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A synopsis of the Bee occurrence data of northern Tanzania.

ABSTRACT:

Background

Bees (Hymenoptera: Apoidea: Anthophila) are the most important group of pollinators with about 20,507 known species worldwide. Despite the critical role of bees in providing pollination services, studies aiming at understanding which species are present across disturbance gradients are scarce. Limited taxononomic information for the existing and unidentified bee species in Tanzania make their conservation haphazard. Here, we present a dataset of bee species records obtained from a survey in nothern Tanzania i.e. Kilimanjaro, Arusha and Manyara regions. Our findings serve as baseline data necessary for understanding the diversity and distribution of bees in the northern parts of the country, which is a critical step in devising robust conservation and monitoring strategies for their populations.

New information

In this paper, we present information on 45 bee species belonging to 20 genera and four families sampled using a combination of sweep-netting and pan trap methods. Most species (27, ~ 60%) belong to the family Halictidae followed by 16 species (35.5%) from the family Apidae. Megachilidae and Andrenidae were the least represented, each with only one species (2.2%). Additional species of Apidae and Megachilidae sampled during this survey are not yet published on Global Biodiversity Information Facility (GBIF), once they will be available on GBIF, they will be published in a subsequent paper. From a total of 953 occurrences, highest numbers were recorded in Kilimanjaro Region (n = 511), followed by Arusha (n = 410) and Manyara (n = 32), but this pattern reflects the sampling efforts of the research project rather than real bias in the distributions of bee species in northern Tanzania.

SUBMITTER: Lasway JV

PROVIDER: S-EPMC8384828 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:A dataset describing the occurrence of wild bees and their interaction with forage plants along livestock grazing gradient is critical in understanding bee-plant interaction networks and in developing conservation plans to ensure ecosystem services in human-modified landscapes. Despite this need, bee-plant datasets are scarce in Africa, and Tanzania is no exception. Therefore, in this article, we present a dataset of wild bee species richness, occurrence, and distribution collected across sites with different levels of livestock grazing intensity and forage resources thereby. The data presented in this paper supports a research article by Lasway et al., 2022 describing the effects of grazing intensity on East African bee assemblages. The paper presents primary data on bee species, collection method, date of collection, bee family, identifier, plant forage resource, forage plant life form, forage plant family, location (GPS coordinates), grazing intensity category, mean annual temperature (°C), and elevation (m asl). The data were collected intermittently between August 2018 and March 2020 from 24 study sites distributed along three levels of livestock grazing intensity with eight replicates for each: low, moderate, and high livestock grazing intensity. In each study site, two 50 × 50 m study plots were set from which bees and floral resources were sampled and quantified. The two plots were placed in a way to capture the overall structural heterogeneity of the respective habitat by placing the two plots in contrasting microhabitats where possible. For example, in moderately livestock-grazed habitats, plots were placed on sites with and without tree or shrub cover to ensure representativeness. This paper presents a dataset comprising 2,691 bee individuals from 183 species representing 55 genera of the five bee families: Halictidae (74), Apidae (63), Megachilidae (40), Andrenidae (5), and Colletidae (1). In addition, the dataset comprises 112 species of flowering plants that were identified as potential forage resources for bees. This paper supplements rare but critical data on bee pollinators in Northern Tanzania and advances our knowledge of the potential drivers of bee-pollinator whose populations diversity are declining globally. The dataset will also promote collaborations among researchers who would wish to combine and extend their data for further analysis to gain a broader understanding of the phenomenon on a larger spatial scale.

Project description:BACKGROUND:More than five million perinatal deaths occur each year globally. Despite efforts put forward during the millennium development goals era, perinatal deaths continue to increase relative to under-five deaths, especially in low- and middle-income countries. This study aimed to determine predictors of perinatal death in the presence of missing data using birth registry data from Kilimanjaro Christian Medical Center (KCMC), between 2000-2015. METHODS:This was a retrospective cohort study from the medical birth registry at KCMC referral hospital located in Moshi Municipality, Kilimanjaro region, northern Tanzania. Data were analyzed using Stata version 15.1. Multiple imputation by fully conditional specification (FCS) was used to impute missing values. Generalized estimating equations (GEE) were used to determine the marginal effects of covariates on perinatal death using a log link mean model with robust standard errors. An exchangeable correlation structure was used to account for the dependence of observations within mothers. RESULTS:Among 50,487 deliveries recorded in the KCMC medical birth registry between 2000-2015, 4.2% (95%CI 4.0%, 4.3%) ended in perinatal death (equivalent to a perinatal mortality rate (PMR) of 41.6 (95%CI 39.9, 43.3) deaths per 1,000 births). After the imputation of missing values, the proportion of perinatal death remained relatively the same. The risk of perinatal death was significantly higher among deliveries from mothers who resided in rural compared to urban areas (RR = 1.241, 95%CI 1.137, 1.355), with primary education level (RR = 1.201, 95%CI 1.083, 1.332) compared to higher education level, with <4 compared to ?4 antenatal care (ANC) visits (RR = 1.250, 95%CI 1.146, 1.365), with postpartum hemorrhage (PPH) (RR = 2.638, 95%CI 1.997, 3.486), abruption placenta (RR = 4.218, 95%CI 3.438, 5.175), delivered a low birth weight baby (LBW) (RR = 4.210, 95%CI 3.788, 4.679), male child (RR = 1.090, 95%CI 1.007, 1.181), and were referred for delivery (RR = 2.108, 95%CI 1.919, 2.317). On the other hand, deliveries from mothers who experienced premature rupture of the membranes (PROM) (RR = 0.411, 95%CI 0.283, 0.598) and delivered through cesarean section (CS) (RR = 0.662, 95%CI 0.604, 0.724) had a lower risk of perinatal death. CONCLUSIONS:Perinatal mortality in this cohort is higher than the national estimate. Higher risk of perinatal death was associated with low maternal education level, rural residence, <4 ANC visits, PPH, abruption placenta, LBW delivery, child's sex, and being referred for delivery. Ignoring missing values in the analysis of adverse pregnancy outcomes produces biased covariate coefficients and standard errors. Close clinical follow-up of women at high risk of experiencing perinatal death, particularly during ANC visits and delivery, is of high importance to increase perinatal survival.

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A synopsis of the Bee occurrence data of northern Tanzania.

Background

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