Seasonally and spatially referenced estimates of recreational shore-angling effort,catch composition,catch rates and total catch in the Goukamma Marine Protected Area,South Africa

A roving creel survey of the recreational shore fishery along the 16.4-km coastline in the Goukamma Marine Protected Area on the south coast of South Africa was conducted from 2009 to 2011. Some 838 patrols were stratified equally among months, areas and years, but intentionally biased towards weekends. Angler densities at Buffalo Bay and Groenvlei were 0.59 and 0.28 anglers km?1, respectively. Weekend densities were double to quadruple weekday densities and fishing during winter was more popular than during summer. Area, habitat and distance to access points explained variation in angler densities. Shannon–Wiener diversity in catches declined from 2.18 in an earlier (1993–2002) survey to 1.79. Although the order of species abundance in the catches remained largely unchanged, blacktail Diplodus capensis dominance increased to 57.3% by number, at the expense of galjoen Dichistius capensis. Habitat explained 27% of the variance in catch composition. The catch per unit effort (CPUE) for the top nine species ranged from 0.19 to 6.35 fish 100-h?1. The CPUE of all species, except spotted grunter Pomadasys commersonnii, declined. Blacktail and galjoen CPUE declined by 17% and 77%, respectively. The total catch estimate was 2 986 fish y?1. Transgressions of size limits were common. The results suggest that the fishery is overexploited and that catch rates are declining.     

Classification of marine bioregions on the east coast of South Africa

Marine bioregional planning requires a meaningful classification and spatial delineation of the ocean environment using biological and physical characteristics. The relative inaccessibility of much of the ocean and the paucity of directly measured data spanning entire planning regions mean that surrogate data, such as satellite imagery, are frequently used to develop spatial classifications. However, due to a lack of appropriate biological data, these classifications often rely on abiotic variables, which act as surrogates for biodiversity. The aim of this study was to produce a fine-scale bioregional classification, using multivariate clustering, for the inshore and offshore marine environment off the east coast of South Africa, adjacent to the province of KwaZulu-Natal and out to the boundary of the exclusive economic zone (EEZ), 200 nautical miles offshore. We used remotely sensed data of sea surface temperature, chlorophyll a and turbidity, together with interpolated bathymetry and continental-slope data, as well as additional inshore data on sediments, seabed oxygen and bottom temperature. A multivariate k-means analysis was used to produce a fine-scale marine bioregionalisation, with three bioregions subdivided into 12 biozones. The offshore classification was primarily a pelagic bioregionalisation, whereas the inshore classification (on the continental shelf) was a coupled benthopelagic bioregionalisation, owing to the availability of benthic data for this area. The resulting classification was used as a base layer for a systematic conservation plan developed for the province, and provided the methods for subsequent planning conducted for the entire South African EEZ. Validation of the classification is currently being conducted in marine research programmes that are sampling benthic biota and habitats in a sampling design stratified according to the biozones delineated in this study.     

Assessment of carbon in woody plants and soil across a vineyard-woodland landscape

Background

Quantification of ecosystem services, such as carbon (C) storage, can demonstrate the benefits of managing for both production and habitat conservation in agricultural landscapes. In this study, we evaluated C stocks and woody plant diversity across vineyard blocks and adjoining woodland ecosystems (wildlands) for an organic vineyard in northern California. Carbon was measured in soil from 44 one m deep pits, and in aboveground woody biomass from 93 vegetation plots. These data were combined with physical landscape variables to model C stocks using a geographic information system and multivariate linear regression.

Results

Field data showed wildlands to be heterogeneous in both C stocks and woody tree diversity, reflecting the mosaic of several different vegetation types, and storing on average 36.8 Mg C/ha in aboveground woody biomass and 89.3 Mg C/ha in soil. Not surprisingly, vineyard blocks showed less variation in above- and belowground C, with an average of 3.0 and 84.1 Mg C/ha, respectively.

Conclusions

This research demonstrates that vineyards managed with practices that conserve some fraction of adjoining wildlands yield benefits for increasing overall C stocks and species and habitat diversity in integrated agricultural landscapes. For such complex landscapes, high resolution spatial modeling is challenging and requires accurate characterization of the landscape by vegetation type, physical structure, sufficient sampling, and allometric equations that relate tree species to each landscape. Geographic information systems and remote sensing techniques are useful for integrating the above variables into an analysis platform to estimate C stocks in these working landscapes, thereby helping land managers qualify for greenhouse gas mitigation credits. Carbon policy in California, however, shows a lack of focus on C stocks compared to emissions, and on agriculture compared to other sectors. Correcting these policy shortcomings could create incentives for ecosystem service provision, including C storage, as well as encourage better farm stewardship and habitat conservation.