Spatio-temporal distribution of coastal brown bears and visitors in Katmai National Park, Alaska

2021 ◽  
Author(s):  
Kelsey Griffin
2004 ◽  
Vol 118 (2) ◽  
pp. 247 ◽  
Author(s):  
Tom S. Smith ◽  
Steven T. Partridge ◽  
John W. Schoen

We describe several encounters between Brown Bears (Ursus arctos) and Gray Wolves (Canis lupus) that were observed at Katmai National Park and Preserve in southwest Alaska. Katmai Brown Bears and Gray Wolves were observed interacting in a variety of behavioral modes that ranged from agonistic to tolerant. These observations provide additional insight regarding the behavioral plasticity associated with bear-wolf interactions.


Oryx ◽  
2021 ◽  
pp. 1-9
Author(s):  
Herbert H.T. Prins ◽  
Yorick Liefting ◽  
Joost F. de Jong

Abstract In areas where farmland borders protected areas, wildlife may be attracted to crops and cause substantial financial damage for farmers. Elephants, in particular, can destroy a year's harvest in a single night, and can also cause damage to buildings and other farm structures. Few studies have examined whether damage caused by wild elephants increases social inequalities in farmer communities. We interviewed settlement leaders and subsistence rice farmers living in the buffer zone of Bardiya National Park, Nepal, to examine (1) the variation and spatial distribution of wealth within the farmer community, (2) the severity and spatio-temporal distribution of damage inflicted by Asian elephants Elephas maximus, and (3) the willingness to insure against such damage. We investigated whether particular societal strata are disproportionally affected by negative interactions with elephants. We found that farmers near the boundary between agricultural and wilderness areas were significantly poorer and had smaller landholdings than those further into the cultivated lands. Concomitantly, damage to crops and houses was more frequent nearer the wilderness–agriculture boundary than further away from it. Hence, in the buffer zone of Bardiya National Park, farmers near the wilderness–cultivation boundary, with small landholdings, had a relatively higher cost of elephant damage, yet were less willing to pay for an insurance scheme. We infer that in areas where both social inequality and damage caused by wildlife are spatially structured, conservation success may cause economic hardship for the local community, particularly for the poorer class. We discuss causes of the current lack of communal mitigation measures against the damage caused by elephants in the Park, and potential solutions.


2013 ◽  
Vol 38 (7) ◽  
pp. 1286-1294 ◽  
Author(s):  
Zong-Xin LI ◽  
Yuan-Quan CHEN ◽  
Qing-Cheng WANG ◽  
Kai-Chang LIU ◽  
Wang-Sheng GAO ◽  
...  

2019 ◽  
Author(s):  
Rudra Mohan Pradhan ◽  
◽  
Karrie A. Weber ◽  
Karrie A. Weber ◽  
Daniel Snow ◽  
...  

2021 ◽  
Vol 13 (5) ◽  
pp. 892
Author(s):  
Xiaomei Li ◽  
Pinhua Xie ◽  
Ang Li ◽  
Jin Xu ◽  
Zhaokun Hu ◽  
...  

This paper studied the method for converting the aerosol extinction to the mass concentration of particulate matter (PM) and obtained the spatio-temporal distribution and transportation of aerosol, nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations in Dalian (38.85°N, 121.36°E), Qingdao (36.35°N, 120.69°E), and Shanghai (31.60°N, 121.80°E) from 2019 to 2020. The PM2.5 measured by the in situ instrument and the PM2.5 simulated by the conversion formula showed a good correlation. The correlation coefficients R were 0.93 (Dalian), 0.90 (Qingdao), and 0.88 (Shanghai). A regular seasonality of the three trace gases is found, but not for aerosols. Considerable amplitudes in the weekly cycles were determined for NO2 and aerosols, but not for SO2 and HCHO. The aerosol profiles were nearly Gaussian, and the shapes of the trace gas profiles were nearly exponential, except for SO2 in Shanghai and HCHO in Qingdao. PM2.5 presented the largest transport flux, followed by NO2 and SO2. The main transport flux was the output flux from inland to sea in spring and winter. The MAX-DOAS and the Copernicus Atmosphere Monitoring Service (CAMS) models’ results were compared. The overestimation of NO2 and SO2 by CAMS is due to its overestimation of near-surface gas volume mixing ratios.


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