1 Forest structural heterogeneity and logging intensity as proxies for the 1 assessment of biodiversity trends in sustainable forest management areas: a 2 potential approach for REDD+ safeguards MRV. 3 4 Aguilar-Amuchastegui, N. a* ; Tovar-Martinez, A. b ; Amatya, S. c ; Henebry, G.M. c ; Spinola, M. b ; 5 Sanchun, A. d ; Muss, J. c ; Forrest, J. e ; Delgado, D. f . 6 7 * Corresponding Author. Email: Naikoa.Aguilar-Amuchastegui@wwfus.org 8 a. World Wildlife Fund (WWF) International Forest and Climate Program, 1250 N 24 st NW, Washington DC, 9 20037, USA 10 b. Instituto Internacional en Conservacion y Manejo de Vida Silvestre (ICOMVIS), Universidad Nacional de Costa 11 Rica, Heredia, Costa Rica. 12 c. Geospatial Sciences Center of Excellence (GIS-CE), South Dakota State University (SDSU). 13 d. Fundación para el Desarrollo de la Cordillera Volcánica Central (FUNDECOR), Heredia, Costa Rica. 14 e. World Wildlife Fund US (WWF-US), 1250 N 24 St. NW, Washington DC, 20037, USA 15 f . Centro Agronómico Tropical de Investigación y Enseñanza (CATIE), Turrialba, Costa Rica. 16 17 Abstract 18 The inclusion of sustainable forest management (SFM) as part of the activities considered under REDD+ 19 has given additional relevance to the question of how to assess the sustainability of SFM practices at large 20 scale. This highlights the logistic limitations related with traditional field approaches and the necessity for 21 linking such assessments with the data used to assess other REDD+ activities like Deforestation and 22 Degradation as part of the overall MRV exercise. Past results have shown how forest management 23 variables such as harvest intensity are correlated with forest structural heterogeneity dynamic change and 24 how both these are related with biodiversity levels of indicators groups such as Dung beetles. However, in 25 order to get a broader picture of management impacts or lack thereof, more indicator groups, showing a 26 diversity of sensitives and responses to disturbance regimes need to be assessed and linked with structural 27 data specific to the locations under management. We present results obtained when assessing dung 28