Changes in spatial patterns of sika deer distribution and herbivory of planted seedlings: a comparison before and after deer population control by culling

2015 ◽  
Vol 21 (2) ◽  
pp. 84-91 ◽  
Author(s):  
Tsutomu Enoki ◽  
Tsuneaki Yabe ◽  
Toru Koizumi
Keyword(s):  
Spatial Patterns ◽  
Sika Deer ◽  
Population Control ◽  
Deer Population ◽  
Before And After

Sika Deer Population Irruptions and Their Management on Hokkaido Island, Japan

Sika Deer ◽  
2008 ◽  
pp. 405-419 ◽  
Author(s):  
Hiroyuki Uno ◽  
Koichi Kaji ◽  
Katsumi Tamada
Keyword(s):  
Sika Deer ◽  
Deer Population ◽  
Hokkaido Island

scholarly journals Mitigation of bark stripping on spruce: the need for red deer population control

2020 ◽  
Author(s):  
Romain Candaele ◽  
Philippe Lejeune ◽  
Alain Licoppe ◽  
Céline Malengreaux ◽  
Yves Brostaux ◽  
...  
Keyword(s):  
Red Deer ◽  
Population Control ◽  
Bark Stripping ◽  
Deer Population

scholarly journals Spatial distribution of pedestrian-motor vehicle collisions before and after pedestrian countdown signal installation in Toronto, Canada

2017 ◽  
Vol 25 (2) ◽  
pp. 110-115 ◽  
Author(s):  
Linda Rothman ◽  
Marie-Soleil Cloutier ◽  
Alison K Macpherson ◽  
Sarah A Richmond ◽  
Andrew William Howard
Keyword(s):  
Spatial Distribution ◽  
Spatial Patterns ◽  
Spatial Data ◽  
Motor Vehicle ◽  
Spatial Data Analysis ◽  
Motor Vehicle Collisions ◽  
Vehicle Collisions ◽  
Point Patterns ◽  
Kernel Density Estimates ◽  
Before And After

BackgroundPedestrian countdown signals (PCS) have been installed in many cities over the last 15 years. Few studies have evaluated the effectiveness of PCS on pedestrian motor vehicle collisions (PMVC). This exploratory study compared the spatial patterns of collisions pre and post PCS installation at PCS intersections and intersections or roadways without PCS in Toronto, and examined differences by age.MethodsPCS were installed at the majority of Toronto intersections from 2007 to 2009. Spatial patterns were compared between 4 years of police-reported PMVC prior to PCS installation to 4 years post installation at 1864 intersections. The spatial distribution of PMVC was estimated using kernel density estimates and simple point patterns examined changes in spatial patterns overall and stratified by age. Areas of higher or lower point density pre to post installation were identified.ResultsThere were 14 911 PMVC included in the analysis. There was an overall reduction in PMVC post PCS installation at both PCS locations and non-PCS locations, with a greater reduction at non-PCS locations (22% vs 1%). There was an increase in PMVC involving adults (5%) and older adults (9%) at PCS locations after installation, with increased adult PMVC concentrated downtown, and older adult increases occurring throughout the city following no spatial pattern. There was a reduction in children’s PMVC at both PCS and non-PCS locations, with greater reductions at non-PCS locations (35% vs 48%).ConclusionsResults suggest that the effects of PCS on PMVC may vary by age and location, illustrating the usefulness of exploratory spatial data analysis approaches in road safety. The age and location effects need to be understood in order to consistently improve pedestrian mobility and safety using PCS.

Impact of puma predation on the decline and recovery of a mule deer population in southeastern Idaho

2006 ◽  
Vol 84 (11) ◽  
pp. 1555-1565 ◽  
Author(s):  
J.W. Laundré ◽  
L. Hernández ◽  
S.G. Clark
Keyword(s):  
Population Change ◽  
Puma Concolor ◽  
Mule Deer ◽  
Odocoileus Hemionus ◽  
Winter Mortality ◽  
Deer Population ◽  
Before And After ◽  
Proximate Factor ◽  
A Minor ◽  
The Impact

We modeled the impact of puma ( Puma concolor (L., 1771)) predation on the decline and recovery of mule deer ( Odocoileus hemionus (Rafinesque, 1817)) in southern Idaho based on estimates of puma numbers, predation rates of pumas, and reproductive variables of deer. Deer populations peaked in 1992–1993, then declined more than 55% and remained low for the next 11 years. Puma numbers peaked 4–6 years after deer populations peaked but then declined to original levels. Estimated puma predation on the deer population before and after the decline was 2.2%–3.3% and 3.1%–5.8%, respectively. At high puma densities (>3 pumas/100 km2), predation by pumas delayed deer recovery by 2–3 years. Percent winter mortality of fawns (r2 = 0.62, P < 0.001) and adult female deer (r2 = 0.68, P < 0.001) correlated positively with December–January snowfall. Incorporation of winter snowfall amounts in the model produced a pattern of deer population change matching estimated changes based on field survey data. We conclude that pumas probably were a minor factor in the decline of the deer population in our area and did not suppress deer recovery. We propose that winter snowfall was the primary ultimate and proximate factor in the deer decline and suppression of their recovery.

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