Historical dataset of population level and growth rate for the Nakuru, Kenya metro area from 1950 to 2025.

Giraffe populations in East Africa have declined in the past thirty years yet there has been limited research on this species. This study had four objectives: i) to provide a baseline population assessment for the two largest populations of Rothschild’s giraffes in Kenya, ii) to assess whether there are differences in population structure between the two enclosed populations, iii) to assess the potential and possible implications of different management practices on enclosed giraffe populations to inform future decision-making, and iv) to add to the availability of information available about giraffes in the wild. I used individual identification to assess the size and structure of the two populations; in Soysambu Conservancy between May 2010 and January 2011, I identified 77 giraffes; in Lake Nakuru National Park between May 2011 and January 2012, I identified 89. Population structure differed significantly between the two sites; Soysambu Conservancy contained a high percentage of juveniles (34%) and subadults (29%) compared to Lake Nakuru NP, which contained fewer juveniles (5%) and subadults (15%). During the time of this study Soysambu Conservancy contained no lions while Lake Nakuru NP contained a high density of lions (30 lions per 100km2). Lions are the main predator of giraffes, and preferential predation on juvenile giraffes has previously been identified in Lake Nakuru NP. My results suggest that high lion density in Lake Nakuru NP may have influenced the structure of the giraffe population by removing juveniles and, consequently, may affect future population growth. I suggest that wildlife managers consider lion densities alongside breeding plans for Endangered species, since the presence of lions appears to influence the population structure of giraffes in enclosed habitats.

BackgroundDiseases of the posterior segment of the eye, including age-related macular degeneration (AMD), have recently been recognised as the leading or second leading cause of blindness in several African countries. However, prevalence of AMD alone has not been assessed. We hypothesized that AMD is an important cause of visual impairment among elderly people in Nakuru, Kenya, and therefore sought to assess the prevalence and predictors of AMD in a diverse adult Kenyan population. Methods and FindingsIn a population-based cross-sectional survey in the Nakuru District of Kenya, 100 clusters of 50 people 50 y of age or older were selected by probability-proportional-to-size sampling between 26 January 2007 and 11 November 2008. Households within clusters were selected through compact segment sampling. All participants underwent a standardised interview and comprehensive eye examination, including dilated slit lamp examination by an ophthalmologist and digital retinal photography. Images were graded for the presence and severity of AMD lesions following a modified version of the International Classification and Grading System for Age-Related Maculopathy. Comparison was made between slit lamp biomicroscopy (SLB) and photographic grading. Of 4,381 participants, fundus photographs were gradable for 3,304 persons (75.4%), and SLB was completed for 4,312 (98%). Early and late AMD prevalence were 11.2% and 1.2%, respectively, among participants graded on images. Prevalence of AMD by SLB was 6.7% and 0.7% for early and late AMD, respectively. SLB underdiagnosed AMD relative to photographic grading by a factor of 1.7. After controlling for age, women had a higher prevalence of early AMD than men (odds ratio 1.5; 95% CI, 1.2–1.9). Overall prevalence rose significantly with each decade of age. We estimate that, in Kenya, 283,900 to 362,800 people 50 y and older have early AMD and 25,200 to 50,500 have late AMD, based on population estimates in 2007. ConclusionsAMD is an important cause of visual impairment and blindness in Kenya. Greater availability of low vision services and ophthalmologist training in diagnosis and treatment of AMD would be appropriate next steps. Please see later in the article for the Editors' Summary

Wildlife conservation is facing numerous and mounting challenges on private and communal lands in Africa, including in Kenya. We analyze the population dynamics of 44 common wildlife species in relation to rainfall variation in the Nakuru Wildlife Conservancy (NWC), located in the Nakuru-Naivasha region of Kenya, based on ground total counts carried out twice each year from March 1996 to May 2015. Rainfall in the region was quasi-periodic with cycle periods dependent on the rainfall component and varying from 2.8 years for the dry season to 10.9 years for the wet season. These oscillations are associated with frequent severe droughts and food scarcity for herbivores. The trends for the 44 wildlife species showed five general patterns during 1996–2015. 1) Steinbuck, bushbuck, hartebeest and greater kudu numbers declined persistently and significantly throughout 1996–2015 and thus merit the greatest conservation attention. 2) Klipspringer, mongoose, oribi, porcupine, cheetah, leopard, ostrich and Sykes monkey numbers also decreased noticeably but not significantly between 1996 and 2015. 3) Dik dik, eland, African hare, Jackal, duiker, hippo and Thomson’s gazelle numbers first increased and then declined between 1996 and 2015 but only significantly for duiker and hippo. 4) Aardvark, serval cat, colobus monkey, bat-eared fox, reedbuck, hyena and baboon numbers first declined and then increased but only the increases in reedbuck and baboon numbers were significant. 5) Grant’s gazelle, Grevy’s zebra, lion, spring hare, Burchell’s zebra, bushpig, white rhino, rock hyrax, topi, oryx, vervet monkey, guinea fowl, giraffe, and wildebeest numbers increased consistently between 1996 and 2015. The increase was significant only for rock hyrax, topi, vervet monkey, guinea fowl, giraffe and wildebeest. 6) Impala, buffalo, warthog, and waterbuck, numbers increased significantly and then seemed to level off between 1996 and 2015. The aggregate biomass of primates and carnivores increased overall whereas that of herbivores first increased from 1996 to 2006 and then levelled off thereafter. Aggregate herbivore biomass increased linearly with increasing cumulative wet season rainfall. The densities of the 30 most abundant species were either strongly positively or negatively correlated with cumulative past rainfall, most commonly with the early wet season component. The collaborative wildlife conservation and management initiatives undertaken on the mosaic of private, communal and public lands were thus associated with increase or no decrease in numbers of 32 and decrease in numbers of 12 of the 44 species. Despite the decline by some species, effective community-based conservation is central to the future of wildlife in the NWC and other rangelands of Kenya and beyond and is crucially dependent on the good will, effective engagement and collective action of local communities, working in partnerships with various organizations, which, in NWC, operated under the umbrella of the Nakuru Wildlife Forum.

Abstract

This research of registered businesses with one to four employees was conducted in Kenya between April 2013 and January 2014, at the same time with Kenya Enterprise Survey 2013. Data from 360 establishments was analyzed. Stratified random sampling was used to select the surveyed businesses. The objective of the survey was to obtain feedback from enterprises on the state of the private sector and constraints to its growth.

Micro-Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90 percent of the questions objectively ascertain characteristics of a country's business environment. The remaining questions assess the survey respondents' opinions on what are the obstacles to firm growth and performance.

Geographic coverage

Central, Nyanza, Mombasa, Nairobi, and Nakuru regions

Analysis unit

The primary sampling unit of the study is an establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.

Universe

The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural private economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors. Companies with 100% government ownership are not eligible to participate in the Enterprise Surveys.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for Ethiopia was selected using stratified random sampling. Two levels of stratification were used: firm sector and geographic region.

For industry stratification, the universe was divided into four manufacturing industries (food, textiles and garments, chemicals and plastics, other manufacturing) and two service sectors (retail and other services).

Regional stratification was defined in five regions: Central, Nyanza, Mombasa, Nairobi, and Nakuru.

2012 Census of Business Establishments of the Kenya National Bureau of Statistics was used as a sample frame for the survey of micro firms.

The enumerated establishments with less than five employees (micro establishments) were used as sample frame for the Kenya micro survey with the aim of obtaining interviews at 360 establishments.

The quality of the frame was assessed at the onset of the project through visits to a random subset of firms and local contractor knowledge. The sample frame was not immune from the typical problems found in establishment surveys: positive rates of non-eligibility, repetition, non-existent units, etc. In addition, the sample frame contains no telephone/fax numbers so the local contractor had to screen the contacts by visiting them.

Given the impact that non-eligible units included in the sample universe may have on the results, adjustments may be needed when computing the appropriate weights for individual observations. The percentage of confirmed non-eligible units as a proportion of the total number of sampled establishments contacted for the survey was 5.2% (39 out of 756) for micro firms.

Mode of data collection

Face-to-face [f2f]

Research instrument

The following survey instruments are available: - Manufacturing Module Questionnaire - Services Module Questionnaire

The survey is fielded via manufacturing or services questionnaires in order not to ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.

There is a skip pattern in the Service Module Questionnaire for questions that apply only to retail firms.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

Response rate

Survey non-response must be differentiated from item non-response. The former refers to refusals to participate in the survey altogether whereas the latter refers to the refusals to answer some specific questions. Enterprise Surveys suffer from both problems and different strategies were used to address these issues.

Item non-response was addressed by two strategies: a- For sensitive questions that may generate negative reactions from the respondent, such as corruption or tax evasion, enumerators were instructed to collect "Refusal to respond" (-8) as a different option from "Don't know" (-9). b- Establishments with incomplete information were re-contacted in order to complete this information, whenever necessary.

Survey non-response was addressed by maximizing efforts to contact establishments that were initially selected for interview. Attempts were made to contact the establishment for interview at different times, days of the week before a replacement establishment (with similar strata characteristics) was suggested for interview. Survey non-response did occur but substitutions were made in order to potentially achieve strata-specific goals.