Multi-scale environmental factors explain fish losses and refuge quality in drying waterholes of Cooper Creek, an Australian arid-zone river

2010 ◽  
Vol 61 (8) ◽  
pp. 842 ◽  
Author(s):  
Angela H. Arthington ◽  
Julian D. Olden ◽  
Stephen R. Balcombe ◽  
Martin C. Thoms
Keyword(s):  
Environmental Factors ◽  
Fish Assemblage ◽  
Arid Zone ◽  
Gross Primary Production ◽  
Dry Season ◽  
Fish Assemblage Structure ◽  
Data Set ◽  
Water Abstraction ◽  
Multi Scale ◽  
Ordination Techniques

Many rivers experience intermittent flows naturally or as a consequence of water abstraction. Climate change is likely to exacerbate flow variability such that dry spells may become more common. It is important to understand the ecological consequences of flow intermittency and habitat fragmentation in rivers, and to identify and protect habitat patches that provide refugia for aquatic biota. This paper explores environmental factors influencing dry season fish losses from isolated waterbodies in Cooper Creek, an unregulated arid-zone river in the Lake Eyre Basin, Australia. Multivariate ordination techniques and classification and regression trees (CART) were used to decompose species–environment relationships into a hierarchically structured data set, and to determine factors explaining changes in fish assemblage structure and species losses over a single dry season. Canonical correspondence analysis (CCA) explained 74% of fish assemblage change in terms of waterhole morphology (wetted perimeter, depth), habitat structure (bench development, off-take channels), waterhole quality (eroded banks, gross primary production), the size of surrounding floodplains and the relative isolation of waterholes. Classification trees for endemic and restricted species reaffirmed the importance of these waterhole and floodplain variables as drivers of fish losses. The CCA and CART models offer valuable tools for identification of refugia in Cooper Creek and, possibly, other dryland rivers.

scholarly journals Spatial and temporal variation in fish-assemblage structure in isolated waterholes during the 2001 dry season of an arid-zone floodplain river, Cooper Creek, Australia

2005 ◽  
Vol 56 (1) ◽  
pp. 25 ◽  
Author(s):  
Angela H. Arthington ◽  
Stephen R. Balcombe ◽  
Glenn A. Wilson ◽  
Martin C. Thoms ◽  
Jon Marshall
Keyword(s):  
Temporal Variation ◽  
Fish Assemblage ◽  
Fish Assemblages ◽  
Arid Zone ◽  
Dry Season ◽  
Assemblage Structure ◽  
Spatial And Temporal Variation ◽  
Fish Assemblage Structure ◽  
Floodplain River ◽  
Floodplain Inundation

Spatial and temporal variation in fish-assemblage structure within isolated waterholes on the floodplains of Cooper Creek, Australia, was studied during the 2001 dry season, a period of natural drought in this arid-zone river. Spatial variation in fish-assemblage structure and the abundance of five species in disconnected waterholes early in the dry season (April 2001) were related to the extent of floodplain inundation 14 months previously, and to the interconnectedness of waterholes and waterhole habitat structure. As the dry season progressed, waterhole volumes decreased owing to evaporative water loss and structural habitat elements (anabranches, bars, boulders) became exposed. Marked changes in fish assemblage structure between the early (April) and late (September) dry season were related to habitat loss but not to water chemistry. Interactions between flow and habitat across a nested hierarchy of spatial scales (the floodplain, the waterhole and habitat patches within waterholes) were crucial to the persistence of fish assemblages through the 2001 dry season. We conclude that the magnitude, timing and frequency of floodplain inundation and natural variations in waterhole volume must be maintained if we wish to sustain the distinctive habitats and fish assemblages of this arid-zone floodplain river.

scholarly journals Assessing Spatial and Temporal Trends in a Mediterranean Fish Assemblage Structure

Diversity ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 368
Author(s):  
Michel Marengo ◽  
Laura Iborra ◽  
Michèle Leduc ◽  
Pierre Lejeune ◽  
Pierre Boissery ◽  
...  
Keyword(s):  
Fish Assemblage ◽  
Fish Community ◽  
Fish Assemblages ◽  
Fish Communities ◽  
Assemblage Structure ◽  
Marine Biodiversity ◽  
Significant Shift ◽  
Fish Assemblage Structure ◽  
Data Set ◽  
General Decline

Coastal fishes are not only valuable elements of marine biodiversity, but they also play an important ecological role in the functioning of coastal ecosystems: food resource, transfer of nutrients, predators. Therefore, data on the compositions of fish assemblages are of great importance. The objectives of the present study were to (i) define the faunistic characteristics of a typical fish community on the Mediterranean coast; (ii) investigate spatiotemporal changes in fish assemblages. Based on a set of indices (Fast protocol) and a long-term data set (6 years, 612 visual counts, 154 h of diving), changes in coastal fish communities were analyzed. Our results indicated that there was a significant shift in fish community structure, with a general decline of the calculated indices. In our study, part of the observed variability in fish assemblage structure could be due to different factors as site location and sampled year. The changes in the fish assemblages associated with inter-annual fluctuations observed in this study also provide important insights into how fish communities may change under environmental and anthropogenic influences.

scholarly journals The Winter Habitat Selection of Red Deer (Cervus elaphus) Based on a Multi-Scale Model

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2454
Author(s):  
Yue Sun ◽  
Yanze Yu ◽  
Jinhao Guo ◽  
Minghai Zhang
Keyword(s):  
Habitat Selection ◽  
Environmental Factors ◽  
Cervus Elaphus ◽  
Red Deer ◽  
Scale Model ◽  
Winter Habitat ◽  
Multi Scale ◽  
Optimal Scale ◽  
Scale Models ◽  
Selection Of

Single-scale frameworks are often used to analyze the habitat selections of species. Research on habitat selection can be significantly improved using multi-scale models that enable greater in-depth analyses of the scale dependence between species and specific environmental factors. In this study, the winter habitat selection of red deer in the Gogostaihanwula Nature Reserve, Inner Mongolia, was studied using a multi-scale model. Each selected covariate was included in multi-scale models at their “characteristic scale”, and we used an all subsets approach and model selection framework to assess habitat selection. The results showed that: (1) Univariate logistic regression analysis showed that the response scale of red deer to environmental factors was different among different covariate. The optimal scale of the single covariate was 800–3200 m, slope (SLP), altitude (ELE), and ratio of deciduous broad-leaved forests were 800 m in large scale, except that the farmland ratio was 200 m in fine scale. The optimal scale of road density and grassland ratio is both 1600 m, and the optimal scale of net forest production capacity is 3200 m; (2) distance to forest edges, distance to cement roads, distance to villages, altitude, distance to all road, and slope of the region were the most important factors affecting winter habitat selection. The outcomes of this study indicate that future studies on the effectiveness of habitat selections will benefit from multi-scale models. In addition to increasing interpretive and predictive capabilities, multi-scale habitat selection models enhance our understanding of how species respond to their environments and contribute to the formulation of effective conservation and management strategies for ungulata.

scholarly journals Seasonal Variation of Rainy and Dry Season Per Capita Water Consumption in Freetown City Sierra Leone

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 499
Author(s):  
Salmatta Ibrahim A ◽  
Fayyaz Ali Memon ◽  
David Butler
Keyword(s):  
Seasonal Variation ◽  
Water Use ◽  
Water Consumption ◽  
Low Income ◽  
Rainy Season ◽  
Predictor Variable ◽  
Dry Season ◽  
Data Set ◽  
Per Capita ◽  
End Use

Ensuring a sustainable urban water supply for developing/low-income countries requires an understanding of the factors affecting water consumption and technical evidence of individual consumption which can be used to design an improved water demand projection. This paper compared dry and rainy season water sources available for consumption and the end-use volume by each person in the different income groups. The study used a questionnaire survey to gather household data for a total of 398 households, which was analysed to develop the relationship between per capita water consumption characteristics: Socio-economic status, demographics, water use behaviour around indoor and outdoor water use activities. In the per capita water consumption patterns of Freetown, a seasonal variation was found: In the rainy season, per capita water consumption was found to be about 7% higher than the consumption for the full sample, whilst in the dry season, per capita water consumption was almost 14% lower than the full survey. The statistical analysis of the data shows that the average per capita water consumption for both households increases with income for informal slum-, low-, middle- and high-income households without piped connection (73, 78, 94 and 112 L/capita/day) and with connection (91, 97, 113 and 133 L/capita/day), respectively. The collected data have been used to develop 20 statistical models using the multiple linear stepwise regression method for selecting the best predictor variable from the data set. It can be seen from the values that the strongest significant relationships of per capita consumption are with the number of occupants (R = −0.728) in the household and time spent to fetch water for use (R = −0.711). Furthermore, the results reveal that the highest fraction of end use is showering (18%), then bathing (16%), followed by toilet use (14%). This is not in agreement with many developing countries where toilet use represents the largest component of indoor end use.

scholarly journals A Fast and Lightweight Method with Feature Fusion and Multi-Context for Face Detection

2018 ◽  
Vol 10 (8) ◽  
pp. 80
Author(s):  
Lei Zhang ◽  
Xiaoli Zhi
Keyword(s):  
Face Detection ◽  
Graphics Processing Units ◽  
High Performance ◽  
Feature Fusion ◽  
Local Context ◽  
Data Set ◽  
Global Context ◽  
Detection Algorithms ◽  
Multi Scale ◽  
Benchmark Datasets

Convolutional neural networks (CNN for short) have made great progress in face detection. They mostly take computation intensive networks as the backbone in order to obtain high precision, and they cannot get a good detection speed without the support of high-performance GPUs (Graphics Processing Units). This limits CNN-based face detection algorithms in real applications, especially in some speed dependent ones. To alleviate this problem, we propose a lightweight face detector in this paper, which takes a fast residual network as backbone. Our method can run fast even on cheap and ordinary GPUs. To guarantee its detection precision, multi-scale features and multi-context are fully exploited in efficient ways. Specifically, feature fusion is used to obtain semantic strongly multi-scale features firstly. Then multi-context including both local and global context is added to these multi-scale features without extra computational burden. The local context is added through a depthwise separable convolution based approach, and the global context by a simple global average pooling way. Experimental results show that our method can run at about 110 fps on VGA (Video Graphics Array)-resolution images, while still maintaining competitive precision on WIDER FACE and FDDB (Face Detection Data Set and Benchmark) datasets as compared with its state-of-the-art counterparts.

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