Tipping points in tropical tree cover: linking theory to data

PLOS ONE, 2019

Observed bimodal tree cover distributions at particular environmental conditions and theoretical models indicate that some areas in the tropics can be in either of the alternative stable vegetation states forest or savanna. However, when including spatial interaction in nonspatial differential equation models of a bistable quantity, only the state with the lowest potential energy remains stable. Our recent reaction-diffusion model of Amazonian tree cover confirmed this and was able to reproduce the observed spatial distribution of forest versus savanna satisfactorily when forced by heterogeneous environmental and anthropogenic variables, even though bistability was underestimated. These conclusions were solely based on simulation results for one set of parameters. Here, we perform an analytical and numerical analysis of the model. We derive the Maxwell point (MP) of the homogeneous reaction-diffusion equation without savanna trees as a function of rainfall and human impact and show that the front between forest and nonforest settles at this point as long as savanna tree cover near the front remains sufficiently low. For parameters resulting in higher savanna tree cover near the front, we also find irregular forest-savanna cycles and woodland-savanna bistability, which can both explain the remaining observed bimodality.

Ecological Modelling, 2001

The effect of climatic change on tropical vegetation is of global and regional concern because of the high biodiversity and the potential feedback to the carbon, water, and nutrient cycles. One of the most critical aspects for assessing broad-scale consequences of climate change is our understanding of how vegetation may change. Models relating vegetation and environmental conditions can be developed for large regions. For a simple application of static models of vegetation-environment relationships, one would have to assume that the probability of species (or vegetation) occurrence conditional on environmental conditions is constant in time (abbreviated as the POCEC assumption). This assumption is critical and difficult. In this paper, we evaluate how the spatial arrangement of forest pattern may constrain vegetation change as predicted by a spatially static artificial neural network (ANN) model. We have relaxed the POCEC assumption by subjoining a spatially dynamic component based on the cellular automata approach. The ANN model quantifies a most suitable forest type based on the conditional probability of vegetation in the environmental space, whereas the cellular automata model imposes spatial constraints on the transition to the best-suited type. We adapt the cellular automata algorithm to successively increase spatial constraints, hence relaxing the POCEC assumption. Our study area is located in Northern Queensland and encompasses 20 000 km 2 . We evaluate the effect of the + 1°C mean annual temperature and the −10% mean annual precipitation change. A comparison of predictions of vegetation change with the different models indicates that the spatial arrangement of vegetation in the 'Wet Tropics' region may impose relatively few constraints for the region's potential change. Depending on the strength of spatial effects included in the models, the predicted future vegetation patterns differ from 1 to 10% of the study area. However, if in addition to spatial constraints ecological constraints also are considered (e.g. prohibiting several transitions that would appear very unlikely to experienced forest researchers), the predictions may differ by as much as 27%, showing a relatively strong dependence of predictions on assumptions about patch-level processes. Furthermore, using different models allows us to assess the uncertainty associated with predictions. The results demonstrate a relative certainty of a predicted decrease of notophyll rainforest types and an increase of medium open forests and woodlands, respectively, whereas the predictions of mesophyll vine forest and wet sclerophyll vegetation differ strongly among different models.

Global Change Biology, 2022

Forest and savanna ecosystems naturally exist as alternative stable states. The maximum capacity of these ecosystems to absorb perturbations without transitioning to the other alternative stable state is referred to as ‘resilience’. Previous studies have determined the resilience of terrestrial ecosystems to hydroclimatic changes predominantly based on space‐for‐time substitution. This substitution assumes that the contemporary spatial frequency distribution of ecosystems’ tree cover structure holds across time. However, this assumption is problematic since ecosystem adaptation over time is ignored. Here we empirically study tropical forests’ stability and hydroclimatic adaptation dynamics by examining remotely sensed tree cover change (ΔTC; aboveground ecosystem structural change) and root zone storage capacity (Sr; buffer capacity towards water‐stress) over the last two decades. We find that ecosystems at high (>75%) and low (<10%) tree cover adapt by instigating considerabl...

Global Ecology and Biogeography, 2014

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 circumboreal 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.

Ecology Letters, 2009

Size frequency distributions of canopy gaps are a hallmark of forest dynamics. But it remains unknown whether legacies of forest disturbance are influencing vertical size structure of landscapes, or space-filling in the canopy volume. We used data from LiDAR remote sensing to quantify distributions of canopy height and sizes of 434 501 canopy gaps in five tropical rain forest landscapes in Costa Rica and Hawaii. The sites represented a wide range of variation in structure and natural disturbance history, from canopy gap dynamics in lowland Costa Rica and Hawaii, to stages and types of standlevel dieback on upland Mauna Kea and Kohala volcanoes. Large differences in vertical canopy structure characterized these five tropical rain forest landscapes, some of which were related to known disturbance events. Although there were quantitative differences in the values of scaling exponents within and among sites, size frequency distributions of canopy gaps followed power laws at all sites and in all canopy height classes. Scaling relationships in gap size at different heights in the canopy were qualitatively similar at all sites, revealing a remarkable similarity despite clearly defined differences in species composition and modes of prevailing disturbance. These findings indicate that powerlaw gap-size frequency distributions are ubiquitous features of these five tropical rain forest landscapes, and suggest that mechanisms of forest disturbance may be secondary to other processes in determining vertical and horizontal size structure in canopies.

Science, 2011

Tree distributions across continents indicate three distinct stable states in tree cover―forest, savanna, and treeless.

Trees, 2010

There is growing evidence that tree turnover in tropical forests has increased over the last decades in permanent sample plots. This phenomenon is generally attributed to the increase in atmospheric CO 2 , but other causes cannot be ruled out. A proper evaluation of historical shifts in tree turnover requires data over longer periods than used so far. Here, we propose two methods to use treering data for detecting long-term changes in tree turnover. We apply these methods to two non-pioneer tree species in a Bolivian moist forest. First, we checked for temporal changes in the frequency of growth releases to determine whether this frequency has increased over time. Second, we calculated the degree of temporal autocorrelation-a measure that indicates temporal changes in growth rates that are likely related to canopy dynamics-and checked for changes in this parameter over time. In addition, we performed analyses that corrected for ontogenetic increases in the measures used by analyzing residuals from sizegrowth relations. No evidence for the occurrence of a large-scale disturbance was found as we did not observe synchronization in the occurrence of releases in time. For both species, we did not detect changes in autocorrelation or release frequency over the last 200-300 years. Only in one size category, we found increased release frequency over time, probably as a result of a remaining ontogenetic effect. In all, our analyses do not provide evidence for long-term changes in tree turnover in the study area. We discuss the suitability of the proposed methods. Keywords Forest dynamics Á Growth release Á Autocorrelated growth Á Ontogeny Á Tree turnover Á Bolivia Communicated by A. Bräuning. Contribution to the special issue ''Tropical Dendroecology''.

Research Square (Research Square), 2023

Although the impact of climate change is slow, the transformation in climate regime can lead to an ecosystem structure change from one stable to another stable state through intermediate bistable or metastable conditions. Therefore, the state transition or resilience in nature can never be sharp or be quanti ed with a single tipping point across the scales; rather, it should be understood through a tipping point range (tipping zone) across hysteresis loop(s). This study uses a satellite data-derived actual forest cover state map of India and high-resolution long-term average precipitation data to predict various tipping point range hysteresis for different forest cover states such as forest, scrubland, grassland and vegetation-less. The forest and vegetation-less states could have one-way, while scrubland and grassland have two-way transition probabilities with a probable shift in precipitation regime. In the dry conditions, the precipitation tipping zone predicted between 154 mm and 452 mm for the forest to scrubland transitions, while the reverse transition (from scrubland to forest) could occur in wet conditions between 1080 mm and 1400 mm. Similarly, the transition between scrubland and grassland, between grassland and vegetation-less state, may occur in contrasting dry and wet conditions, creating a hysteresis loop. The study indicates that the reversal of state change requires differential energy spent during the onward transition. The study proposes a novel characteristic curve demonstrating the varied precipitation tipping points/ zones, precipitation overlaps and distribution of the various life forms, and coexistence zones. The characteristic curve offers valuable inputs to explain life form transition and demarcate regions where forest enrichment and degradation may occur due to climate regime shifts. Such a spatially explicit database could provide vital inputs for planning forest cover restoration and management activities and mitigate the climate change impact.

Journal of Tropical …, 2004

Tropical forest demography and dynamics were examined in three inventory plots across a precipitation gradient in central Panama. The harsh dry season of 1998 that accompanied the 1997–98 El Niño was spanned by censuses at all three sites. The wet ...

Biological Conservation, 2010

Tropical forests are influenced by regional and global bio-climatic processes as well as local anthropogenic disturbances. Most studies have ignored the synergistic influence of bio-physical processes operating at large spatial scales and local human use on forest vegetation and fauna. Assessments of forest condition change using time-series of remotely sensed data need to be supported by measurements under the canopy. The Tadoba-Andhari Tiger Reserve (TATR) in India is a protected area that has a long history of human resource extraction and settlements. Like much of South Asia, it has undergone major shifts in rainfall in the last hundred years. We examine trends in forest greenness over two and half decades and assess spatial patterns in rates of change. We also analyze ground based measurements of human impacts on flora and fauna. Trends in forest canopy greenness show two distinct phases: a period of decline from 1980s to mid-90s, followed by a recovery. These trends are a function of initial greenness and are best explained by prevailing climatic regimes, feed-backs from human use, and park management practices and protection. Negative impacts to flora and fauna on the ground were, however, wide-spread during the recovery period and are influenced by proximity to nearest settlement as well as combined distance from all settlements. Remotely sensed data cannot effectively detect these processes under the canopy. There is an urgent need to incorporate monitoring of long-term bio-climatic processes and their interaction with short and long-term effects of human-use and disturbance arising from processes at local, regional and larger spatial scales around protected areas to effectively manage these reserves.