Validating the Contribution of Nature-Based Farming Solutions (NBFS) to Agrobiodiversity Values through a Multi-Scale Landscape Approach
Abstract
:1. Introduction
2. Materials and Methods
2.1. The Adopted Landscape Ecology Analytical Approach
2.2. The Pilot Case Study: Environmental Context
3. Results and Discussion
3.1. Landscape Ecology Analyses Results
3.1.1. Landscape Structural Indicators Results
- Positively lower MPS values for Fa (MPS equal to 0.43 ha; −19% for the AGR Fa sub-system), which reflect the positive effects related to small-sized agricultural patches among the pilot farm: higher landscape heterogeneity [102,103]; hedge microhabitat and niche diversification [104,105,106]; lower sink effects [54,107]; increased variability of micro-climatic conditions and provision of breeding sites [108,109]; and encouraging species diversification and higher avian diversity (a balance between generalist and specialist behaviors) [54,110,111,112];
- Relatively high MPS values for the La NAT sub-system (MPS equal to 1.12 ha) reflect a proper consistency of natural (woody) patches among La. This can be related to a positive influence on the properties of source areas: interior habitat conditions, higher specialist species population sizes, lowering their probability of local extinction, rising stability traits, and balancing the impacts coming from the neighboring agricultural matrix [13,54]. These traits underline the current pivotal role of the existing woody components and the potential that could be displayed by their preservation, proper management (improvement of their ecological quality), and extension;
- The MTX index showed, as expected: lower occurrence of natural sub-system components in Fa (−63%), which might be enhanced through the further integration of diffused natural and semi-natural components and in between productive fields [102,104,105]; higher relative occurrence in Fa of agricultural sub-system components (+22%); and good stability of the La agricultural matrix (absence of significantly spread impacts derived from non-compatible land uses) (69.6% of total surface), as it was already highlighted by landscape apparatus analysis (Figure 3a,b). This increases the potential for effectively correcting the current ecological trends toward higher quality values [13,113,114,115];
- Indices related to patch shape complexity (MPAR, SI, PFD, and their variants) showed positive results (significantly higher patch complexity) for Fa in their arithmetic mean variants, where the effect of the different Fa and La overall dimensions is kept under control (average single patch values): MPAR (+623% in TOT Fa), MSI (+201% in TOT Fa), and MPFD (+438% in TOT Fa). Thus, MPAR, MSI, and MPFD showed good sensitivity to La and Fa differences. They were also positively correlated (Table 3) and can be consequently considered redundant in the studied context (they capture similar qualities of spatial patterns); their potential interchange might be further tested among larger datasets. In contrast, their area-weighted mean variants (AWSI and AWPFD) showed negative results for Fa. This was influenced by the over-weighting of agricultural patches on wider surfaces in La, while the narrow, small-sized, elongated agricultural patches in Fa were down-weighted by the algorithm. These effects are widened by differences in the overall dimensions of La and Fa, implying that such area-weighted indices are unsuitable for comparing different scale contexts. Further testing of such indicators in equally-sized contexts would integrate such assumptions [59]. PFD values showed relative low sensitivity to Fa and La differences (−3% in AGR Fa and −1% in TOT Fa) compared to the other shape complexity indicators. Its suitability for project purposes should be further checked on wider datasets. Shape complexity in agricultural contexts is suitable for representing the level of patch inter-digitation: high values inform on ecological exchange trends (high exposure to neighboring impacting land uses or high permeability to biotic and resource exchanges with neighboring semi-natural land uses). Thus, their positive or negative ecological value interpretation should be paired with context ecological quality analysis, such as landscape apparatuses and BTC values spatial variability analysis. For instance, among Fa, shape complexity values should be interpreted as positively supporting the NBFS effects as well as the exchanges with the neighboring wooded areas (even if critical exposure to neighboring conventional patches should be considered as well). Moreover, if intended as a measure of land use intensity [69], positive values of shape complexity indices can be indirectly related to heterogeneity and diversity values, especially in rural contexts (checkerboard-shaped landscapes) [55,69,116,117,118].
- Among landscape diversity indicators, both DIV[1a-1b-2] showed relative positive contributions of Fa to the agricultural sub-system heterogeneity (+86%, +98%, and +124% in AGR Fa, respectively). Both DIV[1a-2] showed positive contributions of Fa to the total landscape system diversification, while lower values were registered for the Fa natural sub-system diversity (both for DIV[1a-1b-2]), highlighting the need for further improvement of natural landscape features and their configuration in the pilot case study in order to better counterbalance its positive contributions towards the surrounding context. DIV2 showed the highest relative sensitivity to changes (both for the agricultural subsystem and for the total area), and it should be considered to have higher congruency as it is a normalized version of DIV1a and its values do not depend on the number of land use categories, being more independent of scale [59];
- As expected, DOM [1–2] indicators are inversely correlated to DIV[1a-1b-2] ones (Table 3), and consequently provide redundant information. They were the basis for computing LSD [1–2] values, which showed a positive contribution of Fa to the agricultural sub-system diversification [respectively, +41% (LSD1) and +102% (LSD2) in AGR Fa]. In comparison, the total landscape system LSD [1–2] showed smaller changes (+2% and +44% in TOT Fa, respectively), with LSD2 showing a higher relative sensitivity to changes between total La and Fa, in line with the trend between DIV1a-2 indicators. In line with all DIV[1a-1b-2] values, higher LSD [1–2] values were registered for the La on a natural sub-system (LSD1 −51% for NAT Fa and LSD2 −37% for NAT Fa), confirming the above-cited DIV[1a-1b-2] value interpretation;
- All DIV[1a-1b-2] and LSD [1–2] indicators are positively correlated between each other (Table 3), consequently bringing redundant information, as was expected, and suggesting the opportunity of their screening. Indeed, they were included to allow the comparison of their different performances (a preliminary assessment of their sensitivity to changes among the different studied contexts).
- Higher habitat diversification enables source populations to spillover from semi-natural patches to intensively managed patches, balancing generalist and specialist species presences, rising species richness values of different taxa, and reducing local extinction risks [70,102,104,105,111,119,120,121,122,123,124,125,126];
3.1.2. Landscape Functional Indicators Results
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
Indicators | Equation | References | |
---|---|---|---|
PATCHES METRICS | Medium patches size (MPS) | Ai = total area of each land use categories patches Ni = no. of patches for each land use categories LU = no. of land use categories | [59] |
Matrix (MTX) | Ai = total area of each land use categories patches Atot = total area | [59] | |
SHAPE INDICES | Mean Perimeter area ratio (MPAR) | Pi = Perimeter of each land use category patches NP = total no. of patches | [69] |
Shape index (SI) | [69] | ||
Mean Shape Index (MSI) | [69] | ||
Area weighted mean shape index (AWSI) | [69] | ||
Patch fractal dimension (PFD) | [59,69] | ||
Mean patch fractal dimension (MPFD) | [69] | ||
Area weighted mean patch fractal dimension (AWPFD) | [69] | ||
COMPOSITION INDICES | Diversity_1a/tot (DIV1a) | [59] | |
Diversity_1b/landscape element (DIV1b) | Ay = total area of each landscape system (natural, agricultural, and anthropic) | [59] | |
Diversity_2 (DIV2) | lnS = max(DIV) S = no. of land use categories | [59,142] | |
Dominance_1 (DOM1) | [82,84] | ||
Dominance_2 (DOM2) | [59] | ||
Landscape Structural Diversity_1 (LSD1) | [82,84] | ||
Landscape Structural Diversity_2 (LSD2) | [82,84] | ||
CONNECTIVITY INDICES | Connectivity (CON) | L = no. of links N = no. of nodes | [95] |
Weighted connectivity (WCON) | Li = no. of links for each Ecological Quality Class (EQCi = [1–5]) Wi = EQCi weight: | [95] modified by authors | |
Circuitry (CIR) | [95] | ||
Weighted circuitry (WCIR) | Li = no. of links for each Ecological Quality Class (EQCi = [1–5]) Wi = EQCi weight (as above) | [95] modified by authors | |
FUNCTIONALITY INDICES | Biological Territorial Capacity (BTC) | BTCi = BTC value attributed to each land use category (tabulated values; see references) | [73,94] |
References
- Altieri, M.A. The ecological role of biodiversity in agroecosystems. Agric. Ecosyst. Environ. 1999, 74, 19–31. [Google Scholar] [CrossRef] [Green Version]
- Benton, T.G. Managing Farming’s Footprint on Biodiversity. Science 2007, 315, 341–342. [Google Scholar] [CrossRef] [PubMed]
- Fabbri, P. Natura e Cultura del Paesaggio Agrario, Indirizzi per La Tutela e la Progettazione; Città Studi Edizioni: Milan, Italy, 1997. [Google Scholar]
- Gliessman, S.R. Agroecology: The Ecology of Sustainable Food Systems, 2nd ed.; Taylor & Francis Group, Ed.; CRC Press: Boca Raton, FL, USA, 2007. [Google Scholar]
- Miralles-Wilhelm, F.; Iseman, T. Nature-Based Solutions in Agriculture—The Case and Pathway for Adoption; Food & Agriculture Org. and The Nature Conservancy: Arlington, VA, USA, 2021. [Google Scholar] [CrossRef]
- Wojtkowski, P. Landscape Agroecology, 1st ed.; CRC Press: Boca Raton, FL, USA, 2003. [Google Scholar]
- Altieri, M.A. Agroecology: The Scientific Basis of Alternative Agriculture; Division of Biological Control, University of California: Berkeley, CA, USA, 1983. [Google Scholar]
- Jackson, L.E.; Pascual, U.; Hodgkin, T. Utilizing and conserving agrobiodiversity in agricultural landscapes. Agric. Ecosyst. Environ. 2007, 121, 196–210. [Google Scholar] [CrossRef]
- Oliver, T.H.; Heard, M.S.; Isaac, N.J.B.; Roy, D.B.; Procter, D.; Eigenbrod, F.; Freckleton, R.; Hector, A.; Orme, C.D.L.; Petchey, O.L.; et al. Biodiversity and Resilience of Ecosystem Functions. Trends Ecol. Evol. 2015, 30, 673–684. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kremen, C.; Merenlender, A.M. Landscapes that work for biodiversity and people. Science 2018, 362. [Google Scholar] [CrossRef] [Green Version]
- Tscharntke, T.; Klein, A.; Kruess, A.; Steffan-Dewenter, I.; Thies, C. Landscape perspectives on agricultural intensification and biodiversity—Ecosystem service management. Ecol. Lett. 2005, 8, 857–874. [Google Scholar] [CrossRef]
- Tilman, D.; Isbell, F.; Cowles, J.M. Biodiversity and Ecosystem Functioning. Annu. Rev. Ecol. Evol. Syst. 2014, 45, 471–493. [Google Scholar] [CrossRef]
- Donald, P.F.; Evans, A.D. Habitat connectivity and matrix restoration: The wider implications of agri-environment schemes. J. Appl. Ecol. 2006, 43, 209–218. [Google Scholar] [CrossRef]
- Hooper, D.U.; Chapin Iii, F.S.; Ewel, J.J.; Hector, A.; Inchausti, P.; Lavorel, S.; Lawton, J.H.; Lodge, D.M.; Loreau, M.; Naeem, S.; et al. Effects of biodiversity on ecosystem functioning: A consensus of current knowledge. Ecol. Monogr. 2005, 75, 3–35. [Google Scholar] [CrossRef]
- Opdam, P.; Wascher, D. Climate change meets habitat fragmentation: Linking landscape and biogeographical scale levels in research and conservation. Biol. Conserv. 2004, 117, 285–297. [Google Scholar] [CrossRef]
- Chapin, F.S., III; Zavaleta, E.S.; Eviner, V.T.; Naylor, R.L.; Vitousek, P.M.; Reynolds, H.L.; Hooper, D.U.; Lavorel, S.; Sala, O.E.; Hobbie, S.E.; et al. Consequences of changing biodiversity. Nature 2000, 405, 234–242. [Google Scholar] [CrossRef] [PubMed]
- Oliveira, B.F.; Moore, F.C.; Dong, X. Biodiversity mediates ecosystem sensitivity to climate variability. Commun. Biol. 2022, 5, 628. [Google Scholar] [CrossRef] [PubMed]
- Hulme, P.E. Adapting to climate change: Is there scope for ecological management in the face of a global threat? J. Appl. Ecol. 2005, 42, 784–794. [Google Scholar] [CrossRef]
- Honnay, O.; Verheyen, K.; Butaye, J.; Jacquemyn, H.; Bossuyt, B.; Hermy, M. Possible effects of habitat fragmentation and climate change on the range of forest plant species. Ecol. Lett. 2002, 5, 525–530. [Google Scholar] [CrossRef]
- Grime, J.P.; Brown, V.K.; Thompson, K.; Masters, G.J.; Hillier, S.H.; Clarke, I.P.; Askew, A.P.; Corker, D.; Kielty, J.P. The Response of Two Contrasting Limestone Grasslands to Simulated Climate Change. Science 2000, 289, 762–765. [Google Scholar] [CrossRef]
- Hernández-Morcillo, M.; Burgess, P.; Mirck, J.; Pantera, A.; Plieninger, T. Scanning agroforestry-based solutions for climate change mitigation and adaptation in Europe. Environ. Sci. Policy 2018, 80, 44–52. [Google Scholar] [CrossRef] [Green Version]
- Maes, J.; Jacobs, S. Nature-Based Solutions for Europe’s Sustainable Development. Conserv. Lett. 2017, 10, 121–124. [Google Scholar] [CrossRef] [Green Version]
- European Commission. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions, Green Infrastructure (GI)-Enhancing Europe’s Natural Capital {SWD(2013) 155 Final}. 2013, COM(2013) 249 Final. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52013DC0249 (accessed on 5 January 2023).
- European Commission. Towards an EU Research and Innovation Policy Agenda for Nature-Based Solutions & Re-Naturing Cities: Final Report of the Horizon 2020 Expert Group on ‘Nature-Based Solutions and re-Naturing Cities’: (Full Version); Publications Office, Directorate-General for Research and Innovation: Brussels, Belgium, 2015.
- European Commission. Communication from the Commission to the European Parliament, the European Council, the Council, the European Economic and Social Committee and the Committee of the Regions—The European Green Deal. 2019, 11.12.2019 COM(2019) 640 final. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM%3A2019%3A640%3AFIN (accessed on 5 January 2023).
- European Commission. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions—A Farm to Fork Strategy. 2020, 20.05.2020 COM (2020) 381 final. Available online: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52020DC0381 (accessed on 5 January 2023).
- European Commission. List of Potential Agricultural Practices That Eco-Schemes could Support; European Commission: Brussels, Belgium, 2021. Available online: https://agriculture.ec.europa.eu/news/commission-publishes-list-potential-eco-schemes-2021-01-14_en#moreinfo (accessed on 5 January 2023).
- United Nations. Transforming Our World: The 2030 Agenda for Sustainable Development, Resolution Adopted by the General Assembly on 25 September 2015; United Nations: San Francisco, CA, USA, 2015; A/RES/70/1.
- MEA. Ecosystems and Human Well-Being—Synthesis, Millennium Ecosystem Assessment; Island Press: Washington, DC, USA, 2005; Volume A/RES/70/1. [Google Scholar]
- AAVV. Towards Integrating Biological and Landscape Diversity for Sustainable Agriculture in Europe. In Proceedings of the High-Level Pan-European Conference on Agriculture and Biodiversity, Paris, France, 5–7 June 2002. [Google Scholar]
- Evans, A.D.; Armstrong-Brown, S.; Grice, P.V. The role of research and development in the evolution of a ‘smart’ agri-environment scheme. Asp. Appl. Biol. 2002, 67, 253–262. [Google Scholar]
- Kleijn, D.; Berendse, F.; Smit, R.; Gilissen, N. Agri-environment schemes do not effectively protect biodiversity in Dutch agricultural landscapes. Nature 2001, 413, 723–725. [Google Scholar] [CrossRef]
- Kleijn, D.; Berendse, F.; Smit, R.; Gilissen, N.; Smit, J.; Brak, B.; Groeneveld, R. Ecological Effectiveness of Agri-Environment Schemes in Different Agricultural Landscapes in The Netherlands. Conserv. Biol. 2004, 18, 775–786. [Google Scholar] [CrossRef]
- Krebs, J.R.; Wilson, J.D.; Bradbury, R.B.; Siriwardena, G.M. The second Silent Spring? Nature 1999, 400, 611–612. [Google Scholar] [CrossRef]
- Herzon, I.; Birge, T.; Allen, B.; Povellato, A.; Vanni, F.; Hart, K.; Radley, G.; Tucker, G.; Keenleyside, C.; Oppermann, R.; et al. Time to look for evidence: Results-based approach to biodiversity conservation on farmland in Europe. Land Use Policy 2018, 71, 347–354. [Google Scholar] [CrossRef]
- Burton, R.J.F.; Schwarz, G. Result-oriented agri-environmental schemes in Europe and their potential for promoting behavioural change. Land Use Policy 2013, 30, 628–641. [Google Scholar] [CrossRef] [Green Version]
- Nitsch, H.; Bogner, D.; Dubbert, M.; Fleury, P.; Hofstetter, P.; Knaus, F.; Rudin, S.; Šabec, N.; Schmid, O.; Schramek, J.; et al. MERIT. Review on Result-Oriented Measures for Sustainable Land Management in Alpine Agriculture & Comparison of Case Study Areas. Report of Work Package 1. RURAGRI Res. Programme 2013–2016; European Commission: Luxembourg, 2014.
- Keenleyside, C.; Radley, G.; Tucker, G.; Underwood, E.; Hart, K.; Allen, B.; Menadue, H. Results-Based Payments for Biodiversity Guidance Handbook: Designing and Implementing Results-Based Agri-Environment Schemes 2014-20, Prepared for the European Commission, DG Environment; Institute for European Environmental Policy: London, UK, 2014; Volume Contract No ENV.B.2/ETU/2013/0046. [Google Scholar]
- Underwood, E. Results-Based Payments for Biodiversity, Supplement to Guidance Handbook, Result Indicators Used in Europe, the Selection, Testing Measurement and Verification of Indicators of Biodiversity Results, Prepared for the European Commission, DG Environment; Institute for European Environmental Policy: London, UK, 2014; Volume Contract No ENV.B.2/ETU/2013/0046. [Google Scholar]
- Stolze, M.; Frick, R.; Schmid, O.; Stöckli, S.; Bogner, D.; Chevillat, V.; Dubbert, M.; Fleury, P.; Neuner, S.; Nitsch, H.; et al. Result-Oriented Measures for Biodiversity in Mountain Farming—A Policy Handbook; Researc Institute of Organic Agriculture (FiBL): Frick, Switzerland, 2015. [Google Scholar]
- Schröder, S.; Begemann, F.; Harrer, S. Agrobiodiversity monitoring—Documentation at European level. J. Für Verbrauch. Und Lebensm. 2007, 2, 29–32. [Google Scholar] [CrossRef]
- Taffetani, F.; Rismondo, M. Bioindicators system for the evaluation of the environment quality of agro-ecosystems. Fitosociologia 2009, 46, 3–22. [Google Scholar]
- Taffetani, F.; Rismondo, M.; Lancioni, A. Integrated tools and methods for the analysis of agro-ecosystem’s functionality through vegetational investigations. Fitosociologia 2011, 48, 41–52. [Google Scholar]
- Bassignana, C.F.; Merante, P.; Belliére, S.R.; Vazzana, C.; Migliorini, P. Assessment of Agricultural Biodiversity in Organic Livestock Farms in Italy. Agronomy 2022, 12, 607. [Google Scholar] [CrossRef]
- Tasser, E.; Rüdisser, J.; Plaikner, M.; Wezel, A.; Stöckli, S.; Vincent, A.; Nitsch, H.; Dubbert, M.; Moos, V.; Walde, J.; et al. A simple biodiversity assessment scheme supporting nature-friendly farm management. Ecol. Indic. 2019, 107, 105649. [Google Scholar] [CrossRef] [Green Version]
- Duelli, P.; Obrist, M.K. Biodiversity indicators: The choice of values and measures. Agriculture, Ecosystems & Environment 2003, 98, 87–98. [Google Scholar] [CrossRef]
- Migliorini, P.; Vazzana, C. Biodiversity Indicators for Sustainability Evaluation of Conventional and Organic Agro-ecosystems. Ital. J. Agron. 2007, 2, 105–110. [Google Scholar] [CrossRef]
- Blumetto, O.; Castagna, A.; Cardozo, G.; García, F.; Tiscornia, G.; Ruggia, A.; Scarlato, S.; Albicette, M.M.; Aguerre, V.; Albin, A. Ecosystem Integrity Index, an innovative environmental evaluation tool for agricultural production systems. Ecol. Indic. 2019, 101, 725–733. [Google Scholar] [CrossRef]
- Clergue, B.; Amiaud, B.; Pervanchon, F.; Lasserre-Joulin, F.; Plantureux, S. Biodiversity: Function and assessment in agricultural areas. Rev. Sustain. Agric. 2005, 25, 1–15. [Google Scholar] [CrossRef]
- Chase, J.M.; McGill, B.J.; Thompson, P.L.; Antão, L.H.; Bates, A.E.; Blowes, S.A.; Dornelas, M.; Gonzalez, A.; Magurran, A.E.; Supp, S.R.; et al. Species richness change across spatial scales. Oikos 2019, 128, 1079–1091. [Google Scholar] [CrossRef] [Green Version]
- Mazerolle, M.J.; Villard, M.-A. Patch characteristics and landscape context as predictors of species presence and abundance: A review1. Écoscience 1999, 6, 117–124. [Google Scholar] [CrossRef]
- Duelli, P. Biodiversity Evaluation in Agricultural Landscapes: An Approach at Two Different Scales. Agric. Ecosyst. Environ. 1997, 62, 81–91. [Google Scholar] [CrossRef]
- Dover, J.W.; Bunce, R.G.H. Key Concepts in Landscape Ecology; IALE UK, Coplin Cross Printers Ltd.: Garstang, UK, 1998. [Google Scholar]
- Dramstad, W.E.; Olson, J.D.; Forman, R.T.T. Landscape Ecology Principles in Landscape Architecture and Land Use Planning; Island Press: Washington, DC, USA, 1996. [Google Scholar]
- Forman, R.T.T. Land Mosaics: The Ecology of Landscapes and Regions, 1st ed.; Cambridge University Press: Cambridge, UK, 1995. [Google Scholar]
- Forman, R.T.T.; Godron, M. Landscape Ecology; J. Wiley and Sons: New York, NY, USA, 1986. [Google Scholar]
- Turner, M.G.; Gardner, R.H. Quantitative Methods in Landscape Ecology, the Analysis and Interpretation of Landscape Heterogeneity; Springer: New York, NY, USA, 1991. [Google Scholar]
- Urban, D.L.; O’Neill, R.V.; Shugart, H.H., Jr. Landscape Ecology, A Hierarquical Perspective Can Help Scientists Understand Spatial Patterns. BioScience 1987, 37, 119–127. [Google Scholar] [CrossRef]
- Turner, M.G.; Gardner, R.H. Landscape Ecology in Theory and Practice, Pattern and Process; Springer: New York, NY, USA, 2015. [Google Scholar]
- Wezel, A.; Casagrande, M.; Celette, F.; Vian, J.-F.; Ferrer, A.; Peigné, J. Agroecological practices for sustainable agriculture. A Review. Agron. Sustain. Dev. 2014, 34, 1–20. [Google Scholar] [CrossRef] [Green Version]
- Manning, P.; Loos, J.; Barnes, A.D.; Batáry, P.; Bianchi, F.J.J.A.; Buchmann, N.; De Deyn, G.B.; Ebeling, A.; Eisenhauer, N.; Fischer, M.; et al. Chapter Ten—Transferring biodiversity-ecosystem function research to the management of ‘real-world’ ecosystems. Adv. Ecol. Res. 2019, 61, 323–356. [Google Scholar] [CrossRef] [Green Version]
- Opdam, P.; Foppen, R.; Vos, C. Bridging the gap between ecology and spatial planning in landscape ecology. Landsc. Ecol. 2001, 16, 767–779. [Google Scholar] [CrossRef]
- Braun-Blanquet, J. Pflanzesoziologie; Springer: Wien, Austria, 1964. [Google Scholar]
- Pirola, A. Elementi di Fitosociologia; CLUEB: Bologna, Italy, 1970. [Google Scholar]
- Géhu, J.M. L’analyse symphytosociologique et géosymphytosociologique de l’espace, Théorie et métodologie. Coll. Phytosoc. 1988, 17, 11–46. [Google Scholar]
- Géhu, J.M.; Rivas-Martínez, S. Notions fondamentales de phytosociologie. In “Syntaxonomie”, Berichte der Internationalen Symposien der Internationalen Vereinigung für Vegetationskunde; Vaduz, Cramer: Rinteln, Germany, 1981; pp. 5–33. [Google Scholar]
- Rivas-Martínez, S. Nociones sobre Fitosociología, Biogeografía e Bioclimatología. In La vegetation de España; Universidad de Alcalá de Henares: Alcalá de Henares, Spain, 1987; pp. 19–45. [Google Scholar]
- Honnay, O.; Piessens, K.; Van Landuyt, W.; Hermy, M.; Gulinck, H. Satellite based land use and landscape complexity indices as predictors for regional plant species diversity. Landsc. Urban Plan. 2003, 63, 241–250. [Google Scholar] [CrossRef]
- Moser, D.; Zechmeister, H.G.; Plutzar, C.; Sauberer, N.; Wrbka, T.; Grabherr, G. Landscape patch shape complexity as an effective measure for plant species richness in rural landscapes. Landsc. Ecol. 2002, 17, 657–669. [Google Scholar] [CrossRef]
- Maskell, L.C.; Botham, M.; Henrys, P.; Jarvis, S.; Maxwell, D.; Robinson, D.A.; Rowland, C.S.; Siriwardena, G.; Smart, S.; Skates, J.; et al. Exploring relationships between land use intensity, habitat heterogeneity and biodiversity to identify and monitor areas of High Nature Value farming. Biol. Conserv. 2019, 231, 30–38. [Google Scholar] [CrossRef]
- Burel, F. Effect of landscape structure and dynamics on species diversity in hedgerow networks. Landsc. Ecol. 1992, 6, 161–174. [Google Scholar] [CrossRef] [Green Version]
- Ingegnoli, V.; Pignatti, S. The impact of the widened landscape ecology on vegetation science: Towards the new paradigm. Atti Della Accad. Naz. Dei Lincei. Rend. Lincei. Sci. Fis. E Nat. 2007, 18, 89–122. [Google Scholar] [CrossRef]
- Ingegnoli, V. The study of vegetation for a diagnostical evaluation of agricultural landscapes, some examples fom Lombardy. Ann. Bot. Nuova Ser. 2006, 6, 111–120. [Google Scholar]
- Burel, F. Hedgerows and Their Role in Agricultural Landscapes. Crit. Rev. Plant Sci. 1996, 15, 169–190. [Google Scholar] [CrossRef]
- Franco, D. Paesaggio, Reti Ecologiche ed Agroforestazione: Il Ruolo Dell’ecologia del Paesaggio e Dell’agroforestazione nella Riqualificazione Ambientale e Produttiva del Paesaggio/di Daniel Franco; Il Verde Editoriale: Milan, Italy, 2000. [Google Scholar]
- Franco, D. Ecological networks: The state of the art from a landscape ecology perspective in the national framework. In Reti Ecologiche: Una Chiave per la Conservazione e la Gestione dei Paesaggi Frammentati; Sitzia, T., Reniero, S., Eds.; Pubblicazioni del Corso di Cultura in Ecologia, Atti del XL Corso, Università degli Studi: Padova, Italy, 2004. [Google Scholar]
- Schoeman, Y. The Role of Landscape Ecology in the Management of Agroecosystems; Technical Report (Project Eco Agriculture); University of the Free State: Bloemfontein, South Africa, 2009. [Google Scholar] [CrossRef]
- Ingegnoli, V. Landscape Ecology: A Widening Foundation; Springer: Berlin/Heidelberg, Germany, 2002. [Google Scholar]
- Battisti, C. Frammentazione Ambientale, Connettività, Reti Ecologiche—Un Contributo Teorico e Metodologico con Particolare Riferimento Alla Fauna Selvatica; Provincia di Roma, Assessorato alle Politiche Agricole, Ambientali e Protezione Civile: Rome, Italy, 2004. [Google Scholar]
- Ryszkowski, L. Landscape Ecology in Agroecosystems Management; CRC Press: Boca Raton, FL, USA, 2001. [Google Scholar]
- Pignatti, S. Ecologia del Paesaggio/Sandro Pignatti; UTET: Torino, Italy, 1994. [Google Scholar]
- Ingegnoli, V. Landscape Bionomics: Biological-Integrated Lanscape Ecology; Springer: Milan, Italy, 2015. [Google Scholar]
- Ingegnoli, V.; Bocchi, S.; Giglio, E. Landscape Bionomics: A Systemic Approach to Understand and Govern Territorial Development. WSEAS Trans. Environ. Dev. 2017, 13, 189–196. [Google Scholar]
- Ingegnoli, V.; Giglio, E. Ecologia del Paesaggio: Manuale per Conservare, Gestire e Pianificare L’ambiente; Sistemi Editoriali: Napoli, Italy, 2005. [Google Scholar]
- Geoportale Piemonte. Available online: www.geoportale.piemonte.it/cms/ (accessed on 10 October 2022).
- Istituto Geografico Militare. Available online: www.igmi.org (accessed on 10 October 2022).
- Geoportale Nazionale. Available online: www.pcn.minambiente.it/mattm/ (accessed on 10 October 2022).
- Gibelli, M.G.; Dosi, V.M.; Selva, C. From “Landscape DNA” to Green Infrastructures Planning. In Metropolitan Landscapes: Towards a Shared Construction of the Resilient City of the Future; Contin, A., Ed.; Springer International Publishing: Cham, Switzerland, 2021; pp. 121–137. [Google Scholar]
- Adger, W.N. Vulnerability. Glob. Environ. Chang. 2006, 16, 268–281. [Google Scholar] [CrossRef]
- Gallopin, G.C. Linkages between vulnerability, resilience, and adaptive capacity. Glob. Environ. Chang. 2006, 16, 293–303. [Google Scholar] [CrossRef]
- Janssen, M.A.; Schoon, M.L.; Ke, W.; Börner, K. Scholarly networks on resilience, vulnerability and adaptation within the human dimensions of global environmental change. Glob. Environ. Chang. 2006, 16, 240–252. [Google Scholar] [CrossRef] [Green Version]
- Westman, W.E. Measuring the Inertia and Resilience of Ecosystems. BioScience 1978, 28, 705–710. [Google Scholar] [CrossRef]
- Brandt, J.; Tress, B.; Tress, G. Multifunctional Landscapes: Interdisciplinary Approaches to Landscape Research and Management; Centre for Landscape Research: Roskilde, Denmark, 2000. [Google Scholar]
- Ingegnoli, V.; Giglio, E. Proposal of a synthetic indicator to control ecological dynamics at an ecological mosaic scale. Ann. Bot. 1999, 57, 181–190. [Google Scholar]
- Fabbri, P. Ecologia del Paesaggio per la Pianificazione/Pompeo Fabbri; Aracne: Roma, Italy, 2005. [Google Scholar]
- Pesaresi, S.; Galdenzi, D.; Biondi, E.; Casavecchia, S. Bioclimate of Italy: Application of the worldwide bioclimatic classification system. J. Maps 2014, 10, 538–553. [Google Scholar] [CrossRef]
- Pesaresi, S.; Biondi, E.; Casavecchia, S. Bioclimates of Italy. J. Maps 2017, 13, 955–960. [Google Scholar] [CrossRef] [Green Version]
- Vagge, I. Le foreste di farnia e carpino bianco della pianura lombarda. In Bosco: Biodiversità, Diritti e Culture dal Medioevo al Nostro Tempo (I libri di Viella; 411); Viella: Rome, Italy, 2022. [Google Scholar]
- Camerano, P.; Terzuolo, P.G.; Siniscalco, C. I boschi planiziali del Piemonte. Nat. Brescia. Ann. Mus. Civ. Sc. Nat. 2009, 36, 185–189. [Google Scholar]
- Blasi, C. La Vegetazione d’Italia con Carta delle Serie di Vegetazione Scala 1:500 000; Palombi Editori: Rome, Italy, 2010; p. 539. [Google Scholar]
- Galasso, G.; Conti, F.; Peruzzi, L.; Ardenghi, N.M.G.; Banfi, E.; Celesti-Grapow, L.; Albano, A.; Alessandrini, A.; Bacchetta, G.; Ballelli, S.; et al. An updated checklist of the vascular flora alien to Italy. Plant Biosyst. Int. J. Deal. All Asp. Plant Biol. 2018, 152, 556–592. [Google Scholar] [CrossRef]
- Fahrig, L.; Baudry, J.; Brotons, L.; Burel, F.G.; Crist, T.O.; Fuller, R.J.; Sirami, C.; Siriwardena, G.M.; Martin, J.-L. Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. Ecol. Lett. 2011, 14, 101–112. [Google Scholar] [CrossRef]
- Perović, D.; Gámez-Virués, S.; Börschig, C.; Klein, A.-M.; Krauss, J.; Steckel, J.; Rothenwöhrer, C.; Erasmi, S.; Tscharntke, T.; Westphal, C. Configurational landscape heterogeneity shapes functional community composition of grassland butterflies. J. Appl. Ecol. 2015, 52, 505–513. [Google Scholar] [CrossRef]
- Morelli, F. High nature value farmland increases taxonomic diversity, functional richness and evolutionary uniqueness of bird communities. Ecol. Indic. 2018, 90, 540–546. [Google Scholar] [CrossRef]
- Morelli, F. Relative importance of marginal vegetation (shrubs, hedgerows, isolated trees) surrogate of HNV farmland for bird species distribution in Central Italy. Ecol. Eng. 2013, 57, 261–266. [Google Scholar] [CrossRef]
- Kisel, Y.; McInnes, L.; Toomey, N.H.; Orme, C.D.L. How diversification rates and diversity limits combine to create large-scale species–area relationships. Philos. Trans. R. Soc. B Biol. Sci. 2011, 366, 2514–2525. [Google Scholar] [CrossRef] [PubMed]
- Chen, L.; Fu, B.; Zhao, W. Source-sink landscape theory and its ecological significance. Front. Biol. China 2008, 3, 131–136. [Google Scholar] [CrossRef]
- Stein, A.; Gerstner, K.; Kreft, H. Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales. Ecol. Lett. 2014, 17, 866–880. [Google Scholar] [CrossRef]
- Benton, T.G.; Vickery, J.A.; Wilson, J.D. Farmland biodiversity: Is habitat heterogeneity the key? Trends Ecol. Evol. 2003, 18, 182–188. [Google Scholar] [CrossRef]
- Morelli, F.; Benedetti, Y.; Šímová, P. Landscape metrics as indicators of avian diversity and community measures. Ecol. Indic. 2018, 90, 132–141. [Google Scholar] [CrossRef]
- Schindler, S.; von Wehrden, H.; Poirazidis, K.; Wrbka, T.; Kati, V. Multiscale performance of landscape metrics as indicators of species richness of plants, insects and vertebrates. Ecol. Indic. 2013, 31, 41–48. [Google Scholar] [CrossRef]
- Robinson, R.A.; Sutherland, W.J. Post-war changes in arable farming and biodiversity in Great Britain. J. Appl. Ecol. 2002, 39, 157–176. [Google Scholar] [CrossRef] [Green Version]
- With, K.A.; Crist, T.O. Critical Thresholds in Species’ Responses to Landscape Structure. Ecology 1995, 76, 2446–2459. [Google Scholar] [CrossRef]
- Jules, E.S.; Shahani, P. A broader ecological context to habitat fragmentation: Why matrix habitat is more important than we thought. J. Veg. Sci. 2003, 14, 459–464. [Google Scholar] [CrossRef]
- Fahrig, L. How much habitat is enough? Biol. Conserv. 2001, 100, 65–74. [Google Scholar] [CrossRef]
- O’Neill, R.V.; Krummel, J.R.; Gardner, R.H.; Sugihara, G.; Jackson, B.; DeAngelis, D.L.; Milne, B.T.; Turner, M.G.; Zygmunt, B.; Christensen, S.W.; et al. Indices of landscape pattern. Landsc. Ecol. 1988, 1, 153–162. [Google Scholar] [CrossRef]
- Krummel, J.R.; Gardner, R.H.; Sugihara, G.; O’Neill, R.V.; Coleman, P.R. Landscape Patterns in a Disturbed Environment. Oikos 1987, 48, 321–324. [Google Scholar] [CrossRef] [Green Version]
- Forman, R.T.T. Horizontal Processes, Roads, Suburbs, Societal Objectives, and Landscape Ecology. In Landscape Ecological Analysis: Issues and Applications; Klopatek, J.M., Gardner, R.H., Eds.; Springer: New York, NY, USA, 1999; pp. 35–53. [Google Scholar]
- Holland, J.; Fahrig, L. Effect of woody borders on insect density and diversity in crop fields: A landscape-scale analysis. Agric. Ecosyst. Environ. 2000, 78, 115–122. [Google Scholar] [CrossRef]
- Smart, S.M.; Marrs, R.H.; Le Duc, M.G.; Thompson, K.E.N.; Bunce, R.G.H.; Firbank, L.G.; Rossall, M.J. Spatial relationships between intensive land cover and residual plant species diversity in temperate farmed landscapes. J. Appl. Ecol. 2006, 43, 1128–1137. [Google Scholar] [CrossRef]
- Loss, S.R.; Ruiz, M.O.; Brawn, J.D. Relationships between avian diversity, neighborhood age, income, and environmental characteristics of an urban landscape. Biol. Conserv. 2009, 142, 2578–2585. [Google Scholar] [CrossRef]
- Schindler, S.; von Wehrden, H.; Poirazidis, K.; Hochachka, W.M.; Wrbka, T.; Kati, V. Performance of methods to select landscape metrics for modelling species richness. Ecol. Model. 2015, 295, 107–112. [Google Scholar] [CrossRef]
- Manson, R.H.; Ostfeld, R.S.; Canham, C.D. Responses of a small mammal community to heterogeneity along forest-old-field edges. Landsc. Ecol. 1999, 14, 355–367. [Google Scholar] [CrossRef]
- Hinsley, S.A.; Bellamy, P.E. The influence of hedge structure, management and landscape context on the value of hedgerows to birds: A review. J. Environ. Manag. 2000, 60, 33–49. [Google Scholar] [CrossRef]
- Dramstad, W.E.; Fry, G.; Fjellstad, W.J.; Skar, B.; Helliksen, W.; Sollund, M.L.B.; Tveit, M.S.; Geelmuyden, A.K.; Framstad, E. Integrating landscape-based values—Norwegian monitoring of agricultural landscapes. Landsc. Urban Plan. 2001, 57, 257–268. [Google Scholar] [CrossRef]
- Tews, J.; Brose, U.; Grimm, V.; Tielbörger, K.; Wichmann, M.C.; Schwager, M.; Jeltsch, F. Animal species diversity driven by habitat heterogeneity/diversity: The importance of keystone structures. J. Biogeogr. 2004, 31, 79–92. [Google Scholar] [CrossRef] [Green Version]
- Bennett, A. Linkages in the Landscape: The Role of Corridors and Connectivity in Wildlife Conservation; IUCN: Gland, Switzerland, 2003. [Google Scholar]
- Demers, M.N.; Simpson, J.W.; Boerner, R.E.J.; Silva, A.; Berns, L.; Artigas, F. Fencerows, Edges, and Implications of Changing Connectivity Illustrated by Two Contiguous Ohio Landscapes. Conserv. Biol. 1995, 9, 1159–1168. [Google Scholar] [CrossRef] [PubMed]
- Clergeau, P.; Burel, F. The role of spatio-temporal patch connectivity at the landscape level: An example in a bird distribution. Landsc. Urban Plan. 1997, 38, 37–43. [Google Scholar] [CrossRef]
- With, K.A. The Landscape Ecology of Invasive Spread. Conserv. Biol. 2002, 16, 1192–1203. [Google Scholar] [CrossRef] [Green Version]
- Fahrig, L. Effects of habitat fragmentation on biodiversity. Annu. Rev. Ecol. Evol. Syst. 2003, 34, 487–515. [Google Scholar] [CrossRef] [Green Version]
- Tewksbury, J.J.; Levey, D.J.; Haddad, N.M.; Sargent, S.; Orrock, J.L.; Weldon, A.; Danielson, B.J.; Brinkerhoff, J.; Damschen, E.I.; Townsend, P. Corridors affect plants, animals, and their interactions in fragmented landscapes. Proc. Natl. Acad. Sci. USA 2002, 99, 12923–12926. [Google Scholar] [CrossRef]
- Taylor, P.D.; Fahrig, L.; Henein, K.; Merriam, G. Connectivity Is a Vital Element of Landscape Structure. Oikos 1993, 68, 571–573. [Google Scholar] [CrossRef] [Green Version]
- Wiens, J.A. Metapopulation dynamics and landscape ecology. In Metapopulation Biology—Ecology, Genetics, and Evolution; Academic Press: Cambridge, MA, USA, 1997; pp. 43–62. [Google Scholar] [CrossRef]
- Beier, P.; Noss, R.F. Do Habitat Corridors Provide Connectivity? Conserv. Biol. 1998, 12, 1241–1252. [Google Scholar] [CrossRef]
- Kasparinskis, R.; Ruskule, A.; Vinogradovs, I.; Villoslada, M. The Guidebook on “The Introduction to the Ecosystem Service Framework and Its Application in Integrated Planning; University of Latvia, Faculty of Geography and Earth Sciences: Riga, Latvia, 2018. [Google Scholar]
- Busch, M.; La Notte, A.; Laporte, V.; Erhard, M. Potentials of quantitative and qualitative approaches to assessing ecosystem services. Ecol. Indic. 2012, 21, 89–103. [Google Scholar] [CrossRef]
- Vihervaara, P.; Viinikka, A.; Brander, L.M.; Santos-Martín, F.; Poikolainen, L.; Nedkov, S. Methodological interlinkages for mapping ecosystem services—From data to analysis and decision-support. One Ecosyst. 2019, 4, e26368. [Google Scholar] [CrossRef] [Green Version]
- Babí Almenar, J.; Rugani, B.; Geneletti, D.; Brewer, T. Integration of ecosystem services into a conceptual spatial planning framework based on a landscape ecology perspective. Landsc. Ecol. 2018, 33, 2047–2059. [Google Scholar] [CrossRef] [Green Version]
- Burkhard, B.; Kroll, F.; Nedkov, S.; Müller, F. Mapping ecosystem service supply, demand and budgets. Ecol. Indic. 2012, 21, 17–29. [Google Scholar] [CrossRef]
- Frank, S.; Fürst, C.; Koschke, L.; Makeschin, F. A contribution towards a transfer of the ecosystem service concept to landscape planning using landscape metrics. Ecol. Indic. 2012, 21, 30–38. [Google Scholar] [CrossRef]
- Pielou, E. Ecological Diversity; John Wiley & Sons: New York, NY, USA, 1975. [Google Scholar]
Value | Stratification (Strat) | Development Degree (Dev) | Continuity (Cont) | Autochthonous Degree (Autoct) |
---|---|---|---|---|
1 | No stratification | Low development | Low | Consistent allochthonous species |
2 | Low stratification | Low–medium development | Low–medium | |
3 | Mixed stratified and no stratification | Medium development | Medium | Autochthonous and allochthonous species |
4 | Stratified | Medium–well developed | Medium–good | |
5 | Highly stratified | Well developed | Good | Autochthonous species Dominant |
Patches Metrics | Shape Indices | Composition Indices | ||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Landscape Sub-system | Area [ha] | Perimeter [m] | NP | MPS | MTX | MPAR | SI | MSI | AWSI | PFD | MPFD | AWPFD | DIV1a | DIV1b | DIV2 | DOM1 | DOM2 | LSD1 | LSD2 | |
La | NAT | 76.6 | 25,587 | 49 | 1.12 | 23.5 | 0.010 | 8.2 | 0.47 | 5.4 | 1.50 | 0.16 | 1.46 | 0.5 | 0.6 | 0.2 | 2.4 | 0.8 | 2.6 | 0.6 |
AGR | 226.8 | 108,378 | 273 | 0.53 | 69.6 | 0.002 | 20.3 | 0.16 | 13.8 | 1.58 | 0.05 | 1.56 | 0.8 | 0.8 | 0.3 | 2.0 | 0.7 | 4.3 | 1.1 | |
ANT | 22.2 | 13,886 | 41 | 0.43 | 6.8 | 0.009 | 8.3 | 0.39 | 6.1 | 1.55 | 0.15 | 1.52 | 0.2 | 0.7 | 0.1 | 2.7 | 0.9 | 1.3 | 0.3 | |
TOT | 325.6 | 147,850 | 363 | 0.67 | 100.0 | 0.004 | 23.1 | 0.23 | 11.3 | 1.59 | 0.07 | 1.53 | 1.5 | 0.54 | 1.34 | 0.46 | 6.72 | 1.85 | ||
Fa | NAT | 1.05 | 1315 | 7 | 0.14 | 8.7 | 0.046 | 3.6 | 0.74 | 3.0 | 1.55 | 0.44 | 1.53 | 0.2 | 0.4 | 0.1 | 2.2 | 0.9 | 1.3 | 0.4 |
AGR | 10.24 | 7375 | 26 | 0.43 | 85.2 | 0.021 | 6.5 | 0.64 | 2.9 | 1.54 | 0.39 | 1.46 | 1.6 | 1.7 | 0.7 | 0.8 | 0.3 | 6.0 | 2.2 | |
ANT | 0.73 | 1382 | 8 | 0.09 | 6.1 | 0.047 | 4.6 | 0.80 | 3.3 | 1.63 | 0.40 | 1.60 | 0.2 | 0.7 | 0.1 | 2.2 | 0.9 | 1.1 | 0.3 | |
TOT | 12.02 | 10,071 | 41 | 0.32 | 100.0 | 0.031 | 8.2 | 0.68 | 3.0 | 1.58 | 0.40 | 1.47 | 2.0 | 0.84 | 0.37 | 0.16 | 6.83 | 2.66 | ||
GAP (Fa−La) | TOT | −0.36 | 0.026 | −14.9 | 0.46 | −8.29 | −0.01 | 0.33 | −0.06 | 0.48 | 0.31 | −0.97 | −0.31 | 0.11 | 0.81 | |||||
NAT% | −88% | −63% | 338% | −56% | 57% | −45% | 4% | 181% | 5% | −48% | −35% | −38% | −11% | 7% | −51% | −37% | ||||
AGR% | −19% | 22% | 801% | −68% | 299% | −79% | −3% | 704% | −6% | 86% | 98% | 124% | −59% | −51% | 41% | 102% | ||||
TOT% | −53% | 0% | 623% | −65% | 201% | −74% | −1% | 438% | −4% | 31% | 58% | −72% | −66% | 2% | 44% |
Shape Indices | Composition Indices | ||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
MPAR | SI | MSI | AWSI | PFD | MPFD | AWPFD | DIV1a | DIV1b | DIV2 | DOM1 | DOM2 | LSD1 | LSD2 | ||
MPAR | 1.00 | DIV1a | 1.00 | ||||||||||||
SI | −0.76 | 1.00 | DIV1b | 0.94 | 1.00 | ||||||||||
MSI | 0.93 | −0.89 | 1.00 | DIV2 | 0.99 | 0.96 | 1.00 | ||||||||
AWSI | −0.76 | 0.94 | −0.94 | 1.00 | DOM1 | −0.95 | −0.89 | −0.97 | 1.00 | ||||||
PFD | 0.31 | 0.23 | 0.08 | 0.20 | 1.00 | DOM2 | −0.99 | −0.96 | −1.00 | 0.97 | 1.00 | ||||
MPFD | 0.91 | −0.82 | 0.96 | −0.89 | 0.12 | 1.00 | LSD1 | 0.98 | 0.89 | 0.95 | −0.88 | −0.95 | 1.00 | ||
AWPFD | 0.26 | 0.19 | −0.06 | 0.33 | 0.80 | −0.09 | 1.00 | LSD2 | 1.00 | 0.95 | 1.00 | −0.97 | −1.00 | 0.96 | 1.00 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Vagge, I.; Chiaffarelli, G. Validating the Contribution of Nature-Based Farming Solutions (NBFS) to Agrobiodiversity Values through a Multi-Scale Landscape Approach. Agronomy 2023, 13, 233. https://doi.org/10.3390/agronomy13010233
Vagge I, Chiaffarelli G. Validating the Contribution of Nature-Based Farming Solutions (NBFS) to Agrobiodiversity Values through a Multi-Scale Landscape Approach. Agronomy. 2023; 13(1):233. https://doi.org/10.3390/agronomy13010233
Chicago/Turabian StyleVagge, Ilda, and Gemma Chiaffarelli. 2023. "Validating the Contribution of Nature-Based Farming Solutions (NBFS) to Agrobiodiversity Values through a Multi-Scale Landscape Approach" Agronomy 13, no. 1: 233. https://doi.org/10.3390/agronomy13010233
APA StyleVagge, I., & Chiaffarelli, G. (2023). Validating the Contribution of Nature-Based Farming Solutions (NBFS) to Agrobiodiversity Values through a Multi-Scale Landscape Approach. Agronomy, 13(1), 233. https://doi.org/10.3390/agronomy13010233