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

Genomic islands of speciation separate cichlid ecomorphs in an East African crater lake.

The genomic causes and effects of divergent ecological selection during speciation are still poorly understood. Here we report the discovery and detailed characterization of early-stage adaptive divergence of two cichlid fish ecomorphs in a small (700 meters in diameter) isolated crater lake in Tanzania. The ecomorphs differ in depth preference, male breeding color, body shape, diet, and trophic morphology. With whole-genome sequences of 146 fish, we identified 98 clearly demarcated genomic "islands" of high differentiation and demonstrated the association of genotypes across these islands with divergent mate preferences. The islands contain candidate adaptive genes enriched for functions in sensory perception (including rhodopsin and other twilight-vision-associated genes), hormone signaling, and morphogenesis. Our study suggests mechanisms and genomic regions that may play a role in the closely related mega-radiation of Lake Malawi.The work was funded by Royal Society-Leverhulme Trust Africa Awards AA100023 and AA130107 (M.J.G., B.P.N. and G.F.T.), a Wellcome Trust PhD studentship grant 097677/Z/11/Z (M.M.), Wellcome Trust grant WT098051 (S.S. and R.D.), Wellcome Trust and Cancer Research UK core support and a Wellcome Trust Senior Investigator Award (E.A.M.), a Leverhulme Trust Research Fellowship RF-2014-686 (M.J.G.), a University of Bristol Research Committee award (M.G.), a Bangor University Anniversary PhD studentship (to A.M.T.) and a Fisheries Society of the British Isles award (G.F.T.). Raw sequencing reads are in the SRA nucleotide archive: RAD sequencing (BioProject: PRJNA286304; accessions SAMN03768857 to SAMN03768912) and whole genome sequencing (BioProject PRJEB1254: sample accessions listed in Table S16). The RAD based phylogeny and alignments have been deposited in TreeBase (TB2:S18241). Whole genome variant calls in the VCF format, phylogenetic trees, and primer sequences for Sequenom genotyping are available from the Dryad Digital Repository (http://dx.doi.org/10.5061/dryad.770mc). RD declares his interests as a founder and non-executive director of Congenica Ltd., that he owns stock in Illumina from previous consulting, and is a scientific advisory board member of Dovetail Inc. We thank R. Schley for generating pharyngeal jaw data; S. Mzighani, J. Kihedu and staff of the Tanzanian Fisheries Research Institute for logistical support; A. Smith, H. Sungani, A. Shechonge, P. Parsons, J. Swanstrom, G. Cooke and J. Bridle for contributions to sampling and aquarium maintenance, the Sanger Institute sequencing core for DNA sequencing and Dr. H. Imai (Kyoto University) for the use of spectrometer in his laboratory.This is the author accepted manuscript. The final version is available from AAAS via http://dx.doi.org/10.1126/science.aac992

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

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

The impact of a native dominant plant, Euphorbia jolkinii, on plant–flower visitor networks and pollen deposition on stigmas of co-flowering species in subalpine meadows of Shangri-La, SW China

Anthropogenic activity can modify the distribution of species abundance in a community leading to the appearance of new dominant species. While many studies report that an alien plant species which becomes increasingly dominant can change species composition, plant–pollinator network structure and the reproductive output of native plant species, much less is known about native plant species which become dominant in their communities. Euphorbia jolkinii Boissier (Euphorbia, hereafter) has become a dominant native plant in the over-grazed meadows of Shangri-La, SW China. During the flowering season of Euphorbia and over 2 years, we quantified the impact of Euphorbia on plant richness and flower visitor richness in 12 subalpine meadows along a gradient of Euphorbia dominance. We also evaluated the floral preferences of flower visitors, interaction evenness of plant–flower visitor networks and the deposition of pollen on the stigmas of two co-flowering plant species (Gentiana chungtienensis and Anemone rupestris) in each meadow. The species richness of flower visitors to non-Euphorbia plants was negatively correlated with Euphorbia dominance. As the proportion of Euphorbia increases, flower visitors to Euphorbia decreased, while flower visitors to other co-flowering plants increased. Interaction evenness decreased as the proportion of Euphorbia increased. Furthermore, the conspecific pollen deposition of one of the two co-flowering plant species studied, G. chungtienensis, decreased as the proportion of Euphorbia increased. Synthesis. There appears to be little substantive difference between the impact of a newly dominant native plant and the impacts reported for many alien plants on native plant–pollinator communities. This lack of difference suggests that dominance, in addition to plant origin (alien vs. native), could play an important role in influencing the structure and functioning of native communities. This finding has considerable implications for restoration ecology. Thus, communities where natural dominance order has been changed due to anthropogenic activity may not be considered a problem as all the species are native—in reality though, they may be as damaged as communities invaded by alien species

Reliably predicting pollinator abundance: challenges of calibrating process-based ecological models

1. Pollination is a key ecosystem service for global agriculture but evidence of pollinator population declines is growing. Reliable spatial modelling of pollinator abundance is essential if we are to identify areas at risk of pollination service deficit and effectively target resources to support pollinator populations. Many models exist which predict pollinator abundance but few have been calibrated against observational data from multiple habitats to ensure their predictions are accurate. 2. We selected the most advanced process-based pollinator abundance model available and calibrated it for bumblebees and solitary bees using survey data collected at 239 sites across Great Britain. We compared three versions of the model: one parameterised using estimates based on expert opinion, one where the parameters are calibrated using a purely data-driven approach and one where we allow the expert opinion estimates to inform the calibration process. 3. All three model versions showed significant agreement with the survey data, demonstrating this model's potential to reliably map pollinator abundance. However, there were significant differences between the nesting/floral attractiveness scores obtained by the two calibration methods and from the original expert opinion scores. 4. Our results highlight a key universal challenge of calibrating spatially-explicit, process-based ecological models. Notably, the desire to reliably represent complex ecological processes in finely mapped landscapes necessarily generates a large number of parameters, which are challenging to calibrate with ecological and geographical data that is often noisy, biased, asynchronous and sometimes inaccurate. Purely data-driven calibration can therefore result in unrealistic parameter values, despite appearing to improve model-data agreement over initial expert opinion estimates. We therefore advocate a combined approach where data-driven calibration and expert opinion are integrated into an iterative Delphi-like process, which simultaneously combines model calibration and credibility assessment. This may provide the best opportunity to obtain realistic parameter estimates and reliable model predictions for ecological systems with expert knowledge gaps and patchy ecological data

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