Relationship among functional traits of wetland plants and climatic variables along an aridity gradient across the Highveld, South Africa

Abstract

Wetlands are among the most threatened ecosystems in South Africa due to human activities such as changing land use. In addition to these threats, wetlands are now faced with the threat of climate change, which may affect their biota in the future. Therefore, South Africa needs locally relevant biological indicators to detect changes in wetland ecosystems that can be used in monitoring programmes for wetland vegetation. Plant functional traits are recognised as an effective tool that can be used to understand community assembly processes that determine the abundance and distribution of plant species and their response to climate change. The aim of the study was to determine whether plant functional traits change along an aridity gradient across the Highveld of South Africa. Functional traits of the dominant plant species were collected in the wetlands of the Highveld along a climatic gradient from dry in the west to mesic in the east. The measured traits include plant weight, rhizome internode length, shoot length, leaf nitrogen content (Leaf N) and specific leaf area (SLA). In the analysis canonical ordination techniques were applied to find the correlation between plant functional composition, non-climatic environmental variables and climatic variables. Community-averaged traits were calculated for all wetland vegetation plots and these were plotted against non-climatic environmental variables and climatic variables using the CANOCO program. Hierarchical Cluster Analysis (HCA) was carried out to delineate plant functional groups using the PC-Ord program. Plant functional groups were plotted against non-climatic environmental variables and climatic variables using CANOCO program. The distribution ranges of each plant functional group were mapped using Geographical Information System (ArcGIS). Principal Component Analysis (PCA) was carried out using the PC-Ord program to find the relationship between non-climatic environmental variables and climatic variables. The RDA results showed that the correlations between climatic variables and plant traits in general are not as strong as expected; plants seem to respond much more strongly to non-climatic environmental variables. This means that plants seem to respond much more directly to local factors that determine the wetland habitat and not directly to the climate itself. Nonetheless, it is still possible that these environmental conditions (wetness, inundation, nutrient content of the soil) may change as well in the scenario of climate change, but that would be considered as an indirect effect. The results revealed that plant weight and rhizome internode length are correlated with maximum temperature and evaporation. Species with high plant weight and long rhizome internode length represents species growing in dry areas on the western side of the study area. SLA, shoot length and leaf N are correlated with precipitation and minimum temperature. Species with high SLA, long shoot length and high leaf N are specifically those species growing in mesic areas on the eastern side of the study area. Wetland plant species in dry areas grow in wetlands that are exposed to high temperatures, high evaporation rates, low rainfall and high salinity. These species are short and have low SLA which they use as an adaptation to water stress. Wetland plant species in mesic areas grow in wetlands that are exposed to high rainfall and low temperatures. These species grow faster and are more productive. The functional classification resulted with six plant functional groups namely: tufted graminoids, leafless graminoids, rhizomatous graminoids, salt tolerant forbs, succulent shrubs and short trailing forbs and grasses. The tufted graminoids, leafless graminoids and rhizomatous graminoids are distributed in mesic areas and the succulent shrubs, salt tolerant forbs and short trailing forbs and grasses are distributed in dry areas. Changes in community composition will show how the wetland is responding to climatic variability and environmental change. This will provide an improved basis for monitoring the impacts of climate change on wetland vegetation.