Soil type limits population abundance of rodents in crop fields: case study of the multimammate rat Mastomys natalensis Smith, 1834 in Tanzania

Relative fishing mortality (R) is estimated directly as the ratio of commercial catch divided by a research vessel survey index of relative population abundance. If the survey is conducted near the middle of the fishing year, its catchability is constant, and the rate of catch reporting remains constant, R will be proportional to the actual fishing mortality (F). Trends in R will reflect trends in F. A case study is presented where R at age and length are compared with estimates obtained with sequential population analysis (SPA). They were found to be of similar magnitude and trend. This new method would be useful for stocks where SPA is not possible. It would also be a useful addition to analytical assessments where SPA is used; it provides estimates of relative F at length, it is insensitive to changes in natural mortality provided the research survey occurs close to the middle of the fishing year, and it provides useful diagnostics for interpreting SPA results.

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Do farming practices influence population dynamics of rodents? A case study of the multimammate field rats, Mastomys natalensis, in Tanzania

African Journal of Ecology ◽

10.1111/j.1365-2028.2006.00709.x ◽

2007 ◽

Vol 45 (3) ◽

pp. 293-301 ◽

Cited By ~ 14

Author(s):

A. W. Massawe ◽

W. Rwamugira ◽

H. Leirs ◽

R. H. Makundi ◽

Loth S. Mulungu

Keyword(s):

Population Dynamics ◽

Mastomys Natalensis ◽

Farming Practices

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Benefit of ancillary data acquired at the cooperative level to study soil type and climatic zone influence on berry composition: a case study in Rioja appellation

OENO One ◽

10.20870/oeno-one.2018.52.2.1851 ◽

2018 ◽

Vol 52 (2) ◽

pp. 119-133

Author(s):

Urtzi LEIBAR ◽

Olatz UNAMUNZAGA ◽

María José FERNÁNDEZ-GÓMEZ ◽

Purificación GALINDO-VILLARDÓN ◽

Cesar CASTRO ◽

...

Keyword(s):

Soil Type ◽

Clay Content ◽

Total Surface Area ◽

Colour Intensity ◽

Ancillary Data ◽

Climatic Zones ◽

Berry Composition ◽

Water Holding ◽

Soil Climate

Aim: The main objective of this study was to evaluate the influence of soil type and climate on must qualitative parameters in a winegrower’s cooperative at Rioja appellation.Methods and results: The study was conducted from 2009 to 2011 with data collected routinely before harvest by the technician of a cooperative with a total surface area of 525 ha. Soils were classified using an existing soil map (1:50.000 scale) according to their water-holding capacity (WHC), and two climatic zones were differentiated based on the Huglin index. Effects of soil and climate on berry composition were evaluated using HJ-Biplot statistical analysis. High WHC soils produced musts with high total acidity, mainly due to malic acid. Must K concentrations were lower in soils with lower K and clay content. Soils with lower WHC were the only ones able to produce musts with high anthocyanin concentration and higher colour intensity. The climatic zones established only resulted in small differences in grape composition.Conclusion: It is possible to differentiate berry composition parameters according to soil type considering soil WHC, but less clear differences were observed among climatic zones considering a 50 km2 area and a difference of approximately 200 m in elevation between the two zones.Significance and impact of the study: Many wineries have access to soil, climate and grape composition data. Therefore, these data could be used to make a grape composition classification at harvest that could be assessed every year using simple statistical tools.

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Home ranges, sex ratio and recruitment of the multimammate rat (Mastomys natalensis) in semi-arid areas in Tanzania

Mammalia ◽

10.1515/mammalia-2019-0048 ◽

2020 ◽

Vol 84 (4) ◽

pp. 336-343 ◽

Cited By ~ 1

Author(s):

Emmanuel C.M. Mlyashimbi ◽

Joachim Mariën ◽

Didas N. Kimaro ◽

Akwilin J.P. Tarimo ◽

Robert S. Machang’u ◽

...

Keyword(s):

Sex Ratio ◽

Management Strategies ◽

Home Range Size ◽

Population Increase ◽

Home Ranges ◽

Arid Areas ◽

Mastomys Natalensis ◽

Semi Arid ◽

Over Time ◽

Multimammate Rat

AbstractInvestigation of home ranges, sex ratio and recruitment of the multimammate rat (Mastomys natalensis) in semi-arid areas of Tanzania was conducted in maize and fallow fields using the capture-mark-release (CMR) technique. The aim of this study was to generate useful data for the management of M. natalensis. The relative home range size of M. natalensis was significantly higher during the wet [544 m2 ± 25 standard error (SE)] than during the dry (447 m2 ± 18 SE) season, in males (521 m2 ± 23 SE) than in females (450 m2 ± 17 SE) and in adults (576 m2 ± 34 SE) than in juveniles (459 m2 ± 16 SE). However, there were no significant differences between habitats. Sex ratio was not significantly different (p = 0.44) between habitats. Recruitment was significantly higher (p = 0.000) in maize fields (mean = 0.43) than in fallow land (mean = 0.32) and differed significantly over time (p < 0.0001) with the highest recruitment recorded from April to July and the lowest from October to December. Management strategies should focus on managing rodents inhabiting maize fields using methods that affect their recruitment in order to reduce the population increase of M. natalensis.

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Estimating population abundance with a mixture of physical capture and PIT tag antenna detection data

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2019-0326 ◽

2020 ◽

Vol 77 (7) ◽

pp. 1163-1171

Author(s):

Mary M. Conner ◽

Phaedra E. Budy ◽

Richard A. Wilkison ◽

Michael Mills ◽

David Speas ◽

...

Keyword(s):

Coefficient Of Variation ◽

Population Abundance ◽

Dramatic Reduction ◽

Pit Tag ◽

Abundance Estimates ◽

Detection Probabilities ◽

Significant Change ◽

The Difference

The inclusion of passive interrogation antenna (PIA) detection data has promise to increase precision of population abundance estimates ([Formula: see text]). However, encounter probabilities are often higher for PIAs than for physical capture. If the difference is not accounted for, [Formula: see text] may be biased. Using simulations, we estimated the magnitude of bias resulting from mixed capture and detection probabilities and evaluated potential solutions for removing the bias for closed capture models. Mixing physical capture and PIA detections (pdet) resulted in negative biases in [Formula: see text]. However, using an individual covariate to model differences removed bias and improved precision. From a case study of fish making spawning migrations across a stream-wide PIA (pdet ≤ 0.9), the coefficient of variation (CV) of [Formula: see text] declined 39%–82% when PIA data were included, and there was a dramatic reduction in time to detect a significant change in [Formula: see text]. For a second case study, with modest pdet (≤0.2) using smaller PIAs, CV ([Formula: see text]) declined 4%–18%. Our method is applicable for estimating abundance for any situation where data are collected with methods having different capture–detection probabilities.

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