Habitat heterogeneity is a good predictor of boreal forest biodiversity. (April 2023)

• Record Type: Journal Article
• Authors: Hekkala, Anne-Maarit; Jönsson, Mari; Kärvemo, Simon; Strengbom, Joachim; Sjögren, Jörgen
• Is Part Of: Ecological indicators. Volume 148(2023)
• Publication Date: 2023-04
• Subjects: Deadwood, coarse woody debris, conservation -- Habitat amount -- Indicator -- Structural complexity; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2023.110069
• Languages: English
• ISSNs: 1470-160X

Abstract

Graphical abstract: Highlights: Habitat heterogeneity and resource amount and quality were tested as indicators. Habitat heterogeneity predicts the richness of species of conservation concern. Dead wood and tree age predict the richness of red-listed species. Thresholds for habitat heterogeneity score and deadwood were calculated. Habitat heterogeneity score is useful tool in practical forestry and conservation. Abstract: Reliable assessment measures are crucial for tracking changes in biodiversity and for evaluating the state of biodiversity. Two of the main drivers of biodiversity are habitat heterogeneity and resource amount. These drivers are used as proxies of biodiversity but assessing both is costly, limiting their practical use. To test which of the drivers best predicts the number and abundance of sessile species of conservation concern (including macrofungi, lichens, bryophytes, and vascular plants), we assessed forest stand heterogeneity using a method developed in Sweden ('Habitat Heterogeneity Score HHS'), and quantified the resource amount and quality of ecologically important structural variables (deadwood volume, basal area of living trees, proportion of broadleaved trees, and the age of the oldest tree in the stand). We conducted the assessments in 77 boreal conifer-dominated forest stands in two regions of Sweden. Despite some group-specific organism differences, HHS was the best predictor of both number and abundance of all species of conservation concern, regardless of the region. Further, HHS was the best predictor of red-listed species number and abundance in the southern region, while a model including the volume of deadwood and the age of the oldest tree performed best in the northern region. Deadwood (CWD) volume was the single best resource amount predictor of the number and abundance of species of conservation concern, emphasizing the critical role that dead trees have for biodiversity. In addition, we calculated threshold values for deadwood volume and HHS depicting the level above which the number of red-listed species is significantly higher, and found this value to be higher in the southern region (22.4 m 3 ha −1 deadwood and a HSS value of 17) than in the north (20.0 m 3 ha −1 and 16). These values can be used as guidance when identifying coniferous forests with high enough qualities to support red-listed species. To conclude, the method of assessing habitat heterogeneity presented in this study is a practical and reliable way to identify forests of high biological diversity, and can therefore be part of the toolbox for sustainable forestry in boreal forests.