{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T11:22:51Z","timestamp":1769599371787,"version":"3.49.0"},"reference-count":69,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T00:00:00Z","timestamp":1628640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ecometrica LTD","award":["Forests 2020"],"award-info":[{"award-number":["Forests 2020"]}]},{"DOI":"10.13039\/501100008861","name":"United Kingdom Space Agency","doi-asserted-by":"publisher","award":["Forests 2020"],"award-info":[{"award-number":["Forests 2020"]}],"id":[{"id":"10.13039\/501100008861","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Integrating information about the spatial distribution of carbon stocks and species diversity in tropical forests over large areas is fundamental for climate change mitigation and biodiversity conservation. In this study, spatial models showing the distribution of carbon stocks and the number of species were produced in order to identify areas that maximize carbon storage and biodiversity in the tropical forests of the Yucatan Peninsula, Mexico. We mapped carbon density and species richness of trees using L-band radar backscatter data as well as radar texture metrics, climatic and field data with the random forest regression algorithm. We reduced sources of errors in plot data of the national forest inventory by using correction factors to account for carbon stocks of small trees (&lt;7.5 cm DBH) and for the temporal difference between field data collection and imagery acquisition. We created bivariate maps to assess the spatial relationship between carbon stocks and diversity. Model validation of the regional maps obtained herein using an independent data set of plots resulted in a coefficient of determination (R2) of 0.28 and 0.31 and a relative mean square error of 38.5% and 33.0% for aboveground biomass and species richness, respectively, at pixel level. Estimates of carbon density were influenced mostly by radar backscatter and climatic data, while those of species richness were influenced mostly by radar texture and climatic variables. Correlation between carbon density and species richness was positive in 79.3% of the peninsula, while bivariate maps showed that 39.6% of the area in the peninsula had high carbon stocks and species richness. Our results highlight the importance of combining carbon and diversity maps to identify areas that are critical\u2014both for maintaining carbon stocks and for conserving biodiversity.<\/jats:p>","DOI":"10.3390\/rs13163179","type":"journal-article","created":{"date-parts":[[2021,8,11]],"date-time":"2021-08-11T08:35:52Z","timestamp":1628670952000},"page":"3179","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Carbon Stocks, Species Diversity and Their Spatial Relationships in the Yucat\u00e1n Peninsula, Mexico"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9559-7131","authenticated-orcid":false,"given":"Jos\u00e9 Luis","family":"Hern\u00e1ndez-Stefanoni","sequence":"first","affiliation":[{"name":"Centro de Investigaci\u00f3n Cient\u00edfica de Yucat\u00e1n A.C., Unidad de Recursos Naturales, Calle 43 # 130, Colonia Chuburn\u00e1 de Hidalgo, M\u00e9rida CP 97200, Mexico"}]},{"given":"Miguel \u00c1ngel","family":"Castillo-Santiago","sequence":"additional","affiliation":[{"name":"Laboratorio de An\u00e1lisis de Informaci\u00f3n Geogr\u00e1fica y Estad\u00edstica, El Colegio de la Frontera Sur, Carretera Panamericana y Perif\u00e9rico sur s\/n., San Crist\u00f3bal de las Casas, Chiapas CP 29290, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7419-9206","authenticated-orcid":false,"given":"Juan","family":"Andres-Mauricio","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n Cient\u00edfica de Yucat\u00e1n A.C., Unidad de Recursos Naturales, Calle 43 # 130, Colonia Chuburn\u00e1 de Hidalgo, M\u00e9rida CP 97200, Mexico"}]},{"given":"Carlos A.","family":"Portillo-Quintero","sequence":"additional","affiliation":[{"name":"Geospatial Technologies Laboratory, Department of Natural Resources Management, Texas Tech University, Box 42125, Lubbock, TX 79409-2125, USA"}]},{"given":"Fernando","family":"Tun-Dzul","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n Cient\u00edfica de Yucat\u00e1n A.C., Unidad de Recursos Naturales, Calle 43 # 130, Colonia Chuburn\u00e1 de Hidalgo, M\u00e9rida CP 97200, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7491-6837","authenticated-orcid":false,"given":"Juan Manuel","family":"Dupuy","sequence":"additional","affiliation":[{"name":"Centro de Investigaci\u00f3n Cient\u00edfica de Yucat\u00e1n A.C., Unidad de Recursos Naturales, Calle 43 # 130, Colonia Chuburn\u00e1 de Hidalgo, M\u00e9rida CP 97200, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1314","DOI":"10.1111\/geb.12364","article-title":"Diversity enhances carbon storage in tropical forests","volume":"24","author":"Poorter","year":"2015","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"11635","DOI":"10.1073\/pnas.0901970106","article-title":"Re-evaluation of forest biomass carbon stocks and lessons from the world\u2019s most carbon-dense forests","volume":"106","author":"Keith","year":"2009","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.biocon.2009.09.020","article-title":"Extent and conservation of tropical dry forests in the Americas","volume":"143","year":"2010","journal-title":"Biol. Conserv."},{"key":"ref_4","unstructured":"Carson, R.P., and Schnitzer, S.A. (2008). The disparity in tree species richness among tropical, temperate, and boreal biomes: The geographical area and age hypothesis. Tropical Forest Community Ecology, Blackwell."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1383","DOI":"10.1126\/science.aaf5080","article-title":"Plant diversity patterns in neotropical dry forests and their conservation implications","volume":"353","author":"Banda","year":"2016","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1783","DOI":"10.5194\/essd-11-1783-2019","article-title":"Global carbon budget 2019","volume":"11","author":"Friedlingstein","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1038\/nature13947","article-title":"The performance and potential of protected areas","volume":"515","author":"Watson","year":"2014","journal-title":"Nature"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"9899","DOI":"10.1073\/pnas.1019576108","article-title":"Benchmark map of forest carbon stocks in tropical regions across three continents","volume":"108","author":"Saatchi","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1038\/nclimate1354","article-title":"Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps","volume":"2","author":"Baccini","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1107","DOI":"10.1111\/j.1365-2699.2005.01272.x","article-title":"Global patterns of plant diversity and floristic knowledge","volume":"32","author":"Kier","year":"2005","journal-title":"J. Biogeogr."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5925","DOI":"10.1073\/pnas.0608361104","article-title":"Global patterns and determinants of vascular plant diversity","volume":"104","author":"Kreft","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2009JG000935","article-title":"Importance of biomass in the global carbon cycle","volume":"114","author":"Houghton","year":"2009","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1038\/s41559-019-0799-0","article-title":"Global patterns and drivers of tree diversity integrated across a continuum of spatial grains","volume":"3","author":"Keil","year":"2019","journal-title":"Nat. Ecol. Evol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5559","DOI":"10.3390\/rs6065559","article-title":"A national, detailed map of forest aboveground carbon stocks in Mexico","volume":"6","author":"Cartus","year":"2014","journal-title":"Remote. Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/j.rse.2016.06.004","article-title":"Magnitude, spatial distribution and uncertainty of forest biomass stocks in Mexico","volume":"183","author":"Saatchi","year":"2016","journal-title":"Remote. Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1007\/s10712-019-09532-0","article-title":"Upscaling Forest biomass from field to satellite measurements: Sources of errors and ways to reduce them","volume":"40","author":"Barbier","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1799","DOI":"10.1111\/geb.13158","article-title":"Evaluating the potential of full-waveform lidar for mapping pan-tropical tree species richness","volume":"29","author":"Marselis","year":"2020","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Islebe, G.A., Schmook, B., Calm\u00e9, S., and Le\u00f3n-Cort\u00e9s, J.L. (2015). Chapter 8: Conservation and Use. Biodiversity and Conservation of the Yuca-t\u00e1n Peninsula, Springer.","DOI":"10.1007\/978-3-319-06529-8"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1890\/1051-0761(2003)013[0085:ROBFSC]2.0.CO;2","article-title":"Recovery of biomass following shifting cultivation in dry tropical forests of the Yucatan","volume":"13","author":"Read","year":"2003","journal-title":"Ecol. Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1776","DOI":"10.1890\/14-1593.1","article-title":"Predicting spatial variations of tree species richness in trop-ical forests from high-resolution remote sensing","volume":"25","author":"Fricker","year":"2015","journal-title":"Ecol. Appl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1111\/j.1744-7429.2011.00783.x","article-title":"Patterns and correlates of tropical dry forest structure and composition in a highly replicated chronosequence in Yucatan, Mexico","volume":"44","author":"Dupuy","year":"2012","journal-title":"Biotropica"},{"key":"ref_22","unstructured":"CONAFOR (2018). Inventario nacional forestal y de suelos. Inf. Result., 1, 2009\u20132014."},{"key":"ref_23","first-page":"1","article-title":"Improving aboveground biomass maps of tropical dry forests by integrating LiDAR, ALOS PALSAR, climate and field data","volume":"15","author":"Mas","year":"2020","journal-title":"Carbon Balance Manag."},{"key":"ref_24","first-page":"53","article-title":"Forest biomass retrieval approaches from earth observation in different biomes","volume":"77","author":"Quegan","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wang, R., and Gamon, J.A. (2019). Remote sensing of terrestrial plant biodiversity. Remote. Sens. Environ., 231.","DOI":"10.1016\/j.rse.2019.111218"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2017.08.001","article-title":"Toward a general trop-ical forest biomass prediction model from very high resolution optical satellite images","volume":"200","author":"Ploton","year":"2017","journal-title":"Remote. Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.rse.2015.01.007","article-title":"Potential of high-resolution ALOS\u2013PALSAR mosaic texture for aboveground forest carbon tracking in tropical region","volume":"160","author":"Thapa","year":"2015","journal-title":"Remote. Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-017-03469-3","article-title":"Understanding \u2018saturation\u2019of radar signals over forests","volume":"7","author":"Joshi","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.ecoinf.2010.06.001","article-title":"Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges","volume":"5","author":"Rocchini","year":"2010","journal-title":"Ecol. Inform."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1111\/ele.12277","article-title":"Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales","volume":"17","author":"Stein","year":"2014","journal-title":"Ecol. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"975","DOI":"10.1016\/j.ecolind.2019.02.015","article-title":"Combining high resolution satellite imagery and lidar data to model woody species diversity of tropical dry forests","volume":"101","author":"Dupuy","year":"2019","journal-title":"Ecol. Indic."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1038\/nature16512","article-title":"Biomass resili-ence of Neotropical secondary forests","volume":"530","author":"Poorter","year":"2016","journal-title":"Nature (London)"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Rozendaal, D.M.A., Bongers, F., Aide, T.M., Alvarez-D\u00e1vila, E., Ascarrunz, N., Balvanera, P., Becknell, J.M., Bentos, T.V., Brancalion, P.H.S., and Cabral, G.A.L. (2019). Biodiversity recovery of Neotropical secondary forests. Sci. Adv., 5.","DOI":"10.1126\/sciadv.aau3114"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2381","DOI":"10.1890\/0012-9658(2001)082[2381:WITORB]2.0.CO;2","article-title":"What is the observed relationship between species richness and productivity?","volume":"82","author":"Mittelbach","year":"2001","journal-title":"Ecology"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/srep39102","article-title":"Diversity and carbon storage across the tropical forest biome","volume":"7","author":"Sullivan","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1434","DOI":"10.1111\/cobi.12500","article-title":"Spatial patterns of carbon, biodiversity, deforestation threat, and REDD+ projects in Indonesia","volume":"29","author":"Murray","year":"2005","journal-title":"Conserv. Biol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"163","DOI":"10.21829\/myb.2017.2321452","article-title":"Evaluaci\u00f3n de ecuaciones alom\u00e9tricas de biomasa epigea en una selva mediana subcaducifolia de Yucat\u00e1n","volume":"23","year":"2017","journal-title":"Madera bosques"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s00442-005-0100-x","article-title":"Tree allometry and improved estimation of carbon stocks and balance in tropical forests","volume":"145","author":"Chave","year":"2005","journal-title":"Oecologia"},{"key":"ref_39","unstructured":"Guyot, J. (2011). Estimation du Stock de Carbone dans la V\u00e9g\u00e9tation des Zones Humides de la P\u00e9ninsule du Yucatan. Memoire de fin d\u2019etudes. [Licentiate Thesis, AgroParis Tech-El Colegio de la Frontera Sur]."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/S0378-1127(03)00229-9","article-title":"Composition and aboveground tree biomass of a dry semi-evergreen forest on Mexico\u2019s Yucatan Peninsula","volume":"186","author":"Cairns","year":"2003","journal-title":"For. Ecol. Manag."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.foreco.2007.04.015","article-title":"Regional scale variation in forest structure and biomass in the Yucatan Peninsula, Mexico: Effects of forest disturbance","volume":"247","author":"Dolman","year":"2007","journal-title":"For. Ecol. Manag."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1046\/j.1365-2745.2003.00757.x","article-title":"Spatial and temporal variation of biomass in a tropical forest: Results from a large census plot in Panama","volume":"91","author":"Chave","year":"2003","journal-title":"J. Ecol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"351","DOI":"10.2307\/1942582","article-title":"Ecosystem dynamics of a subtropical floodplain forest","volume":"55","author":"Frangi","year":"1985","journal-title":"Ecol. Monogr."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1109\/JSTARS.2010.2077619","article-title":"Generating Large-Scale High-Quality SAR Mosaic Datasets: Application to PALSAR Data for Global Monitoring","volume":"3","author":"Shimada","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3735","DOI":"10.1080\/01431160902777175","article-title":"Using dual-polarized ALOS PALSAR data for detecting new fronts of deforestation in the Brazilian Amaz\u00f4nia","volume":"30","author":"Shimabukuro","year":"2009","journal-title":"Int. J. Remote. Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"179","DOI":"10.5194\/bg-9-179-2012","article-title":"Mapping tropical forest biomass with radar and spaceborne LiDAR in Lop\u00e9 National Park, Gabon: Overcoming problems of high biomass and persistent cloud","volume":"9","author":"Mitchard","year":"2012","journal-title":"Biogeosciences"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural Features for Image Classification","volume":"SMC-3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1007\/s10712-019-09519-x","article-title":"The relevance of forest structure for biomass and productivity in temperate forests: New perspectives for remote sensing","volume":"40","author":"Fischer","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_49","unstructured":"Zvoleff, A. (2019). Calculate Textures from Grey-Level Co-Occurrence Matrices (GLCMs), R. Package. R Package v 1.6.4."},{"key":"ref_50","unstructured":"Freeman, E.A., Frescino, T.S., and Moisen, G.G. (2021, August 10). ModelMap: And R Package for Model Creation and Map Production. Available online: https:\/\/cran.r-project.org\/web\/packages\/ModelMap\/vignettes\/VModelMap."},{"key":"ref_51","unstructured":"INEGI (2010). Conjunto Nacional de Uso del Suelo y Vegetaci\u00f3n a escala 1:250,000, Serie IV, INEGI."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1826","DOI":"10.1890\/03-3111","article-title":"Disecting the spatial structure of ecological data al multiple scales","volume":"85","author":"Borcard","year":"2004","journal-title":"Ecology"},{"key":"ref_53","first-page":"1","article-title":"Spatial distribution of carbon stored in forests of the Democratic Republic of Congo","volume":"7","author":"Xu","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.rse.2015.12.002","article-title":"Spatial distribution of forest aboveground biomass in China: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data","volume":"173","author":"Su","year":"2016","journal-title":"Remote. Sens. Environ."},{"key":"ref_55","first-page":"1","article-title":"The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations","volume":"148","author":"Santoro","year":"2020","journal-title":"Earth Syst. Sci. Data Discuss."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Luther, J.E., Fournier, R.A., van Lier, O.R., and Bujold, M. (2019). Extending ALS-based mapping of forest attributes with medium resolution satellite and environmental data. Remote. Sens., 11.","DOI":"10.3390\/rs11091092"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"4045","DOI":"10.3390\/rs5084045","article-title":"NASA Goddard\u2019s LiDAR, hyperspectral and thermal (G-LiHT) airborne imager","volume":"5","author":"Cook","year":"2013","journal-title":"Remote. Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13021-018-0093-5","article-title":"Estimation of forest aboveground biomass and uncertainties by integration of field measurements, airborne LiDAR, and SAR and optical satellite data in Mexico","volume":"13","author":"Urbazaev","year":"2018","journal-title":"Carbon Balance Manag."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.rse.2014.12.019","article-title":"Decrease of L-band SAR backscatter with biomass of dense forests","volume":"159","author":"Mermoz","year":"2015","journal-title":"Remote. Sens. Environ."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1786","DOI":"10.1016\/j.foreco.2011.07.008","article-title":"Estimating aboveground biomass in forest and oil palm plantation in Sabah, Malaysian Borneo using ALOS PALSAR data","volume":"262","author":"Morel","year":"2011","journal-title":"For. Ecol. Manag."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1109\/LGRS.2013.2244060","article-title":"Retrieval of forest stand age from SAR image texture for varying distance and orientation values of the gray level co-occurrence matrix","volume":"11","author":"Champion","year":"2014","journal-title":"IEEE Geosci. Remote. Sens-Ing Lett."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"3371","DOI":"10.1109\/TGRS.2012.2219872","article-title":"Forest biomass estimation using texture measurements of high-resolution dual-polarization C-band SAR data","volume":"51","author":"Sarker","year":"2013","journal-title":"IEEE Trans. Geosci. Remote. Sens."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Andres-Mauricio, J., Valdez-Lazalde, J.R., George-Chac\u00f3n, S.P., and Hern\u00e1ndez-Stefanoni, J.L. (2021). Mapping structural attributes of tropical dry forests by combining Synthetic Aperture Radar and high-resolution satellite imagery data. Appl. Veg. Sci., 24.","DOI":"10.1111\/avsc.12580"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1002\/rse2.9","article-title":"Satellite remote sensing to monitor species diversity: Potential and pitfalls","volume":"2","author":"Rocchini","year":"2016","journal-title":"Remote. Sens. Ecol. Conserv."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1002\/env.516","article-title":"Quantitative tools for perfecting species lists","volume":"13","author":"Palmer","year":"2002","journal-title":"Environmetrics"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Soto-Navarro, C., Ravilious, C., Arnell, A., De Lamo, X., Harfoot, M., Hill, S.L.L., Wearn, O.R., Santoro, M., Bouvet, A., and Mermoz, S. (2020). Mapping co-benefits for carbon storage and biodiversity to inform conservation policy and action. Philos. Trans. R. Soc. B, 375.","DOI":"10.1098\/rstb.2019.0128"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1111\/j.1755-263X.2009.00092.x","article-title":"Global congruence of carbon storage and biodiversity in terrestrial ecosystems","volume":"3","author":"Strassburg","year":"2010","journal-title":"Conserv. Lett."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1111\/geb.12143","article-title":"Carbon storage in tropical forests correlates with taxonomic diversity and functional dominance on a global scale","volume":"23","author":"Cavanaugh","year":"2014","journal-title":"Glob. Ecol. Biogeog-Raphy"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1111\/ele.12903","article-title":"The extent and predictability of the biodiversity\u2013carbon correlation","volume":"21","author":"Watson","year":"2018","journal-title":"Ecol. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3179\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:44:08Z","timestamp":1760165048000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3179"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,11]]},"references-count":69,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["rs13163179"],"URL":"https:\/\/doi.org\/10.3390\/rs13163179","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,8,11]]}}}