Gab-Sue Jang

Modelling the spatial distribution of wildlife animals using presence and absence data

This study was conducted to analyze the habitat preference of six major mammals for various environmental factors based on 100 random points within a mountain area in South Korea. In-situ presence and absence data for the mammals were surveyed and collected, and twelve explanatory variables related to topography, water, greenness, and anthropogenic influence were applied to create a habitat distribution model. The best combination of variables was determined using Moran’s I coefficients and Akaike criteria information, and applied to estimate the habitat preference for each species using GRASP v.3.0. The predictive map showed that wildlife animals in this study were mainly categorized into two groups: Group I (Korean squirrel, Sciurus vulgaris, mole, Talpa micrura and water deer, Hydropotes inermis), showed equal preference for all mountainous areas; Group II (weasel, Mustela sibirica, leopard cat, Felis bengalensis and raccoon dog, Nyctereutes procyonoides) showed different preferences in a mountain.

Estimating Water Quality with Airborne and Ground-Based Hyperspectral Sensing

Remotely sensed estimates of water quality parameters would facilitate efforts in spatial and temporal monitoring. In this study we collected hyperspectral water reflectance data with airborne and ground-based sensing systems for multiple arms of Mark Twain Lake, a large manmade reservoir in northeast Missouri. Water samples were also collected and analyzed in the laboratory for chlorophyll, nutrients, and turbidity. Wavelength-selection (i.e., stepwise multiple regression) methods and previously reported indices were used to develop relationships between spectral and water quality data. Within the single measurement date of this study, all measured water quality parameters were strongly related (R2 > 0.6) to reflectance data from the ground system. Relationships between water quality parameters and airborne reflectance data were generally somewhat lower, but still with R2 > 0.6. Previously developed narrow-band reflectance indices also worked well to estimate chlorophyll concentration. Wide-band, multispectral reflectance, simulating Landsat data, was strongly related only to turbidity and those other parameters (e.g., phosphorus) highly correlated to turbidity in this dataset. Thus, hyperspectral sensing, coupled with calibration sampling, can be used to estimate lake water quality differences, and appears to have advantages over multispectral sensing in this application.

Long-Term Agroecosystem Research in the Central Mississippi River Basin: Hyperspectral Remote Sensing of Reservoir Water Quality

In situ methods for estimating water quality parameters would facilitate efforts in spatial and temporal monitoring, and optical reflectance sensing has shown potential in this regard, particularly for chlorophyll, suspended sediment, and turbidity. The objective of this research was to develop and evaluate relationships between hyperspectral remote sensing and lake water quality parameters-chlorophyll, turbidity, and N and P species. Proximal hyperspectral water reflectance data were obtained on seven sampling dates for multiple arms of Mark Twain Lake, a large man-made reservoir in northeastern Missouri. Aerial hyperspectral data were also obtained on two dates. Water samples were collected and analyzed in the laboratory for chlorophyll, nutrients, and turbidity. Previously reported reflectance indices and full-spectrum (i.e., partial least squares regression) methods were used to develop relationships between spectral and water quality data. With the exception of dissolved NH, all measured water quality parameters were strongly related ( ≥ 0.7) to proximal reflectance across all measurement dates. Aerial hyperspectral sensing was somewhat less accurate than proximal sensing for the two measurement dates where both were obtained. Although full-spectrum calibrations were more accurate for chlorophyll and turbidity than results from previously reported models, those previous models performed better for an independent test set. Because extrapolation of estimation models to dates other than those used to calibrate the model greatly increased estimation error for some parameters, collection of calibration samples at each sensing date would be required for the most accurate remote sensing estimates of water quality.

Dynamic influence of patch size on occupancy of woodland birds

Throughout the long history of landscape ecology, scientists have devoted substantial efforts to understand potential forest patch size and isolation effects on the abundance and diversity of woodland species. Which bird species flourish or perish as a response to forest fragmentation may compose fundamental information for the reserve design and landscape management in a region. Here, we designed a bird survey of the urban forest areas in Dangjin city located on South Koreas west coast to test (1) if bird species richness follows the pattern predicted by species-area relationship and (2) if there is seasonal variation in the pattern. As expected, patch area was the most significant variable explaining patch occupancy of resident and summering woodland birds in every season. Our data about the number of dominant vegetation suggest that larger areas contain greater habitat heterogeneity and more diverse niches. About half of the resident species did not appear to be area-sensitive and were categorized as edge species. On the other hand, many summering species showed strong area-sensitivity, potentially avoiding small patches that are almost entirely edge habitats in urban landscape. Our results suggest that lots of contemporary forest edges, fragmented by agricultural or urban development, do not any more function for feeding or nesting places for those species.

Estimating the habitat potential of inland forest patches for birds using a species–area curve model

Abstract Estimating the habitat potential of inland forest patches for birds requires the modeling of species–area relationships, or relationships between habitat size and numbers of bird species in each patch. The accurate estimation of species–area relationships significantly reduces the effort required to recognize the number of species living in each patch. The objective of this study was to estimate the relationship between forest patch size and bird species diversity in Dangjin County, in northwest South Korea, based on the sizes of inland forest patches. KOMPSAT-2 images were obtained and ortho-rectified to construct a map of the target forest patches. The numbers of birds per patch were surveyed four times: August 2008, September 2008, February 2009 and May 2009. Regression models were derived to explain the relationships between the numbers of bird species and patch size. A model that was derived using data from all four observation periods had the highest coefficient of determination (R 2). According to these models, the numbers of bird species at first increased linearly with increasing patch size; however, the curve then plateaued. Our model including observations from four seasons will be useful for estimating the numbers of bird species in other inland forest patches in South Korea.

Detection of superior genotype of fatty acid synthase in Korean native cattle by an environment-adjusted statistical model

Objective This study examines the genetic factors influencing the phenotypes (four economic traits:oleic acid [C18:1], monounsaturated fatty acids, carcass weight, and marbling score) of Hanwoo. Methods To enhance the accuracy of the genetic analysis, the study proposes a new statistical model that excludes environmental factors. A statistically adjusted, analysis of covariance model of environmental and genetic factors was developed, and estimated environmental effects (covariate effects of age and effects of calving farms) were excluded from the model. Results The accuracy was compared before and after adjustment. The accuracy of the best single nucleotide polymorphism (SNP) in C18:1 increased from 60.16% to 74.26%, and that of the two-factor interaction increased from 58.69% to 87.19%. Also, superior SNPs and SNP interactions were identified using the multifactor dimensionality reduction method in Table 1 to 4. Finally, high- and low-risk genotypes were compared based on their mean scores for each trait. Conclusion The proposed method significantly improved the analysis accuracy and identified superior gene-gene interactions and genotypes for each of the four economic traits of Hanwoo.

Considering threats to population viability of the endangered Korean long-tailed goral (Naemorhedus caudatus) using VORTEX

ABSTRACT Population viability analysis (PVA) has frequently been used in conservation biology to predict extinction rates for threatened or endangered species. In this study, we used VORTEX to model Korean long-tailed goral (Naemorhedus caudatus) using previously collected ecological data. We focused on modelling population extinction, mean population size and heterozygosity. The minimum viable population size was found to be at least 50 gorals for 100 years, regardless of carrying capacity. However, populations with fewer than 50 gorals could not remain successful in the model. Inbreeding depression, catastrophes and supplementation also affected patterns of population extinction, mean population size and heterozygosity. Supplementation with new individuals had the strongest effect on extinction, mean population size and heterozygosity, followed by initial population size, inbreeding, catastrophes and carrying capacity. These results suggest that a supplementation by extra goral individuals from goral proliferation facilities would be the most helpful means for the restoration programme. More Korean goral-specific information regarding demographic and habitat parameters is needed for further PVA of the species.