Integrating high-resolution data and species-level traits for enhanced ecosystem projections using a dynamic vegetation model: Case study in Wallonia, Belgium. - 2025
Integrating high-resolution data and species-level traits for enhanced ecosystem projections using a dynamic vegetation model: Case study in Wallonia, Belgium.
CARAIB dynamic vegetation model; Carbon sequestration; Climate change; Land use change; Regional scale; Satellite observation; Carbon; Soil; Belgium; Forests; Carbon Sequestration; Models, Theoretical; Soil/chemistry; Ecosystem; Biomass; Dynamic vegetation model; Gross primary production; Landuse change; Mitigation strategy; Satellite observations; Total soil carbon; Environmental Engineering; Waste Management and Disposal; Management, Monitoring, Policy and Law
Abstract :
[en] Accurate quantification of carbon dynamics is critical for developing effective climate mitigation strategies. In this study, we employed the CARAIB dynamic vegetation model (DVM) to analyze carbon fluxes and stocks (biomass and total soil carbon) in Wallonia, Belgium (1980-2070), integrating species-level traits, high-resolution land use/land cover (LULC) data, climate data, and type-1 fuzzy logic for uncertainty quantification. We provide insights into ecosystem resilience and carbon sequestration under Representative Concentration Pathways (RCPs) 2.6 and 8.5. Historical results (1980-2020) demonstrated strong model performance, with gross primary production (GPP) validation achieving R2 > 0.85 against MODIS and GOSIF datasets, and aboveground biomass correlating well with GEDI (R2 = 0.77) and ESA-CCI (R2 = 0.91) datasets. Grasslands emerged as critical carbon sinks, exhibiting the highest mean GPP (2480 g C m-2 yr-1), surpassing forests due to rapid growth and belowground carbon storage. Future projections (2021-2070) identified afforestation as a robust mitigation strategy, increasing forest GPP by 18% and total biomass by 60-110 Mt C under RCP 8.5. Under RCP 2.6, total biomass was more stable due to the milder emissions trajectory, emphasizing its potential for long-term ecosystem resilience. Interestingly, total soil carbon showed similar levels across both RCPs, indicating belowground carbon resilience despite emissions differences. Sensitivity analyses of LULC scenarios highlighted grassland resilience, with grasslands sustaining a high GPP (2604-2728 g C m-2 yr-1) and contributing significantly to soil carbon storage, while deforestation caused substantial carbon losses. These findings underscore the need for nuanced land management, integrating afforestation and grassland conservation, to enhance resilience and sustainable carbon sequestration under climate change.
Hambuckers, Alain ; Université de Liège - ULiège > Département de Biologie, Ecologie et Evolution > Biologie du comportement - Ethologie et psychologie animale
François, Louis ; Université de Liège - ULiège > Département d'astrophysique, géophysique et océanographie (AGO) > Modélisation du climat et des cycles biogéochimiques
Language :
English
Title :
Integrating high-resolution data and species-level traits for enhanced ecosystem projections using a dynamic vegetation model: Case study in Wallonia, Belgium.
Amani, M., Ghorbanian, A., Ahmadi, S.A., Kakooei, M., Moghimi, A., Mirmazloumi, S.M., Moghaddam, S.H.A., Mahdavi, S., Ghahremanloo, M., Parsian, S., Wu, Q., Brisco, B., Google Earth Engine cloud computing platform for remote sensing big data applications: a comprehensive review. IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing 13 (2020), 5326–5350, 10.1109/JSTARS.2020.3021052.
Augusto, L., Boča, A., Tree functional traits, forest biomass, and tree species diversity interact with site properties to drive forest soil carbon. Nat. Commun., 13, 2022, 1097, 10.1038/s41467-022-28748-0.
Ball, J.T., Woodrow, I.E., Berry, J.A., A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions. Biggins, J., (eds.) Progress in Photosynthesis Research, 1987, Springer, Netherlands, Dordrecht, 221–224, 10.1007/978-94-017-0519-6_48.
Bastos, A., O'Sullivan, M., Ciais, P., Makowski, D., Sitch, S., Friedlingstein, P., Chevallier, F., Rödenbeck, C., Pongratz, J., Luijkx, I.T., Patra, P.K., Peylin, P., Canadell, J.G., Lauerwald, R., Li, W., Smith, N.E., Peters, W., Goll, D.S., Jain, A.K., Kato, E., Lienert, S., Lombardozzi, D.L., Haverd, V., Nabel, J.E.M.S., Poulter, B., Tian, H., Walker, A.P., Zaehle, S., Sources of uncertainty in regional and global terrestrial CO2 exchange estimates. Global Biogeochem. Cycles, 34, 2020, e2019GB006393, 10.1029/2019GB006393.
Beckers, V., Beckers, J., Vanmaercke, M., Van Hecke, E., Van Rompaey, A., Dendoncker, N., Modelling farm growth and its impact on agricultural land use: a country scale application of an agent-based model. Land, 7, 2018, 109, 10.3390/land7030109.
Bian, C., Xia, J., Uncertainty propagation in a global biogeochemical model driven by leaf area data. Front. Ecol. Evol., 11, 2023, 1105832, 10.3389/fevo.2023.1105832.
Bhan, M., Gingrich, S., Roux, N., Le Noë, J., Kastner, T., Matej, S., Schwarzmueller, F., Erb, K.-H., Quantifying and attributing land use-induced carbon emissions to biomass consumption: a critical assessment of existing approaches. J. Environ. Manag., 286, 2021, 112228, 10.1016/j.jenvman.2021.112228.
Bultan, S., Nabel, J.E.M.S., Hartung, K., Ganzenmüller, R., Xu, L., Saatchi, S., Pongratz, J., Tracking 21st century anthropogenic and natural carbon fluxes through model-data integration. Nat. Commun., 13, 2022, 5516, 10.1038/s41467-022-32456-0.
Cai, W., Prentice, I.C., Recent trends in gross primary production and their drivers: analysis and modelling at flux-site and global scales. Environ. Res. Lett., 15, 2020, 124050, 10.1088/1748-9326/abc64e.
Dass, P., Houlton, B.Z., Wang, Y., Warlind, D., Grasslands may be more reliable carbon sinks than forests in California. Environ. Res. Lett., 13, 2018, 074027, 10.1088/1748-9326/aacb39.
De Wergifosse, L., André, F., Goosse, H., Caluwaerts, S., De Cruz, L., De Troch, R., Van Schaeybroeck, B., Jonard, M., CO2 fertilization, transpiration deficit and vegetation period drive the response of mixed broadleaved forests to a changing climate in Wallonia. Ann. For. Sci., 77, 2020, 70, 10.1007/s13595-020-00966-w.
Dury, M., Hambuckers, A., Warnant, P., Henrot, A., Favre, E., Ouberdous, M., François, L., Responses of European forest ecosystems to 21st century climate: assessing changes in interannual variability and fire intensity. iForest 4 (2011), 82–99, 10.3832/ifor0572-004.
Dury, M., Mertens, L., Fayolle, A., Verbeeck, H., Hambuckers, A., François, L., Refining species traits in a dynamic vegetation model to project the impacts of climate change on tropical trees in Central Africa. Forests, 9, 2018, 722, 10.3390/f9110722.
Duncanson, L., Armston, J., Disney, M., Avitabile, V., Barbier, N., Calders, K., Carter, S., Chave, J., Herold, M., Crowther, T.W., Falkowski, M., Kellner, J.R., Labrière, N., Lucas, R., MacBean, N., McRoberts, R.E., Meyer, V., Næsset, E., Nickeson, J.E., Paul, K.I., Phillips, O.L., Réjou-Méchain, M., Román, M., Roxburgh, S., Saatchi, S., Schepaschenko, D., Scipal, K., Siqueira, P.R., Whitehurst, A., Williams, M., The importance of consistent global forest aboveground biomass product validation. Surv. Geophys. 40 (2019), 979–999, 10.1007/s10712-019-09538-8.
Farquhar, G.D., von Caemmerer, S., Berry, J.A., A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149 (1980), 78–90, 10.1007/BF00386231.
Friedlingstein, P., O'Sullivan, M., Jones, M.W., Andrew, R.M., Bakker, D.C.E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I.T., Peters, G.P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J.G., Ciais, P., Jackson, R.B., Alin, S.R., Anthoni, P., Barbero, L., Bates, N.R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I.B.M., Cadule, P., Chamberlain, M.A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L.P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R.A., Feng, L., Ford, D.J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R.A., Hurtt, G.C., Iida, Y., Ilyina, T., Jacobson, A.R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R.F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J.I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P.C., McKinley, G.A., Meyer, G., Morgan, E.J., Munro, D.R., Nakaoka, S.-I., Niwa, Y., O'Brien, K.M., Olsen, A., Omar, A.M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C.M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T.M., Schwinger, J., Séférian, R., Smallman, T.L., Smith, S.M., Sospedra-Alfonso, R., Sun, Q., Sutton, A.J., Sweeney, C., Takao, S., Tans, P.P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., Van Der Werf, G.R., Van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Global carbon budget 2023. Earth Syst. Sci. Data 15 (2023), 5301–5369, 10.5194/essd-15-5301-2023.
François, L.M., Goddéris, Y., Warnant, P., Ramstein, G., de Noblet, N., Lorenz, S., Carbon stocks and isotopic budgets of the terrestrial biosphere at mid-Holocene and last glacial maximum times. Chem. Geol. 159 (1999), 163–189, 10.1016/S0009-2541(99)00039-X.
François, L., Utescher, T., Favre, E., Henrot, A.-J., Warnant, P., Micheels, A., Erdei, B., Suc, J.-P., Cheddadi, R., Mosbrugger, V., Modelling Late Miocene vegetation in Europe: results of the CARAIB model and comparison with palaeovegetation data. Palaeogeogr. Palaeoclimatol. Palaeoecol. 304 (2011), 359–378, 10.1016/j.palaeo.2011.01.012.
García-Álvarez, D., Camacho Olmedo, M.T., Paegelow, M., Mas, J.F., (eds.) Land Use Cover Datasets and Validation Tools: Validation Practices with QGIS, 2022, Springer International Publishing, Cham, 10.1007/978-3-030-90998-7.
Gérard, J.C., Nemry, B., François, L.M., Warnant, P., The interannual change of atmospheric CO2: Contribution of subtropical ecosystems. Geophys. Res. Lett. 26 (1999), 243–246, 10.1029/1998GL900269.
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R., Google Earth engine: planetary-scale geospatial analysis for everyone. Remote Sensing of Environment 202 (2017), 18–27, 10.1016/j.rse.2017.06.031.
Gourlez De La Motte, L., Jérôme, E., Mamadou, O., Beckers, Y., Bodson, B., Heinesch, B., Aubinet, M., Carbon balance of an intensively grazed permanent grassland in southern Belgium. Agric. For. Meteorol. 228–229 (2016), 370–383, 10.1016/j.agrformet.2016.06.009.
Guo, L.B., Gifford, R.M., Soil carbon stocks and land use change: a meta analysis. Global Change Biol. 8 (2002), 345–360, 10.1046/j.1354-1013.2002.00486.x.
Hambuckers, A., Trolliet, F., Dury, M., Henrot, A.-J., Porteman, K., El Hasnaoui, Y., Van Den Bulcke, J., De Mil, T., Remy, C.C., Cheddadi, R., François, L., Towards a more realistic simulation of plant species with a dynamic vegetation model using field-measured traits: the atlas cedar, a case study. Forests, 13, 2022, 446, 10.3390/f13030446.
Hari, M., Tyagi, B., Terrestrial carbon cycle: tipping edge of climate change between the atmosphere and biosphere ecosystems. Environ. Sci.: Atmos. 2 (2022), 867–890, 10.1039/D1EA00102G.
Haseeb, M., Tahir, Z., Mehmood, S.A., Gill, S.A., Farooq, N., Butt, H., Iftikhar, A., Maqsood, A., Abdullah-Al-Wadud, M., Tariq, A., Enhancing carbon sequestration through afforestation: evaluating the impact of land use and cover changes on carbon storage dynamics. Earth Syst. Environ., 2024, 10.1007/s41748-024-00414-z.
Henrot, A.-J., Utescher, T., Erdei, B., Dury, M., Hamon, N., Ramstein, G., Krapp, M., Herold, N., Goldner, A., Favre, E., Munhoven, G., François, L., Middle Miocene climate and vegetation models and their validation with proxy data. Palaeogeogr. Palaeoclimatol. Palaeoecol. 467 (2017), 95–119, 10.1016/j.palaeo.2016.05.026.
Hong, C., Burney, J.A., Pongratz, J., Nabel, J.E.M.S., Mueller, N.D., Jackson, R.B., Davis, S.J., Global and regional drivers of land-use emissions in 1961–2017. Nature 589 (2021), 554–561, 10.1038/s41586-020-03138-y.
Houghton, R.A., Terrestrial fluxes of carbon in GCP carbon budgets. Glob. Change Biol. 26 (2020), 3006–3014, 10.1111/gcb.15050.
Hu, X., He, Y., Kong, Z., Zhang, J., Yuan, M., Yu, L., Peng, C., Zhu, Q., Evaluation of future impacts of climate change, CO2, and land use cover change on global net primary productivity using a processed model. Land, 10, 2021, 365, 10.3390/land10040365.
Hubert, B., Francois, L., Warnant, P., Strivay, D., Stochastic generation of meteorological variables and effects on global models of water and carbon cycles in vegetation and soils. J. Hydrol. 212–213 (1998), 318–334, 10.1016/S0022-1694(98)00214-5.
Hunka, N., Santoro, M., Armston, J., Dubayah, R., McRoberts, R.E., Næsset, E., Quegan, S., Urbazaev, M., Pascual, A., May, P.B., Minor, D., Leitold, V., Basak, P., Liang, M., Melo, J., Herold, M., Málaga, N., Wilson, S., Durán Montesinos, P., Arana, A., Ernesto De La Cruz Paiva, R., Ferrand, J., Keoka, S., Guerra-Hernández, J., Duncanson, L., On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake. Environ. Res. Lett., 18, 2023, 124042, 10.1088/1748-9326/ad0b60.
Jacquemin, I., Berckmans, J., Henrot, A.-J., Dury, M., Tychon, B., Hambuckers, A., Hamdi, R., François, L., Using the CARAIB dynamic vegetation model to simulate crop yields in Belgium - validation and projections for the 2035 horizon. Geo-Eco-Trop 44 (2020), 541–552.
Journée, M., Bertrand, C., Geostatistical merging of ground-based and satellite-derived data of surface solar radiation. Adv. Sci. Res. 6 (2011), 1–5, 10.5194/asr-6-1-2011.
Journée, M., Goudenhoofdt, E., Vannitsem, S., Delobbe, L., Quantitative rainfall analysis of the 2021 mid-July flood event in Belgium. Hydrol. Earth Syst. Sci. 27 (2023), 3169–3189, 10.5194/hess-27-3169-2023.
Junttila, V., Minunno, F., Peltoniemi, M., Forsius, M., Akujärvi, A., Ojanen, P., Mäkelä, A., Quantification of forest carbon flux and stock uncertainties under climate change and their use in regionally explicit decision making: case study in Finland. Ambio 52 (2023), 1716–1733, 10.1007/s13280-023-01906-4.
Jian, J., Bailey, V., Dorheim, K., Konings, A.G., Hao, D., Shiklomanov, A.N., Snyder, A., Steele, M., Teramoto, M., Vargas, R., Bond-Lamberty, B., Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle. Nat. Commun., 13, 2022, 1733, 10.1038/s41467-022-29391-5.
Kattge, J., Bönisch, G., Díaz, S., Lavorel, S., Prentice, I.C., Leadley, P., et al. TRY plant trait database – enhanced coverage and open access. Global Change Biol. 26 (2020), 119–188, 10.1111/gcb.14904.
Kong, R., Zhang, Z., Huang, R., Tian, J., Feng, R., Chen, X., Projected global warming-induced terrestrial ecosystem carbon across China under SSP scenarios. Ecol. Indicat., 139, 2022, 108963, 10.1016/j.ecolind.2022.108963.
Krause, A., Papastefanou, P., Gregor, K., Layritz, L.S., Zang, C.S., Buras, A., Li, X., Xiao, J., Rammig, A., Quantifying the impacts of land cover change on gross primary productivity globally. Sci. Rep., 12, 2022, 18398, 10.1038/s41598-022-23120-0.
Latte, N., Colinet, G., Fayolle, A., Lejeune, P., Hébert, J., Claessens, H., Bauwens, S., Description of a new procedure to estimate the carbon stocks of all forest pools and impact assessment of methodological choices on the estimates. Eur. J. Forest Res. 132 (2013), 565–577, 10.1007/s10342-013-0701-6.
Lettens, S., Orshoven, J., Wesemael, B., Muys, B., Perrin, D., Soil organic carbon changes in landscape units of Belgium between 1960 and 2000 with reference to 1990. Global Change Biol. 11 (2005), 2128–2140, 10.1111/j.1365-2486.2005.001074.x.
Lettens, S., Van Orshoven, J., Perrtn, D., Van Wesemael, B., Muys, B., Organic carbon stocks and stock changes of forest biomass in Belgium derived from forest inventory data in a spatially explicit approach. Ann. For. Sci., 65, 2008, 10.1051/forest:2008034 604–604.
Li, W., MacBean, N., Ciais, P., Defourny, P., Lamarche, C., Bontemps, S., Houghton, R.A., Peng, S., Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992–2015). Earth Syst. Sci. Data 10 (2018), 219–234, 10.5194/essd-10-219-2018.
Li, Xiao, Mapping photosynthesis solely from solar-induced chlorophyll fluorescence: a global, fine-resolution dataset of gross primary production derived from OCO-2. Rem. Sens., 11, 2019, 2563, 10.3390/rs11212563.
Loudiyi, I., Jacquemin, I., Lahlou, M., Balaghi, R., Tychon, B., François, L., Atmospheric CO2 fertilization effect on cereal yields in Morocco using the CARAIB dynamic vegetation model. Eur. J. Agron., 161, 2024, 127374, 10.1016/j.eja.2024.127374.
Miner, G.L., Bauerle, W.L., Baldocchi, D.D., Estimating the sensitivity of stomatal conductance to photosynthesis: a review. Plant Cell Environ. 40 (2017), 1214–1238, 10.1111/pce.12871.
McGlynn, E., Li, S., F Berger, M., Amend, M., L Harper, K., Addressing uncertainty and bias in land use, land use change, and forestry greenhouse gas inventories. Climatic Change, 170, 2022, 5, 10.1007/s10584-021-03254-2.
Meinshausen, M., Smith, S.J., Calvin, K., Daniel, J.S., Kainuma, M.L.T., Lamarque, J.-F., Matsumoto, K., Montzka, S.A., Raper, S.C.B., Riahi, K., Thomson, A., Velders, G.J.M., Van Vuuren, D.P.P., The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change 109 (2011), 213–241, 10.1007/s10584-011-0156-z.
O'Sullivan, M., Friedlingstein, P., Sitch, S., Anthoni, P., Arneth, A., Arora, V.K., Bastrikov, V., Delire, C., Goll, D.S., Jain, A., Kato, E., Kennedy, D., Knauer, J., Lienert, S., Lombardozzi, D., McGuire, P.C., Melton, J.R., Nabel, J.E.M.S., Pongratz, J., Poulter, B., Séférian, R., Tian, H., Vuichard, N., Walker, A.P., Yuan, W., Yue, X., Zaehle, S., Process-oriented analysis of dominant sources of uncertainty in the land carbon sink. Nat. Commun., 13, 2022, 4781, 10.1038/s41467-022-32416-8.
Pastorello, G., The FLUXNET2015 Dataset and the ONEFlux Processing Pipeline for Eddy Covariance Data, vol. 7, 2020, 225, 10.1038/s41597-020-0534-3.
Phan, T.N., Kuch, V., Lehnert, L.W., Land cover classification using Google Earth Engine and Random Forest classifier—the role of image composition. Rem. Sens., 12, 2020, 2411, 10.3390/rs12152411.
Pongratz, J., Schwingshackl, C., Bultan, S., Obermeier, W., Havermann, F., Guo, S., Land use effects on climate: current state, recent progress, and emerging topics. Curr. Clim. Change Rep. 7 (2021), 99–120, 10.1007/s40641-021-00178-y.
Prescher, A.-K., Grünwald, T., Bernhofer, C., Land use regulates carbon budgets in eastern Germany: from NEE to NBP. Agric. For. Meteorol. 150 (2010), 1016–1025, 10.1016/j.agrformet.2010.03.008.
Roebroek, C.T.J., Duveiller, G., Seneviratne, S.I., Davin, E.L., Cescatti, A., Releasing global forests from human management: how much more carbon could be stored?. Science 380 (2023), 749–753, 10.1126/science.add5878.
Rojas-Botero, S., Teixeira, L.H., Prucker, P., Kloska, V., Kollmann, J., Le Stradic, S., Root traits of grasslands rapidly respond to climate change, while community biomass mainly depends on functional composition. Funct. Ecol. 37 (2023), 1841–1855, 10.1111/1365-2435.14345.
Sun, Y., Frankenberg, C., Wood, J.D., Schimel, D.S., Jung, M., Guanter, L., Drewry, D.T., Verma, M., Porcar-Castell, A., Griffis, T.J., Gu, L., Magney, T.S., Köhler, P., Evans, B., Yuen, K., OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence. Science, 358, 2017, eaam5747, 10.1126/science.aam5747.
Tang, X., Li, H., Huang, N., Li, X., Xu, X., Ding, Z., Xie, J., A comprehensive assessment of MODIS-derived GPP for forest ecosystems using the site-level FLUXNET database. Environ. Earth Sci. 74 (2015), 5907–5918, 10.1007/s12665-015-4615-0.
Trugman, A.T., Quetin, G.R., Leveraging uncertainty in terrestrial ecosystem carbon stocks and fluxes. Earth's Future, 11, 2023, e2022EF003322, 10.1029/2022EF003322.
Vande Walle, I., Van Camp, N., Perrin, D., Lemeur, R., Verheyen, K., Van Wesemael, B., Laitat, E., Growing stock-based assessment of the carbon stock in the Belgian forest biomass. Ann. For. Sci 62 (2005), 853–864, 10.1051/forest:2005076.
Warnant, P., François, L., Strivay, D., Gérard, J.-C., CARAIB: a global model of terrestrial biological productivity. Global Biogeochem. Cycles 8 (1994), 255–270, 10.1029/94GB00850.
Yang, Y., Zhao, J., Zhao, P., Wang, H., Wang, B., Su, S., Li, M., Wang, L., Zhu, Q., Pang, Z., Peng, C., Trait-based climate change predictions of vegetation sensitivity and distribution in China. Front. Plant Sci., 10, 2019, 908, 10.3389/fpls.2019.00908.
Yuh, Y.G., Tracz, W., Matthews, H.D., Turner, S.E., Application of machine learning approaches for land cover monitoring in northern Cameroon. Ecol. Inf., 74, 2023, 101955, 10.1016/j.ecoinf.2022.101955.
Zakharova, L., Meyer, K.M., Seifan, M., Trait-based modelling in ecology: a review of two decades of research. Ecol. Model., 407, 2019, 108703, 10.1016/j.ecolmodel.2019.05.008.
Zhao, G., Liu, L., Wang, Z.-Y., Jin, Z., He, J.-S., Grassland science in a new era. Fundamental Research 3 (2023), 149–150, 10.1016/j.fmre.2023.02.001.
Zhou, Y., Chartin, C., Van Oost, K., Van Wesemael, B., High-resolution soil organic carbon mapping at the field scale in Southern Belgium (Wallonia). Geoderma, 422, 2022, 115929, 10.1016/j.geoderma.2022.115929.
