Do evolution and ecology need the Gaia hypothesis?

Global patterns of human-wildlife spatial associations and implications for differentiating conservation strategies

Understanding the global patterns of human and wildlife spatial associations is essential for pragmatic conservation implementation, yet analytical foundations and indicator-based assessments that would further this understanding are lacking. We integrated the global distributions of 30,664 terrestrial vertebrates and human pressures to map human-nature index (HNI) categories that indicate the extent and intensity of human-wildlife interactions. Along the 2 dimensions of biodiversity and human activity, the HNI allowed placement of terrestrial areas worldwide in one of 4 HNI categories: anthropic (human-dominated areas), wildlife-dominated (little human influence and rich in wildlife), co-occurring (substantial presence of humans and wildlife), and harsh-environment (limited presence of humans and wildlife) areas. The HNI varied considerably among taxonomic groups, and the leading driver of HNI was global climate patterns. Co-occurring regions were the most prevalent (35.9%), and wildlife-dominated and anthropic regions encompassed 26.45% and 6.50% of land area, respectively. Our results highlight the necessity for customizing conservation strategies to regions based on human-wildlife spatial associations and the distribution of existing protected area networks. Human activity and biodiversity should be integrated for complementary strategies to support conservation toward ambitious and pragmatic 30×30 goals.

Planetary Scale Information Transmission in the Biosphere and Technosphere: Limits and Evolution

Information transmission via communication between agents is ubiquitous on Earth, and is a vital facet of living systems. In this paper, we aim to quantify this rate of information transmission associated with Earth's biosphere and technosphere (i.e., a measure of global information flow) by means of a heuristic order-of-magnitude model. By adopting ostensibly conservative values for the salient parameters, we estimate that the global information transmission rate for the biosphere might be ∼1024 bits/s, and that it may perhaps exceed the corresponding rate for the current technosphere by ∼9 orders of magnitude. However, under the equivocal assumption of sustained exponential growth, we find that information transmission in the technosphere can potentially surpass that of the biosphere ∼90 years in the future, reflecting its increasing dominance.

An ecosystem framework for understanding and treating disease

Pathogens and cancers are pervasive health risks in the human population. I argue that if we are to better understand disease and its treatment, then we need to take an ecological perspective of disease itself. I generalize and extend an emerging framework that views disease as an ecosystem and many of its components as interacting in a community. I develop the framework for biological etiological agents (BEAs) that multiply within humans—focusing on bacterial pathogens and cancers—but the framework could be extended to include other host and parasite species. I begin by describing why we need an ecosystem framework to understand disease, and the main components and interactions in bacterial and cancer disease ecosystems. Focus is then given to the BEA and how it may proceed through characteristic states, including emergence, growth, spread and regression. The framework is then applied to therapeutic interventions. Central to success is preventing BEA evasion, the best known being antibiotic resistance and chemotherapeutic resistance in cancers. With risks of evasion in mind, I propose six measures that either introduce new components into the disease ecosystem or manipulate existing ones. An ecosystem framework promises to enhance our understanding of disease, BEA and host (co)evolution, and how we can improve therapeutic outcomes.

Diversity-Function Relationships in Natural, Applied, and Engineered Microbial Ecosystems

The connection between ecosystem function and taxonomic diversity has been of interest and relevance to macroecologists for decades. After many years of lagging behind due to the difficulty of assigning both taxonomy and function to poorly distinguishable microscopic cells, microbial ecology now has access to a suite of powerful molecular tools which allow its practitioners to generate data relating to diversity and function of a microbial community on an unprecedented scale. Instead, the problem facing today's microbial ecologists is coupling the ease of generation of these datasets with the formulation and testing of workable hypotheses relating the diversity and function of environmental, host-associated, and engineered microbial communities. Here, we review the current state of knowledge regarding the links between taxonomic alpha- and beta-diversity and ecosystem function, comparing our knowledge in this area to that obtained by macroecologists who use more traditional techniques. We consider the methodologies that can be applied to study these properties and how successful they are at linking function to diversity, using examples from the study of model microbial ecosystems, methanogenic bioreactors (anaerobic digesters), and host-associated microbiota. Finally, we assess ways in which our newly acquired understanding might be used to manipulate diversity in ecosystems of interest in order to improve function for the benefit of us or the environment in general through the provision of ecosystem services.

Simple additive simulation overestimates real influence: altered nitrogen and rainfall modulate the effect of warming on soil carbon fluxes

Experiments and models have led to a consensus that there is positive feedback between carbon (C) fluxes and climate warming. However, the effect of warming may be altered by regional and global changes in nitrogen (N) and rainfall levels, but the current understanding is limited. Through synthesizing global data on soil C pool, input and loss from experiments simulating N deposition, drought and increased precipitation, we quantified the responses of soil C fluxes and equilibrium to the three single factors and their interactions with warming. We found that warming slightly increased the soil C input and loss by 5% and 9%, respectively, but had no significant effect on the soil C pool. Nitrogen deposition alone increased the soil C input (+20%), but the interaction of warming and N deposition greatly increased the soil C input by 49%. Drought alone decreased the soil C input by 17%, while the interaction of warming and drought decreased the soil C input to a greater extent (-22%). Increased precipitation stimulated the soil C input by 15%, but the interaction of warming and increased precipitation had no significant effect on the soil C input. However, the soil C loss was not significantly affected by any of the interactions, although it was constrained by drought (-18%). These results implied that the positive C fluxes-climate warming feedback was modulated by the changing N and rainfall regimes. Further, we found that the additive effects of [warming × N deposition] and [warming × drought] on the soil C input and of [warming × increased precipitation] on the soil C loss were greater than their interactions, suggesting that simple additive simulation using single-factor manipulations may overestimate the effects on soil C fluxes in the real world. Therefore, we propose that more multifactorial experiments should be considered in studying Earth systems.

From endosymbiosis to holobionts: Evaluating a conceptual legacy

In her influential 1967 paper, Lynn Margulis synthesized a range of data to support the idea of endosymbiosis. Building on the success of this work, she applied the same methodology to promote the role of symbiosis more generally in evolution. As part of this broader project, she coined the term 'holobiont' to refer to a unified entity of symbiont and host. This concept is now applied with great gusto in microbiome research, and often implies not just a physiological unit but also various senses of an evolving system. My analysis will track how Margulis came to propose the term, its current use in microbiome research, and how those applications link back to Margulis. I then evaluate what contemporary use says about Margulis's legacy for microbiome research.

Organismal homeostasis buffers the effects of abiotic change on community dynamics

The problem of linking fine-scale processes to broad-scale patterns remains a central challenge of ecology. As rates of abiotic change intensify, there is a critical need to understand how individual responses aggregate to generate compensatory dynamics that stabilize community processes. Notably, while local and global resource enhancement (e.g., nutrient and CO2 release) can reverse dominance relationship between key species (e.g., shifts from naturally kelp-dominated to turf-dominated systems), herbivores can counter these shifts by consuming the additional productivity of competing species (e.g., turfs). Here, we test whether consumer plasticity in energy intake to maintain growth in varying environments can underpin changes in consumption that buffer varying levels of productivity. In response to carbon and nutrient enrichment, herbivores increased consumption of higher-quality food, which acted as a buffer against enhanced production, while maintaining organismal processes across varying abiotic conditions (i.e., growth). These results not only suggest plasticity in feeding behavior, but also in energy acquisition and utilization to maintain organismal processes. Such plasticity may not only underpin organismal homeostasis, but also compensatory dynamics that emerge from the aggregate of these responses to buffer change in community processes.

The Case for a Gaian Bottleneck: The Biology of Habitability

The prerequisites and ingredients for life seem to be abundantly available in the Universe. However, the Universe does not seem to be teeming with life. The most common explanation for this is a low probability for the emergence of life (an emergence bottleneck), notionally due to the intricacies of the molecular recipe. Here, we present an alternative Gaian bottleneck explanation: If life emerges on a planet, it only rarely evolves quickly enough to regulate greenhouse gases and albedo, thereby maintaining surface temperatures compatible with liquid water and habitability. Such a Gaian bottleneck suggests that (i) extinction is the cosmic default for most life that has ever emerged on the surfaces of wet rocky planets in the Universe and (ii) rocky planets need to be inhabited to remain habitable. In the Gaian bottleneck model, the maintenance of planetary habitability is a property more associated with an unusually rapid evolution of biological regulation of surface volatiles than with the luminosity and distance to the host star.

What good are abstract and what-if models? Lessons from the Gaïa hypothesis

This article on the epistemology of computational models stems from an analysis of the Gaïa hypothesis (GH). It begins with James Kirchner's criticisms of the central computational model of GH: Daisyworld. Among other things, the model has been criticized for being too abstract, describing fictional entities (fictive daisies on an imaginary planet) and trying to answer counterfactual (what-if) questions (how would a planet look like if life had no influence on it?). For these reasons the model has been considered not testable and therefore not legitimate in science, and in any case not very interesting since it explores non actual issues. This criticism implicitly assumes that science should only be involved in the making of models that are "actual" (by opposition to what-if) and "specific" (by opposition to abstract). I challenge both of these criticisms in this article. First by showing that although the testability-understood as the comparison of model output with empirical data-is an important procedure for explanatory models, there are plenty of models that are not testable. The fact that these are not testable (in this restricted sense) has nothing to do with their being "abstract" or "what-if" but with their being predictive models. Secondly, I argue that "abstract" and "what-if" models aim at (respectable) epistemic purposes distinct from those pursued by "actual and specific models". Abstract models are used to propose how-possibly explanation or to pursue theorizing. What-if models are used to attribute causal or explanatory power to a variable of interest. The fact that they aim at different epistemic goals entails that it may not be accurate to consider the choice between different kinds of model as a "strategy".

The emergence of environmental homeostasis in complex ecosystems

The Earth, with its core-driven magnetic field, convective mantle, mobile lid tectonics, oceans of liquid water, dynamic climate and abundant life is arguably the most complex system in the known universe. This system has exhibited stability in the sense of, bar a number of notable exceptions, surface temperature remaining within the bounds required for liquid water and so a significant biosphere. Explanations for this range from anthropic principles in which the Earth was essentially lucky, to homeostatic Gaia in which the abiotic and biotic components of the Earth system self-organise into homeostatic states that are robust to a wide range of external perturbations. Here we present results from a conceptual model that demonstrates the emergence of homeostasis as a consequence of the feedback loop operating between life and its environment. Formulating the model in terms of Gaussian processes allows the development of novel computational methods in order to provide solutions. We find that the stability of this system will typically increase then remain constant with an increase in biological diversity and that the number of attractors within the phase space exponentially increases with the number of environmental variables while the probability of the system being in an attractor that lies within prescribed boundaries decreases approximately linearly. We argue that the cybernetic concept of rein control provides insights into how this model system, and potentially any system that is comprised of biological to environmental feedback loops, self-organises into homeostatic states.

Life on Earth is perhaps greater than three and a half billion years old and it would appear that once it started it never stopped. During this period a number of dramatic shocks and drivers have affected the Earth. These include the impacts of massive asteroids, runaway climate change and increases in brightness of the Sun. Has life on Earth simply been lucky in withstanding such perturbations? Are there any self-regulating or homeostatic processes operating in the Earth system that would reduce the severity of such perturbations? If such planetary processes exist, to what extent are they the result of the actions of life? In this study, we show how the regulation of environmental conditions can emerge as a consequence of life's effects. If life is both affected by and affects it environment, then this coupled system can self-organise into a robust control system that was first described during the early cybernetics movement around the middle of the twentieth century. Our findings are in principle applicable to a wide range of real world systems - from microbial mats to aquatic ecosystems up to and including the entire biosphere.

Oscillating microbial dynamics driven by small populations, limited nutrient supply and high death rates

Predicting and controlling the behaviour of microbial ecosystems demands a fundamental understanding of the factors controlling their dynamics. In the natural environment microbes typically live in small local populations with limited and unpredictable nutrient supply and high death rates. Here, we show that these conditions can produce oscillations in microbial population dynamics, even for a single population. For a large population, with deterministic growth dynamics, our model predicts transient (damped) oscillations. For a small population, demographic noise causes these oscillations to be sustained indefinitely. We show that the same mechanism can produce sustained stochastic oscillations in a two-species, nutrient-cycling microbial ecosystem. Our results suggest that oscillatory population dynamics may be a common feature of small microbial populations in the natural environment, even in the absence of complex interspecies interactions or spatial structuring.

Theory of the origin, evolution, and nature of life

Life is an inordinately complex unsolved puzzle. Despite significant theoretical progress, experimental anomalies, paradoxes, and enigmas have revealed paradigmatic limitations. Thus, the advancement of scientific understanding requires new models that resolve fundamental problems. Here, I present a theoretical framework that economically fits evidence accumulated from examinations of life. This theory is based upon a straightforward and non-mathematical core model and proposes unique yet empirically consistent explanations for major phenomena including, but not limited to, quantum gravity, phase transitions of water, why living systems are predominantly CHNOPS (carbon, hydrogen, nitrogen, oxygen, phosphorus, and sulfur), homochirality of sugars and amino acids, homeoviscous adaptation, triplet code, and DNA mutations. The theoretical framework unifies the macrocosmic and microcosmic realms, validates predicted laws of nature, and solves the puzzle of the origin and evolution of cellular life in the universe.

Regime shift and robustness of organism-created environments: A model for microbial ecosystems

Organism-environment interactions are different from organism-resource interactions in two respects: (1) resources can only be consumed by organisms whereas environmental conditions can be increased or decreased depending on the species; (2) high resource conditions generally stimulate the growth of organisms, whereas extreme environmental conditions are not necessarily favored because each species usually has an optimum range for growth. To investigate the properties of an organism-environment feedback system, we analyze a model for microbial ecosystems in which a single microorganism species can modify the environmental pH. We demonstrate that the equilibrium level of the environmental pH can be partially regulated at a relatively constant value even if the pH in the influx to the ecosystem changes over a wide range. For species that acidify the medium, the equilibrium pH is somewhat lower than the pH optimal for the species. The pH-stabilizing effect of microorganisms is stronger if their growth is self-limited by the environmental pH. When the influx becomes sufficiently alkaline, the population of the organism suddenly disappears and the environmental pH changes abruptly. The system shows bi-stability and hysteresis and therefore differs from a standard resource competition model composed of a single species that consumes resources.

Parallel ecological networks in ecosystems

In ecosystems, species interact with other species directly and through abiotic factors in multiple ways, often forming complex networks of various types of ecological interaction. Out of this suite of interactions, predator-prey interactions have received most attention. The resulting food webs, however, will always operate simultaneously with networks based on other types of ecological interaction, such as through the activities of ecosystem engineers or mutualistic interactions. Little is known about how to classify, organize and quantify these other ecological networks and their mutual interplay. The aim of this paper is to provide new and testable ideas on how to understand and model ecosystems in which many different types of ecological interaction operate simultaneously. We approach this problem by first identifying six main types of interaction that operate within ecosystems, of which food web interactions are one. Then, we propose that food webs are structured among two main axes of organization: a vertical (classic) axis representing trophic position and a new horizontal 'ecological stoichiometry' axis representing decreasing palatability of plant parts and detritus for herbivores and detrivores and slower turnover times. The usefulness of these new ideas is then explored with three very different ecosystems as test cases: temperate intertidal mudflats; temperate short grass prairie; and tropical savannah.

Ecological and evolutionary consequences of niche construction for its agent

Niche construction can generate ecological and evolutionary feedbacks that have been underinvestigated so far. We present an eco-evolutionary model that incorporates the process of niche construction to reveal its effects on the ecology and evolution of the niche-constructing agent. We consider a simple plant-soil nutrient ecosystem in which plants have the ability to increase the input of inorganic nutrient as an example of positive niche construction. On an ecological time scale, the model shows that niche construction allows the persistence of plants under infertile soil conditions that would otherwise lead to their extinction. This expansion of plants' niche, however, requires a high enough rate of niche construction and a high enough initial plant biomass to fuel the positive ecological feedback between plants and their soil environment. On an evolutionary time scale, we consider that the rates of niche construction and nutrient uptake coevolve in plants while a trade-off constrains their values. Different evolutionary outcomes are possible depending on the shape of the trade-off. We show that niche construction results in an evolutionary feedback between plants and their soil environment such that plants partially regulate soil nutrient content. The direct benefit accruing to plants, however, plays a crucial role in the evolutionary advantage of niche construction.