Comparison among three approaches to evaluate winter habitat selection by white-tailed deer on Anticosti Island using occurrences from an aerial survey and forest vegetation maps

2003 ◽  
Vol 81 (10) ◽  
pp. 1662-1670 ◽  
Author(s):  
François Potvin ◽  
Barry Boots ◽  
Alastair Dempster
Keyword(s):  
Habitat Selection ◽  
Selection Process ◽  
Spatial Scales ◽  
Abies Balsamea ◽  
Basal Area ◽  
Aerial Survey ◽  
Winter Habitat ◽  
Regeneration Stage ◽  
Wide Range ◽  
Anticosti Island

Habitat-selection analysis involves a comparison between the proportions of different cover types that are used by the animal and the proportions that are available. Telemetry locations or animal occurrences (e.g., from aerial surveys) can provide information on habitat utilization. With telemetry data, a classical approach involves computing habitat use at the individual location sites or inside fixed circle buffers applied to the sites. We used this approach (200 m radius circles) on data from a systematic aerial survey on Anticosti Island, where 260 groups of white-tailed deer (Odocoileus virginianus) (374 animals) were counted in a 270-km2 block. We compared the selection indices obtained from site occurrences with those of two approaches that define areas of high intensity (animal concentrations): 50% fixed kernels (0.5–2 km bandwidth) and the local K function (0.5–2 km distance). The results were very consistent among the three sets of approaches, with the same cover types generally identified as those having the highest or lowest indices. White-tailed deer preferred forest stands where balsam fir (Abies balsamea) was present as high regeneration or was dominant in the tree layer (>50% basal area) and stands at the regeneration stage. In the studied landscape, there seems to be a wide range of spatial scales where the selection process can be analysed from aerial survey data.

Winter habitat selection by white-tailed deer on Anticosti Island 2: relationship between deer density from an aerial survey and the proportion of balsam fir forest on vegetation maps

2004 ◽  
Vol 82 (4) ◽  
pp. 671-676 ◽  
Author(s):  
François Potvin ◽  
Barry Boots
Keyword(s):  
Habitat Management ◽  
Abies Balsamea ◽  
Window Size ◽  
Aerial Survey ◽  
Balsam Fir ◽  
Winter Habitat ◽  
Deer Density ◽  
Vegetation Maps ◽  
Anticosti Island ◽  
The Relationship

Determining at what scale to operate and how much cover is needed are important questions for winter habitat management of white-tailed deer, Odocoileus virginianus (Zimmermann, 1780), through logging. We used binary cover maps (reclassified forest vegetation maps) and windows of different sizes (0.2 km × 0.2 km, 0.5 km × 0.5 km, 1 km × 1 km, 2 km × 2 km, and 3 km × 3 km) to describe the relationship between deer density from an aerial survey and the proportion of balsam fir, Abies balsamea (L.) P. Mill., forest (BF) cover in a 270-km2 block on Anticosti Island, Quebec. Maximum white-tailed deer densities reached were quite similar (31–34 deer/km2) irrespective of window size, except for the 3 km × 3 km window for which maximum density remained half lower. Density increased with the amount of BF cover and then reached a plateau above 60% or 70% (two smaller windows) or decreased above 50% or 60% (1 km × 1 km and 2 km × 2 km windows). Results confirm goals previously used for habitat management of deeryards. This new method allows greater flexibility in research applications for describing density–cover relationships because both scale and proportion of cover can be analysed simultaneously.

scholarly journals Cross-scale Correlations and the Design and Analysis of Avian Habitat Selection Studies

The Condor ◽  
2006 ◽  
Vol 108 (1) ◽  
pp. 59-70 ◽  
Author(s):  
James Battin ◽  
Joshua J. Lawler
Keyword(s):  
Habitat Selection ◽  
Multiple Scales ◽  
Hierarchical Modeling ◽  
Selection Process ◽  
Spatial Scales ◽  
Classification Tree ◽  
Data Interpretation ◽  
Habitat Associations ◽  
Selection Decisions ◽  
Habitat Variables

Abstract It has long been suggested that birds select habitat hierarchically, progressing from coarser to finer spatial scales. This hypothesis, in conjunction with the realization that many organisms likely respond to environmental patterns at multiple spatial scales, has led to a large number of avian habitat studies that have attempted to quantify habitat associations at multiple scales. Typically, multiscale habitat selection studies involve the assessment of habitat selection separately at two or more scales. Until recently, these studies have ignored the potential for cross-scale correlations: correlations among habitat variables across scales. If environmental patterns are correlated across the scales being analyzed, researchers using traditional analytical methods may reach erroneous conclusions about the presence or strength of habitat associations at a given scale. We discuss the ways in which cross-scale correlations manifest themselves in two types of habitat selection studies: (1) “constrained” designs that assume a hierarchical ordering of habitat selection decisions, and (2) “unconstrained” designs, which do not assume such a selection process. We demonstrate approaches for quantifying and modeling cross-scale correlations, including a simulation model, a variance decomposition technique, and a hierarchical modeling approach based on classification tree analysis. We conclude that cross-scale correlations have the potential to affect data interpretation in all types of habitat selection studies and that, even with careful attention to experimental design and the application of newly developed statistical techniques, it is likely their effects cannot be eliminated.

scholarly journals Impact of a spruce budworm outbreak in balsam fir and subsequent stand development over a 40-year period

2008 ◽  
Vol 84 (1) ◽  
pp. 60-69 ◽  
Author(s):  
David A MacLean ◽  
Allison R Andersen
Keyword(s):  
Stand Structure ◽  
Abies Balsamea ◽  
Basal Area ◽  
Stand Density ◽  
Spruce Budworm ◽  
Balsam Fir ◽  
Stand Development ◽  
Wide Range ◽  
Break Up ◽  
The Impact

Nine 0.04-ha plots were established in 1956 (age 35 years) in a balsam fir (Abies balsamea [L.] Mill.) stand in northwestern New Brunswick, Canada to determine the impact of an uncontrolled spruce budworm (Choristoneura fumiferana [Clem.]) outbreak on stand development. The plots were measured annually from 1956 to 1961 and at five-year intervals from 1965 to 1995. Moderate to severe defoliation occurred from 1951 to 1957 and again in 1975 to 1977, 1981, and 1986 to 1988. Budworm-caused mortality from 1956 to 1961 (age 35 to 40 years) varied considerably among plots, reducing volume by 35 to 113 m3/ha (34%-84%), and resulting in a wide range of post-outbreak plot densities. Plots were grouped into three post-budworm outbreak (1965, age 45 years) basal area classes, of ≤ 20 m2/ha, 21 to 27 m2/ha, and ≥ 28 m2/ha, to examine stand recovery. Recovery of volume up to age 60 years ranged from 72 to 132 m3/ha, in the lowest to highest basal area classes, respectively. From age 60 to 75 years, five plots declined in volume due to the onset of stand break-up and four plots increased in volume. By age 60 years, survivor growth was greatest in the high basal area plots, ranging from 6.2 to 9.0 m3/ha/yr in seven plots, versus 2.6 to 3.2 m3/ha/yr in two low basal area plots. From age 60 to 75 years, survivor growth averaged only 2.8 to 5.2 m3/ha/yr, and the stand exhibited major decline, with 63%, 74%, and 78% mortality of fir ≤ 15 cm DBH in the low to high basal area plots, respectively. Budworm-caused "thinning" in the 1950s largely determined subsequent stand development and the rate of stand break-up 25 to 35 years later. The timing and rate of natural stand decline was strongly influenced by post-outbreak stand density. Key words: budworm-caused mortality, stand structure, stand development, growth, mortality, stand density

Sapwood/Heartwood Width Relationships with Tree Age in Balsam Fir

IAWA Journal ◽  
1991 ◽  
Vol 12 (1) ◽  
pp. 95-99 ◽  
Author(s):  
G. Hazenberg ◽  
K. C. Yang
Keyword(s):  
Abies Balsamea ◽  
Basal Area ◽  
Ring Expansion ◽  
Balsam Fir ◽  
Tree Age ◽  
Thunder Bay ◽  
Wide Range ◽  
The Cost ◽  
The University ◽  
Response Variables

On the basis of five response variables, the sapwood/heartwood relationships with tree age were studied in balsam fir [Abies balsamea (L.) Mill.] trees. One hundred and one samples, from a wide range of stand densities, were collected from the university forest near Thunder Bay, Ontario. The age at breast height ranged from 4 to 85 years. The five response variables measured were the number of sapwood and heartwood rings, sapwood and heartwood width and sapwood basal area. First and second degree polynomials in tree age were fitted for the five response variables and the best fit for each, based on the significance of the regression coefficients, was selected. The number of heartwood rings expanded quite rapidly to 0.81 ring per year, at the cost of sapwood ring expansion which averaged 0.19 ring per year.

scholarly journals On the generation of internal waves by river plumes in subcritical initial conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. Mendes ◽  
J. C. B. da Silva ◽  
J. M. Magalhaes ◽  
B. St-Denis ◽  
D. Bourgault ◽  
...  
Keyword(s):  
Numerical Modeling ◽  
Internal Waves ◽  
Coastal Waters ◽  
Initial Conditions ◽  
Spatial Scales ◽  
River Plumes ◽  
Wide Range ◽  
Near Shore ◽  
Generation Mechanisms ◽  
Douro River

AbstractInternal waves (IWs) in the ocean span across a wide range of time and spatial scales and are now acknowledged as important sources of turbulence and mixing, with the largest observations having 200 m in amplitude and vertical velocities close to 0.5 m s−1. Their origin is mostly tidal, but an increasing number of non-tidal generation mechanisms have also been observed. For instance, river plumes provide horizontally propagating density fronts, which were observed to generate IWs when transitioning from supercritical to subcritical flow. In this study, satellite imagery and autonomous underwater measurements are combined with numerical modeling to investigate IW generation from an initial subcritical density front originating at the Douro River plume (western Iberian coast). These unprecedented results may have important implications in near-shore dynamics since that suggest that rivers of moderate flow may play an important role in IW generation between fresh riverine and coastal waters.

scholarly journals Deriving Tree Size Distributions of Tropical Forests from Lidar

2021 ◽  
Vol 13 (1) ◽  
pp. 131
Author(s):  
Franziska Taubert ◽  
Rico Fischer ◽  
Nikolai Knapp ◽  
Andreas Huth
Keyword(s):  
Size Distribution ◽  
Spatial Scales ◽  
Basal Area ◽  
Tree Height ◽  
Tree Size ◽  
Diameter Distribution ◽  
Forest Inventories ◽  
Allometric Relations ◽  
Lidar Measurements ◽  
Derived Data

Remote sensing is an important tool to monitor forests to rapidly detect changes due to global change and other threats. Here, we present a novel methodology to infer the tree size distribution from light detection and ranging (lidar) measurements. Our approach is based on a theoretical leaf–tree matrix derived from allometric relations of trees. Using the leaf–tree matrix, we compute the tree size distribution that fit to the observed leaf area density profile via lidar. To validate our approach, we analyzed the stem diameter distribution of a tropical forest in Panama and compared lidar-derived data with data from forest inventories at different spatial scales (0.04 ha to 50 ha). Our estimates had a high accuracy at scales above 1 ha (1 ha: root mean square error (RMSE) 67.6 trees ha−1/normalized RMSE 18.8%/R² 0.76; 50 ha: 22.8 trees ha−1/6.2%/0.89). Estimates for smaller scales (1-ha to 0.04-ha) were reliably for forests with low height, dense canopy or low tree height heterogeneity. Estimates for the basal area were accurate at the 1-ha scale (RMSE 4.7 tree ha−1, bias 0.8 m² ha−1) but less accurate at smaller scales. Our methodology, further tested at additional sites, provides a useful approach to determine the tree size distribution of forests by integrating information on tree allometries.

scholarly journals The Winter Habitat Selection of Red Deer (Cervus elaphus) Based on a Multi-Scale Model

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2454
Author(s):  
Yue Sun ◽  
Yanze Yu ◽  
Jinhao Guo ◽  
Minghai Zhang
Keyword(s):  
Habitat Selection ◽  
Environmental Factors ◽  
Cervus Elaphus ◽  
Red Deer ◽  
Scale Model ◽  
Winter Habitat ◽  
Multi Scale ◽  
Optimal Scale ◽  
Scale Models ◽  
Selection Of

Single-scale frameworks are often used to analyze the habitat selections of species. Research on habitat selection can be significantly improved using multi-scale models that enable greater in-depth analyses of the scale dependence between species and specific environmental factors. In this study, the winter habitat selection of red deer in the Gogostaihanwula Nature Reserve, Inner Mongolia, was studied using a multi-scale model. Each selected covariate was included in multi-scale models at their “characteristic scale”, and we used an all subsets approach and model selection framework to assess habitat selection. The results showed that: (1) Univariate logistic regression analysis showed that the response scale of red deer to environmental factors was different among different covariate. The optimal scale of the single covariate was 800–3200 m, slope (SLP), altitude (ELE), and ratio of deciduous broad-leaved forests were 800 m in large scale, except that the farmland ratio was 200 m in fine scale. The optimal scale of road density and grassland ratio is both 1600 m, and the optimal scale of net forest production capacity is 3200 m; (2) distance to forest edges, distance to cement roads, distance to villages, altitude, distance to all road, and slope of the region were the most important factors affecting winter habitat selection. The outcomes of this study indicate that future studies on the effectiveness of habitat selections will benefit from multi-scale models. In addition to increasing interpretive and predictive capabilities, multi-scale habitat selection models enhance our understanding of how species respond to their environments and contribute to the formulation of effective conservation and management strategies for ungulata.

scholarly journals Quantifying Understory Complexity in Unmanaged Forests Using TLS and Identifying Some of Its Major Drivers

2021 ◽  
Vol 13 (8) ◽  
pp. 1513
Author(s):  
Dominik Seidel ◽  
Peter Annighöfer ◽  
Christian Ammer ◽  
Martin Ehbrecht ◽  
Katharina Willim ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Structural Equation Models ◽  
Light Availability ◽  
Structural Complexity ◽  
Basal Area ◽  
Ecosystem Functions ◽  
Canopy Openness ◽  
Seasonal Precipitation ◽  
Wide Range ◽  
Precipitation And Temperature

The structural complexity of the understory layer of forests or shrub layer vegetation in open shrublands affects many ecosystem functions and services provided by these ecosystems. We investigated how the basal area of the overstory layer, annual and seasonal precipitation, annual mean temperature, as well as light availability affect the structural complexity of the understory layer along a gradient from closed forests to open shrubland with only scattered trees. Using terrestrial laser scanning data and the understory complexity index (UCI), we measured the structural complexity of sites across a wide range of precipitation and temperature, also covering a gradient in light availability and basal area. We found significant relationships between the UCI and tree basal area as well as canopy openness. Structural equation models (SEMs) confirmed significant direct effects of seasonal precipitation on the UCI without mediation through basal area or canopy openness. However, annual precipitation and temperature effects on the UCI are mediated through canopy openness and basal area, respectively. Understory complexity is, despite clear dependencies on the available light and overall stand density, significantly and directly driven by climatic parameters, particularly the amount of precipitation during the driest month.

Influence of Well Pad Activity on Winter Habitat Selection Patterns of Mule Deer

2009 ◽  
Vol 73 (7) ◽  
pp. 1052-1061 ◽  
Author(s):  
Hall Sawyer ◽  
Matthew J. Kauffman ◽  
Ryan M. Nielson
Keyword(s):  
Habitat Selection ◽  
Mule Deer ◽  
Winter Habitat
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