Average Kernel Density Research Articles

Factors controlling distribution of mountainous gullies at the regional scale: An example of the Yuanmou dry-hot valley (SW China)

The primary factors controlling regional gully distribution in mountainous areas are poorly understood. To investigate the spatial characteristics and controlling factors of mountainous gullies at the regional scale, kernel density (KD) estimation, semivariogram, and Geodetector methods were used based on 11 environmental factors of gullies in the Yuanmou dry-hot valley. The results show that (a) gullies are widely but unevenly distributed in the valley, with an average KD of 1.155 km/km2, and gully distribution displays spatial autocorrelation with environmental factors over diverse scales; (b) relief amplitude (Ra), landform type, and slope are the primary factors controlling gully distribution, and land use type, precipitation, and elevation are also important factors; and (c) a high risk of gully erosion occurs in areas with an elevation of more than 1437 m, slope greater than 15°, and Ra greater than 173 m, with grassland vegetation or luvisols and cambisols soil types. These results will not only help to understand the spatial pattern and formation mechanism of gullies at the macroscopic scale but also provide a scientific reference for regional gully management.

Resource Selection by Recolonizing American Black Bears

ABSTRACTAmerican black bears (Ursus americanus) were extirpated from Oklahoma, USA, in the early twentieth century but have since recolonized eastern portions of the state after immigrating from Arkansas, where they were successfully translocated. Within the last 2 decades, a population of black bears was detected in the Oklahoma Ozark region, prompting studies to determine population size, growth rate, and genetic makeup. To understand how black bears were recolonizing the human‐dominated landscape, we investigated resource selection at 2 scales. Between 2011 and 2016, we collected global positioning system collar spatial data for 10 males and 13 females. We calculated average kernel density home ranges on a seasonal scale for all collared bears. We used generalized linear mixed models to calculate resource selection functions at the study area, defined by locations of all radio‐collared black bears (second order) and the scale of individual black bear home ranges (third order). Resource selection did not differ significantly by sex. Black bears across seasons and scales selected riparian forest and moist oak (Quercus spp.) forest land cover types and mostly selected against indicators of human activity (e.g., pasture‐prairie, anthropogenic land cover types, roads, and areas of high human population density). Black bears also selected areas with rugged terrain at high elevations, although not consistently across seasons and scales. Black bear recolonization appeared to be negatively affected by areas and features characterized as human‐altered. Further expansion of the range of black bears may be limited by anthropogenic disturbance in the region. © 2021 The Wildlife Society.

Spatial differentiation of gully clusters based on the regional scale: an example from northeastern China.

Gully erosion represents a serious environmental threat around the world, but their spatial distribution law are unclear at the regional scale. To quantitatively characterize the spatial distribution model of gullies and determine the regularity of regional differentiation, this paper used spatial analyst and statistics method to study the spatial distribution of gullies in 34 sample areas of northeastern China based on interpretations of high-resolution remote sensing images. The results showed that the kernel density could quantitatively describe the continuous spatial clustering of gullies. Gullies in northeastern China had the characteristics of a spatially unbalanced distribution at the scale of the sample area. The average kernel density of the 34 sample areas (Moran’s I was 0.43, P¡0.01P < 0.01) also indicated clustering distribution at the regional scale. The horizontal clustering characteristics of gullies exhibited an azonal distribution of being low values in the middle plain and high values on the three mountainous areas. The average kernel density in the southeastern part of the study area was highest (maximum value of 2.38). In the vertical direction, gullies were relatively undeveloped in low- and high-altitude areas, while middle-altitude areas were beneficial to the development of gullies. The effect of height differences on gully development was more significant than altitude. As the height difference increased, gullies tended to be more clustered, which can be expressed by a power function. The results of this study will not only help to understand the regional differentiation characteristics of gullies but will also provide a scientific reference for the study of spatial distribution of gullies in future.

Primary environmental factors controlling gully distribution at the local and regional scale: An example from Northeastern China

Gully erosion is the main cause of global land degradation. The factors controlling gully erosion at watershed scale have been extensively studied, but the spatial pattern of gullies and their primary environmental factors are unclear. In order to explore the primary factors at the regional scale of over thousands of square kilometers, 34 sample areas were selected in northeastern China and 10 environmental factors were proposed. Based on gully interpretations from high-resolution Google Earth images and spatial analysis, kernel density estimation (with polyline features), and correlation analysis, the results show that the maximum kernel density (KD) of the 34 sample areas ranged from 0.11 to 87.16, and there were significant positive correlations between the average KD and the maximum value and standard deviation. At the regional scale, topography (relief amplitude, slope, surface roughness, surface incision, and elevation with correlation coefficients (ρ) of 0.60, 0.59, 0.57, 0.48, and 0.41 respectively) was the primary environmental factor, with a significant positive correlation with KD. The correlation coefficients of the normalized difference vegetation index (NDVI) (ρ = 0.32), annual precipitation (ρ = 0.19), and soil (silt, sand, and clay content with ρ of 0.139, −0.117, and 0.085, respectively) decreased successively with the KD. At sample area scale, there were six areas with weak correlations between environmental factors and KD, 20 areas with topographic factors, six areas with annual precipitation, and two areas with NDVI as the primary factor. The correlation between soil texture and KD was low. There were different positive or negative correlations between the environmental factors and KD. The spatial distribution of gullies in northeastern China is heterogeneous, and the primary environmental factors were diverse. This study will help to understand the spatial pattern and formation mechanism of gullies at large scale.

Effect of spatial scale on gully distribution in northeastern China

Gully erosion is one of the world’s major environmental problems, and it is also an important cause of land degradation. To reveal how gully distribution changes with spatial scale and the optimal scale for their evaluation, gullies in northeastern China were visually interpreted via high-resolution imagery, and the methods of geo-spatial statistics and kernel density estimation were used to quantitatively evaluate the distribution of gully clusters in 27 sampling areas. The results show that changes in scale always led to changes in the average value and standard deviation of the kernel density, whose trend was the same for average kernel density and standard deviation. The spatial distribution of gullies was characterized by heterogeneity; the average kernel density undergoes complex change with the scale, which varied drastically in the low-value portion of the scale range but was relatively stable in its high-value portion. For 70% of the sample areas, scale was significantly correlated with average kernel density and its standard deviation with high or medium correlation, for which the correlation coefficient of over 2/3 of the sample areas is positive. The average kernel density of each sample area varied with the scale used. These relationships were simulated with the linear, logarithmic, power, S, and exponential function models. According to the relationship between kernel density and scale, the maximum value or inflection point was then used to evaluate the optimal scale (i.e., proposed area) of the gully distribution. The optimal scale of different regions also differed among them, being closely related to the statistical characteristics of gully kernel density (correlation coefficients with standard deviation, average, and coefficient of variation were 0.60, 0.47, and 0.38, respectively).

Impact of road transportation development on habitat quality in economically developed areas: A case study of Jiangsu Province, China

AbstractThe excessive expansion of road transportation often has an impact on the quality of regional habitats. This paper attempts to assess the impact of road transportation on regional habitat quality in economically developed areas. A kernel density analysis was used to characterise the road transportation development in Jiangsu Province from 2000 to 2015. An Integrated Valuation of Ecosystem Services and Trade‐offs (InVEST) habitat quality model was applied to assess changes in habitat quality. Furthermore, a fixed‐effect regression model was utilised to examine the impact of road transportation development in Jiangsu Province on habitat quality. The analysis indicates that the average kernel density of road transportation in the province increased from 0.109 to 0.551 km/km2 while the habitat quality decreased from 0.51 to 0.48. The development of road transportation in Jiangsu Province has had a serious negative impact on the quality of the habitat. For every 1‐ha increase in land area for road use, the habitat quality index will decrease by 0.066; for every 1 km/km2 increase in road transportation kernel density, the habitat quality index will decline by 0.121.

Home Range Size and Distance Traveled from Hibernacula in Northern Pinesnakes in the New Jersey Pine Barrens

We studied home range size and maximum dispersal distance from hibernacula in Northern Pinesnakes (Pituophis m. melanoleucus) at a 1418-ha preserve in Cumberland County, New Jersey, USA, between 1993 and 2003. We discovered 22 different winter hibernacula that were used by 39 Northern Pinesnakes. Of the 10 snakes monitored in hibernacula for 3–5 yr, shifting was observed by 8 individuals, and 2 females showed hibernacula philopatry for five consecutive years. The average minimum convex polygon home range of 14 radio-tracked Northern Pinesnakes was 105.51 ha (located 30–108 times/snake), whereas the average kernel density estimator home range was 50% isopleth = 38.99 ha and 90% isopleth = 133.15 ha. There were no differences in home range as a function of sex, but the number of years snakes were radio-tracked affected home range size. An adult male had the largest home range of 258 ha. The average distance traveled by radio-tracked Northern Pinesnakes from their winter hibernacula was 1321.05 m, with a maximum distance of 2146.91 m. Of all snakes followed, 27.3% (n = 3) traveled <1000 m, 18.2% (n = 2) traveled 1000–1100 m, 18.2% (n = 2) traveled 1100–1200 m, and 36.4% (n = 4) traveled >1200 m. The average number of hibernacula available per home range was 3.2. Snakes that were monitored for ≥2 yr had larger home ranges than snakes that were only radio-tracked for 1 yr. Thus, radio-tracking several adult snakes over a 3–5-yr period is the most effective method to determine home ranges, locate hibernacula sites of meta-populations, and reveal an understanding of their ecology, behavior, and conservation requirements.

Responses to Selection for Endosperm Hardness and Associated Changes in Agronomic Traits after Four Cycles of Recurrent Selection in Maize

Increased endosperm hardness of grain in maize (Zea mays L.) is desirable for dry milling, storage, and expert purposes. This study was conducted to evaluate changes in endosperm hardness resulting from four cycles of visual recurrent selection for increased hardness in two dent corn synthetics representative of U.S. Corn Belt germplasm, and to determine associated responses in other agronomic traits. Testcrosses of random S1 lines from each cycle of selection were grown in replicated trials at four locations in each of 2 yr for determination of grain hardness and evaluation of agronomic traits. Evaluation of grain hardness was through measurement of average kernel density and the Stenvert hardness test. Significant increase in endosperm hardness was limited to the first cycle of selection in both synthetics. No significant changes corresponding to altered endosperm hardness were detected for any of five agronomic traits measured in testcross hybrids from S1 lines representing each cycle of selection. Estimated genetic correlation coefficients indicated a negative, nonsignificant trend between grain yield and grain hardness. These results indicate increases in grain hardness can be achieved through selection in dent corn germplasm common to the U.S. Corn Belt. However, continual progress in recurrent selection may require quantification of hardness by measurements such as kernel density and the Stenvert hardness test, rather than simple visual judgment of relative hardness. Genetic correlation coefficients indicate selection progress can be simultaneously made for both grain yield and grain quality.