Partial migration (when only some individuals in a population undertake seasonal migrations) is common in many species and geographical contexts. Despite the development of modern statistical methods for analyzing partial migration, there have been no studies on what influences partial migration in tropical environments. We present research on factors affecting partial migration in African buffalo (Syncerus caffer) in northeastern Namibia. Our dataset is derived from 32 satellite tracking collars, spans 4 years and contains over 35,000 locations. We used remotely sensed data to quantify various factors that buffalo experience in the dry season when making decisions on whether and how far to migrate, including potential man-made and natural barriers, as well as spatial and temporal heterogeneity in environmental conditions. Using an information-theoretic, non-linear regression approach, our analyses showed that buffalo in this area can be divided into 4 migratory classes: migrants, non-migrants, dispersers, and a new class that we call “expanders”. Multimodel inference from least-squares regressions of wet season movements showed that environmental conditions (rainfall, fires, woodland cover, vegetation biomass), distance to the nearest barrier (river, fence, cultivated area) and social factors (age, size of herd at capture) were all important in explaining variation in migratory behaviour. The relative contributions of these variables to partial migration have not previously been assessed for ungulates in the tropics. Understanding the factors driving migratory decisions of wildlife will lead to better-informed conservation and land-use decisions in this area.

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Summary1. Most hypotheses for translocation success are elaborate, hierarchical, and untested combinations of socio-ecological predictors. Empirical support for those tested is vulnerable to spurious single-predictor relationships and does not account for the hierarchy amongst predictors and nonindependence amongst individuals or cohorts. Testing hypotheses as a priori multi-level models promotes stronger inference. 2. We apply a 25-year (1981-2005) data base including 89 reintroduction and 102 restocking events that released 682 black rhinoceros Diceros bicornis into 81 reserves to test 24 hypotheses for translocation success, defined as survival to 1 year post-release. We made information-theoretic comparisons of hypotheses represented as hierarchical models incorporating random effects for reserve and release cohort predictors of death. 3. Mortality rates after restocking were higher than for reintroductions (13AE4 cf. 7AE9%, respectively) due largely to intraspecific fighting. No predictors strongly influenced reintroduction success, although cohorts consisting entirely of adult males were 8AE2% of individuals but contributed 21AE9% of deaths, and reserves with lowest carrying capacities (i.e. <0AE1 rhino km )2 ) had a 16AE3% mortality rate. Most models for restocking success were not supported. Only those including age class received substantial support. Age was the only predictor to strongly influence death rates. Predictors previously thought influential, like population density, reserve area and quality, and cohort size, were not supported. 4. Synthesis and applications. Simple rules succeeded where complex ecological and demographic hypotheses failed to predict survival after translocation of critically endangered black rhinoceros. Results support bold attempts by managers at translocations towards species recovery in most ways that they have historically occurred. Groups of rhinoceros of different size and composition can be successfully moved over large distances between different ecological contexts. Also, the release of cohorts into reserves that are relatively small, poorer habitat or already stocked need not be avoided so long as calves and all-male cohorts are not reintroduced, and only adults used for restocking. Our analysis demonstrates the importance of information-theoretic comparisons of a priori hierarchical models to test hypotheses for conservation management. We caution against interpreting simple correlations or regression amongst a large number of nested ecological and demographic variables.

Migrations of most animal taxa are declining as a result of anthropogenic pressures and land-use transformation. Here, we document and characterize a previously unknown multi-country migration of Burchell's zebra Equus quagga that is the longest of all recorded large mammal migrations in Africa. Our data from eight adult female zebras collared on the border of Namibia and Botswana show that in December 2012 all individuals crossed the Chobe River and moved due south to Nxai Pan National Park in Botswana, where they spent a mean duration of 10 weeks before returning, less directly, to their dry season floodplain habitat. The same southward movements were also observed in December 2013. Nxai Pan appeared to have similar environmental conditions to several possible alternative wet season destinations that were closer to the dry season habitat on the Chobe River, and water availability, but not habitat or vegetation biomass, was associated with higher-use areas along the migratory pathway. These results suggest a genetic and/or cultural basis for the choice of migration destination, rather than an environmental one. Regardless of the cause, the round-trip, straight-line migration distance of 500 km is greater than that covered by wildebeest Connochaetes taurinus during their well-known seasonal journey in the Serengeti ecosystem. It merits conservation attention, given the decline of large-scale ecological processes such as animal migrations.

Connectivity conservation is aimed at sustaining animal movements and ecological processes important to ecosystem functioning and the maintenance of biodiversity. However, connectivity conservation plans are typically developed around a single species and rarely empirically evaluated for their relevance to others, thereby limiting our understanding of how connectivity requirements differ across species. We used an omnidirectional application of circuit theory and GPS data from six species to evaluate connectivity at multiple scales for multiple species within the world's largest transfrontier conservation landscape in southern Africa. We evaluated the effects of linear barriers, natural habitat types and anthropogenic land use on movement. We identified multispecies connectivity hotspots as areas where current flow was concentrated or channelled through pinch points. To evaluate surrogate species for connectivity, we evaluated the correspondence among single‐species connectivity across the entire landscape and also examined whether a more localized corridor for African savanna elephant Loxodonta africana captured high multispecies connectivity values. Connectivity models revealed many intact areas across the landscape with diffuse current flow, but also evidence that fences, rivers, roads and areas of anthropogenic use acted as strong barriers to movement—particularly in the case of fences, which completely blocked female elephant movement. Tests of correspondence among single‐species connectivity models revealed spotted hyaena and African wild dog as the strongest surrogate species of connectivity. Female elephants were found to be the weakest surrogate species of connectivity at the landscape scale. However, focusing within a localized elephant corridor revealed the areas of concentrated or channelled connectivity for most species in our study. Synthesis and applications. Our results suggest that the single‐species focus permeating connectivity literature may result in conservation plans that poorly conserve the connectivity needs of co‐occurring species. Our study also highlights the importance of testing the efficacy of surrogate species for connectivity at multiple scales. We recommend evaluating multispecies connectivity to prioritize areas for conservation that safeguard the connectivity needs of multiple species of conservation concern.