Indigenous knowledge related to climate variability and change: insights from droughts in semi-arid areas of former Makueni District, Kenya

This article describes the indigenous knowledge (IK) that agro-pastoralists in larger Makueni District, Kenya hold and how they use it to monitor, mitigate and adapt to drought. It examines ways of integrating IK into formal monitoring, how to enhance its value and acceptability. Data was collected through target interviews, group discussions and questionnaires covering 127 households in eight villages. Daily rainfall data from 1961–2003 were analysed. Results show that agro-pastoralists hold IK on indicators of rainfall variability; they believe in IK efficacy and they rely on them. Because agro-pastoralists consult additional sources, the authors interpret that IK forms a basic knowledge frame within which agro-pastoralists position and interpret meteorological forecasts. Only a few agro-pastoralists adapt their practices in anticipation of IK-based forecasts partly due to the conditioning of the actors to the high rainfall variability characteristic of the area and partly due to lack of resources. Non-drought factors such as poverty, inadequate resources and lack of preparedness expose agro-pastoralists to drought impacts and limit their adaptive capacity. These factors need to be understood and effectively addressed to increase agro-pastoralists’ decision options and the influence of IK-based forecasts on their decision-making patterns. The limited intergenerational transfer of IK currently threatens its existence in the longer term. One way to ensure its continued existence and use is to integrate IK into the education curriculum and to link IK with formal climate change research through the participation of the local people. However, further studies are necessary to address the reliability and validity of the identified IK indicators of climate variability and change.

Seasonal variation and sources of low molecular weight organic acids in precipitation in the rural area of Anshun

Low mol. wt. (LMW) org. acids are important and ubiquitous chem. constituents in the atm. A comprehensive study of the chem. compn. of pptn. was carried out from June 2007 to June 2008 at a rural site in Anshun, in the west of Guizhou Province, China. During this period, 118 rainwater samples were collected and the main LMW carboxylic acids were detd. using ion chromatog. The av. pH of rainwater was 4.89 which is a typical acidic value. The most abundant carboxylic acids were formic acid (vol. wt. mean concn.: 8.77 μmol L-1) and acetic acid (6.90 μmol L-1), followed by oxalic acid (2.05 μmol L-1). The seasonal variation of concns. and wet deposition fluxes of org. acids indicated that direct vegetation emissions were the main sources of the org. acids. Highest concns. were obsd. in winter and were ascribed to the low winter rainfall and the contribution of other air pollution sources northeast of the study area. The ratio of formic and acetic acids in the pptn. ([F/A]T) was proposed as an indicator of pollution source. This suggested that the pollution resulted from direct emissions from natural or anthropogenic sources. Comparison with acid pptn. in other urban and rural areas in Guizhou showed that there was a decreasing contribution of LMW org. acids to free acidity and all anions in rainwater from urban to remote rural areas. Consequently, it is necessary to control emissions of org. acids to reduce the frequency of acid rain, esp. in rural and remote areas. [on SciFinder(R)]

Measuring Correlation Between HIV Sequence Variation and Disease Stage of HIV-Infected Individuals

With a virus such as Human Immunodeficiency Virus (HIV) that has infected millions of people worldwide, and with many unaware that they are infected, it becomes vital to understand how the virus works and how it functions at the molecular level. Because there currently is no vaccine and no way to eradicate the virus from an infected person, any information about how the virus interacts with its host greatly increases the chances of understanding how HIV works and brings scientists one step closer to being able to combat such a destructive virus. Thousands of HIV viruses have been sequenced and are available in many online databases for public use. Attributes that are linked to each sequence include the viral load within the host and how sick the patient is currently. Being able to predict the stage of infection for someone is a valuable resource, as it could potentially aid in treatment options and proper medication use. Our approach of analyzing region-specific amino acid composition for select genes has been able to predict patient disease state up to an accuracy of 85.4%. Moreover, we output a set of classification rules based on the sequence that may prove useful for diagnosing the expected clinical outcome of the infected patient.

Wolf habitat selection at the territory level : seasonal and interannual variation and influence on reproductive success

Habitat selection has been one of the main research topics in ecology for decades. Nevertheless, many aspects of habitat selection still need to be explored. In particular, previous studies have overlooked the importance of temporal variation in habitat selection and the value of including data on reproductive success in order to describe the best quality habitat for a species. We used data collected from radiocollared wolves in Yellowstone National Park (USA), between 1996 and 2008, to describe wolf habitat selection. In particular, we aimed to identify i) seasonal differences in wolf habitat selection, ii) factors influencing interannual variation in habitat selection, and iii) the effect of habitat selection on wolf reproductive success. We used probability density functions to describe wolf habitat use and habitat coverages to represent the habitat available to wolves. We used regression analysis to connect habitat use with habitat characteristics and habitat selection with reproductive success. Our most relevant result was discovering strong interannual variability in wolf habitat selection. This variability was in part explained by pack identity and differences in litter size and leadership of a pack between two years (summer) and in pack size and precipitation (winter). We also detected some seasonal differences. Wolves selected open habitats, intermediate elevations, intermediate distances from roads, and avoided steep slopes in late winter. They selected areas close to roads and avoided steep slopes in summer. In early winter, wolves selected wetlands, herbaceous and shrub vegetation types, and areas at intermediate elevation and distance from roads. Surprisingly, the habitat characteristics selected by wolves were not useful in predicting reproductive success. We hypothesize that interannual variability in wolf habitat selection may be too strong to detect effects on reproductive success. Moreover, prey availability and competitor pressure may also have an influence on wolf reproductive success, which we did not assess. This project demonstrated how important temporal variation is in shaping patterns of habitat selection. We still believe in the value of running long-term studies, but the effect of temporal variation should always be taken into account.