The importance of shading by riparian vegetation and wetlands in fish survival in stagnant water holes, Great Ruaha River, Tanzania

Epaphras, A. M.; Gereta, Emmanuel; Lejora, Inyasi A. V.; Mtahiko, M. G. G.

doi:10.1007/s11273-007-9033-y

Cited by 9 publications

(5 citation statements)

References 12 publications

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“…All of these disturbances threaten wetland ecosystems, and can greatly influence the population structure and diversity of the bird community supported by that ecosystem (Birdlife International, Corsby 2003). The loss of wetland communities leads to loss of plant diversity, reduction in primary production and consequently loss of faunal diversity of wetland ecosystem due to loss of habitat, food, decreased aeration of sediments and increased nutrient levels (Epaphras et al 2007;Armstrong et al 2008). A comparative analysis of the four National Red Data Lists from 1996 to 2010 of the critically endangered (CR) birds and their dependency in the habitat reveals that 28 species listed under this category are wetland dependent species which implies 35% of total wetland bird species in Nepal are considered threatened, far more than other habitat types (Baral et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Avifaunal Diversity and Threats to them in Phewa Wetland, Nepal

Khatri

Neupane

Timilsina

et al. 2019

Forestry: J. Inst. Fores. Nep.

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We assessed species diversity and relative abundance during February - March by employing transect method in four line transects and 30 point count stations, and associated threats by direct observations and consultation with people (n= 1) living in vicinity of Phewa wetland. We counted 2651 bird individuals of 148 species belonging to 104 Genera of 44 Families under 11 Orders. Anatidae and Passeriformes with 11% and 39%, respectively were the dominant family and order among the recorded species. Out of these, seven bird species were globally threatened and 12 were nationally threatened. Terrestrial birds had higher species diversity (H'= 3.27), species richness (R= 11.98) and species evenness (e= 0.74) as compared to wetland birds (H' = 3.07, R= 8.44 and e = 0.73). Common pigeon (7.50%) was the most abundant bird followed by lesser whistling duck (6.98%). People in the vicinity of Phewa wetland reported that water pollution caused by domestic sewages and waste water disposal was the major threat to birds and their habitat. Phewa wetland is providing crucial habitat to adequate residential and migratory bird species for which it should be protected for further enhancement of number of avian species.

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Section: Introductionmentioning

confidence: 99%

Assessment of Avifaunal Diversity and Threats to them in Phewa Wetland, Nepal

Khatri

Neupane

Timilsina

et al. 2019

Forestry: J. Inst. Fores. Nep.

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“…2c). Traced back to the bundled date of each dataset in neurons I and VII, we found distinct time frames of summer fish kill type (neuron VII) and non-summer one (neuron I), where the SOM classified events 1, 3, 4, 5, 10, 11, 16, and 17 as non-summer fish kill type, and events 2,6,7,8,9,12,13,14,15,18, and 19 as summer fish kills (Table 1).…”

Section: Recognize Types Of Fish Kills By the Sommentioning

confidence: 98%

“…Negative impacts of fish kill on river ecosystems include declines in fish populations, degradation of water quality 3 , 4 , and socio-economic costs involved in cleaning up dead fish that affect amenity values 6 . While fish kills can be attributed to a wide range of reasons, such as eutrophication, high ammonia concentration, heat exhaustion and disease 3 , 7 , 8 , a common cause is the level of dissolved oxygen 8 , 9 . Exhaustion of localized DO, acute reductions of DO to hypoxia (i.e., DO < 2 mg/L) 10 , 11 , and/or any kind of DO depletion pose real threats to fish that can lead to low-dissolved oxygen syndrome and death 3 , 9 , 10 .…”

Section: Introductionmentioning

confidence: 99%

Using machine learning to understand the implications of meteorological conditions for fish kills

Chen

Nicholson

Cheng

2020

Sci Rep

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Fish kills, often caused by low levels of dissolved oxygen (DO), involve with complex interactions and dynamics in the environment. In many places the precise cause of massive fish kills remains uncertain due to a lack of continuous water quality monitoring. In this study, we tested if meteorological conditions could act as a proxy for low levels of DO by relating readily available meteorological data to fish kills of grey mullet (Mugil cephalus) using a machine learning technique, the self-organizing map (SOM). Driven by different meteorological patterns, fish kills were classified into summer and non-summer types by the SOM. Summer fish kills were associated with extended periods of lower air pressure and higher temperature, and concentrated storm events 2–3 days before the fish kills. In contrast, non-summer fish kills followed a combination of relatively low air pressure, continuous lower wind speed, and successive storm events 5 days before the fish kills. Our findings suggest that abnormal meteorological conditions can serve as warning signals for managers to avoid fish kills by taking preventative actions. While not replacing water monitoring programs, meteorological data can support fishery management to safeguard the health of the riverine ecosystems.

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“…1) until recently. Wildlife in RNP is totally dependent on the Great Ruaha River (GRR) and a few scattered springs in the RNP, these being the only source of water in the dry season (Mtahiko et al 2006;Epaphras et al 2007 and. Starting in the 1990s and intensifying in the 2000s, GRR water was over-used for irrigation by large-scale rice farms and thousands of unregulated small landholders in the Usangu plains along the GRR upstream of RNP.…”

Section: The Water Crisis In Tanzania's Protected Areasmentioning

confidence: 99%