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Multiple stable states, bifurcations and thresholds are fashionable concepts in the ecological literature, a recognition that complex ecosystems may at times exhibit the interesting dynamic behaviours predicted by relatively simple biomathematical models. Recently, several papers in Global Ecology and Biogeography, Proceedings of the National Academy of Sciences USA, Science and elsewhere have attempted to quantify the prevalence of alternate stable states in the savannas of Africa, Australia and South America, and the tundra-taiga-grassland transitions of the circum-boreal region using satellite-derived woody canopy cover. While we agree with the logic that basins of attraction can be inferred from the relative frequencies of ecosystem states observed in space and time, we caution that the statistical methodologies underlying the satellite product used in these studies may confound our ability to infer the presence of multiple stable states. We demonstrate this point using a uniformly distributed 'pseudo-tree cover' database for Africa that we use to retrace the steps involved in creation of the satellite tree-cover product and subsequent analysis. We show how classification and regression tree ( CART)-based products may impose discontinuities in satellite tree-cover estimates even when such discontinuities are not present in reality. As regional and global remote sensing and geospatial data become more easily accessible for ecological studies, we recommend careful consideration of how error distributions in remote sensing products may interact with the data needs and theoretical expectations of the ecological process under study. [ABSTRACT FROM AUTHOR]

Aim We present a continental-scale analysis that explores the processes controlling woody community structure in tropical savannas. We analyse how biotic and abiotic factors interact to promote and modify tree cover, examine alternative ecological hypotheses and quantify disturbance effects using satellite estimates of tree cover. Location African savannas. Methods Tree cover is represented as a resource-driven potential cover related to rainfall and soil characteristics perturbed by natural and human factors such as fire, cattle grazing, human population and cultivation. Within this framework our approach combines semi-empirical modelling and information theory to identify the best models. Results Woody community structure across African savannas is best represented by a sigmoidal response of tree cover to mean annual precipitation (MAP), with a dependency on soil texture, which is modified by the separate effects of fire, domestic livestock, human population density and cultivation intensity. This model explains c. 66% of the variance in tree cover and appears consistent across the savanna regions of Africa. Main conclusions The analysis provides a new understanding of the importance and interaction of environmental and disturbance factors that create the broad spatial patterns of tree cover observed in African savannas. Woody cover increases with rainfall, but is modified by disturbances. These ‘perturbation’ effects depend on MAP regimes: in arid savannas (MAP < 400 mm) they are generally small (< 1% decrease in cover), while in semi-arid and mesic savannas (400–1600 mm), perturbations result in an average 2% (400 mm) to 23% (1600 mm) decrease in cover; fire frequency and human population have more influence than cattle, and cultivation appears, on average, to lead to small increases in woody cover. Wet savannas (1600–2200 mm) are controlled by perturbations that inhibit canopy closure and reduce tree cover by, on average, 24–34%. Full understanding of the processes determining savanna structure requires consideration of resource limitation and disturbance dynamics. [ABSTRACT FROM AUTHOR]

Staver & Hansen (2015, Global Ecology and Biogeography, doi: 10.1111/geb.12285) comment on our recent paper ( Hanan et al., Global Ecology and Biogeography, 2014, 23, 259-263) in which we argue that classification and regression tree methods used with remote sensing data to predict tree cover may bias inference of bifurcations in savanna vegetation communities. While we agree with several of their comments, we remain unconvinced that a remote sensing product based on an inherently discontinuous statistical approach can, or should, be used to test for discontinuities. [ABSTRACT FROM AUTHOR]