↓ Skip to main content

Modelling moose–forest interactions under different predation scenarios at Isle Royale National Park, USA

Overview of attention for article published in Ecological Applications, April 2017
Altmetric Badge

Mentioned by

facebook
1 Facebook page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
54 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Modelling moose–forest interactions under different predation scenarios at Isle Royale National Park, USA
Published in
Ecological Applications, April 2017
DOI 10.1002/eap.1526
Pubmed ID
Authors

Nathan R. De Jager, Jason J. Rohweder, Brian R. Miranda, Brian R. Sturtevant, Timothy J. Fox, Mark C. Romanski

Abstract

Loss of top predators may contribute to high ungulate population densities and chronic over-browsing of forest ecosystems. However, spatial and temporal variability in the strength of interactions between predators and ungulates occurs over scales that are much shorter than the scales over which forest communities change, making it difficult to characterize trophic cascades in forest ecosystems. We applied the LANDIS-II forest succession model and a recently developed ungulate browsing extension to model how the moose population could interact with the forest ecosystem of Isle Royale National Park, USA, under three different wolf predation scenarios. We contrasted a 100-year future without wolves (no predation) with two predation scenarios (weak = long-term average predation rates and strong = higher than average rates). Increasing predation rates led to lower peak moose population densities, lower biomass removal rates, and higher estimates of forage availability and landscape carrying capacity, especially during the first forty-years of simulations. Thereafter, moose population density was similar for all predation scenarios, but available forage biomass and the carrying capacity of the landscape continued to diverge among predation scenarios. Changes in total aboveground live biomass and species composition were most pronounced in the no and weak predation scenarios. Consistent with smaller-scale studies, high browsing rates led to reductions in the biomass of heavily browsed Populus tremuloides, Betula papyrifera, and Abies balsamea, and increases in the biomass of unbrowsed Picea glauca and P. mariana, especially after the simulation year 2050 when existing boreal hardwood stands at Isle Royale are projected to senesce. As a consequence, lower predation rates corresponded with a landscape that progressively shifted toward dominance by P. glauca and P. mariana, and lacking available forage biomass. Consistencies with previously documented small-scale successional shifts, and population estimates and trends that approximate those from this and other boreal forests that support moose provide some confidence that these dynamics represent a trophic cascade and therefore provide an important baseline against which to evaluate long-term and large-scale effects of alternative predator management strategies on ungulate populations and forest succession. This article is protected by copyright. All rights reserved.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 24%
Student > Master 10 19%
Student > Bachelor 10 19%
Researcher 5 9%
Student > Postgraduate 3 6%
Other 1 2%
Unknown 12 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 43%
Environmental Science 9 17%
Earth and Planetary Sciences 3 6%
Medicine and Dentistry 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 1 2%
Unknown 15 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 June 2017.
All research outputs
#22,409,725
of 25,002,204 outputs
Outputs from Ecological Applications
#3,301
of 3,351 outputs
Outputs of similar age
#277,118
of 315,601 outputs
Outputs of similar age from Ecological Applications
#63
of 63 outputs
Altmetric has tracked 25,002,204 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,351 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 315,601 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.