• Roe, S. et al. Contribution of the land sector to a 1.5 °C world. Nat. Clim. Change 9, 817–828 (2019).

    Article 

    Google Scholar
     

  • Seddon, N. et al. Understanding the value and limits of nature-based solutions to climate change and other global challenges. Philos. Trans. R. Soc. B Biol. Sci. 375, 20190120 (2020).

    Article 

    Google Scholar
     

  • Sarira, T. V., Zeng, Y., Neugarten, R., Chaplin-Kramer, R. & Koh, L. P. Co-benefits of forest carbon projects in Southeast Asia. Nat. Sustain. 5, 393–396 (2022).

    Article 

    Google Scholar
     

  • Phelps, J., Webb, E. L. & Adams, W. M. Biodiversity co-benefits of policies to reduce forest-carbon emissions. Nat. Clim. Change 2, 497–503 (2012).

    Article 

    Google Scholar
     

  • Donofrio, S.-M., Patrick–Daley, C.-C. & Ciro–Lin, K. The Art of Integrity: State of the Voluntary Carbon Markets 2022 Q3 (Forest Trends’ Ecosystem Marketplace, 2022).

  • Hyde, M. et al. Refining carbon credits to contribute to large carnivore conservation: the jaguar as a case study. Conserv. Lett. 15, e12880 (2022).

    Article 

    Google Scholar
     

  • International Union for Conservation of Nature. IUCN Global Standard for Nature-Based Solutions: A User-Friendly Framework for the Verification, Design and Scaling up of NbS 1st edn (International Union for Conservation of Nature, 2020).

  • Soto-Navarro, C. et al. Mapping co-benefits for carbon storage and biodiversity to inform conservation policy and action. Philos. Trans. R. Soc. B Biol. Sci. 375, 20190128 (2020).

    Article 

    Google Scholar
     

  • Key, I. B. et al. Biodiversity outcomes of nature-based solutions for climate change adaptation: characterising the evidence base. Front. Environ. Sci. 10, 905767 (2022).

  • Lou, J., Hultman, N., Patwardhan, A. & Qiu, Y. L. Integrating sustainability into climate finance by quantifying the co-benefits and market impact of carbon projects. Commun. Earth Environ. 3, 1–11 (2022).

    Article 

    Google Scholar
     

  • Gonzalez, A. & Londoño, M. C. Monitor biodiversity for action. Science 378, 1147–1147 (2022).

    Article 

    Google Scholar
     

  • Oliver, R. Y. et al. Camera trapping expands the view into global biodiversity and its change. Philos. Trans. R. Soc. B Biol. Sci. 378, 20220232 (2023).

    Article 

    Google Scholar
     

  • Pimm, S. L. et al. Emerging technologies to conserve biodiversity. Trends Ecol. Evol. 30, 685–696 (2015).

    Article 

    Google Scholar
     

  • Deiner, K. et al. Environmental DNA metabarcoding: transforming how we survey animal and plant communities. Mol. Ecol. 26, 5872–5895 (2017).

    Article 

    Google Scholar
     

  • Kelly, R. P. et al. Harnessing DNA to improve environmental management. Science 344, 1455–1456 (2014).

    Article 

    Google Scholar
     

  • Jaureguiberry, P. et al. The direct drivers of recent global anthropogenic biodiversity loss. Sci. Adv. 8, eabm9982 (2022).

    Article 

    Google Scholar
     

  • Stanturf, J. A., Palik, B. J. & Dumroese, R. K. Contemporary forest restoration: a review emphasizing function. For. Ecol. Manag. 331, 292–323 (2014).

    Article 

    Google Scholar
     

  • Carbon Direct. State of the voluntary carbon market. https://www.carbon-direct.com/research-and-reports/state-of-the-voluntary-carbon-market (2023).

  • Ebeling, J. & Yasué, M. Generating carbon finance through avoided deforestation and its potential to create climatic, conservation and human development benefits. Philos. Trans. R. Soc. B Biol. Sci. 363, 1917–1924 (2008).

    Article 

    Google Scholar
     

  • Pan, C. et al. Key challenges and approaches to addressing barriers in forest carbon offset projects. J. For. Res. 33, 1109–1122 (2022).

    Article 

    Google Scholar
     

  • The Integrity Council for the Voluntary Carbon Market. Core carbon principles, assessment framework and assessment procedure. https://policycommons.net/artifacts/4433491/ccp-foreword-final-28mar23/5230721/ (2023).

  • Merger, E., Dutschke, M. & Verchot, L. Options for REDD+ voluntary certification to ensure net GHG benefits, poverty alleviation, sustainable management of forests and biodiversity conservation. Forests 2, 550–577 (2011).

    Article 

    Google Scholar
     

  • Richards, M. & Panfil, S. Social and Biodiversity Impact Assessment (SBIA) Manual for REDD+ Projects: Part 1—Core Guidance for Project Proponents (Climate, Community & Biodiversity Alliance, Forest Trends, Fauna & Flora International, and Rainforest Alliance, 2011).

  • Waldon, J., Miller, B. W. & Miller, C. M. A model biodiversity monitoring protocol for REDD projects. Trop. Conserv. Sci. 4, 254–260 (2011).

    Article 

    Google Scholar
     

  • Kelly, R. P. et al. Toward a national eDNA strategy for the United States. Environ. DNA 6, e432 (2024).

    Article 

    Google Scholar
     

  • UNESCO. Environmental DNA expeditions in UNESCO world heritage marine sites. https://www.unesco.org/en/edna-expeditions (2024).

  • Bálint, M. et al. Accuracy, limitations and cost efficiency of eDNA‐based community survey in tropical frogs. Mol. Ecol. Resour. 18, 1415–1426 (2018).

    Article 

    Google Scholar
     

  • Mena, J. L. et al. Environmental DNA metabarcoding as a useful tool for evaluating terrestrial mammal diversity in tropical forests. Ecol. Appl. 31, e02335 (2021).

    Article 

    Google Scholar
     

  • Beng, K. C. & Corlett, R. T. Applications of environmental DNA (eDNA) in ecology and conservation: opportunities, challenges and prospects. Biodivers. Conserv. 29, 2089–2121 (2020).

    Article 

    Google Scholar
     

  • Valentin, R. E. et al. Moving eDNA surveys onto land: strategies for active eDNA aggregation to detect invasive forest insects. Mol. Ecol. Resour. 20, 746–755 (2020).

    Article 

    Google Scholar
     

  • van der Heyde, M., Bunce, M. & Nevill, P. Key factors to consider in the use of environmental DNA metabarcoding to monitor terrestrial ecological restoration. Sci. Total Environ. 848, 157617 (2022).

    Article 

    Google Scholar
     

  • Lynggaard, C. et al. DNA-based arthropod diversity assessment in Amazonian iron mine lands show ecological succession towards undisturbed reference sites. Front. Ecol. Evol. 8, 590976 (2020).

    Article 

    Google Scholar
     

  • Van Der Heyde, M. et al. Changes in soil microbial communities in post mine ecological restoration: Implications for monitoring using high throughput DNA sequencing. Sci. Total Environ. 749, 142262 (2020).

    Article 

    Google Scholar
     

  • Van Der Heyde, M. et al. Scat DNA provides important data for effective monitoring of mammal and bird biodiversity. Biodivers. Conserv. 30, 3585–3602 (2021).

    Article 

    Google Scholar
     

  • Van Der Heyde, M. et al. Evaluating restoration trajectories using DNA metabarcoding of ground‐dwelling and airborne invertebrates and associated plant communities. Mol. Ecol. 31, 2172–2188 (2022).

    Article 

    Google Scholar
     

  • International Union for Conservation of Nature. eBioAtlas: Using the Power of eDNA to Fill Global Biodiversity Knowledge Gaps and Deliver Impact in Conservation (International Union for Conservation of Nature, 2023).

  • Abarenkov, K. et al. Publishing DNA-derived data through biodiversity data platforms, version 1.3.0, 7 June 2023 (Global Biodiversity Information Facility, 2023).

  • Lynggaard, C. et al. Airborne environmental DNA for terrestrial vertebrate community monitoring. Curr. Biol. 32, 701–707 (2022).

    Article 

    Google Scholar
     

  • Kyle, K. E. et al. Combining surface and soil environmental DNA with artificial cover objects to improve terrestrial reptile survey detection. Conserv. Biol. 36, e13939 (2022).

  • Allen, M. C. et al. Sampling environmental DNA from trees and soil to detect cryptic arboreal mammals. Sci. Rep. 13, 180 (2023).

    Article 

    Google Scholar
     

  • Leempoel, K., Hebert, T. & Hadly, E. A. A comparison of eDNA to camera trapping for assessment of terrestrial mammal diversity. Proc. R. Soc. B 287, 20192353 (2020).

    Article 

    Google Scholar
     

  • Newton, J. P., Bateman, P. W., Heydenrych, M. J., Mousavi-Derazmahalleh, M. & Nevill, P. Home is where the hollow is: revealing vertebrate tree hollow user biodiversity with eDNA metabarcoding. Environ. DNA 4, 1078–1091 (2022).

    Article 

    Google Scholar
     

  • Allen, M. C. et al. Using surface environmental DNA to assess arthropod biodiversity within a forested ecosystem. Environ. DNA 5, 1652–1666 (2023).

    Article 

    Google Scholar
     

  • Marquina, D., Esparza‐Salas, R., Roslin, T. & Ronquist, F. Establishing arthropod community composition using metabarcoding: surprising inconsistencies between soil samples and preservative ethanol and homogenate from Malaise trap catches. Mol. Ecol. Resour. 19, 1516–1530 (2019).

    Article 

    Google Scholar
     

  • Banerjee, P. et al. Environmental DNA analysis as an emerging non-destructive method for plant biodiversity monitoring: a review. AoB Plants 14, plac031 (2022).

    Article 

    Google Scholar
     

  • Johnson, M. D. et al. Environmental DNA as an emerging tool in botanical research. Am. J. Bot. 110, e16120 (2023).

    Article 

    Google Scholar
     

  • Watson, C. D. et al. Global meta-analysis shows progress towards recovery of soil microbiota following revegetation. Biol. Conserv. 272, 109592 (2022).

    Article 

    Google Scholar
     

  • Eaton, W. D., Shokralla, S., McGee, K. M. & Hajibabaei, M. Using metagenomics to show the efficacy of forest restoration in the New Jersey Pine Barrens. Genome 60, 825–836 (2017).

    Article 

    Google Scholar
     

  • Dyson, K. et al. Coupling remote sensing and eDNA to monitor environmental impact: A pilot to quantify the environmental benefits of sustainable agriculture in the Brazilian Amazon. PLoS ONE 19, e0289437 (2024).

    Article 

    Google Scholar
     

  • Pitman, N. Social and Biodiversity Impact Assessment Manual for REDD+ Projects: Part 3 – Biodiversity Impact Assessment Toolbox (Forest Trends, Climate, Community & Biodiversity Alliance, Rainforest Alliance and Fauna & Flora International, 2011).

  • Tedersoo, L. et al. Towards a co-crediting system for carbon and biodiversity. Plants People Planet 6, 18–28 (2024).

    Article 

    Google Scholar
     

  • Forbes, R. J., Watson, S. J., O’Connor, E., Wescott, W. & Steinbauer, M. J. Diversity and abundance of Lepidoptera and Coleoptera in multiple-species reforestation plantings to offset emissions of carbon dioxide. Aust. For. 82, 89–106 (2019).

    Article 

    Google Scholar
     

  • Nakakaawa, C., Aune, J. & Vedeld, P. Changes in carbon stocks and tree diversity in agro-ecosystems in south western Uganda: what role for carbon sequestration payments? New For. 40, 19–44 (2010).

    Article 

    Google Scholar
     

  • Mekuria, W. et al. Restoring aboveground carbon and biodiversity: a case study from the Nile basin, Ethiopia. For. Sci. Technol. 11, 86–96 (2015).


    Google Scholar
     

  • Bartels, S. F. & Macdonald, S. E. Dynamics and recovery of forest understory biodiversity over 17 years following varying levels of retention harvesting. J. Appl. Ecol. 60, 725–736 (2023).

    Article 

    Google Scholar
     

  • Haq, S. M. et al. Biodiversity and carbon stocks of the understory vegetation as indicators for forest health in the Zabarwan Mountain Range, Indian Western Himalaya. Ecol. Indic. 159, 111685 (2024).

    Article 

    Google Scholar
     

  • Karimi, B. et al. Microbial diversity and ecological networks as indicators of environmental quality. Environ. Chem. Lett. 15, 265–281 (2017).

    Article 

    Google Scholar
     

  • Borges, F. L. G., da Rosa Oliveira, M., de Almeida, T. C., Majer, J. D. & Garcia, L. C. Terrestrial invertebrates as bioindicators in restoration ecology: a global bibliometric survey. Ecol. Indic. 125, 107458 (2021).

    Article 

    Google Scholar
     

  • Deiner, K., Fronhofer, E. A., Mächler, E., Walser, J.-C. & Altermatt, F. Environmental DNA reveals that rivers are conveyer belts of biodiversity information. Nat. Commun. 7, 12544 (2016).

    Article 

    Google Scholar
     

  • Macher, T., Schütz, R., Hörren, T., Beermann, A. J. & Leese, F. It’s raining species: rainwash eDNA metabarcoding as a minimally invasive method to assess tree canopy invertebrate diversity. Environ. DNA 5, 3–11 (2023).

    Article 

    Google Scholar
     

  • Lynggaard, C. et al. Vertebrate environmental DNA from leaf swabs. Curr. Biol. 33, R853–R854 (2023).

    Article 

    Google Scholar
     

  • Massey, A. L. et al. Invertebrates for vertebrate biodiversity monitoring: comparisons using three insect taxa as iDNA samplers. Mol. Ecol. Resour. 22, 962–977 (2022).

    Article 

    Google Scholar
     

  • Coutant, O. et al. Amazonian mammal monitoring using aquatic environmental DNA. Mol. Ecol. Resour. 21, 1875–1888 (2021).

    Article 

    Google Scholar
     

  • Lyet, A. et al. eDNA sampled from stream networks correlates with camera trap detection rates of terrestrial mammals. Sci. Rep. 11, 1–14 (2021).

    Article 

    Google Scholar
     

  • Valentin, R. E., Kyle, K. E., Allen, M. C., Welbourne, D. J. & Lockwood, J. L. The state, transport, and fate of aboveground terrestrial arthropod eDNA. Environ. DNA 3, 1081–1092 (2021).

    Article 

    Google Scholar
     

  • Corlett, R. T. & Primack, R. B. Tropical rainforest conservation: a global perspective. Trop. For. Community Ecol. 442, 457 (2008).


    Google Scholar
     

  • Jackman, J. M. et al. eDNA in a bottleneck: obstacles to fish metabarcoding studies in megadiverse freshwater systems. Environ. DNA 3, 837–849 (2021).

    Article 

    Google Scholar
     

  • van der Reis, A. L., Beckley, L. E., Olivar, M. P. & Jeffs, A. G. Nanopore short-read sequencing: a quick, cost-effective and accurate method for DNA metabarcoding. Environ. DNA 5, 282–296 (2023).

    Article 

    Google Scholar
     

  • Kéry, M. & Royle, J. A. Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS: Volume 1: Prelude and Static Models (Academic Press, 2016).

  • Bush, A. et al. Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages. Mol. Ecol. Resour. 23, 1275–1287 (2023).

    Article 

    Google Scholar
     

  • Nichols, J. D. et al. Multi-scale occupancy estimation and modelling using multiple detection methods. J. Appl. Ecol. 45, 1321–1329 (2008).

    Article 

    Google Scholar
     

  • West, T. A. P. et al. Action needed to make carbon offsets from forest conservation work for climate change mitigation. Science 381, 873–877 (2023).

    Article 

    Google Scholar
     

  • Page, M. J. et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int. J. Surg. 88, 105906 (2021).

    Article 

    Google Scholar
     



  • Source link