scholarly journals Spatial distribution pattern of Tarsius Lariang in lore lindu national park

2019 ◽  
Vol 13 (2) ◽  
pp. 606 ◽  
Author(s):  
Abdul Rosyid ◽  
Yanto Santosa ◽  
I Nengah Surati Jaya ◽  
M. Bismark ◽  
Agus P. Kartono
Keyword(s):  
Spatial Distribution ◽  
Distribution Pattern ◽  
Land Surface ◽  
National Park ◽  
Spatial Distribution Pattern ◽  
Systematic Sampling ◽  
Affecting Factors ◽  
Factors Affecting ◽  
Insect Abundance ◽  
Lore Lindu National Park

<p><span>Tarsius lariang (T. lariang) is an endemic species in Lore Lindu National Park (LLNP). Available information regarding T. lariang is limited to only morphological, anatomical, cytogenetic, and voices issues. Knowledge for its geospatial characteristics such as spatial preferences and spatial distribution is rare. The main objective of this study is to identify the spatial distribution pattern of T. lariang in LLNP. An additional objective is to identify the environmental factors affecting its spatial distribution patterns. Field observation for distribution pattern was done at the observation plot that were using systematic sampling with random start. Furthermore, the density estimation in each point was calculated using Triangle Count and Concentration Count method, while insect abundance was estimated using light traps sample data. Finally, spatial pattern was estimated using nearest neighbor index, while the environmental affecting factors were identified by using spatial analysis and correlation analyses. From 45 observation points, the T. lariang distribution pattern was clumped. It is also recognized that the significant factors affecting the spatial distribution were insect abundance, proximity from the commercially utilized land, and land surface temperature.</span></p><p> </p>

Relationship between spatial distribution pattern and factors affecting weight per thousand seeds of cultivated barley in Qinghai-Tibet Plateau

2018 ◽  
Vol 38 (3) ◽  
Author(s):  
王建林 WANG Jianlin ◽  
冯西博 FENG Xibo ◽  
付刚 FU Gang ◽  
侯维海 HOU Weihai ◽  
王改花 WANG Gaihua ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Distribution Pattern ◽  
Spatial Distribution Pattern ◽  
Tibet Plateau ◽  
Factors Affecting ◽  
Cultivated Barley ◽  
Qinghai Tibet Plateau

scholarly journals The intertidal gastropods (Gastropoda: Mollusca) diversity and taxa distribution in Alas Purwo National Park, East Java, Indonesia

2019 ◽  
Vol 20 (7) ◽  
Author(s):  
SUSINTOWATI SUSINTOWATI ◽  
NYOMAN PUNIAWATI ◽  
ERNY POEDJIRAHAJOE ◽  
NIKEN SATUTI NUR HANDAYANI ◽  
SUWARNO HADISUSANTO
Keyword(s):  
Spatial Distribution ◽  
Distribution Pattern ◽  
National Park ◽  
Diversity Index ◽  
Principal Component ◽  
Spatial Distribution Pattern ◽  
Intertidal Zones ◽  
Diverse Environment ◽  
Morisita Index ◽  
Diversity Profile

Abstract. Susintowati, Puniawati N, Poedjirahajoe, Handayani NSN, Hadisusanto S. 2019. The intertidal gastropods (Gastropoda: Mollusca) diversity and taxa distribution in Alas Purwo National Park, East Java, Indonesia. Biodiversitas 20: 2016-2027. Gastropods play an essential role in the ecosystem and can be used as bioindicators of environmental pollution. Understanding of their behavior, habitat, and distribution, and how these factors evolve, is crucial. This paper aimed to describe the diversity of the gastropod community and their spatial taxa distribution, based on the specimen frequency across all observed samples, in the diverse environment of Alas Purwo National Park (APNP), East Java, Indonesia. We studied eight beaches and two mangroves areas, and the study areas of the intertidal zone divided into upper, middle, and lower zones towards the sea. The purposive sampling was used to determine the locations and multi-plot quadrats for observations. The diversity of gastropods was elucidated by using the Shannon and Simpson indexes, while the Morisita index was applied for analyzing their spatial distribution pattern. However, the correspondence analysis and principal component analysis were performed using the software of PAST 3.22 for describing the diversity profile and individual rarefaction of gastropods together with environmental quality. There were three beach types: rocky, sandy, and muddy beaches were found in APNP. The highest diversity index (H’) was found on Pancur beach: H’ = 3.271, D = 0.947 of 67 species. The spatial distribution pattern of gastropods species was weakly clumped to random, with Ip: 0.165 - 0.016. Gastropods, both predators and scavengers, were distributed from the upper to lower zones. The distribution of gastropods in APNP is mostly in type B. These results expand our knowledge of gastropods diversity and distribution of Indonesia’s beach and can contribute to the future environmental assessments of biodiversity of tropical intertidal zones worldwide.

scholarly journals Spatial Distribution Pattern and Influencing Factors of Sports Tourism Resources in China

2021 ◽  
Vol 10 (7) ◽  
pp. 428
Author(s):  
Yifan Zuo ◽  
Huan Chen ◽  
Jincheng Pan ◽  
Yuqi Si ◽  
Rob Law ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Distribution Pattern ◽  
Explanatory Power ◽  
Spatial Distribution Pattern ◽  
Core Area ◽  
Border Area ◽  
Factors Affecting ◽  
Resource Endowment ◽  
Sports Tourism ◽  
Tourism Resources

Sports tourism is an emerging tourism product. In the sports and tourism industry, resource mining is the foundation that provides positive significance for theoretical support. This study takes China’s sports tourism boutique projects as the study object, exploring its spatial distribution pattern through the average nearest neighbor index, kernel density, and spatial autocorrelation. On the strength of the wuli–shili–renli system approach, the entropy value method and geographic detector probe model are used to identify the driving factors affecting the spatial distribution pattern. Findings reveal the following: (1) From 2013 to 2014, the sports tourism resources in China present a distribution pattern with the Yangtze River Delta urban agglomeration as the high-density core area and the Guizhou–Guangxi border area and the western Hubei ecological circle as the sub-density core areas. (2) From 2014 to 2018, China’s sports tourism boutique projects increased by 381, and the regional differences among various provinces tended to converge. The high-density core area remained unchanged. The sub-density cores are now the Yunqian border area of the Karst Plateau, the Qinglong border area of the Qilian Mountains, and the Jinji border area of the Taihang Mountains, shaping the distribution trends of “depending on the city, near the scenery” and “large concentration, small dispersion”. (3) The proportion of provincial sports tourism development classified as being in the coordinated stage is 61.29%. (4) The explanatory power of the factors affecting the spatial layout in descending order is natural resource endowment, sports resource endowment, transportation capacity, industrial support and guidance, market cultivation and development, people’s living standards, software and hardware services, and economic benefit effects. The explanatory power of the interaction of two different factors is higher than that of the single factor.

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