It is generally assumed that birds build nests according to a genetic ‘template’, little influenced by learning or memory. One way to confirm the role of genetics in nest building is to assess the repeatability of nest morphology with repeated nest attempts. Solitary weaver birds, which build multiple nests in a single breeding season, are a useful group with which to do this. Here we show that repeatability of nest morphology was low, but significant, in male Southern Masked weaver birds and not significant in the Village weavers. The larger bodied Village weavers built larger nests than did Southern Masked weavers, but body size did not explain variation in Southern Masked weaver nest dimensions. Nests built by the same male in both species got shorter and lighter as more nests were constructed. While these data demonstrate the potential for a genetic component of variation in nest building in solitary weavers, it is also clear that there remains plenty of scope in both of these species for experience to shape nest construction.

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SummaryCape Vulture Gyps coprotheres is endemic to southern Africa and is globally threatened. Colonies in Botswana comprise part of one of the two core breeding areas in the species's range, and very little has previously been published about them. Ground censusing of 11 Cape Vulture sites in Botswana was undertaken from 1992 to 1999, continuing a monitoring programme initiated by the authors in 1984. Survey methods and census procedures are documented. The potential Cape Vulture breeding population in Botswana is estimated to be about 600 pairs, comprising at least 100 pairs at Mannyelanong in the south-east and about 500 pairs in eastern Botswana. This represents an increase from previous estimates, and reflects improved census techniques rather than an increase in population size. The mean turnover rate of nest site usage from one year to the next averaged 21% at Mannyelanong, and was about 26% at Manong Yeng in eastern Botswana. Annual productivity of nest sites increased with the number of years the site had been occupied. Over the eight years of study eggs were laid in at least 436 of 477 nests (91.4%) at Mannyelanong; chicks survived to mid season (60-80 days old) in 327 nests (75% of eggs laid), and fledged (best estimate) in 248 nests (56.9% of eggs laid and 52% of pairs attempting to breed). In eastern Botswana eggs were laid in at least 1,825 of 2,101 nests (86.9%); chicks survived to mid season in 1,272 nests (69.7% of eggs laid). Two seasons have been excluded for eastern Botswana (1994 and1995) due to incomplete data, and breeding success can be estimated only from 1997 to 1999: of 990 eggs laid out of 1,108 nests, chicks fledged in 384 nests (38.8% of eggs laid and 34.6% of pairs attempting to breed). The eastern Botswana breeding population remains in a state of flux following the collapse of a primary colony that was the country's Cape Vulture stronghold. Conservation concerns and the vulnerability of Cape Vulture sites are discussed.

Summary1. The habitat requirements of various species have been evaluated by statistical models. However, recent studies have shown that models are often not transferable between regions, limiting their applicability and ability to inform management decisions. One possible cause is that models tend to reflect dominant landscape features, which vary between regions. Transferability, and thus applicability, may be increased by developing models from multiple regions. 2. We addressed this via a case study of two vulture species (white-backed and lappet-faced vultures, Gyps africanus and Aegypius tracheliotos) from six biogeographically different regions across southern Africa. Logistic models, developed using an information-theoretic approach, were used to predict nest occurrence based on explanatory variables derived from a Geographic Information System (GIS), the usual method for species with large ranges. Variables reflected key requirements at different spatial scales: food availability, human disturbance and nesting trees. We developed models using data from single and multiple regions, and tested the cross-regional transferability. We also collected field data to asses the adequacy of the GIS variables. 3. There was a significant negative correlation between specificity and regional generality, multiregion models tending to be more consistently transferable than single-region models but having a weaker fit within the regions where they were developed. Multi-region models of nesting habitat were more structurally similar to each other than single-region models. GIS variables adequately represented the landscape but with differing adequacy between regions. There were no observed fitness benefits to the observed site selection. 4. Synthesis and applications. Models of species distribution are not transferable between regions, and use of models to inform management decisions in regions other than that used for model development should be undertaken with caution. Models are often built using GIS predictors only broadly related to the landscape properties of interest and the adequacy of such proxies can vary between regions, leading to models that emphasize dominant landscape features. Models developed from multiple regions partially overcome this problem by identifying predictors that apply across many regions and are more transferable. However, this increased generality trades off against reduced specificity. Models should be constructed with consideration to their intended use.

The White‐headed Vulture Trigonoceps occipitalis (WhV) is uncommon and largely restricted to protected areas across its range in sub‐Saharan Africa. We used the World Database on Protected Areas to identify protected areas (PAs) likely to contain White‐headed Vultures. Vulture occurrence on road transects in Southern, East, and West Africa was adjusted to nests per km2 using data from areas with known numbers of nests and corresponding road transect data. Nest density was used to calculate the number of WhV nests within identified PAs and from there extrapolated to estimate the global population. Across a fragmented range, 400 PAs are estimated to contain 1893 WhV nests. Eastern Africa is estimated to contain 721 nests, Central Africa 548 nests, Southern Africa 468 nests, and West Africa 156 nests. Including immature and nonbreeding birds, and accounting for data deficient PAs, the estimated global population is 5475 ‐ 5493 birds. The identified distribution highlights are alarming: over 78% (n = 313) of identified PAs contain fewer than five nests. A further 17% (n = 68) of PAs contain 5 ‐ 20 nests and 4% (n = 14) of identified PAs are estimated to contain >20 nests. Just 1% (n = 5) of PAs are estimated to contain >40 nests; none is located in West Africa. Whilst ranging behavior of WhVs is currently unknown, 35% of PAs large enough to hold >20 nests are isolated by more than 100 km from other PAs. Spatially discrete and unpredictable mortality events such as poisoning pose major threats to small localized vulture populations and will accelerate ongoing local extinctions. Apart from reducing the threat of poisoning events, conservation actions promoting linkages between protected areas should be pursued. Identifying potential areas for assisted re‐establishment via translocation offers the potential to expand the range of this species and alleviate risk.