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Abstract: Eutrophication of fresh water systems is one of the most important factors contributing to the invasion of fresh water bodies by water hyacinth, Eichhornia crassipes. The South American mite, Orthogalumna terebrantis, established on the weed in South Africa in the late 1980s, but the impact of mite herbivory on the weed has never been quantified. Water hyacinth was grown under low, medium and high nitrogen and phosphorus nutrient conditions and the effect of mite herbivory on the weed''s growth was examined. Additionally, the impact of different mite herbivory intensities on the weed''s photosynthetic performance was examined because herbivory may have more subtle effects on the plant than can be seen from changes in plant growth parameters. Water nutrient content had a great impact on plant growth, but growth was unaffected by mite herbivory in all levels of nutrients tested. Photosynthetic performance of water hyacinth leaves exposed to varying levels of mite herbivory was assessed by measuring net photosynthetic rate (A), leaf conductance (g l ), transpiration rate (E) and intercellular CO2 concentration (C i ), and by measuring specific fluorescence parameters including maximal fluorescence (F m ), efficiency of photosystem II (F v /F m ) and certain JIP-test parameters. Photosynthesis decreased as mite herbivory increased, but there was a positive correlation between g l , E and C i , and the amount of leaf tissue damaged through mite feeding. The efficiency of photosystem II (PSII) decreased as mite herbivory increased, as seen in the altered fluorescence emission of mite-damaged plants, but this was not the consequence of decreased chlorophyll content. Feeding by O. terebrantis thus decreased water hyacinth photosynthetic rate and the light reaction performance, even at relatively low mite densities. These results show that the impact of a biological control agent on its host plant may not be obvious at a plant growth level, but may nonetheless affect the plant at a physiological level. [Copyright &y& Elsevier]

• Invasive macrophytes grown at elevated CO 2 increased in biomass and leaf C:N. • Feeding damage caused by biological control agents was reduced at elevated CO 2. • CO 2 availability was the primary determinant of plant responses and not herbivory. • Invasive macrophytes will be more challenging to manage through biological control in future climates. There has been a rapid increase in atmospheric CO 2 concentration, from pre-industrial values of 280 ppm to more than 400 ppm currently, and this is expected to double by the end of the 21st century. Studies have shown that plants grown at elevated CO 2 concentrations have increased growth rates and invest more in carbon-based defences. This has important implications for the management of invasive alien plants, especially using biological control which is mostly dependent on herbivorous insects. The aim of this study was to investigate the effects of elevated atmospheric CO 2 on the biological control of four invasive aquatic weeds (Azolla filiculoides, Salvinia molesta, Pistia stratiotes and Myriophyllum aquaticum). These species are currently under successful control by their respective biological control agents (Stenopelmus rufinasus, Cyrtobagous salviniae, Neohydronomus affinis, and Lysathia sp.) in South Africa. The plant species were grown in a two factorial design experiment, where atmospheric CO 2 concentrations were set at ambient (400 ppm) or elevated (800 ppm), and plants were either subjected to or not subjected to herbivory by their target biological control agents. There was an overall increase in biomass production and C:N across all species at elevated CO 2 , both in the absence and presence of biological control, although C:N of M. aquaticum and biomass of A. filiculoides with herbivory were not constant with this trend. Insect feeding damage was reduced by elevated CO 2 , except for S. molesta. Thus, we can expect that plants will respond differently to CO 2 increase, but the general trend suggests that these species will become more challenging to manage through biological control in future. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • Vachellia karroo seedlings were grown in 180 ppm, 270 ppm, 400 ppm, and 800 ppm CO 2. • Drought was initiated and monitored at drought day-30 and drought day-60. • The increases in photosynthetic parameters from eCO2 were diminished by drought. • The increases in whole-plant from eCO2 were diminished by drought. • Drought is a more dominant abiotic filter influencing bush encroachment than eCO2. Abstract There is theoretical, empirical and modeled evidence that atmospheric enrichment of carbon dioxide (CO 2 ) is driving the conversion of open savannas to woodlands (i.e., woody thickening or bush encroachment). This study measured the impacts of available CO 2 and water limitation on seedling growth and physiology to determine how these two environmental conditions may be influencing savanna seedling establishment. We hypothesized that a model savanna tree, Vachellia karroo , would experience positive growth responses to increasing CO 2 and that CO 2 enrichment would partially offset slowed growth and physiological inhibition imposed by drought. To test this hypothesis, we grew V. karroo in open-top chambers at the Kirstenbosch Research Center (Cape Town, South Africa). The seedlings were divided equally into four CO 2 treatments: 180 ppm, 270 ppm, 400 ppm, and 800 ppm. Seedlings were grown in their CO 2 treatments for 35 days before drought was initiated. The drought was initiated by removing the irrigation from half of the pots. Leaf gas-exchange, stem water potential, leaf non-structural carbohydrate concentrations, and plant morphology were measured at drought day-30 and drought day-60. The results showed significant benefits from CO 2 enrichment to aboveground plant structures, including larger leaves and stems, when water was abundant ( p < 0.05). CO 2 -related increases to photosynthetic parameters, such as instantaneous water-use efficiency, were significantly diminished by water limitation ( p < 0.05). Our results present the first experimental evidence of the relationship between the two driving factors structuring the large-scale spatial patterns of savanna vegetation productivity and cover. These results suggest that atmospheric enrichment of CO 2 will significantly affect aspects of plant growth and physiology, yet prolonged drought will remain an overarching determinant of savanna plant community dynamics. [ABSTRACT FROM AUTHOR]

Models used to predict species’ potential distributions have been described as either correlative or mechanistic. We attempted to determine whether correlative models could perform as well as mechanistic models for predicting species potential distributions, using a case study. We compared potential distribution predictions made for a coastal dune plant (Scaevola plumieri) along the coast of South Africa, using a mechanistic model based on summer water balance (SWB), and two correlative models (a profile and a group discrimination technique). The profile technique was based on principal components analysis (PCA) and the group-discrimination technique was based on multiple logistic regression (LR). Kappa (κ) statistics were used to objectively assess model performance and model agreement. Model performance was calculated by measuring the levels of agreement (using κ) between a set of testing localities (distribution records not used for model building) and each of the model predictions. Using published interpretive guidelines for the kappa statistic, model performance was “excellent” for the SWB model (κ=0.852), perfect for the LR model (κ=1.000), and “very good” for the PCA model (κ=0.721). Model agreement was calculated by measuring the level of agreement between the mechanistic model and the two correlative models. There was “good” model agreement between the SWB and PCA models (κ=0.679) and “very good” agreement between the SWB and LR models (κ=0.786). The results suggest that correlative models can perform as well as or better than simple mechanistic models. The predictions generated from these three modelling designs are likely to generate different insights into the potential distribution and biology of the target organism and may be appropriate in different situations. The choice of model is likely to be influenced by the aims of the study, the biology of the target organism, the level of knowledge the target organism’s biology, and data quality. [Copyright &y& Elsevier]