34 research outputs found

    Conserving the birds of Uganda's Banana-Coffee Arc: Land Sparing and Land Sharing Compared

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    Reconciling the aims of feeding an ever more demanding human population and conserving biodiversity is a difficult challenge. Here, we explore potential solutions by assessing whether land sparing (farming for high yield, potentially enabling the protection of non-farmland habitat), land sharing (lower yielding farming with more biodiversity within farmland) or a mixed strategy would result in better bird conservation outcomes for a specified level of agricultural production. We surveyed forest and farmland study areas in southern Uganda, measuring the population density of 256 bird species and agricultural yield: food energy and gross income. Parametric non-linear functions relating density to yield were fitted. Species were identified as "winners" (total population size always at least as great with agriculture present as without it) or "losers" (total population sometimes or always reduced with agriculture present) for a range of targets for total agricultural production. For each target we determined whether each species would be predicted to have a higher total population with land sparing, land sharing or with any intermediate level of sparing at an intermediate yield. We found that most species were expected to have their highest total populations with land sparing, particularly loser species and species with small global range sizes. Hence, more species would benefit from high-yield farming if used as part of a strategy to reduce forest loss than from low-yield farming and land sharing, as has been found in Ghana and India in a previous study. We caution against advocacy for high-yield farming alone as a means to deliver land sparing if it is done without strong protection for natural habitats, other ecosystem services and social welfare. Instead, we suggest that conservationists explore how conservation and agricultural policies can be better integrated to deliver land sparing by, for example, combining land-use planning and agronomic support for small farmers

    Fish farming in Tanzania: the availability and nutritive value of local feed ingredients

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    An investigative field survey was performed to gather baseline data on locally available feed ingredients and fish farming practices in different regions of Tanzania. More than 80% of respondents relied on locally available feed ingredients as a major feed supplement for their cultured fish, with maize bran being the most commonly used feed ingredient in all regions. Crude protein content in most analyzed local feed ingredients was medium-high, while crude fat content was high in some animal and agricultural by-products, and medium-low in other ingredients. Most respondents were males and the majority of fish farms were owned by individuals. Earthen pond was the most common fish farming system in all regions except Dar es Salaam. Semi-intensively mixed-sex tilapia monoculture was the dominating fish farming practice. The results of the survey presented provide a good platform for future development of culture systems and feeding strategies for tilapia in Tanzania

    Current conservation status of the Blue Swallow Hirundo atrocaerulea Sundevall 1850 in Africa

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    The global Blue Swallow Hirundo atrocaerulea was classified as Vulnerable in 2010 on account of its small and rapidly declining population estimated at less than 1 500 pairs. We undertook this study to gain a better understanding of the current status and threats facing this migratory species. Three previously unknown areas that might be part of the species’ non-breeding range were identified in Kenya and northern Tanzania. Within its breeding range we identified three previously unknown areas of potentially suitable habitat, one in Tanzania and two in Malawi, which require further exploration. Population viability assessment predicted that the Blue Swallow population will decline by 8% in 10 years. The overall probability of extinction of the species in the wild is 3%. Minimum viable population size analysis suggests that a goal for the long-term conservation of the Blue Swallow should be to mitigate current threats that are driving declines such that the population increases to a minimum of 3 600 individuals. This should consist of at least 900 individuals in each of the four clusters identified, along with a minimum of 500 individuals in at least one of the meta-populations per cluster. The four clusters are located in (1) the southeasten Democratic Republic of the Congo, (2) highlands of southern Tanzania and northern Malawi, (3) eastern highlands of Zimbabwe and (4) South Africa and Swaziland. The current proportions of the Blue Swallow population in strictly protected and unprotected areas on their breeding grounds are 53% and 47%, respectively, whereas on their non-breeding grounds the corresponding percentages are 25% and 75%, respectively. Our reassessment of the Blue Swallow’s risk of extinction indicates that it continues to qualify as Vulnerable according to the IUCN/SSC criteria C2a(i).http://www.tandfonline.com/loi/tost202016-09-30hb2016Zoology and Entomolog

    Local selection in the presence of high levels of gene flow: Evidence of heterogeneous insecticide selection pressure across Ugandan Culex quinquefasciatus populations

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    Background: Culex quinquefasciatus collected in Uganda, where no vector control interventions directly targeting this species have been conducted, was used as a model to determine if it is possible to detect heterogeneities in selection pressure driven by insecticide application targeting other insect species. Methodology/Principal findings: Population genetic structure was assessed through microsatellite analysis, and the impact of insecticide pressure by genotyping two target-site mutations, Vgsc-1014F of the voltage-gated sodium channel target of pyrethroid and DDT insecticides, and Ace1-119S of the acetylcholinesterase gene, target of carbamate and organophosphate insecticides. No significant differences in genetic diversity were observed among populations by microsatellite markers with HE ranging from 0.597 to 0.612 and low, but significant, genetic differentiation among populations (FST = 0.019, P = 0.001). By contrast, the insecticide-resistance markers display heterogeneous allelic distributions with significant differences detected between Central Ugandan (urban) populations relative to Eastern and Southwestern (rural) populations. In the central region, a frequency of 62% for Vgsc-1014F, and 32% for the Ace1-119S resistant allele were observed. Conversely, in both Eastern and Southwestern regions the Vgsc-1014F alleles were close to fixation, whilst Ace1-119S allele frequency was 12% (although frequencies may be underestimated due to copy number variation at both loci). Conclusions/Significance: Taken together, the microsatellite and both insecticide resistance target-site markers provide evidence that in the face of intense gene flow among populations, disjunction in resistance frequencies arise due to intense local selection pressures despite an absence of insecticidal control interventions targeting Culex

    The influence of nest-site characteristics on the nesting success of the Karoo Prinia (Prinia maculosa)

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    Choice of nest site has important consequences for nest survival. We examined nest-site characteristics relative to nest success in Karoo Prinias breeding in coastal dwarf shrubland, where high nest predation is the main cause of nest failure. Initially, we compared nests that failed during the building, laying, incubation and nestling stages and those from which young were successfully raised, to test whether nests that survived to progressive stages in the nesting cycle differed in their nest-site characteristics. Subsequently, we compared the characteristics of successful nests with those of unsuccessful nests. The nest-site characteristics considered included nest height, nest-plant height, nest-plant species, distance from lateral foliage edge, nest concealment, nest-patch heterogeneity and vegetation cover at four different heights. We were unable to distinguish between the nest-site characteristics of nests that failed during the various stages of the nesting cycle. Concealment was the main nest-site characteristic that differentiated successful nests from unsuccessful nests, with successful nests being located in more concealed sites. The other variables that contributed to the discrimination between successful and unsuccessful nests by discriminant function analysis included nest-plant type and distance from edge, which are also directly related to concealment. This suggests that nest concealment is the most important variable influencing nesting success at this site, which has a preponderance of visually-oriented predators. Ostrich 2004, 75(4): 269–27

    Nest-site partitioning in a strandveld shrubland bird community

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    Nest-site selection may vary adaptively among co-existing species as a result of competitive interactions among the species or in response to density-dependent nest predation. We examined nest-site characteristics and degree of partitioning among 14 co-existing bird species breeding in dwarf strandveld shrubland at Koeberg Nature Reserve, South Africa. Habitat characteristics of nest sites differed significantly among species, indicating strong nest-site partitioning. The principal variables distinguishing nest-site characteristics among species (substrate height, cover at 1m, cover at 2m) were features that distinguish tall-shrub species which are strongly associated with patches of Dune Thicket from shorter-shrub species which are strongly associated with more open Sand Plain Fynbos. Two groups of species which differ primarily in their selection of habitat patch type within the patchy nesting landscape were identified. One group nested predominantly in low shrubs associated with open Sand Plain Fynbos. A second group nested at a variety of heights within tall-shrub species associated with Dune Thicket. Species within each of these groups differed from each other in their relative nest height (ratio of nest height to substrate height), distance of nest from foliage edge, nest concealment and choice of particular substrate plant species. On average, stepwise discriminant function analysis classified 52.6% of the nest sites correctly as belonging to one of the 14 species, considerably better than the expected random classification of 11.8%. Individual species' classifications were 2–12 times better than a random classification. We suggest that high levels of nest predation may have selected for strong nest-site partitioning in this community. Ostrich 2004, 75(4): 250–258

    Examples of species with different types of fitted density-yield functions.

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    <p>(A, F) Cattle Egret <i>Bubulcus ibis</i>, which at all production targets is a winner for which land sparing is the best strategy. (B, G) Common Bulbul <i>Pycnonotus barbatus</i>, a winner for which land sharing is always the best strategy. (C, H) Black-necked Weaver <i>Ploceus nigricollis</i>, a loser for which land sparing is always the best strategy. (D, I) Splendid-glossy Starling <i>Lamprotornis splendidus</i>, a loser for which the best strategy depends on the production target. (E, J) Black-headed Weaver <i>Ploceus melanocephalus</i>, a winner for which the best strategy depends on the production target.</p

    Winners and losers with food energy production targets by range size.

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    <p>Number of species which have larger total populations with than without agriculture (winners: light colours) and those with smaller total populations (losers: dark colours) in relation to the production target for food energy. Species which have their largest total populations with the highest energy yield and land sparing (red/pink) those with largest populations with lowest permissible energy yield (land sharing: dark/light blue) and those benefitting most from intermediate yield (dark/light purple) are shown separately. Conventions are as for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0054597#pone-0054597-g003" target="_blank">Figure 3</a>. A is for species with a large global range, B is for species with a small global range.</p
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