No abstract

Including biodiversity assessments in forest management planning is becoming increasingly important due to the importance of biodiversity for forest ecosystem resilience provision and sustainable functioning. Here we investigated the potential to include biodiversity indicators into forest management planning in Europe. In particular, we aimed to (i) identify biodiversity indicators and data collection methods for biodiversity assessments at the stand and landscape levels, and (ii) evaluate the practicality of those indicators for forest management planning. We performed a literature review in which we screened 188 research studies published between 1990 and 2020. We selected 94 studies that fulfilled the inclusion criteria and examined in more detail. We considered three aspects of biodiversity: structure, composition, and function, and four forest management categories: unmanaged, managed, plantation, and silvopastoral. We used three criteria to evaluate the practicality of forest biodiversity indicators: cost-effectiveness, ease of application, and time-effectiveness. We identified differences in the practicality of biodiversity indicators for their incorporation into management plans. Stand-level indicators are more practical than landscape-level indicators. Moreover, structural biodiversity indicators (e.g., large trees, canopy openness, and old forest stands) are more useful in management plans than compositional indicators, as these are easily observable by non-professionals and can be obtained by forest inventories. Compositional indicators such are vascular plants, fungi, bryophyte, lichens, and invertebrate species are hard to identify by non-professionals and thus are impractical. Functional indicators (e.g., nutrient cycling) are not sufficiently addressed in the literature. Using recently updated existing databases (e.g., national forest inventories and bird atlases) is very time and cost-efficient. Remote sensing and other technology (e.g., smartphone applications) are promising for efficient data collection in the future. However, more research is needed to make these tools more accurate and applicable to a variety of ecological conditions and scales. Until then, forest stand structural variables derived from inventories can help improve management plans to prepare European forests towards an uncertain future.

Aim of study: Practically and simply assessing biodiversity by using inventory variables in four types of forest plantation stands (mixed and pure) including species such are chestnut, blue gum and maritime pine. Area of study: Northwest Portugal in Vale do Sousa (14,840 ha), which is 97% covered with plantation forests. Material and methods: Simulated data, from 90-year stand-level forest management planning, were considered using three indicators: tree species (number of different species and species origin—native or exotic), mean diameter at breast height (DBH), and shrub biomass. Two shrub regeneration types (fully regeneration by seed and fully regeneration by resprouting), and three site quality conditions were also considered. Main results: Mean biodiversity scores varied between very low (10.13) in pure blue gum stands on lowest-quality sites with shrub regeneration by seed, and low (29.85) in mixed stands with a dominance of pine, on best-quality sites with shrub regeneration by resprouting. Site quality and shrub regeneration type significantly affected all biodiversity scores in mixed stands dominated by pine and pure chestnut stands, while less affected pure blue gum stands and mixed stands dominated by blue gum. Research highlights: The considered biodiversity indicators cover the major biodiversity aspects and allow biodiversity assessment over time. The findings are relevant for biodiversity conservation and fire protection management.

Motivation and objective: Because biodiversity conservation in forest management planning is necessary for ensuring regular ecosystem functioning, resilience and sustainability, the specific objective of this research was to quantify biodiversity at the landscape level in a forest plantation. Case study: Vale de Sousa, Forest Intervention Zone (ZIF), is located in the North of Portugal. ZIFs were formed all over the county with the objective to prevent forest fires, desertification and the abandonment of rural areas. The total case study area is 14.773 ha, mainly covered by plantation forests. The predominant forest species are maritime pine (Pinus pinaster) and blue gum (Eucalyptus globulus) either as pure or mixed stands. Methods:Fuzzy-logic system can serve as a platform for bundling expert knowledge on estimating ecosystem services provision and examining the consequences of contradictory expert views. The method was used to evaluate biodiversity as was recently proposed and demonstrated by Biber et al. (2018) in the context of the European Union (EU) project ALTERFOR (Alternative models and robust decision-making for future forest management - https://www.alterfor-project.eu/key-facts.html). In this study, we applied a fuzzy-logic approach for testing three biodiversity indicators: resident birds, heterogeneity of tree species diameter, and tree and shrub species richness. This approach generates scores for the rotation period of each plantation species between 0 (very low) and 1 (very high) for biodiversity categories. It also allows qualitative value rules regarding the above indicators. Scores are established according to stakeholder’s knowledge and validated by experts. Initially, the scores for each indicator are expressed as coloured matrices, but a final fuzzy output of biodiversity is expressed as a score between 0 and 1. Results: Our fuzzy outputs demonstrated low scores for biodiversity in monoculture stands, but medium scores in mixed stands. Tree and shrub species richness and diameter heterogeneity have low scores in analysed plantations but need to be tested in other forest types. However, the score for resident birds had medium values in monoculture forests, but due to the low score of the other biodiversity indicators, the overall biodiversity score is low. Conclusion: The results demonstrate that monocultures have the lowest score for biodiversity due to the zero level of all biodiversity indicators after the clear cut. Mixed stands have different periods of clear cut and this contributes to a higher score for biodiversity in general (fuzzy output). The fuzzy-logic approach is a very useful tool that may contribute to include biodiversity conservation in forest management decisions. This approach can be potentially used for the assessment of other biodiversity indicators (e.g. deadwood, large trees) in other forest types (including semi-natural and natural forests).