Old-growth forests (OGF) provide valuable ecosystem services such as habitat provision, carbon sequestration or recreation maintaining biodiversity, carbon storage, or human well-being. Long-term human pressure caused OGFs in Europe to be rare and scattered. Their detailed extent and current status are largely unknown. This review aims to identify potential methods to map temperate old-growth forests (tOGF) by remote sensing (RS) technology, highlights the potentials and benefits, and identifies main knowledge gaps requesting further research. RS offers a wide range of data and methods to map forests and their properties, applicable from local to continental scale. We structured existing mapping approaches in three main groups. First, parameter-based approaches, which are based on forest parameters and usually applied on local to regional scale using detailed data, often from airborne laser scanning (ALS). Second, direct approaches, usually employing machine learning algorithms to generate information from RS data, with high potential for large-area mapping but so far lacking operational applications and related sound accuracy assessment. Finally, indirect approaches integrating various existing data sets to predict OGF existence. These approaches have also been used for large area mapping with a main drawback of missing physical evidence of the identified areas to really hold OGFs as compared to the likelihood of OGF existence. In conclusion, studies dealing with the mapping of OGF using remote sensing are quite limited, but there is a huge amount of knowledge from other forestry-related applications that is yet to be leveraged for OGF identification. We discuss two scenarios, where different data and approaches are suitable, recognizing that one single system cannot serve all potential needs. These may be hot spot identification, detailed area delineation, or status assessment. Further, we pledge for a combined method to overcome the identified limitations of the individual approaches.

Maintaining and improving the state of biodiversity is a primary factor guiding management activities in conservation areas, including protected areas (PAs) and other effective area-based conservation measures (OECMs). Due to the complex nature of conservation programs, a common management approach cannot be prescribed. Robust monitoring programs supporting management activities are required to evaluate the state of species and habitats. However, limited resources, poor data management practices, and competing requirements of stakeholder groups increase the challenges that must be addressed through realization of monitoring programs. We propose a framework of seven basic questions to guide conservation area managers to implement effective biodiversity monitoring techniques. The result is identification of indicators, site characteristics, and resources to promote the development of a biodiversity monitoring program. We call for adoption of a strategic guideline providing this framework to harmonize decision making processes across national and international networks. Implementation of this robust framework will support comparative monitoring data, contributing to systematic approaches for adaptive management in PAs and OECMs and improving the body of knowledge surrounding global biodiversity.