Spatiotemporal distribution of barley and wheat plants naturally infected with bacterial black node in fields in western Japan

2017 ◽  
Vol 84 (1) ◽  
pp. 35-43 ◽  
Author(s):  
Akira Kawaguchi ◽  
Rikuto Yoshioka ◽  
Mitsutaka Mori ◽  
Fumihiro Nishimura ◽  
Kazutoshi Kawata ◽  
...  
Keyword(s):  
Spatiotemporal Distribution ◽  
Western Japan ◽  
Black Node

Random isn't real: How the patchy distribution of ecological rewards may generate “incentive hope”

2019 ◽  
Vol 42 ◽  
Author(s):  
Laurel Symes ◽  
Thalia Wheatley
Keyword(s):  
Natural Environment ◽  
Random Distribution ◽  
Spatiotemporal Distribution ◽  
Patchy Distribution ◽  
Distribution Of Resources

AbstractAnselme & Güntürkün generate exciting new insights by integrating two disparate fields to explain why uncertain rewards produce strong motivational effects. Their conclusions are developed in a framework that assumes a random distribution of resources, uncommon in the natural environment. We argue that, by considering a realistically clumped spatiotemporal distribution of resources, their conclusions will be stronger and more complete.

Spatiotemporal distribution of foraging in a marine predator: behavioural drivers of hotspot formation

2020 ◽  
Vol 635 ◽  
pp. 187-202
Author(s):  
T Brough ◽  
W Rayment ◽  
E Slooten ◽  
S Dawson
Keyword(s):  
Time Of Day ◽  
Spatiotemporal Distribution ◽  
Temporal Effects ◽  
Marine Predator ◽  
Marine Predators ◽  
Additive Mixed Models ◽  
Density Analysis ◽  
The Times ◽  
Passive Acoustic ◽  
Spatial Locations

Many species of marine predators display defined hotspots in their distribution, although the reasons why this happens are not well understood in some species. Understanding whether hotspots are used for certain behaviours provides insights into the importance of these areas for the predators’ ecology and population viability. In this study, we investigated the spatiotemporal distribution of foraging behaviour in Hector’s dolphin Cephalorhynchus hectori, a small, endangered species from New Zealand. Passive acoustic monitoring of foraging ‘buzzes’ was carried out at 4 hotspots and 6 lower-use, ‘reference areas’, chosen randomly based on a previous density analysis of visual sightings. The distribution of buzzes was modelled among spatial locations and on 3 temporal scales (season, time of day, tidal state) with generalised additive mixed models using 82000 h of monitoring data. Foraging rates were significantly influenced by all 3 temporal effects, with substantial variation in the importance and nature of each effect among locations. The complexity of the temporal effects on foraging is likely due to the patchy nature of prey distributions and shows how foraging is highly variable at fine scales. Foraging rates were highest at the hotspots, suggesting that feeding opportunities shape fine-scale distribution in Hector’s dolphin. Foraging can be disrupted by anthropogenic influences. Thus, information from this study can be used to manage threats to this vital behaviour in the locations and at the times where it is most prevalent.

Life cycles of the rhizocephalan Boschmaella japonica Deichmann & Høeg, 1990 (Cirripedia: Chthamalophilidae) and its host barnacle Chthamalus challengeri Hoek, 1883 (Cirripedia: Chthamalidae)

2020 ◽  
Vol 40 (6) ◽  
pp. 825-832 ◽  
Author(s):  
Miku Yabuta ◽  
Jens T Høeg ◽  
Shigeyuki Yamato ◽  
Yoichi Yusa
Keyword(s):  
Life Cycle ◽  
Brood Size ◽  
Life Cycles ◽  
The Body ◽  
Egg Volume ◽  
Size Number ◽  
Rhizocephalan Barnacles ◽  
Western Japan ◽  
Upper Intertidal ◽  
Chthamalus Challengeri

Abstract Although parasitic castration is widespread among rhizocephalan barnacles, Boschmaella japonica Deichmann & Høeg, 1990 does not completely sterilise the host barnacle Chthamalus challengeri Hoek, 1883. As little information is available on the relationships with the host in “barnacle-infesting parasitic barnacles” (family Chthamalophilidae), we studied the life cycles of both B. japonica and C. challengeri and the effects of the parasite on the host reproduction. Specimens of C. challengeri were collected from an upper intertidal shore at Shirahama, Wakayama, western Japan from April 2017 to September 2018 at 1–3 mo intervals. We recorded the body size, number of eggs, egg volume, and the presence of the parasite for each host. Moreover, settlement and growth of C. challengeri were followed in two fixed quadrats. Chthamalus challengeri brooded from February to June. The prevalence of B. japonica was high (often exceeded 10%) from April to July, and was rarely observed from September to next spring. The life cycle of the parasite matched well with that of the host. The parasite reduced the host’s brooding rate and brood size, to the extent that no hosts brooded in 2018.

scholarly journals Archaeointensity Determinations from Western Japan

1986 ◽  
Vol 38 (12) ◽  
pp. 1323-1329 ◽  
Author(s):  
H. SAKAI ◽  
K. HIROOKA
Keyword(s):  
Western Japan

Evolution of Sex Chromosome Heteromorphy in Geographic Populations of the Japanese Tago’s Brown Frog Complex

2021 ◽  
pp. 1-9
Author(s):  
Chiao Kuwana ◽  
Hiroyuki Fujita ◽  
Masataka Tagami ◽  
Takanori Matsuo ◽  
Ikuo Miura
Keyword(s):  
Sex Chromosomes ◽  
Sex Chromosome ◽  
Mitochondrial Gene ◽  
Population Level ◽  
Chromosome 7 ◽  
Geographic Population ◽  
Geographic Populations ◽  
Western Japan ◽  
Brown Frog ◽  
Eastern Japan

The sex chromosomes of most anuran amphibians are characterized by homomorphy in both sexes, and evolution to heteromorphy rarely occurs at the species or geographic population level. Here, we report sex chromosome heteromorphy in geographic populations of the Japanese Tago’s brown frog complex (2n = 26), comprising Rana sakuraii and R. tagoi. The sex chromosomes of R. sakuraii from the populations in western Japan were homomorphic in both sexes, whereas chromosome 7 from the populations in eastern Japan were heteromorphic in males. Chromosome 7 of R. tagoi, which is distributed close to R. sakuraii in eastern Japan, was highly similar in morphology to the Y chromosome of R. sakuraii. Based on this and on mitochondrial gene sequence analysis, we hypothesize that in the R. sakuraii populations from eastern Japan the XY heteromorphic sex chromosome system was established by the introduction of chromosome 7 from R. tagoi via interspecies hybridization. In contrast, chromosome 13 of R. tagoi from the 2 large islands in western Japan, Shikoku and Kyushu, showed a heteromorphic pattern of constitutive heterochromatin distribution in males, while this pattern was homomorphic in females. Our study reveals that sex chromosome heteromorphy evolved independently at the geographic lineage level in this species complex.

scholarly journals A Machine Learning Method for Predicting Vegetation Indices in China

2021 ◽  
Vol 13 (6) ◽  
pp. 1147
Author(s):  
Xiangqian Li ◽  
Wenping Yuan ◽  
Wenjie Dong
Keyword(s):  
Machine Learning ◽  
Growing Season ◽  
Crop Growth ◽  
Spatiotemporal Distribution ◽  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Severe Drought ◽  
Vegetation Growth ◽  
Extreme Gradient Boosting ◽  
Boosting Method

To forecast the terrestrial carbon cycle and monitor food security, vegetation growth must be accurately predicted; however, current process-based ecosystem and crop-growth models are limited in their effectiveness. This study developed a machine learning model using the extreme gradient boosting method to predict vegetation growth throughout the growing season in China from 2001 to 2018. The model used satellite-derived vegetation data for the first month of each growing season, CO2 concentration, and several meteorological factors as data sources for the explanatory variables. Results showed that the model could reproduce the spatiotemporal distribution of vegetation growth as represented by the satellite-derived normalized difference vegetation index (NDVI). The predictive error for the growing season NDVI was less than 5% for more than 98% of vegetated areas in China; the model represented seasonal variations in NDVI well. The coefficient of determination (R2) between the monthly observed and predicted NDVI was 0.83, and more than 69% of vegetated areas had an R2 > 0.8. The effectiveness of the model was examined for a severe drought year (2009), and results showed that the model could reproduce the spatiotemporal distribution of NDVI even under extreme conditions. This model provides an alternative method for predicting vegetation growth and has great potential for monitoring vegetation dynamics and crop growth.

scholarly journals Spatiotemporal Distribution Characteristics and Driving Forces of PM2.5 in Three Urban Agglomerations of the Yangtze River Economic Belt

2021 ◽  
Vol 18 (5) ◽  
pp. 2222
Author(s):  
Jin-Wei Yan ◽  
Fei Tao ◽  
Shuai-Qian Zhang ◽  
Shuang Lin ◽  
Tong Zhou
Keyword(s):  
Geographically Weighted Regression ◽  
Yangtze River ◽  
National Level ◽  
National Development ◽  
Urban Agglomeration ◽  
Spatiotemporal Distribution ◽  
Weighted Regression ◽  
Series Data ◽  
The Yangtze River ◽  
Urban Agglomerations

As part of one of the five major national development strategies, the Yangtze River Economic Belt (YREB), including the three national-level urban agglomerations (the Cheng-Yu urban agglomeration (CY-UA), the Yangtze River Middle-Reach urban agglomeration (YRMR-UA), and the Yangtze River Delta urban agglomeration (YRD-UA)), plays an important role in China’s urban development and economic construction. However, the rapid economic growth of the past decades has caused frequent regional air pollution incidents, as indicated by high levels of fine particulate matter (PM2.5). Therefore, a driving force factor analysis based on the PM2.5 of the whole area would provide more information. This paper focuses on the three urban agglomerations in the YREB and uses exploratory data analysis and geostatistics methods to describe the spatiotemporal distribution patterns of air quality based on long-term PM2.5 series data from 2015 to 2018. First, the main driving factor of the spatial stratified heterogeneity of PM2.5 was determined through the Geodetector model, and then the influence mechanism of the factors with strong explanatory power was extrapolated using the Multiscale Geographically Weighted Regression (MGWR) models. The results showed that the number of enterprises, social public vehicles, total precipitation, wind speed, and green coverage in the built-up area had the most significant impacts on the distribution of PM2.5. The regression by MGWR was found to be more efficient than that by traditional Geographically Weighted Regression (GWR), further showing that the main factors varied significantly among the three urban agglomerations in affecting the special and temporal features.

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