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As a first step in stock identification of estuarine round herring Gilchristella aestuaria, a morphometric analysis of multiple standardised traits and body condition was conducted on samples from sites across the distribution range of the species, including freshwater and estuarine populations. Multivariate analyses, including a principal component analysis (PCA), revealed that sites on the same river system and sites in close geographic proximity tend to share morphometric traits. Most of the variation in PCA was due to caudal fin length (CFL). Single traits were analysed with generalised additive models with river system location as the smooth term. CFL was strongly related to river systems, and to a lesser extent salinity and turbidity. Unlike previous local-scale studies, this broad-scale study did not support the notion of ecotypes based on eye diameter. Condition indices like body depth and relative weight were related to climatic conditions, salinity and turbidity, more than to river system. The findings agree with previous studies on phylogenetic history and limited gene flow in G. aestuaria, and suggest variation in environmental productivity that affects body condition in different populations. Subsequent research should examine temporal changes in traits like CFL and body condition based on long-term seasonal sampling. Safeguarding this potential resource may be enabled by adopting appropriate management methods based on delineation of stocks with different levels of productivity and connectivity, before widespread fishing of this species is promoted.

The use of action cameras for underwater video sampling provides a non-harmful alternative for monitoring endangered and threatened fish populations in clear headwater streams. Here, we examine the...

A South African inland fisheries policy will depend on a reliable long-term supply of social-ecological data covering freshwater fisheries at a broad geographic scale. Approaches to systematic planning of research and monitoring are demonstrated herein, based on a fishery-independent gillnet dataset covering 44 dams, and geographic information system maps of monthly and annual climate variables, human land use, and road access in a 5 km zone around 442 dams. Generalised linear mixed models were used to determine the covariates of gillnet catch per unit effort. Such covariates are required for a model-based process to select a subset of state-owned dams for a long-term fishery survey programme. The models indicated a monthly climate influence on catch per unit effort and climatic drivers of fish species distributions. However, unexplained variation is overwhelming and precludes a model-based survey design process. Non-hierarchical clustering of 442 dams was then done based on annual climate and human land use variables around dams. The resulting clusters of dams with shared climate and land use characteristics indicates the types of dams that should be selected for monitoring to represent the full range of climate and land use characteristics. Surrounding land use could indicate the socioeconomic characteristics of fisheries, for example, dams that may support subsistence-based communities that require increased research effort. Finally, although primary catchments could be useful for organising national-scale management, land use cover in the 5 km zone around dams varied widely within the respective primary catchments. Beyond these proposed approaches to plan research, this study also reveals various data deficiencies and recommends additional future studies on other possible methods for systematic research planning.

Abalones are poikilotherms, and their rate of development is intrinsically linked with temperature. Understanding the effect of temperature on development is key for the successful production planning in abalone hatcheries and the reseeding of cultured abalone larvae for stock enhancement. This study investigates the effect of temperature on the development of the abalone larvae Haliotis midae. Newly hatched trochophore larvae were raised at temperatures of 14°C, 16°C, 18°C, 20°C, and 22°C until settlement. The temperature had a significant effect on the larval development—most rapid at 22°C [3 days and 65 degree-days (DD), °C day] and slowest at 14°C (6.7 days and 95 DD). Larval settlement was highest at 22°C (43.44% ± 3.73%, larvae). Larvae should preferably be seeded at temperatures between 20°C and 22°C as this will potentially increase settlement, thereby reducing larval dispersion outside of the seeding area.

Using the Southern African Bird Atlas Project (SABAP2) as a case study, we examine the possible determinants of spatial bias in volunteer sampling effort and how well such biased data represent environmental gradients across the area covered by the atlas. For each province in South Africa, we used generalized linear mixed models to determine the combination of variables that explain spatial variation in sampling effort (number of visits per 5′ × 5′ grid cell, or “pentad”). The explanatory variables were distance to major road and exceptional birding locations or “sampling hubs,” percentage cover of protected, urban, and cultivated area, and the climate variables mean annual precipitation, winter temperatures, and summer temperatures. Further, we used the climate variables and plant biomes to define subsets of pentads representing environmental zones across South Africa, Lesotho, and Swaziland. For each environmental zone, we quantified sampling intensity, and we assessed sampling completeness with species accumulation curves fitted to the asymptotic Lomolino model. Sampling effort was highest close to sampling hubs, major roads, urban areas, and protected areas. Cultivated area and the climate variables were less important. Further, environmental zones were not evenly represented by current data and the zones varied in the amount of sampling required representing the species that are present. SABAP2 volunteers' preferences in birding locations cause spatial bias in the dataset that should be taken into account when analyzing these data. Large parts of South Africa remain underrepresented, which may restrict the kind of ecological questions that may be addressed. However, sampling bias may be improved by directing volunteers toward undersampled regions while taking into account volunteer preferences.

Episodic river flooding has the capacity to ‘reset’ estuaries and redirect these systems on a new path towards some sort of dynamic physical and biological equilibrium. A major river flood through the Kariega Estuary, South Africa, during 2012, provided an ideal opportunity to monitor the occupation of seagrass (Zostera capensis) beds by juveniles of the marine sparid Rhabdosargus holubi, post flood recovery. The estuary contained extensive dense submerged Z. capensis beds throughout the system prior to the flood, almost all of which was removed from the system as a result of the flood. Over the following four years there was a gradual recovery in the extent of cover of submerged Z. capensis beds, which by the end of 2015 had recovered to near the same levels of cover as the pre-flood conditions. In addition to the positive relationship between seagrass development and R. holubi abundance that was recorded, there was also a greater utilisation of this habitat type by the smaller (10–40 mm SL) compared to the larger (41–60 mm SL) juvenile size classes. This new finding emphasizes that occupation of particular estuarine nursery habitats by the juveniles of estuary-associated fish species may not necessarily be uniform and may change with age. The study also reinforces the changing nature of estuarine environments over time and highlights, once again, the importance of this habitat type for the most abundant estuary-dependent marine fish species on the African subcontinent.

B.J.v.R. and S.H. acknowledge the support from the University of Pretoria and the DST-NRF Centre of Excellence for Invasion Biology.

The spatial distribution of alien species richness often correlates positively with native species richness, and reflects the role of human density and activity, and primary productivity and habitat heterogeneity, in facilitating the establishment and spread of alien species. Here, we investigate the relationship between the spatial distribution of alien bird species, human density, and anthropogenic and natural environmental conditions. Next, we examined the relationship between the spatial distribution of alien bird species and native bird species richness. We examined alien species richness as a response variable, using correlative analyses that take spatial autocorrelation into account. Further, each alien bird species was examined as a response variable, using logistic regression procedures based on binary presence–absence data. A combination of human density and natural habitat heterogeneity best explained the spatial distribution of alien species richness. This contrasts with the results for individual alien species and with previous studies on other non-native taxa showing the importance of primary productivity and anthropogenic habitat modification as explanatory variables. In general, native species richness is an important correlate of the spatial distribution of alien species richness and individual alien species, with alien species being more similar to common species than to rare species.

Aim: To investigate explanations for the maintenance of a positive spatial species richness-human population density correlation at broad scales, despite the negative impact of humans on species richness. These are (hypotheses 1-4): (1) human activities that create a habitat mosaic and (2) a more favourable climate, and (3) adequate conservation measures (e.g. sufficient natural habitat), maintain the positive species richness-human density correlation; or (4) the full range of human densities decrease the slope of the correlation without changing its form. Location: South Africa. Methods: Avian species richness data from atlas distribution maps and human population density data derived from 2001 census results were converted to a quarter-degree resolution. We investigated the number of land transformation types (anthropogenic habitat heterogeneity), irrigated area (increasing productivity), and other covarying factors (e.g. primary productivity) as predictors of species richness. We compared species richness-human density relationships among regions with different amounts of natural habitat, and investigated whether the full range of human densities decrease species richness in relation to primary productivity. Results: Hypotheses 1, 2 and 3 were supported. Human densities and activities that increase habitat heterogeneity and productivity are important beneficial factors to common species, but not to rare species. The species richness-human density relationship persists only at low land transformation levels, and no significant relationship exists at higher levels. For common species, the relationship becomes non-significant at lower land transformation levels than for rare species. Main conclusions: The persistence of the species richness-human density relationship depends mostly on the amount of remaining natural habitat. In addition, certain human activities benefit especially common species. Common species seem to be more flexible than rare species in response to human activity and habitat loss. © 2008 The Authors Journal compilation

The distributions of naturalised alien plant species that have invaded natural or semi-natural habitat are often geographically restricted by the environmental conditions in their new range, implying that alien species with similar environmental requirements and tolerances may form assemblages and characterise particular areas. The aim of this study was to use objective numerical techniques to reveal any possible alien phytogeographic regions (i.e. geographic areas with characteristic alien plant assemblages) in southern Africa. Quarter degree resolution presence records of naturalised alien plant species of South Africa, Lesotho, Swaziland, Namibia and Botswana were analysed through a divisive hierarchical classification technique, and the output was plotted on maps for further interpretation. The analyses revealed two main alien phytogeographic regions that could be subdivided into eight lower level phytogeographic regions. Along with knowledge of the environmental requirements of the characteristic species and supported by further statistical analyses, we hypothesised on the main drivers of alien phytogeographic regions, and suggest that environmental features such as climate and associated biomes were most important, followed by human activities that modify climatic and vegetation features, such as irrigation and agriculture. Most of the characteristic species are not currently well-known as invasive plant species, but many may have potential to become troublesome in the future. Considering the possibility of biotic homogenization, these findings have implications for predicting the characteristics of the plant assemblages of the future. However, the relatively low quality of the dataset necessitates further more in-depth studies with improved data before the findings could be directly beneficial for management.