Unraveling the characteristic spatial scale of habitat selection for forest grouse species in the boreal landscape
Mazziotta, Adriano; Lindén, Andreas; Eyvindson, Kyle; Bianchi, Simone; Kangas, Annika; Melin, Markus; Ruha, Leena; Forsman, Jukka T. (2024)
Mazziotta, Adriano
Lindén, Andreas
Eyvindson, Kyle
Bianchi, Simone
Kangas, Annika
Melin, Markus
Ruha, Leena
Forsman, Jukka T.
Julkaisusarja
Forest ecology and management
Volyymi
563
Sivut
11 s.
Elsevier
2024
Adriano Mazziotta, Andreas Lindén, Kyle Eyvindson, Simone Bianchi, Annika Kangas, Markus Melin, Leena Ruha, Jukka T. Forsman, Unraveling the characteristic spatial scale of habitat selection for forest grouse species in the boreal landscape, Forest Ecology and Management, Volume 563, 2024, 122008, ISSN 0378-1127, https://doi.org/10.1016/j.foreco.2024.122008
Julkaisun pysyvä osoite on
http://urn.fi/URN:NBN:fi-fe2024052940795
http://urn.fi/URN:NBN:fi-fe2024052940795
Tiivistelmä
The characteristic spatial scale at which species respond strongest to forest structure is unclear and species-specific and depends on the degree of landscape heterogeneity. Research often analyzes a pre-defined spatial scale when constructing species distribution models relating forest variables with occupancy patterns. This is a limitation, as forest characteristics shape the species use of habitat at multiple spatial scales. To explore the drivers of this relationship, we conducted an in-depth investigation into how scaling forest variables at biologically relevant spatial scales affects occupancy of grouse species in boreal forest. We used 4,790 grouse observations (broods and adults) collected over 39,303 stands for 15 years of four forest grouse species (capercaillie, black grouse, hazel grouse, and willow grouse) obtained from comprehensive Finnish wildlife triangle census data and forest variables obtained from Airborne Laser Scanning and satellite data originally sampled at 16 m resolution. We fitted Generalized Additive Mixed Models linking grouse presence/absence in the Finnish boreal forest with forest stand structure and composition. We estimated the effects of predictor variables aggregated at three spatial scales reflecting the species use of the landscape: local level at stand scale, home range level at 1 km radius, and regional level at 5 km radius. Multi-grain models considering forest-species relationships at multiple scales were used to evaluate whether there is a specific scale at which forest characteristics best predict local grouse occupancy. We found that that the spatial scale affected the predictive capacity of the grouse occupancy models and the characteristic scale of habitat selection was the same (i.e., stand scale) among species. Different grouse species exhibited varying optimal spatial scales for occupancy prediction. Forest structure was more important than compositional diversity in predicting grouse occupancy irrespective of the scale. A limited number of forest predictors related to availability of multi-layered vegetation and of suitable thickets explained the occupancy patterns for all the grouse species at different scales. In conclusion, modeling grouse occupancy using forest predictors at different spatial scales can inform forest managers about the scale at which the species perceive the landscape. This evidence calls for an integrated multiscale approach to habitat modelling for forest species.
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