Cited by 24Ecology and biodiversity studiesForest ecology and managementWildlife Ecology and Conservation

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Predicting Biomass of Beaver Food from Willow Stem Diameters

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Baker, Bruce W., Cade, Brian S.·1995·Journal of Range Management

Abstract

Beaver (Castor canadensis Kuhl) and willow (Salix spp.) are important components of riparian restoration on degraded western rangelands. Land managers need quantitative information to evaluate carrying capacity and potential habitat quality for beavers in riparian-willow systems. Our objectives were to determine the best model to predict biomass components of coyote willow (S. exigua Nuttall) from basal stem diameters and compare model predictions to diameter class averages. The study was conducted in a shrub-steppe ecosystem of northwestern Colorado. We estimated oven-dried weights of annual and total beaver food and total live biomass by diameter class from a sample of 160 willow stems. Several variants of a logistic function were fit with nonlinear least squares regression to select a model that best predicted mean biomass by stem diameter. A four-parameter logistic model provided the best fit for all 3 stem components. Predicted biomass estimates of beaver food and total live biomass had smaller standard errors than sample means for all 10 stem diameter class midpoints. Percentage of stem weight that was beaver food varied from 93.6% for the smallest stems to 12.2% for the largest. We concluded that the logistic model provided reliable estimates of beaver food biomass and could be used with food consumption rates and stem density data to evaluate carrying capacity for beaver or test assumptions in the beaver habitat suitability index model.

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  1. [2]2. Alaback, P.B. 198613. Biomass-dimension relationships of understory vegeta- tion in relation to site and stand age, p. 141-148. by: E. H. Wharton and T. Cunia (eds.), Estimating tree biomass regressions and their error. USDA For. Serv. Gen. Tech. Rep. NE-GTR-I 17.
  2. [6]6. by: C. Zimmerman (cd.), Proc. Fourth Annu. Conv. Colo. Riparian Assoc., Steamboat Springs, Colo.
  3. [8]8. Bonham, CD. 1989. hleasurements for terrestrial vegetation. John Wiley and Sons. Inc., New York.
  4. [19]19. McClure, J. P., and R. L. Czaplewski. 1987. High order regression models for regional volume equations, p. 295-303. In: E. H. Wharton and T. Cunia (eds.), Estimating tree biomass regressions and their error. USDA For. Serv. Gen. Tech. Rep. NE-GTR-I 17.
  5. [21]21. O'Brien, D.F. 1938. A qualitative and quantitative food habit study of beavers in Maine. M.S. Thesis, Univ. Maine, Orono, Maine.
  6. [24]24. Pearson, D.C. 1977. Population and natural history studies of beavers (C'nsror cmmfensis) on Las Flores Ranch, Summit Valley, California. h1.S. Thesis. Cal. State Polytechnic Univ., Pomona, Cal.
  7. [31]31. Varies, K.C. 1974. A vegetation inventory and analysis of the Piceance Basin and adjacent drainages. M.S. Thesis, Western State College of Colo.. Gunnison. Colo.
  8. [32]32. Wilkinson, L. 1990. SYSTAT: the system for statistics. SYSTAT, Inc., Evanston. Ill. JOURNAL OF RANGE MANAGEMENT 48(4), July 1995

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Metadata

Authors
Baker, B. W., & Cade, B. S.
Venue
Journal of Range Management
Publisher
JSTOR
Published
1995-07
Volume
48
Issue
4
Pages
322
ISSN
0022-409X (ISSN-L)
OpenAlex
W324085173
Cited by
24
References
26
Citations by year
2022: 2 · 2021: 1 · 2020: 2 · 2018: 2 · 2013: 2 · 2012: 1
FWCI
0.00
Type
journal article
Language
en
Open access
Locations
  • Journal of Range Management (publishedVersion)
  • UA Campus Repository (The University of Arizona) (submittedVersion)
Topics
  • Physical Sciences › Environmental Science › Ecology › Ecology and biodiversity studies
  • Life Sciences › Agricultural and Biological Sciences › Forestry › Forest ecology and management
  • Physical Sciences › Environmental Science › Ecology › Wildlife Ecology and Conservation
Keywords
beavers, Castor canadensis, Salix exigua, biomass prediction, four-parameter logistic model, riparian restoration, shrub-steppe, living biomass, dietary intake

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