Five fundamental ways in which complex food webs may spiral out of control

Theory suggests that increasingly long, negative feedback loops of many interacting species may destabilize food webs as complexity increases. Less attention has, however, been paid to the specific ways in which these 'delayed negative feedbacks' may affect the response of complex ecosystems to global environmental change. Here, we describe five fundamental ways in which these feedbacks might pave the way for abrupt, large-scale transitions and species losses. By combining topological and bioenergetic models, we then proceed by showing that the likelihood of such transitions increases with the number of interacting species and/or when the combined effects of stabilizing network patterns approach the minimum required for stable coexistence. Our findings thus shift the question from the classical question of what makes complex, unaltered ecosystems stable to whether the effects of, known and unknown, stabilizing food-web patterns are sufficient to prevent abrupt, large-scale transitions under global environmental change.

Northern expansion is not compensating for southern declines in North American boreal forests

Climate change is expected to shift the boreal biome northward through expansion at the northern and contraction at the southern boundary respectively. However, biome-scale evidence of such a shift is rare. Here, we used remotely-sensed tree cover data to quantify temporal changes across the North American boreal biome from 2000 to 2019. We reveal a strong north-south asymmetry in tree cover change, coupled with a range shrinkage of tree cover distributions. We found no evidence for tree cover expansion in the northern biome, while tree cover increased markedly in the core of the biome range. By contrast, tree cover declined along the southern biome boundary, where losses were related largely to wildfires and timber logging. We show that these contrasting trends are structural indicators for a possible onset of a biome contraction which may lead to long-term carbon declines.

A Changing Number of Alternative States in the Boreal Biome: Reproducibility Risks of Replacing Remote Sensing Products

Publicly available remote sensing products have boosted science in many ways. The openness of these data sources suggests high reproducibility. However, as we show here, results may be specific to versions of the data products that can become unavailable as new versions are posted. We focus on remotely-sensed tree cover. Recent studies have used this public resource to detect multi-modality in tree cover in the tropical and boreal biomes. Such patterns suggest alternative stable states separated by critical tipping points. This has important implications for the potential response of these ecosystems to global climate change. For the boreal region, four distinct ecosystem states (i.e., treeless, sparse and dense woodland, and boreal forest) were previously identified by using the Collection 3 data of MODIS Vegetation Continuous Fields (VCF). Since then, the MODIS VCF product has been updated to Collection 5; and a Landsat VCF product of global tree cover at a fine spatial resolution of 30 meters has been developed. Here we compare these different remote-sensing products of tree cover to show that identification of alternative stable states in the boreal biome partly depends on the data source used. The updated MODIS data and the newer Landsat data consistently demonstrate three distinct modes around similar tree-cover values. Our analysis suggests that the boreal region has three modes: one sparsely vegetated state (treeless), one distinct ‘savanna-like’ state and one forest state, which could be alternative stable states. Our analysis illustrates that qualitative outcomes of studies may change fundamentally as new versions of remote sensing products are used. Scientific reproducibility thus requires that old versions remain publicly available.

Can we infer plant facilitation from remote sensing? a test across global drylands

Facilitation is a major force shaping the structure and diversity of plant communities in terrestrial ecosystems. Detecting positive plant-plant interactions relies on the combination of field experimentation and the demonstration of spatial association between neighboring plants. This has often restricted the study of facilitation to particular sites, limiting the development of systematic assessments of facilitation over regional and global scales. Here we explore whether the frequency of plant spatial associations detected from high-resolution remotely sensed images can be used to infer plant facilitation at the community level in drylands around the globe. We correlated the information from remotely sensed images freely available through Google Earth with detailed field assessments, and used a simple individual-based model to generate patch-size distributions using different assumptions about the type and strength of plant-plant interactions. Most of the patterns found from the remotely sensed images were more right skewed than the patterns from the null model simulating a random distribution. This suggests that the plants in the studied drylands show stronger spatial clustering than expected by chance. We found that positive plant co-occurrence, as measured in the field, was significantly related to the skewness of vegetation patch-size distribution measured using Google Earth images. Our findings suggest that the relative frequency of facilitation may be inferred from spatial pattern signals measured from remotely sensed images, since facilitation often determines positive co-occurrence among neighboring plants. They pave the road for a systematic global assessment of the role of facilitation in terrestrial ecosystems.

Collapse and reorganization of a food web of Mwanza Gulf, Lake Victoria

Lake Victoria in East Africa is the world's second largest freshwater system. Over the past century the ecosystem has undergone drastic changes. Some 30 years after the introduction of Nile perch (Lates niloticus) and Nile tilapia (Oreochromis niloticus) in the 1950s, the highly diverse community of native haplochromines collapsed, leaving a system dominated by only four species: the native cyprinid dagaa (Rastrineobola argentea) and shrimp (Caridina nilotica), as well as the introduced Nile perch and Nile tilapia. More recently, an unexpected resurgence of haplochromines has been reported. To understand these changes in terms of ecosystem functioning and of changes in growth of trophic groups, we created mass balances of the food web near Mwanza, Tanzania, before, during, and after the Nile perch boom (1977, 1987, and 2005), using the application ECOPATH. We connected these mass balances with a dynamic model assuming linear trends in net growth rates of the trophic groups. Our analysis suggests that the Nile perch boom initially altered the biomass distribution over trophic levels. Also, results indicate that not only fishing but also changes at the detritivores' trophic level might have played an important role in driving changes in the system. Both the mass balances and the dynamic model connecting them reveal that, after a major distortion during the Nile perch boom, the biomass distribution over the main trophic levels had largely recovered its original (1977) state by 2005. However, no such return appeared in terms of community structure. Biodiversity in the new state is dramatically lower, consisting of introduced species and a few native surviving species. We conclude that at an aggregate level Lake Victoria's ecosystem has proved to be resilient in the sense that its overall trophic structure has apparently recovered after a major perturbation. By contrast, its intricate functional structure and associated biodiversity have proved to be fragile and seem unlikely to recover.

Global resilience of tropical forest and savanna to critical transitions

It has been suggested that tropical forest and savanna could represent alternative stable states, implying critical transitions at tipping points in response to altered climate or other drivers. So far, evidence for this idea has remained elusive, and integrated climate models assume smooth vegetation responses. We analyzed data on the distribution of tree cover in Africa, Australia, and South America to reveal strong evidence for the existence of three distinct attractors: forest, savanna, and a treeless state. Empirical reconstruction of the basins of attraction indicates that the resilience of the states varies in a universal way with precipitation. These results allow the identification of regions where forest or savanna may most easily tip into an alternative state, and they pave the way to a new generation of coupled climate models.

Resonance of plankton communities with temperature fluctuations

The interplay between intrinsic population dynamics and environmental variation is still poorly understood. It is known, however, that even mild environmental noise may induce large fluctuations in population abundances. This is due to a resonance effect that occurs in communities on the edge of stability. Here, we use a simple predator-prey model to explore the sensitivity of plankton communities to stochastic environmental fluctuations. Our results show that the magnitude of resonance depends on the timescale of intrinsic population dynamics relative to the characteristic timescale of the environmental fluctuations. Predator-prey communities with an intrinsic tendency to oscillate at a period T are particularly responsive to red noise characterized by a timescale of τ = T/2π. We compare these theoretical predictions with the timescales of temperature fluctuations measured in lakes and oceans. This reveals that plankton communities will be highly sensitive to natural temperature fluctuations. More specifically, we demonstrate that the relatively fast temperature fluctuations in shallow lakes fall largely within the range to which rotifers and cladocerans are most sensitive, while marine copepods and krill will tend to resonate more strongly with the slower temperature variability of the open ocean.

Floating plant dominance as a stable state

Invasion by mats of free-floating plants is among the most important threats to the functioning and biodiversity of freshwater ecosystems ranging from temperate ponds and ditches to tropical lakes. Dark, anoxic conditions under thick floating-plant cover leave little opportunity for animal or plant life, and they can have large negative impacts on fisheries and navigation in tropical lakes. Here, we demonstrate that floating-plant dominance can be a self-stabilizing ecosystem state, which may explain its notorious persistence in many situations. Our results, based on experiments, field data, and models, represent evidence for alternative domains of attraction in ecosystems. An implication of our findings is that nutrient enrichment reduces the resilience of freshwater systems against a shift to floating-plant dominance. On the other hand, our results also suggest that a single drastic harvest of floating plants can induce a permanent shift to an alternative state dominated by rooted, submerged growth forms.

Perpest model, a case-based reasoning approach to predict ecological risks of pesticides

The PERPEST model is a model that predicts the ecological risks of pesticides in freshwater ecosystems. This model simultaneously predicts the effects of a particular concentration of a pesticide on various (community) endpoints. In contrast to most effect models, PERPEST is based on empirical data extracted from the literature. This model is based on case-based reasoning, a technique that solves new problems (e.g., what is the effect of pesticide A?) by using past experience (e.g., published microcosm experiments). The database containing the past experience has been constructed by performing a review of freshwater model ecosystem studies. This review assessed the effects on various endpoints (e.g., community metabolism, phytoplankton, and macroinvertebrates) and classified them according to their magnitude and duration. The PERPEST model searches for analogous situations in the database, based on relevant (toxicity) characteristics of the compound. This allows the model to predict effects of pesticides for which no effects on a semifield scale have been published. The PERPEST model results in a prediction showing the probability of classes of effects (no, slight, or clear effects, plus an optional indication of recovery) on the various grouped endpoints. This paper discusses the scientific background of the model as well as its strengths, limitations, and possible applications.