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1.
Sci Total Environ ; 648: 1560-1569, 2019 Jan 15.
Article in English | MEDLINE | ID: mdl-30340301

ABSTRACT

Agricultural intensification has significantly increased yields and fed growing populations across the planet, but has also led to considerable environmental degradation. In response an alternative process of 'Sustainable Intensification' (SI), whereby food production increases while environmental impacts are reduced, has been advocated as necessary, if not sufficient, for delivering food and environmental security. However, the extent to which SI has begun, the main drivers of SI, and the degree to which degradation is simply 'offshored' are uncertain. In this study we assess agroecosystem services in England and two contrasting sub-regions, majority-arable Eastern England and majority-pastoral South-Western England, since 1950 by analysing ecosystem service metrics and developing a simple system dynamics model. We find that rapid agricultural intensification drove significant environmental degradation in England in the early 1980s, but that most ecosystem services except farmland biodiversity began to recover after 2000, primarily due to reduced livestock and fertiliser usage decoupling from high yields. This partially follows the trajectory of an Environmental Kuznets Curve, with yields and GDP growth decoupling from environmental degradation above ~£17,000 per capita per annum. Together, these trends suggest that SI has begun in England. However, the lack of recovery in farmland biodiversity, and the reduction in UK food self-sufficiency resulting in some agricultural impacts being 'offshored', represent major negative trade-offs. Maintaining yields and restoring biodiversity while also addressing climate change, offshored degradation, and post-Brexit subsidy changes will require significant further SI in the future.


Subject(s)
Agriculture/methods , Conservation of Natural Resources/methods , Models, Theoretical , United Kingdom
2.
Trends Ecol Evol ; 33(8): 633-645, 2018 08.
Article in English | MEDLINE | ID: mdl-30041995

ABSTRACT

Recently postulated mechanisms and models can help explain the enduring 'Gaia' puzzle of environmental regulation mediated by life. Natural selection can produce nutrient recycling at local scales and regulation of heterogeneous environmental variables at ecosystem scales. However, global-scale environmental regulation involves a temporal and spatial decoupling of effects from actors that makes conventional evolutionary explanations problematic. Instead, global regulation can emerge by a process of 'sequential selection' in which systems that destabilize their environment are short-lived and result in extinctions and reorganizations until a stable attractor is found. Such persistence-enhancing properties can in turn increase the likelihood of acquiring further persistence-enhancing properties through 'selection by survival alone'. Thus, Earth system feedbacks provide a filter for persistent combinations of macroevolutionary innovations.


Subject(s)
Ecosystem , Models, Biological , Biological Evolution , Earth, Planet , Feedback , Selection, Genetic
3.
Ecology ; 97(11): 3079-3090, 2016 11.
Article in English | MEDLINE | ID: mdl-27870052

ABSTRACT

Global environmental change presents a clear need for improved leading indicators of critical transitions, especially those that can be generated from compositional data and that work in empirical cases. Ecological theory of community dynamics under environmental forcing predicts an early replacement of slowly replicating and weakly competitive "canary" species by slowly replicating but strongly competitive "keystone" species. Further forcing leads to the eventual collapse of the keystone species as they are replaced by weakly competitive but fast-replicating "weedy" species in a critical transition to a significantly different state. We identify a diagnostic signal of these changes in the coefficients of a correlation between compositional disorder and biodiversity. Compositional disorder measures unpredictability in the composition of a community, while biodiversity measures the amount of species in the community. In a stochastic simulation, sequential correlations over time switch from positive to negative as keystones prevail over canaries, and back to positive with domination of weedy species. The model finds support in empirical tests on multi-decadal time series of fossil diatom and chironomid communities from lakes in China. The characteristic switch from positive to negative correlation coefficients occurs for both communities up to three decades preceding a critical transition to a sustained alternate state. This signal is robust to unequal time increments that beset the identification of early-warning signals from other metrics.


Subject(s)
Biodiversity , Diatoms/physiology , Insecta/physiology , Models, Biological , Animals , Population Dynamics , Stochastic Processes
4.
PLoS Comput Biol ; 9(5): e1003050, 2013.
Article in English | MEDLINE | ID: mdl-23696719

ABSTRACT

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.


Subject(s)
Earth, Planet , Ecosystem , Homeostasis , Models, Biological , Computational Biology , Computer Simulation
5.
J Theor Biol ; 313: 172-80, 2012 Nov 21.
Article in English | MEDLINE | ID: mdl-22902427

ABSTRACT

Models which explore the possibilities of emergent self-regulation in the Earth system often assume the timescales associated with changes in various sub-systems to be predetermined. Given their importance in guiding the fixed point dynamics of such models, relatively little formalism has been established. We analyse a classic model of environmental self-regulation, Daisyworld, and interpret the original equations for model temperature, changes in insolation, and self-organisation of the biota as an important separation of timescales. This allows a simple analytical solution where the model is reduced to two states while retaining important characteristics of the original model. We explore the consequences of relaxing some key assumptions. We show that increasing the rate of change of insolation relative to adaptation of the biota shows a sharp transition between regulating, and lifeless states. Additionally, in slowing the rate of model temperature change relative to the adapting biota we derive expressions for the damping rate of fluctuations, along with a threshold beyond which damped oscillations occur. We relax the assumption that seeding occurs globally by extending this analysis to solve a two-dimensional cellular automata Daisyworld. We conclude by reviewing a number of previous Daisyworld models and make explicit their respective timescales, and how their behaviour can be understood in light of our analysis.


Subject(s)
Environment , Models, Biological , Social Control, Informal , Computer Simulation , Diffusion , Numerical Analysis, Computer-Assisted , Temperature , Time Factors
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