Modelling long-term effects of forest management on epiphytic lichens in northern Sweden

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Abstract

Species-habitat models are important tools in conservation and wildlife management today. Models simulating the long-term ecological consequences of forestry on biodiversity have large potential as guidance for management. In this paper, we evaluated a model, lichen biomass spatially explicit model (LIBSEM) that predicts the temporal and spatial distribution of epiphytic lichens in boreal coniferous forests. We assessed model performance by simulating the standing crop of pendulous lichens (Bryoria spp.) over a 50-year period in a managed forest landscape (Brattåker, 4405 ha). We compared the simulated data with independent field data based on sampling of lichen litter in 54 plots stratified by forest age class. Simulated epiphyte standing crop was significantly related to field data but overall model performance was rather poor at the cell level (50m×50 m cells) with a modelling efficiency of 12%. Results suggest that the model succeeded better in predicting lichen biomass on the landscape level. We used LIBSEM to assess possible long-term consequences on epiphytes of four management scenarios differing in the length of the rotation cycle. The change in epiphyte biomass was projected over a 200-year period. Results show that an even-aged silvicultural system with a normal rotation (110 years) only can support a low amount of pendulous lichens while short rotation (60 years) is very detrimental to epiphyte communities. Thus, to enhance the abundance of epiphytic lichens it is necessary to use extended rotations, preferably in combination with forest reserves. We conclude that spatially explicit landscape models may act as a guide for managing boreal forests to improve conditions for epiphytes.

Introduction

Most of the boreal forests in Fennoscandia are used by commercial forestry. This has numerous and mostly negative consequences for biodiversity (Esseen et al., 1997, Niemela, 1997. However, it is not a trivial task to assess the long-term effects of forest management on biodiversity. This is because of the intrinsically slow development of forest stands and because disturbance plays a major role in shaping the structure and dynamics of forest ecosystems (Oliver and Larson, 1990, Engelmark, 1999). The processes that influence the dynamics of both natural and managed forests operate over a vast range of spatial and temporal scales (Spies and Turner, 1999). This makes it difficult or at least costly to assess the ecological effects of forest management activities on biodiversity through comparative field studies or large-scale landscape experiments.

Species-habitat models are important tools with large potential in conservation and wildlife management (e.g. Verner et al., 1986, Haefner, 1996, Beutel et al., 1999). Spatially explicit landscape models have much to offer to conservation managers (Meir and Kareiva, 1999, Mladenoff and Baker, 1999). For example, landscape models may help us to better understand the long-term consequences of different forest management scenarios. They can, thus, act as a guide to find the best compromise between multiple management goals.

Forest management practices have important implications for canopy-dwelling organisms such as epiphytes. Epiphytic lichens are particularly sensitive to forestry (Esseen et al., 1996, Sillett et al., 2000). This is because many species are associated with particular conditions only found in old-growth forests, and because epiphytic lichen biomass accumulates slowly over time. For example, it may take 100–400 years to build up high epiphyte biomass in the forest canopy (McCune, 1993, Esseen et al., 1996). Recent studies strongly suggest that dispersal limitation is a key factor behind the low epiphyte abundance in young managed forests (Dettki et al., 2000, Sillett et al., 2000, Hilmo and Sastad, 2001). Epiphytic lichens have several important functional roles in forest ecosystems. They increase structural complexity, modify canopy water regimes, influence nutrient cycling and provide habitat, food and nest material for many animals (Galloway, 1992, Rhoades, 1995). There is, thus, a need to develop forest management methods that permit the accumulation of abundant and diverse epiphyte communities.

In this paper, we applied the spatially explicit landscape model, lichen biomass spatially explicit model (LIBSEM); Dettki, 2000) to a managed forest landscape. LIBSEM predicts the spatial and temporal distribution of epiphytic lichen biomass in boreal forest landscapes by linking lichen population dynamics (growth, dispersal, litterfall) to the pattern of forest harvesting and succession. The paper has two objectives. First, we validated the efficiency of the model by comparing predicted data with field data on abundance of pendulous lichens (Bryoria spp.) for a managed boreal forest landscape. Second, we analysed possible long-term consequences of forestry on epiphyte abundance in the landscape by simulating four different management scenarios, differing in the length of the rotation cycle, over a period of 200 years and assessed the overall effect of these scenarios.

Section snippets

Study area

Field sampling was performed in the Brattåker area, located in Västerbotten county, northernmost Sweden (Fig. 1). The Brattåker area is located at 63°35′N, 20°15′E (WGS84), 60 km north-west of Umeå, and has a total area of 6400 ha. It belongs to the middle boreal zone as defined by Ahti et al. (1968). The landscape is limited to the east by the Vindel River. From the riverbanks at 150–170 m a.s.l., the landscape comprises to the west of coarse glaciofluvial sediments, followed by hilly terrain

Sample plots

An extensive data set on stand structure was already available from the Brattåker area. Information on size and form of forest compartments was obtained from the landowner, the forest company Holmen AB, in the form of GIS-data (Arc/Info; ESRI, 1998). Data on stand structure from 1996 was obtained from a detailed stand inventory performed in the area (Christoffersson and Jonsson, 1996, Wallerman, 1998). This inventory was based on measurements made in 2446 circular plots (10 m radius) distributed

Lichen abundance

The litter of pendulous lichens on the forest floor was dominated by Bryoria spp. (84.5%), followed by Alectoria sarmentosa (10.2%) and Usnea spp. (5.3%). There was large variation in the amount of lichen litter among forest cells, from 0.001 to 1.99 g/m2, with an overall mean of 0.303g/m2±0.055 g/m2 (mean±1S.E.; n=54; Table 1). The combined biomass of all pendulous lichens increased with forest age (r=0.33, P=0.014). Old stands (>130 years) had four times higher litter biomass than stands of

Lichen abundance

The composition of the epiphyte community in the Brattåker landscape showed large similarity with that of other managed forests in northern Sweden (Dettki and Esseen, 1998, Dettki et al., 2000). Green-algal foliose lichens as Hypogymnia spp. were common and the abundance of pendulous lichens was low due to the large proportion of young stands. This is because of the generally slow accumulation of epiphyte mass in boreal forests (Esseen et al., 1996). The dominant pendulous lichens were Bryoria

Conclusions

We conclude that spatially explicit landscape models may act as a guide for managing boreal forests to improve conditions for epiphytic lichens. This will be important in fulfilling multiple management goals like sustainable forestry, reindeer husbandry, and conservation of biodiversity. Models like LIBSEM may help us to determine the harvest levels and the distribution of rotation ages required for a long-term sustainable biomass of pendulous lichens. Further, the merging of LIBSEM with other

Acknowledgements

We thank Jörgen Wallerman and Holmen AB for providing the Brattåker forestry database and GIS data, and Mikael Rännar for model programming. Bengt Gunnar Jonsson and two anonymous referees improved the manuscript with constructive comments. This study was financed by Centre for Environmental Research, Umeå, and the Swedish Environmental Protection Agency.

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