Biocomplexity: the Autonomous Agroecological Alternative

Abstract

This dissertation examines biocomplexity in agroecological systems. Throughout the dissertation, theoretical frameworks are developed, and then validated using empirical and observational studies. Three major themes are explored: 1) autonomous biological control, 2) fragmented landscapes, and 3) the complex and irreversible consequences of human-management for ecosystem states.

In autonomous biological control, interactions between diverse assemblages of natural enemies are hypothesized to maintain pest populations consistently below economic thresholds. Chapters I-III test whether autonomous biological control can be achieved through strong negative coupling of biological control agents that are ineffective in isolation. Competing agents wrestle for dominance, but are unable to persist in isolation. Pests move chaotically between control by one or the other agent, yet remain for long timescales at densities below economic thresholds. Coupling biological control agents may also reduce spatial clustering in pests, eliminating local outbreaks.

Chapters IV-V assess the population structures of pest-natural enemy systems across fragmented urban landscapes. Fragmentation can structure populations along a continuum between metapopulations and source-sinks. Dispersal from sources to sinks synchronizes population fluctuations, while isolation in metapopulations causes asynchrony. This structure leaves signatures on the spatio-temporal dynamics of populations. Asynchrony can reduce variances in populations to levels lower than their mean sizes would predict, causing the exponent of a well known scaling law, Taylor’s law to move towards 1. Thus, calculations of Taylor’s law may help in addressing where populations in fragmented landscapes exist on the continuum between metapopulations and source-sinks. This approach paired with a microsatellite analysis of aphid population genetics suggest that urban gardens in Ann Arbor may represent sinks for dispersing aphids. Chapters VI and VII examine the potential for management decisions to irreversibly impact biological control and agriculture. When parameters in simple population and nutrient dynamic models are correlated, complicated hysteretic patterns including “unattainable” stable states emerge. Certain desirable ecosystem states, once lost, may never be recovered.

In summary, biocomplexity very easily emerges from interactions between components of diverse agricultural systems. Spatial heterogeneity, a defining characteristic of agriculture, further increases this complexity. These complexities can be leveraged to promote the success of agroecological alternatives to harmful conventional practices.