scispace - formally typeset
Search or ask a question
Author

Barend F.N. Erasmus

Bio: Barend F.N. Erasmus is an academic researcher from University of the Witwatersrand. The author has contributed to research in topics: Climate change & Vegetation. The author has an hindex of 29, co-authored 93 publications receiving 9608 citations. Previous affiliations of Barend F.N. Erasmus include University of York & University of Pretoria.


Papers
More filters
Proceedings ArticleDOI
07 Jul 2008
TL;DR: This paper proposes a method which combines rapid static DGPS, EDM topographic surveying and mobile GIS techniques to capture, compute and record absolute positions and vegetation parameters of preferred fuelwood tree species in African savanna woodlands.
Abstract: Most rural and some low-income urban households in southern Africa rely on fuelwood and charcoal to meet their domestic energy demands, targeting specific tree species for their calorific value. The lack of quantitative data on extractable standing woody biomass makes it difficult for energy planners to ascertain the sustainability of exploiting such resources. Large scale estimation of biomass using ground-based methods is both tedious and time-consuming. Optical remote sensing techniques are constrained by adverse atmospheric conditions such as clouds and haze, and in any case survey only the upper surface of the vegetation canopy. Recent advances in synthetic aperture radar (SAR) remote sensing and Global Positioning Systems (GPS) technologies coupled with geographic information systems (GIS) offer innovative ways to quantify and assess available woody biomass. Tree species heterogeneity in savanna woodlands requires training data with minimal target-to-image noise to distinguish tree vegetation on SAR imagery. The absolute positioning of trees is critical for correlating ground survey measurements with the corresponding aerial photography or satellite positions. The ground truth data is useful for calibrating and validating radar satellite imagery in biomass assessment surveys. GPS offers rapid methods of establishing both control and capturing field data. While Differential-GPS gives highly accurate ground positions, Electronic Distance Meter (EDM) surveying techniques are used to compliment GPS measurements when field conditions are not favourable. GPS accuracy is degraded when receivers are operated under dense tree canopies. Connecting field surveys to national mapping systems or GPS networks allows easy integration of woodland spatial information with data from other sectors. This is constrained by the lack of common reference frameworks. In Africa, a unified African Reference Framework (AFREF) is still in its formative stages and network GPS is not yet fully developed. South Africa is the probably the only country that has a well developed GPS infrastructure. Although commercial GPS base stations are available, the required initial capital investment and annual maintenance charges often limit their use in developing countries. This paper proposes a method which combines rapid static DGPS, EDM topographic surveying and mobile GIS techniques to capture, compute and record absolute positions and vegetation parameters of preferred fuelwood tree species in African savanna woodlands. The proposed method will generate ground-truth data for preferred fuelwood species in selected case study villages under the VW Foundation Biofuels Modeling project, covering Zambia, Mozambique and South Africa.

11 citations

Journal ArticleDOI
TL;DR: Here, the contribution made by browse to the diet of sable in the study area is quantified and a substantial amount of browsing by sable is observed in this study area during the dry season.
Abstract: The late dry season is a crucial period for grazing ungulates because the nutritional value of the remaining brown grass is lowest then and levels of crude protein and digestible organic matter may fall below the maintenance requirements of herbivores (Owen-Smith, 1982). During this adverse period, mixed feeders like impala (Aepyceros melampus) increase the proportion of browse in the form of the leaves of the woody plants they consume (Owen-Smith & Cooper, 1985). Crude protein levels are generally higher and seasonally more constant in foliage of woody plants than in grasses (Owen-Smith, 1982), but the foliage is commonly defended by tannins or spines that restrict consumption by grazers not adapted to cope with them (Cooper & Owen-Smith, 1985, 1986; Cooper, Owen-Smith & Bryant, 1988). Sable antelope (Hippotragus niger) are predominantly grazers and are distributed throughout southern African savannahs (Estes, 1991; Skinner & Chimimba, 2005) where the dry season is prolonged and ambient temperatures are high before the rains begin. Grass quality is especially poor on infertile, sandy soils (Bell, 1984). Sable typically depend on green grass persisting in drainage sump grasslands or in recently burned areas during the dry season (Estes & Estes, 1974; Parrini & Owen-Smith, 2009). However, contrary to previous reports, we observed a substantial amount of browsing by sable in our study area during the dry season. Here, we quantify the contribution made by browse to the diet of sable in our study area. Methods

10 citations

Journal Article
TL;DR: In this paper, the authors quantified and compared tree canopy cover and height distributions between areas of contrasting management in the Lowveld savanna region of South Africa, a region connecting communal landscapes with heavy utilization (especially fuel wood harvesting) to fully protected public (Kruger National Park) and private reserves (SabiSand Game Reserve) that conserve biodiversity.

10 citations

Journal ArticleDOI
TL;DR: The Carnegie Airborne Observatory is made possible by the Avatar Alliance Foundation, Margaret A. Cargill Foundation, John D. and Catherine T. MacArthur Foundation, G.M. Keck Foundation, Gordon and Betty Moore Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr as mentioned in this paper.
Abstract: The Carnegie Airborne Observatory is made possible by the Avatar Alliance Foundation, Margaret A. Cargill Foundation, John D. and Catherine T. MacArthur Foundation, Grantham Foundation for the Protection of the Environment, W.M. Keck Foundation, Gordon and Betty Moore Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr. and William R. Hearst III. Application of the CAO data in South Africa is made possible by the Andrew Mellon Foundation and the endowment of the Carnegie Institution for Science.

10 citations

Journal ArticleDOI
TL;DR: Ward et al. as discussed by the authors assessed the species composition of the riparian woodland in 2007/2008 along belt transects, recording living and dead individuals in different size classes plus signs of elephant damage and the presence of juvenile plants.
Abstract: Co-ordinating Editor: David Ward Abstract Questions: How has the composition and diversity of canopy tree species in a riparian woodland changed over time? How are the compositional changes related to impact of elephants? Does the composition of juvenile plants indicate that the woodland retains the potential to recover its former composition? Location: Northern Botswana adjoining the Linyanti River. Methods: We assessed the species composition of the riparian woodland in 2007/2008 along belt transects, recording living and dead individuals in different size classes plus signs of elephant damage and the presence of juvenile plants. We related this current composition to the composition recorded in a previous survey in 1991/1992 and reconstructed the earlier composition by combining living and dead trees recorded in 1991/1992. We established the association between mortality and impact agent, severity, year and size class using model selection statistics. Changes in species diversity were assessed using the Shannon diversity index. Results: The composition of canopy trees changed from the initial dominance of two Acacia spp. towards the current situation with these two species forming <5% of the woodland canopy. Dead trees were strongly associated with severe damage inflicted by elephants, including bark stripping and felling. As the acacia trees declined, elephant impacts shifted onto other canopy tree species. The woodland canopy became progressively more open because recruitment from juvenile and sapling stages to replace trees that had died was also suppressed. Nevertheless, the tree species that had decreased in abundance in the canopy remained abundant as juvenile plants. Conclusion: Substantial changes in woodland composition can occur in the presence of high elephant concentrations because of the selective damage that elephants impose on particular tree species and size classes. The loss of functionally important species may not be reflected by changes in compositional diversity measures.

9 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.

13,120 citations

Journal ArticleDOI
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.

7,589 citations

Journal ArticleDOI
08 Jan 2004-Nature
TL;DR: Estimates of extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.
Abstract: Climate change over the past approximately 30 years has produced numerous shifts in the distributions and abundances of species and has been implicated in one species-level extinction. Using projections of species' distributions for future climate scenarios, we assess extinction risks for sample regions that cover some 20% of the Earth's terrestrial surface. Exploring three approaches in which the estimated probability of extinction shows a power-law relationship with geographical range size, we predict, on the basis of mid-range climate-warming scenarios for 2050, that 15-37% of species in our sample of regions and taxa will be 'committed to extinction'. When the average of the three methods and two dispersal scenarios is taken, minimal climate-warming scenarios produce lower projections of species committed to extinction ( approximately 18%) than mid-range ( approximately 24%) and maximum-change ( approximately 35%) scenarios. These estimates show the importance of rapid implementation of technologies to decrease greenhouse gas emissions and strategies for carbon sequestration.

7,089 citations

Journal ArticleDOI
TL;DR: An overview of recent advances in species distribution models, and new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales are suggested.
Abstract: In the last two decades, interest in species distribution models (SDMs) of plants and animals has grown dramatically. Recent advances in SDMs allow us to potentially forecast anthropogenic effects on patterns of biodiversity at different spatial scales. However, some limitations still preclude the use of SDMs in many theoretical and practical applications. Here, we provide an overview of recent advances in this field, discuss the ecological principles and assumptions underpinning SDMs, and highlight critical limitations and decisions inherent in the construction and evaluation of SDMs. Particular emphasis is given to the use of SDMs for the assessment of climate change impacts and conservation management issues. We suggest new avenues for incorporating species migration, population dynamics, biotic interactions and community ecology into SDMs at multiple spatial scales. Addressing all these issues requires a better integration of SDMs with ecological theory.

5,620 citations

Journal ArticleDOI
TL;DR: This paper presents a tuning method that uses presence-only data for parameter tuning, and introduces several concepts that improve the predictive accuracy and running time of Maxent and describes a new logistic output format that gives an estimate of probability of presence.
Abstract: Accurate modeling of geographic distributions of species is crucial to various applications in ecology and conservation. The best performing techniques often require some parameter tuning, which may be prohibitively time-consuming to do separately for each species, or unreliable for small or biased datasets. Additionally, even with the abundance of good quality data, users interested in the application of species models need not have the statistical knowledge required for detailed tuning. In such cases, it is desirable to use "default settings", tuned and validated on diverse datasets. Maxent is a recently introduced modeling technique, achieving high predictive accuracy and enjoying several additional attractive properties. The performance of Maxent is influenced by a moderate number of parameters. The first contribution of this paper is the empirical tuning of these parameters. Since many datasets lack information about species absence, we present a tuning method that uses presence-only data. We evaluate our method on independently collected high-quality presence-absence data. In addition to tuning, we introduce several concepts that improve the predictive accuracy and running time of Maxent. We introduce "hinge features" that model more complex relationships in the training data; we describe a new logistic output format that gives an estimate of probability of presence; finally we explore "background sampling" strategies that cope with sample selection bias and decrease model-building time. Our evaluation, based on a diverse dataset of 226 species from 6 regions, shows: 1) default settings tuned on presence-only data achieve performance which is almost as good as if they had been tuned on the evaluation data itself; 2) hinge features substantially improve model performance; 3) logistic output improves model calibration, so that large differences in output values correspond better to large differences in suitability; 4) "target-group" background sampling can give much better predictive performance than random background sampling; 5) random background sampling results in a dramatic decrease in running time, with no decrease in model performance.

5,314 citations