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Research Publications (Systems Science)

Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/842

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Author: search.filters.author.Duffy, Kevin JanHas files: Yes

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    Indigenous strategies and empirical models for adaptability of the maize-bean intercropping system to climate change
    (UZ Foundatoin, 2016-12) Mapanda, S.; Chitja, J. M.; Duffy, Kevin Jan
    This review article discusses on different ways of indigenous strategies and empirical models as an adaptation to climate change by smallholder farmers in Africa. Indigenous adaptation strategies are methods that enable individuals or communities to adjust to the impacts of climate change in local areas. Some of the strategies practiced are: zero tillage, mulching, soil management techniques, organic agriculture and fallow system of cultiva-tion, intercropping with legumes, early planting and use of tolerant varieties to drought, water conservation and crop diversification. Scientists developed many empirical models that are used to project the impact of climate change to agriculture. Some of the empirical models include: CERES-Maize Crop Model, Global Circulation Models (GCM) and histori-cal data records. There is also use of empirical evidence such as indigenous land unit framework, indigenous early warning systems, use of rainmakers, movement of birds, ants and crying of dogs by the indigenous smallholder farmers in Africa. Intercropping system is the best practice used as a strategy to climate change adaptability, and one of the most suitable intercropping systems is that of maize and bean. However, the current research findings revealed that there is a lack of consideration of indigenous knowledge that could enhance livelihoods that depend on natural resources directly affected by climate change.
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    Understanding multiple species ecosystem dynamics using a consumer resource model
    (Wiley, 2016) Collins, Obiora Cornelius; Duffy, Kevin Jan
    Most ecological systems comprise multiple species coex-isting and the dynamics of these multiple species can be important for understanding, management, and conservation. One method to study such ecological system dynamics is the use of heterogeneous models. Here we for-mulate and analyze a multiple species (n patches or groups) consumer re-source model. Initial insights are gained by analyzing the special cases n =1 and n = 2. A threshold consumption number C0 is used to investigate system stability and hence the long-term dynamics of the system. It is shown how this threshold consumption number can measure the effects and extent of multiple species coexistence in the system.
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    Heavy impact on seedlings by the impala suggests a central role in woodland dynamics
    (Cambridge University Press, 2012-04-12) O'Kane, Christopher A. J.; Duffy, Kevin Jan; Page, Bruce R.; Macdonald, David W.
    Research has increasingly established that mesoherbivores influence the regeneration of woody plants. However the relationship between mesoherbivore density and degree of impact, and the spatial component of this impact, has not been well established. Using a novel sampling design, we assessed in iMfolozi Park, South Africa, the impact of impala (Aepyceros melampus) across the full complement of woody species within the home range, evaluating its spatial component and relationship to impala density. We used four GPS collars, in separate breeding herds, and a GIS to detect zones of different density of impala in the landscape, thus defining a fine-grain browsing gradient. We assessed impact on woody recruits (≤ 0.5 m height) across this gradient by means of 1600 random 1 × 1-m quadrats. Densities of woody seedlings, and mean percentage of remaining canopy, were significantly less in areas of high impala density versus low-density areas. There was a significant correlation between increasing impala density and decreasing density of favoured woody recruits. We propose a hypothesis of impala-induced patch dynamics. It seems likely that the ubiquitous impala may create and sustain a shifting mosaic of patches, and thus function as a key determinant of landscape heterogeneity.
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    Using Maximum Entropy modeling to predict the potential distributions of large trees for conservation planning
    (Ecological Society of America, 2012-06) Smith, Alain; Page, Bruce R.; Duffy, Kevin Jan; Slotow, Rob
    Large trees, as keystone structures, are functionally important in savanna ecosystems, and low recruitment and slow growth makes their conservation important. Understanding factors influencing their distribution is essential for mitigation of excessive mortality, for example from management fires or large herbivores. We recorded the locations of large trees in Hluhluwe-Imfolozi Park (HiP) using GPS to record trees along 43 km of 10 m-wide transects. Maximum entropy modeling (MaxEnt) uses niche modeling to predict the distribution of a species from the probability of finding it within raster squares, based on environmental variables and recorded locations. MaxEnt is typically applied at a regional spatial scale, and here we assessed its usefulness when predicting the distribution of species at a small (local) scale. HiP has variable topography, heterogeneous soils, and a strong rainfall gradient, resulting in a wide variety of habitat types. We used locations of 179 Acacia nigrescens and 106 Sclerocarya birrea (large trees ≥ 5m), and raster environmental layers for: aspect, elevation, geology, annual rainfall, slope, soil and vegetation. A. nigrescens was largely restricted to the Imfolozi section, while S. birrea had a wider distribution across the reserve. Understanding the interaction of environmental variables dictating tree distribution may facilitate habitat restoration, and will assist planning decisions for persistence of large trees within reserves, including options to reduce fire frequency or herbivore impacts. Though the AUC (Area Under the Curve) values used to test model predictions were high for both species, the ground truthing test data showed that distribution for A. nigrescens was more accurate than that for S. birrea, highlighting the need for independent test data to assess model accuracy. We emphasize that MaxEnt can be used at finer spatial scales than those typically used for species occurrence, but models must be tested using spatially independent test data.