scholarly journals Forest management affects seasonal source-sink dynamics in a territorial, group-living bird

Oecologia ◽  
2021 ◽  
Author(s):  
Kate Layton-Matthews ◽  
Michael Griesser ◽  
Christophe F. D. Coste ◽  
Arpat Ozgul

AbstractThe persistence of wildlife populations is under threat as a consequence of human activities, which are degrading natural ecosystems. Commercial forestry is the greatest threat to biodiversity in boreal forests. Forestry practices have degraded most available habitat, threatening the persistence of natural populations. Understanding population responses is, therefore, critical for their conservation. Population viability analyses are effective tools to predict population persistence under forestry management. However, quantifying the mechanisms driving population responses is complex as population dynamics vary temporally and spatially. Metapopulation dynamics are governed by local dynamics and spatial factors, potentially mediating the impacts of forestry e.g., through dispersal. Here, we performed a seasonal, spatially explicit population viability analysis, using long-term data from a group-living territorial bird (Siberian jay, Perisoreus infaustus). We quantified the effects of forest management on metapopulation dynamics, via forest type-specific demography and spatially explicit dispersal, and how forestry impacted the stability of metapopulation dynamics. Forestry reduced metapopulation growth and stability, through negative effects on reproduction and survival. Territories in higher quality natural forest contributed more to metapopulation dynamics than managed forests, largely through demographic processes rather than dispersal. Metapopulation dynamics in managed forest were also less resilient to disturbances and consequently, may be more vulnerable to environmental change. Seasonal differences in source-sink dynamics observed in managed forest, but not natural forests, were caused by associated seasonal differences in dispersal. As shown here, capturing seasonal source-sink dynamics allows us to predict population persistence under human disturbance and to provide targeted conservation recommendations.

Ecology ◽  
1998 ◽  
Vol 79 (7) ◽  
pp. 2516-2530 ◽  
Author(s):  
W. S. C. Gurney ◽  
A. R. Veitch ◽  
I. Cruickshank ◽  
G. McGeachin

Ecography ◽  
2014 ◽  
Vol 37 (8) ◽  
pp. 797-804 ◽  
Author(s):  
Thomas Ranius ◽  
Petter Bohman ◽  
Olof Hedgren ◽  
Lars-Ove Wikars ◽  
Alexandro Caruso

2007 ◽  
Vol 83 (1) ◽  
pp. 36-40 ◽  
Author(s):  
L A Venier ◽  
J L Pearce ◽  
B A Wintle ◽  
S A Bekessy

In this paper, we provide an overview of a project that we initiated to explore the utility of spatially-explicit metapopulation models linked to dynamic landscape models as a way of incorporating biological indicators into sustainable forest management. We developed models for three indicator species as case studies; brown creeper (Certhis americana), redbacked vole (Clethrionomys gapperi) and red-backed salamander (Plethodon cinereus) in a northern Ontario landscape. Results from the project to date suggest that there are significant advantages to models that are spatially-explicit and dynamic in their treatment of both populations and landscapes. Dynamic landscape metapopulation (DLMP) models allow a manager to track population change through time in response to a changing landscape and a fluctuating environment. These DLMP models may be used to predict the impact of current and alternative forest management strategies on population sizes of a suite of species chosen to indicate the health of forest ecosystems. Key words: biological indicators, population viability analysis, population modeling, dynamic landscape modeling, sustainable forest management, brown creeper, red-backed salamander, red-backed vole


1985 ◽  
Vol 61 (2) ◽  
pp. 168-170
Author(s):  
Jack Ward Thomas

Keywords: Renewable Resource Management, Forest Management, Wildlife Management, Integration, Multiple Use.


2011 ◽  
Vol 5 (4) ◽  
pp. 361-390 ◽  
Author(s):  
Georg Winkel ◽  
Johanna Gleißner ◽  
Till Pistorius ◽  
Metodi Sotirov ◽  
Sabine Storch

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