Exploring alternative states in ecological systems with a qualitative analysis of community feedback

Demonstrating and predicting the existence of alternative states in natural communities remains a challenge for ecologists and is essential for resource managers. Positive feedback is often presented as central in maintaining alternative ecosystem states, but no formal approach relates this part of theory to real world applications. Through qualitative modelling of community response to long-term perturbations, we define generic mechanistic links between positive feedback and the occurrence of alternative states. Positive feedback diminishes a system's overall resistance to change, and can create and maintain correlations in the relative abundance of variables that coincide with alternative states.Through specific models of the dynamics of Tasmanian rocky-reef communities, which are affected by climate and fishing and persist within alternative states, we demonstrate the ability of our theoretical framework to predict alternative states in ecosystems and inform management intervention. A qualitative knowledge of community structure permits a thorough analysis of system feedback and an assessment of the potential for an ecosystem to exhibit alternative states. We illustrate the usefulness of the approach to inform management priorities, and to focus monitoring and field research on the key drivers of ecosystem dynamics.     

Generation and analysis of mixed chlorinated/brominated homologs of the halogenated natural product heptachloro-1'-methyl-1,2'-bipyrrole

The 2,3,3′,4,4′,5,5′-heptachloro-1′-methyl-1,2′-bipyrrole (Q1, MBP-79) and further halogenated 1′-methyl-1,2′-bipyrroles (MBPs) are a class of marine natural products repeatedly detected in seafood and marine mammals from all over the world. Only Q1 is currently commercially available as reference standard and the full synthesis of mixed brominated-chlorinated compound is rather complicated. For this reason, synthetic Q1 (240 mg) was transferred into bromine-containing MBPs by UV-irradiation in the presence of bromine. Bromine, which rapidly vanished from the solutions, was re-newed during the reaction in order to generate higher amounts of Br-containing MBPs. A total of ∼150 mg Q1 was transferred after ∼10 min irradiation with high amounts of Br₂ to give 30.5 mg BrCl₆-MBPs along with lower proportions of Br₂Cl₅-, Br₃Cl₄-, Br₄Cl₃- and traces of Br₅Cl₂-MBPs. Longer UV-irradiation in the presence of Br₂ even allowed for the detection of Br₆Cl-MBPs and traces of Br₇-MBP. However, this reaction also provided some unknown by-products. A sample stored in the dark and later in in-door light (no UV irradiation) also eliminated Q1 after 76 d in favour of heptahalogenated MBPs with up to three bromine substituents. The irradiation products were separated on silica, and fractions containing only Q1 and BrCl₆-MBPs were then further fractionated by non-aqueous RP-HPLC. A pure isolate of the major BrCl₆-MBP (∼1.5 mg) was characterized by GC/MS and ¹³C NMR to be 2-bromo-3,3′,4,4′,5,5′-hexachloro-1-methyl-1,2′-bipyrrole (Br-MBP-75). Partial GC enantioseparation of the axially chiral Br-MBP-75 was achieved on a β-PMCD column. A full enantioseparation was managed by enantioselective HPLC using a NUCLEOCEL DELTA S column. Low amounts of pure BrCl₆-MBP enantiomers could be trapped.     

Assessing model structure uncertainty through an analysis of system feedback and Bayesian networks.

Ecological predictions and management strategies are sensitive to variability in model parameters as well as uncertainty in model structure. Systematic analysis of the effect of alternative model structures, however, is often beyond the resources typically available to ecologists, ecological risk practitioners, and natural resource managers. Many of these practitioners are also using Bayesian belief networks based on expert opinion to fill gaps in empirical information. The practical application of this approach can be limited by the need to populate large conditional probability tables and the complexity associated with ecological feedback cycles. In this paper, we describe a modeling approach that helps solve these problems by embedding a qualitative analysis of sign directed graphs into the probabilistic framework of a Bayesian belief network. Our approach incorporates the effects of feedback on the model's response to a sustained change in one or more of its parameters, provides an efficient means to explore the effect of alternative model structures, mitigates the cognitive bias in expert opinion, and is amenable to stakeholder input. We demonstrate our approach by examining two published case studies: a host-parasitoid community centered on a nonnative, agricultural pest of citrus cultivars and the response of an experimental lake mesocosm to nutrient input. Observations drawn from these case studies are used to diagnose alternative model structures and to predict the system's response following management intervention.