areas the current extent of this zone would need to be expanded threefold by 2050 with different spatial prioriti sation depending on the landuse policy to be implemented in the future as suggested for other protected areas of Mediterranean climate Mar tinezHarms et al 2021 Lanzas et al 2021 Regos et al 2018 Core areas in future scenarios overlap to a great extent with existing Tran sition areas indicating that the required expansion of Core areas should Fig 4 Mean potential fire intensity class per zone in each landscape management scenario and RCP 2005 scenario is represented by a single line since we used one unique map For landscape management sce narios the 10 runs for each scenario are aggregated in boxplots Lower and upper hinges of the boxplots correspond to the first and third quartiles Q1 and Q3 while the vertical line inside the box represents the median Lower whisker represents data at Q1 15 IQR and upper whisker represents data at Q3 15 IQR Data beyond that range are outliers and represented individually with points MC Iglesias et al Journal of Environmental Management 322 2022 116045 10 be done at the expense of Transition areas In this regard our scenarios consistently identified particular areas of the BR that would be essential to maintain the BRs capacity to support agricultural practices and the ecological requirements for some openhabitat species under the Tran sition area These areas at lower altitudes in the BR comprise mainly agricultural areas and urban settlements which are already part of the Transition areas and would not be expected to significantly change over time Fig 6 Our simulations showed that these areas can remain under the Transition area regardless of management scenario Many other lo cations can be removed from the Transition area and allocated to other management zones allowing for a significant reduction in extent of the Transition area and an expansion of the other management zones Conversely areas allocated to the Core area in our simulations changed among management scenarios highlighting the need to account for landscape dynamics and climate change effects on biodiversity and ES in case of redesigning the BR Regos et al 2021 In addition our results indicate that at present there are areas in the reserve that are not required to meet the targets established in this exercise Not selected category in Fig 6 These areas could be allocated to the Transition area in future management plans to meet other goals and objectives To enhance the effectiveness of the BR for biodiversity conservation and ES supply in coming years we sought to achieve management goals in areas expected to burn at lower intensities Core and Buffer zones showed higher fire intensity since they are mostly covered by forest and shrubland which are essential to meet biodiversity and ES targets all but cultivated terrestrial plants High fire hazard in key biodiversity Fig 5 Amounts of ecosystem services secured as a ratio between the amount of ecosystem service held in each zone and the zone target required for each landscape scenario and RCP 2005 scenario is represented by a single line since we used one unique map For landscape management scenarios the 10 runs for each scenario are aggregated in boxplots Affo Afforestation scenario FRet FarmReturn scenario AfRet AgroforestRe scenario Lower and upper hinges of the boxplots correspond to the first and third quartiles Q1 and Q3 while the vertical line inside the box represents the median Lower whisker represents data at Q1 15 IQR and upper whisker represents data at Q3 15 IQR Data beyond that range are outliers and represented individually with points MC Iglesias et al Journal of Environmental Management 322 2022 116045 11 and ES supply areas highlights the importance and urgency of preven tion measures such as fuel management through grazing understorey clearing thinning prescribed burning or even unplanned fires under mild weather conditions to avoid highintensity uncontrollable wild fires Fernandes et al 2013 Regos et al 2014 Regarding biodiversity and ES coverage our simulations indicate that high amounts of ES could be secured in the future without compromising biodiversity conserva tion or other ES even under scenarios that simulate current fire man agement and land abandonment where conflicts among objectives could be expected Venier et al 2021 However regardless of management the Meseta Iberica BR is expected to experience a turnover in species composition in addition to a decline in species richness due to climate change To mitigate losses specific recovery andor management plans could be developed for target species Also the individual protected areas and Natura 2000 sites that comprise the BR should be redesigned to account for shifts in the distribution of species and ecosystems as responses to environmental change mainly climate change Dobrowski et al 2021 Lawler et al 2020 which will affect the limits and the extension of the Meseta Iberica Considering our management objec tives our results highlight the need to deviate from current management policies since they will put ES supply and biodiversity conservation at risk due to higher fire hazard that alternative management policies can decrease Afforestation if favouring the use of native species and sub jected to fuel treatments could lower fire intensity in comparison to shrubland dominated landscapes Moreira et al 2011 Simultaneously afforestation could contribute to climate adaptation and mitigation by enhancing carbon sequestration while providing habitat for forest dwelling species Firesmart policies that promote sustainable agricul ture and forestry are expected to lower fire intensity across all man agement zones Fig 4 while also increasing efficiency in resource use clearing by grazing and fire suppression Campos et al 2021 enhancing resilience and natural fire regulation capacity in the land scape Sil et al 2019 Additionally simulated firesmart policies maintained the provision of ES and enhanced biodiversity conservation in open habitats since they incorporate sustainable practices in areas of high agricultural value In this context our results indicate that the Meseta Iberica BR has the potential to adapt its management to both kinds of policies or even explore the simultaneous implementation of climate and firesmart policies which could be an opportunity to enhance the provision of ES and habitat for a wider range of species under climate and landscape change Law et al 2017 The current zoning of Meseta Iberica was designated based on existing conservation areas Protected Areas and Natura 2000 sites following different objectives criteria and scales and at different times Protected areas in the BR were created to preserve biodiversity and naturalcultural heritage at the national level according to the Portuguese and Spanish systems of protected areas The designation of these areas their conservation figure under national policy area and borders reflect social and political compromises among administra tions local governments and local and national groups of stakeholders The interaction of these factors often leads BRs to be more political than conservation tools as has been highlighted for various BRs in Spanish and Portuguese territory including Meseta Iberica Paül et al 2022 Despite the uncertainty inherent to any modelling framework our approach provides new insights into the BR design and management that can eventually help managers and decision makers deal with climaterelated risks in a proactive and costeffective way In future developments and applications our analytical framework can be enhanced by including other taxonomic groups such as plants invertebrates and fungi In addition our modelling approach would strongly benefit from a more explicit incorporation of climate change effects on ES quantification Beyond the biophysical assessment of the targeted ES the economic valuation of a larger set of ES will give additional support to our findings Considering a wider range of ES could also help setting ES targets more accurately as well as improving our understanding of their tradeoffs Lastly although fire intensity and frequency are extremely dependent on weather conditions Turco et al 2018 our analyses were restricted to the worstcase scenario for fire weather without considering the uncertainty of climate change sce narios Future research would also benefit from incorporating additional aspects of wildfires that can be beneficial to some species by promoting habitat renewability 5 Conclusions Integrated management and planning of biodiversity and ES features under past and future scenarios provide a powerful tool to address the effectiveness of current conservation policy and its role in conservation under uncertain global change Under this approach our results showed that the Meseta Iberica BR could maintain habitat for most species and conditions to the supply of several groups of ES To do so changes in management and planning would be needed in order to ensure the maximum potential of the BR in terms of biodiversity conservation and ecosystem services supply in the coming decades We mainly identified two required changes i An internal redesign of the zoning of the BR especially regarding Core Areas which would need a considerable expansion to help mitigate changes in biodiversity and accommodate ES supply under expected changes in climate and species distribution ii The BR needs to deviate from current management policies since they will result in encroached landscapes prone to high intensity uncon trollable wildfires with the potential to heavily damage ecosystems and compromise the supply of ES Instead management should focus on either climate or firesmart policies since both can enhance the effec tiveness of the BR although focusing on different management goals Implementation of these changes together with speciesoriented man agement plans will help promote multifunctional landscapes that help mitigate and adapt to climate change and ensure the best possible maintenance of biodiversity and ES supply under uncertain future climate conditions Author contributions MC Miguel Canibe Conceptualization Methodology Formal Analysis Writing Original Draft Writing Review Editing VH AR Virgilio Hermoso Adrian Regos Conceptualization Methodology Project Administration Funding Acquisition Writing Original Draft Writing Review Editing JCC CCS AS Joao C Campos Claudia CarvalhoSantos ˆAngelo Sil Conceptualization Methodology Writing Original Draft Writing Review Editing PMF JPH JAS Paulo M Fernandes Joao P Honrado Joao A Santos Project Administration Funding Acquisition Writing Original Draft Writing Review Editing TRF Teresa R Freitas Methodology Writing Original Draft Table 3 Summary of species turnover in the Meseta Iberica Biosphere Reserve under different landscape management and RCP scenarios in relation to the 2005 scenario Persist refers to the species that met the representation targets in both 2005 and future scenarios regardless of their changes in number of oc currences New species appear in the area in future scenarios and meet their representation targets Fail species are those whose levels of prevalence make meeting their targets impossible Lost species are completely absent from the area in future scenarios Results are presented with ranges to indicate variability between runs of the same scenario RCP Scenario Persist New Fail Lost 45 Afforestation 133135 1112 2022 39 BAU 133135 11 2022 39 FarmReturn 133134 11 2122 39 AgroforestRe 133135 11 2022 39 85 Afforestation 140 10 21 33 BAU 138139 10 2223 33 FarmReturn 139 10 22 33 AgroforestRe 139 10 2123 3234 MC Iglesias et al Journal of Environmental Management 322 2022 116045 12 Writing Review Editing JCA Joao C Azevedo Conceptualization Methodology Resources Supervision Project Administration Funding Acquisition Writing Original Draft Writing Review Editing Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper Data availability Data will be made available on request Acknowledgements This study was supported by national funds Portuguese Foundation for Science and Technology under the FirESmart project PCIFMOG 00832017 and the project UIDB040332020 CCS is supported by the Financiamento Programatico UIDP040502020 funded by na tional funds through the FCT IP VH was funded by the Junta de Fig 6 Maps of the management zones according to Marxan with Zones under a Reference scenario of 2005 b Afforestation c BAU d FarmReturn and e AgroforestRe scenarios Maps of the future scenarios show the best solution for the first run under the RCP 45 scenario MC Iglesias et al Journal of Environmental Management 322 2022 116045 13 Andalucía through an Emergia contract EMERGIA2000135 AR is supported by Juan de la Cierva fellowship program funded by the Spanish Ministry of Science and Innovation IJC2019041033I ˆAS received support from the Portuguese Foundation for Science and Technology FCT through PhD Grant SFRHBD1328382017 funded by the Ministry of Science Technology and Higher Education and by the European Social Fund Operational Program Human Capital within the 20142020 EU Strategic Framework We thank ZASNET European Grouping of Territorial Cooperation for providing us with data on the zonation of the RBTMI Appendix A Supplementary 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