How biodiversity changes with elevation has long attracted the interest of researchers because it provides key clues to how biota respond to geophysical drivers. Experimental evidence reveals that biodiversity often peaks at intermediate elevations, and yet a clear explanation is still elusive. Here, we investigate a factor that has been overlooked to date: Mountainous landscapes hold fractal properties with elevational bands forming habitat patches that are characterized by different areal extent and connectivity, well-known drivers of biodiversity. When the geometry of real landscapes is taken into account, ecological dynamics naturally produce mid-peak elevational gradients of species richness. These results further biodiversity theory and our understanding of the distribution of life on Earth.
g that people vary in how they play economic games has led to the conclusion that people vary in their preference for fairness. Consequently, people have been divided into fair cooperators that make sacrifices for the good of the group and selfish free-riders that exploit the cooperation of others. This conclusion has been used to challenge evolutionary theory and economic theory and to guide social policy. We show that variation in behavior in the public-goods game is better explained by variation in understanding and that misunderstanding leads to cooperation.
The foundational concepts behind the persistence of ecological communities have been based on two ecological properties: dynamical stability and feasibility. The former is typically regarded as the capacity of a community to return to an original equilibrium state after a perturbation in species abundances and is usually linked to the strength of interspecific interactions. The latter is the capacity to sustain positive abundances on all its constituent species and is linked to both interspecific interactions and species demographic characteristics. Over the last 40 years, theoretical research in ecology has emphasized the search for conditions leading to the dynamical stability of ecological communities, while the conditions leading to feasibility have been overlooked. However, thus far, we have no evidence of whether species interactions are more conditioned by the community's need to be stable or feasible. Here, we introduce novel quantitative methods and use empirical data to investigate the consequences of species interactions on the dynamical stability and feasibility of mutualistic communities. First, we demonstrate that the more nested the species interactions in a community are, the lower the mutualistic strength that the community can tolerate without losing dynamical stability. Second, we show that high feasibility in a community can be reached either with high mutualistic strength or with highly nested species interactions. Third, we find that during the assembly process of a seasonal pollinator community located at The Zackenberg Research Station (northeastern Greenland), a high feasibility is reached through the nested species interactions established between newcomer and resident species. Our findings imply that nested mutualistic communities promote feasibility over stability, which may suggest that the former can be key for community persistence.
Species' functional roles in key ecosystem processes such as predation, pollination or seed dispersal are determined by the resource use of consumer species. An interaction between resource and consumer species usually requires trait matching (e.g. a congruence in the morphologies of interaction partners). Species' morphology should therefore determine species' functional roles in ecological processes mediated by mutualistic or antagonistic interactions. We tested this assumption for Neotropical plant–bird mutualisms. We used a new analytical framework that assesses a species's functional role based on the analysis of the traits of its interaction partners in a multidimensional trait space. We employed this framework to test (i) whether there is correspondence between the morphology of bird species and their functional roles and (ii) whether morphologically specialized birds fulfil specialized functional roles. We found that morphological differences between bird species reflected their functional differences: (i) bird species with different morphologies foraged on distinct sets of plant species and (ii) morphologically distinct bird species fulfilled specialized functional roles. These findings encourage further assessments of species' functional roles through the analysis of their interaction partners, and the proposed analytical framework facilitates a wide range of novel analyses for network and community ecology.
Ecological systems comprise of individuals and species interacting with each other and their environment, and these interactions combine to form complex networks. The maintenance of biodiversity and many ecosystem functions depend upon these ecological interactions. Humans, their crops and livestock can also be considered as part of these networks of interactions making network analysis valuable for considering the resilience of ecosystem services, i.e., the benefits we gain from nature. Networks are visually appealing and visualisation can attract attention and inform, both to communicate overall messages and provide comparisons between networks. There are many different approaches and layouts for visualising networks, but there is little research to help guide best practice. Ultimately though, best practice should be to ensure that messages are supported by evidence and clearly communicated with reference to the competence of the audience. Given the appeal of visualisations and the importance of networks in communicating the interdependence of species (including humans), ecological networks and their visualisation can be used to support excellent public engagement and can be used to enhance the value of citizen science, in which people actively contribute to scientific research. Network approaches could also be valuable for engagement with decision-makers and stakeholders, including their application to complex socio-economic systems, especially where co-production of network visualisations could provide evidence-based overviews of data. In summary, ecological networks and their visualisation are an important tool for scientific inquiry, communicatio
Insect pollination constitutes an ecosystem service of global importance, providing significant economic and aesthetic benefits as well as cultural value to human society, alongside vital ecological processes in terrestrial ecosystems. It is therefore important to understand how insect pollinator populations and communities respond to rapidly changing environments if we are to maintain healthy and effective pollinator services. This chapter considers the importance of conserving pollinator diversity to maintain a suite of functional traits and provide a diverse set of pollinator services. We explore how we can better understand and mitigate the factors that threaten insect pollinator richness, placing our discussion within the context of populations in predominantly agricultural landscapes in addition to urban environments. We highlight a selection of important evidence gaps, with a number of complementary research steps that can be taken to better understand: (i) the stability of pollinator communities in different landscapes in order to provide diverse pollinator services; (ii) how we can study the drivers of population change to mitigate the effects and support stable sources of pollinator services and (iii) how we can manage habitats in complex landscapes to support insect pollinators and provide sustainable pollinator services for the future. We advocate a collaborative effort to gain higher quality abundance data to understand the stability of pollinator populations and predict future trends. In addition, for effective mitigation strategies to be adopted, researchers need to conduct rigorous field testing of outcomes under different landscape settings, acknowledge the needs of end-users when developing research proposals and consider effective methods of knowledge transfer to ensure effective uptake of actions.
Technical University of Denmark (DTU) invites highly talented young researchers who have obtained outstanding results during their PhD studies and demonstrated excellence and potential in their field of study to apply for one of the 16 fellowships under the international H.C. Ørsted Postdoc COFUND Programme, co-funded by Marie Curie Actions.
Applicants can apply for an individual postdoctoral fellowship of 12 to 24 months. At the time of deadline, the applicant must not have resided or carried out their main activity in Denmark for more than 12 months in the 3 years immediately prior to the deadline. The applicant must be an Experienced Researcher, i.e. must have obtained a PhD degree, or be very close to graduating (PhD degree must be obtained by the time of employment).
Application deadline is Tuesday 23 February 2016 (midnight, CET).
The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web is a fruitful environment for the massive diffusion of unverified rumors. In this work, using a massive quantitative analysis of Facebook, we show that information related to distinct narratives––conspiracy theories and scientific news––generates homogeneous and polarized communities (i.e., echo chambers) having similar information consumption patterns. Then, we derive a data-driven percolation model of rumor spreading that demonstrates that homogeneity and polarization are the main determinants for predicting cascades’ size.
Mosaics of forests and grasslands—as shown here for the southern Patanal, Brazil—are common in the tropics and subtropics. The grasslands have long been interpreted as secondary vegetation produced by deforestation, and many are targets for “reforestation” (1). However, they have a rich endemic ancient biota adapted to frequent fires.
In recent years, several extreme weather disasters have partially or completely damaged regional crop production. While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964–2007. We show that droughts and extreme heat significantly reduced national cereal production by 9–10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8–11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.
We study a large data set of protein structure ensembles of very diverse sizes determined by nuclear magnetic resonance. By examining the distance-dependent correlations in the displacement of residues pairs and conducting finite size scaling analysis it was found that the correlations and susceptibility behave as in systems near a critical point implying that, at the native state, the motion of each amino acid residue is felt by every other residue up to the size of the protein molecule. Furthermore certain protein's shapes corresponding to maximum susceptibility were found to be more probable than others. Overall the results suggest that the protein's native state is critical, implying that despite being posed near the minimum of the energy landscape, they still preserve their dynamic flexibility.
Critical fluctuations in proteins native states Qian-Yuan Tang, Yang-Yang Zhang, Jun Wang, Wei Wang, Dante R. Chialvo
Real-world complex systems interact with one another, and these interactions increase the probability of catastrophic failure. Using interdependent networks to model these phenomena helps understand a system’s robustness and enables design of more robust infrastructures. Previous research has been limited to an idealized case where each layer is undirected, but almost all real-world networks are directed and exhibit in-degree and out-degree correlations. Therefore, we develop a general theoretical framework for analyzing the breakdown of interdependent directed networks with, or without, in-degree and out-degree correlations, and apply it to real-world international trade networks. Surprisingly, we find that the robustness of interdependent heterogeneous networks increases, whereas that of interdependent homogeneous networks with strong coupling strengths decreases with in-degree and out-degree correlations.
By importing food and agricultural goods, countries cope with the heterogeneous global water distribution and often rely on water resources available abroad. The virtual displacement of the water used to produce such goods (known as virtual water) connects together, in a global water system, all countries participating to the international trade network. Local food-production crises, having social, economic or environmental origin, propagate in this network, modifying the virtual water trade and perturbing local and global food availability, quantified in terms of virtual water. We analyze here the possible effects of local crises by developing a new propagation model, parsimonious but grounded on data-based and statistically-verified assumptions, whose effectiveness is proved on the Argentinean crisis in 2008–09. The model serves as the basis to propose indicators of crisis impact and country vulnerability to external food-production crises, which highlight that countries with largest water resources have the highest impact on the international trade, and that not only water-scarce but also wealthy and globalized countries are among the most vulnerable to external crises. The temporal analysis reveals that global average vulnerability has increased over time and that stronger effects of crises are now found in countries with low food (and water) availability.
Analysis of plant–frugivore interactions provides a quantitative framework for integrating community structure and ecosystem function in terms of how the roles and attributes of individual species contribute to network structure and resilience. In this study, we used centrality metrics to rank and detect the most important species in a mutualistic network of fruit-eating birds and plants in a cloud forest in the Colombian Andes. We identified a central core of ten bird and seven plant species in a network of 135 species that perform dual roles as local hubs and connectors. The birds were mostly large forest frugivores, such as cracids, cotingas, and toucans, which consume fruits of all sizes. The plants were species of intermediate successional stages with small- to medium-sized seeds that persist in mature forest or forest borders (e.g., Miconia, Cecropia,Ficus). We found the resilience of our network depends on super-generalist species, because their elimination makes the network more prone to disassemble than random extinctions, potentially disrupting seed-dispersal processes. At our study site, extirpation of large frugivores has already been documented, and if this continues, the network might collapse despite its high diversity. Our results suggest that generalist species play critical roles in ecosystem function and should be incorporated into conservation and monitoring programs.
Human impacts on the planet, including anthropogenic climate change, are reshaping ecosystems in unprecedented ways. To meet the challenge of conserving biodiversity in this rapidly changing world, we must understand how ecological assemblages respond to novel conditions (1). However, species in ecosystems are not fixed entities, even without human-induced change. All ecosystems experience natural turnover in species presence and abundance. Taking account of this baseline turnover in conservation planning could play an important role in protecting biodiversity.
Species diversity, and the various interactions that occur between species, supports ecosystems functioning and benefit human societies. Monitoring the response of species interactions to human alterations of the environment is thus crucial for preserving ecosystems. Ecological networks are now the standard method for representing and simultaneously analyzing all the interactions between species. However, deciphering such networks requires considerable time and resources to observe and sample the organisms, to identify them at the species level and to characterize their interactions. Next-generation sequencing (NGS) techniques, combined with network learning and modelling, can help alleviate these constraints. They are essential for observing cryptic interactions involving microbial species, as well as short-term interactions such as those between predator and prey. Here, we present three case studies, in which species associations or interactions have been revealed with NGS. We then review several currently available statistical and machine-learning approaches that could be used for reconstructing networks of direct interactions between species, based on the NGS co-occurrence data. Future developments of these methods may allow us to discover and monitor species interactions cost-effectively, under various environmental conditions and within a replicated experimental design framework.
A recent analysis of microbial community dynamics shows that, contrary to current assumption, too much cooperation among species can destabilize their communities. This is a first step towards understanding what makes a stable microbiome and, thus, transforming microbiome research into a more predictive science.
Receptors on the surface of lymphocytes specifically recognize foreign pathogens. The diversity of these receptors sets the range of infections that can be detected and fought off. Recent experiments show that, despite the many differences between these receptors in different cell types and species, their distribution of diversity is a strikingly reproducible power law. By introducing effective models of repertoire dynamics that include environmental and antigenic fluctuations affecting lymphocyte growth or “fitness,” we show that a temporally fluctuating fitness is responsible for the observed heavy tail distribution. These models are general and describe the dynamics of various cell types in different species. They allow for the classification of the functionally relevant repertoire dynamics from the features of the experimental distributions.
Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits—wood density, specific leaf area and maximum height—consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.
Tropical tree size distributions are remarkably consistent despite differences in the environments that support them. With data analysis and theory, we found a simple and biologically intuitive hypothesis to explain this property, which is the foundation of forest dynamics modeling and carbon storage estimates. After a disturbance, new individuals in the forest gap grow quickly in full sun until they begin to overtop one another. The two-dimensional space-filling of the growing crowns of the tallest individuals relegates a group of losing, slow-growing individuals to the understory. Those left in the understory follow a power-law size distribution, the scaling of which depends on only the crown area–to–diameter allometry exponent: a well-conserved value across tropical forests.
Patterns of species association reveal that terrestrial plant and animal communities today are structured differently from communities spanning the 300 million years that preceded large-scale human activity
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