Modelling nonlinear dynamics of interacting tipping elements on complex networks: the PyCascades package

Tipping elements occur in various systems such as in socio-economics, ecology and the climate system. In many cases, the individual tipping elements are not independent of each other, but they interact across scales in time and space. To model systems of interacting tipping elements, we here introduce the PyCascades open source software package for studying interacting tipping elements (https://doi.org/10.5281/zenodo.4153102). PyCascades is an object-oriented and easily extendable package written in the programming language Python. It allows for investigating under which conditions potentially dangerous cascades can emerge between interacting dynamical systems, with a focus on tipping elements. With PyCascades it is possible to use different types of tipping elements such as double-fold and Hopf types and interactions between them. PyCascades can be applied to arbitrary complex network structures and has recently been extended to stochastic dynamical systems. This paper provides an overview of the functionality of PyCascades by introducing the basic concepts and the methodology behind it. In the end, three examples are discussed, showing three different applications of the software package. First, the moisture recycling network of the Amazon rainforest is investigated. Second, a model of interacting Earth system tipping elements is discussed. And third, the PyCascades modelling framework is applied to a global trade network

Recurrent droughts increase risk of cascading tipping events by outpacing adaptive capacities in the Amazon rainforest

Tipping elements are nonlinear subsystems of the Earth system that have the potential to abruptly shift to another state if environmental change occurs close to a critical threshold with large consequences for human societies and ecosystems. Among these tipping elements may be the Amazon rainforest, which has been undergoing intensive anthropogenic activities and increasingly frequent droughts. Here, we assess how extreme deviations fromclimatological rainfall regimes may cause local forest collapse that cascades through the coupled forest-climate system. We develop a conceptual dynamic network model to isolate and uncover the role of atmospheric moisture recycling in such tipping cascades. We account for heterogeneity in critical thresholds of the forest caused by adaptation to local climatic conditions. Our results reveal that, despite this adaptation, a future climate characterized by permanent drought conditions could trigger a transition to an open canopy state particularly in the southern Amazon.Theloss of atmospheric moisture recycling contributes to one-third of the tipping events.Thus, by exceeding local thresholds in forest adaptive capacity, local climate change impacts may propagate to other regions of the Amazon basin, causing a risk of forest shifts even in regions where critical thresholds have not been crossed locally

Initiating and upscaling mussel reef establishment with life cycle informed restoration:Successes and future challenges

Worldwide, coastal ecosystems are rapidly degrading in quality and extent. While novel restoration designs include facilitation to enhance restoration success in stressful environments, they typically focus on a single life-stage, even though many organisms go through multiple life-stages accompanied by different bottlenecks. A new approach – life cycle informed restoration – was designed to ameliorate multiple bottlenecks throughout an organism's life cycle. It has successfully been tested on a small scale to facilitate intertidal bivalve reef formation in the Netherlands and Florida. Yet, it remains unknown whether this approach can be scaled to ecosystem-relevant scales. To test whether life cycle informed restoration is upscalable, we conducted a large-scale restoration experiment using blue mussel reefs as a model system. In our experiment, we used biodegradable structures to temporarily facilitate mussel reef formation by providing early-life settlement substrates, and subsequently, reduce post-settlement predation on an intertidal flat in the Wadden Sea, the Netherlands. The structures were placed in 10 × 20 m plots, mimicking bands found in natural mussel beds, spread out across 650 m, and were followed for two years. Our results show that the structures enhance mussel biomass (0.7 ± 0.2 kg DW m−2), as mussels were absent in bare plots. However, biomass varied within plots; in intact structures it was 60 times higher (1.2 ± 0.2 kg DW m−2) than in those that became buried (0.02 ± 0.009 kg DW m−2). Next to burial, 18–46% of the structures were lost due to technical failure, especially during winters at this exposed site. We show that the life cycle informed restoration principle works, but we encountered technical challenges due to larger scale processes (e.g. sedimentation). Furthermore, environmental information is essential for site selection, and for restoration, the functioning of such structures should be tested under extreme conditions before upscaling

Post-fire Regeneration Traits of Understorey Shrub Species Modulate Successional Responses to High Severity Fire in Mediterranean Pine Forests

Recurrent fires can impede the spontaneous recruitment capacity of pine forests. Empirical studies have suggested that this can lead to a prolonged replacement of pine forest by shrubland, especially if shrub species are pyrophytic. Model-based studies, however, have suggested that post-fire succession of pine forest under current climatic conditions will eventually tend towards the dominance of oaks under high fire severity and recurrence. These previous modelling studies did not address the role of the various post-fire regeneration traits of the understory shrub species. Considering the dichotomy of obligate seeder vs. resprouter species, either obligate or facultative resprouter, we hypothesized that when the shrubs present are post-fire seeders, the oaks steadily occupy the forest, whereas resprouter shrub species might compete with oaks and delay or arrest post-fire succession. To test this hypothesis, we developed a dynamic, cellular automaton model for simulating post-fire successional transitions in pine forests, including shrubs, pines and oaks, and stochastic fires of regular frequency. Our results showed a strong tendency towards oak dominance as final model state and a very reduced role of fire recurrence in this final state, with low yearly acorn input delaying oak dominance. Most relevantly, and in line with our hypothesis, the trend towards oak dominance depended markedly on the two types of shrub species, being delayed by resprouter species, which extended the shrub-dominated succession stage for several centuries. Our simulation results supported the view that the type of understorey species should be a key consideration in post-fire restoration strategies aiming to enhance fire resilience

Structural diversity and tree density drives variation in the biodiversity-ecosystem function relationship of woodlands and savannas

Positive biodiversity-ecosystem function relationships (BEFRs) have been widely documented, but it is unclear if BEFRs should be expected in disturbance-driven systems. Disturbance may limit competition and niche differentiation, which are frequently posited to underlie BEFRs. We provide the first exploration of the relationship between tree species diversity and biomass, one measure of ecosystem function, across southern African woodlands and savannas, an ecological system rife with disturbance from fire, herbivores and humans. We used >1000 vegetation plots distributed across 10 southern African countries, and structural equation modelling, to determine the relationship between tree species diversity and aboveground woody biomass, accounting for interacting effects of resource availability, disturbance by fire, tree stem density and vegetation type. We found positive effects of tree species diversity on aboveground biomass, operating via increased structural diversity. The observed BEFR was highly dependent on organismal density, with a minimum threshold of c. 180 mature stems ha-1. We found that water availability mainly affects biomass indirectly, via increasing species diversity. The study underlines the close association between tree diversity, ecosystem structure, environment and function in highly disturbed savannas and woodlands. We suggest that tree diversity is an under-appreciated determinant of wooded ecosystem structure and function

Circum-Arctic distribution of chemical anti-herbivore compounds suggests biome-wide trade-off in defence strategies in Arctic shrubs

Spatial variation in plant chemical defence towards herbivores can help us understand variation in herbivore top-down control of shrubs in the Arctic and possibly also shrub responses to global warming. Less defended, non-resinous shrubs could be more influenced by herbivores than more defended, resinous shrubs. However, sparse field measurements limit our current understanding of how much of the circum-Arctic variation in defence compounds is explained by taxa or defence functional groups (resinous/non-resinous). We measured circum-Arctic chemical defence and leaf digestibility in resinous (Betula glandulosa, B. nana ssp. exilis) and non-resinous (B. nana ssp. nana, B. pumila) shrub birches to see how they vary among and within taxa and functional groups. Using liquid chromatography-mass spectrometry (LC-MS) metabolomic analyses and in vitro leaf digestibility via incubation in cattle rumen fluid, we analysed defence composition and leaf digestibility in 128 samples from 44 tundra locations. We found biogeographical patterns in anti-herbivore defence where mean leaf triterpene concentrations and twig resin gland density were greater in resinous taxa and mean concentrations of condensing tannins were greater in non-resinous taxa. This indicates a biome-wide trade-off between triterpene- or tannin-dominated defences. However, we also found variations in chemical defence composition and resin gland density both within and among functional groups (resinous/non-resinous) and taxa, suggesting these categorisations only partly predict chemical herbivore defence. Complex tannins were the only defence compounds negatively related to in vitro digestibility, identifying this previously neglected tannin group as having a potential key role in birch anti-herbivore defence. We conclude that circum-Arctic variation in birch anti-herbivore defence can be partly derived from biogeographical distributions of birch taxa, although our detailed mapping of plant defence provides more information on this variation and can be used for better predictions of herbivore effects on Arctic vegetation.Peer reviewe

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis. Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe

Traditional plant functional groups explain variation in economic but not size-related traits across the tundra biome

Aim Plant functional groups are widely used in community ecology and earth system modelling to describe trait variation within and across plant communities. However, this approach rests on the assumption that functional groups explain a large proportion of trait variation among species. We test whether four commonly used plant functional groups represent variation in six ecologically important plant traits. Location Tundra biome. Time period Data collected between 1964 and 2016. Major taxa studied 295 tundra vascular plant species. Methods We compiled a database of six plant traits (plant height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, seed mass) for tundra species. We examined the variation in species-level trait expression explained by four traditional functional groups (evergreen shrubs, deciduous shrubs, graminoids, forbs), and whether variation explained was dependent upon the traits included in analysis. We further compared the explanatory power and species composition of functional groups to alternative classifications generated using post hoc clustering of species-level traits. Results Traditional functional groups explained significant differences in trait expression, particularly amongst traits associated with resource economics, which were consistent across sites and at the biome scale. However, functional groups explained 19% of overall trait variation and poorly represented differences in traits associated with plant size. Post hoc classification of species did not correspond well with traditional functional groups, and explained twice as much variation in species-level trait expression. Main conclusions Traditional functional groups only coarsely represent variation in well-measured traits within tundra plant communities, and better explain resource economic traits than size-related traits. We recommend caution when using functional group approaches to predict tundra vegetation change, or ecosystem functions relating to plant size, such as albedo or carbon storage. We argue that alternative classifications or direct use of specific plant traits could provide new insights for ecological prediction and modelling.Peer reviewe

Global plant trait relationships extend to the climatic extremes of the tundra biome

The majority of variation in six traits critical to the growth, survival and reproduction of plant species is thought to be organised along just two dimensions, corresponding to strategies of plant size and resource acquisition. However, it is unknown whether global plant trait relationships extend to climatic extremes, and if these interspecific relationships are confounded by trait variation within species. We test whether trait relationships extend to the cold extremes of life on Earth using the largest database of tundra plant traits yet compiled. We show that tundra plants demonstrate remarkably similar resource economic traits, but not size traits, compared to global distributions, and exhibit the same two dimensions of trait variation. Three quarters of trait variation occurs among species, mirroring global estimates of interspecific trait variation. Plant trait relationships are thus generalizable to the edge of global trait-space, informing prediction of plant community change in a warming world.Peer reviewe