Connectance of species interaction networks and conservation value: Is it any good to be well connected?

Recently, the focus of conservation efforts gradually changed from a species-centred approach to a broader ambition of conserving functional ecosystems. This new approach relies on the understanding that much ecosystem function is a result of the interaction of species to form complex interaction networks. Therefore measures summarising holistic attributes of such ecological networks have the potential to provide useful indicators to guide and assess conservation objectives. The most generally accepted insight is that complexity in species interactions, measured by network connectance, is an important attribute of healthy communities which usually protects them from secondary extinctions. An implicit and overlooked corollary to this generalization is that conservation efforts should be directed to conserve highly connected communities. We conducted a literature review to search for empirical evidence of a relationship between connectance (complexity) and conservation value (communities on different stages of degradation). Our results show that the often assumed positive relationship between highly connected and desirable (i.e. with high conservation value) communities does not derive from empirical data and that the topic deserves further discussion. Given the conflicting empirical evidence revealed in this study, it is clear that connectance on its own cannot provide clear information about conservation value. In the face of the ongoing biodiversity crisis, studies of species interaction networks should incorporate the different ‘conservation value’ of nodes (i.e. species) in a network if it is to be of practical use in guiding and evaluating conservation practice.     

Maximizing biodiversity, information and sustainability

Numerous global changes—notably anthropogenic extinction—force reconsideration of our management practices and the ways we regulate human influence in today’s world. Here, I define management to maximize biodiversity and illustrate the science that provides information to set goals for such management. Maximizing biodiversity simultaneously achieves sustainability and systemic health by avoiding the abnormal or pathological. The normal or sustainable are determined through the use of empirical integrative patterns to objectively account for the complexity of systems within which we find ourselves as a species. The science that reveals these integrative patterns provides measures of problems that can be solved by maximizing biodiversity—problems heretofore recognized only qualitatively. I use the Shannon-Weiner information index to test, and, with no surprise, reject the null hypothesis that there is no direct anthropogenic effect on biodiversity. The results of this science serve as examples of the kind of information most useful for guiding management and illustrate maximized biodiversity as a standard for management. Reference points based on maximized biodiversity are preferable to statistical parameters in meeting the objective of avoiding the abnormal or pathological in our interactions with other species, ecosystems and the biosphere. Management to maximize biodiversity is implemented by modifying human interactions with other biotic systems to achieve consistency in such interactions by mimicking natural role models of sustainability. Human influence is a significant factor in today’s world and the magnitude of such influence is illustrated by comparing humans with other species.     

Aging mechanism as the "down side" of adaptation: a network approach

Many diverse hypotheses on aging are in play. All from "aging genes" over decreasing telomere length to increased level of gene mutations has been suggested to determine an organism's lifespan, but no unifying theory exists. As part of a growing interest toward more integrative approaches in the field we propose a simplistic model based on the "use-it-or-lose-it" concept: we hypothesize that biological aging is a systemic property and the down side of adaptation in complex biological networks at various levels of organization: from brain over the immune system to specialized tissues or organs. The simple dynamical model undergoes three phases during its lifetime: (1) general plasticity (childhood), (2) optimization/adaptation to given conditions (youth and adolescence) and (3) steady state associated with high rigidity (aging). Furthermore, our model mimics recent data on the dynamics of the immune system during aging and, although simplistic, thus captures essential characteristics of the aging process. Finally, we discuss the abstract model in relation to current knowledge on aging and propose experimental setups for testing some of the theoretical predictions.     

A combined oligonucleotide and protein microarray for the codetection of nucleic acids and antibodies associated with human immunodeficiency virus, hepatitis B virus, and hepatitis C virus infections

A multiplexed assay based on the codetection of nucleic acids and antibodies in human serum infected by human immunodeficiency virus (HIV), hepatitis B virus (HBV) or hepatitis C virus was proposed. The combined immuno- and oligosorbent array (CombOLISA) microarray is prepared in 96-well standard microplates by spotting (1). nucleic probes specific for a virus genome, (2). viral proteins for the capture of serum antibodies, and (3). nonspecific proteins for verifying specificity. Experimental assay conditions were optimized so that both DNA hybridization and immunological reactions can be achieved simultaneously in the same well and buffer and all at the same temperature. A generic detection system based on the precipitation of an insoluble colorimetric substrate in the presence of enzyme-labeled antibodies or streptavidin was proposed. The optical density of each spot was correlated to the corresponding analyte concentration. The influence of critical parameters on CombOLISA performance such as serum concentration was studied. Calibration curves and sensitivity thresholds were established for each parameter. Serial dilutions of serum were correlated to results obtained with validated immunoassay platforms such as a microplate enzyme-linked immunosorbent assay or the VIDAS automat. Also, several HIV- and HBV-infected serum samples were tested independently by CombOLISA and VIDAS. Coefficients of variation for genomic and proteomic parameters vs spot density were below 15%.     

A complexity drain on cells in the evolution of multicellularity

A hypothesis has been advanced recently predicting that, in evolution, as higher-level entities arise from associations of lower-level organisms, and as these entities acquire the ability to feed, reproduce, defend themselves, and so on, the lower-level organisms will tend to lose much of their internal complexity (McShea 2001a). In other words, in hierarchical transitions, there is a drain on numbers of part types at the lower level. One possible rationale is that the transfer of functional demands to the higher level renders many part types at the lower level useless, and thus their loss in evolution is favored by selection for economy. Here, a test is conducted at the cell level, comparing numbers of part types in free-living eukaryotic cells (protists) and the cells of metazoans and land plants. Differences are significant and consistent with the hypothesis, suggesting that tests at other hierarchical levels may be worthwhile.     

Accuracy and precision of simpler and lower-cost technologies to measure the initial lean angle,step length and step velocity for forward lean releases

Current technologies to measure the maximum forward lean angle, step length and velocity in a clinical setting are neither simple nor cheap. Therefore, the purpose of this study was to determine the accuracy and precision of four live and one post-processing measurement methods compared to the 3D motion analysis gold standard. Twelve healthy younger adults recovered balance, after being released from six randomly ordered forward initial lean angles, using four different live measurement methods: LabVIEW, load cell, inclinometer and protractor. The initial lean angle, step length and velocity were also calculated in post-processing using 2D video analysis and 3D motion analysis. The LabVIEW method was the most accurate and precise, followed by the protractor, inclinometer and load cell methods. The load cell method was the most complex, followed by the LabVIEW, inclinometer and protractor methods. The LabVIEW method was the most expensive, followed by the load cell, inclinometer and protractor methods. Video analysis was sufficiently accurate and precise, equal in complexity and much less expensive than the gold standard. Simpler and lower-cost technologies to measure the initial lean angle, step length and velocity are sufficiently accurate and precise (live: protractor, post-processing: video analysis) to potentially use in a clinical setting.     

Exploring the temporal consequences of chasing the elements in Rosen's relational diagrams

In the work 'Life Itself', Rosen showed that a formal mechanism cannot be 'closed to efficient cause'. Additionally, he claimed that organisms are 'closed to efficient cause' and that, by logical extension, organisms cannot be mechanisms. This paper shows that it is possible for mechanisms to be 'nearly closed to efficient cause', with the requirement that some unentailed efficient-cause agents are placed inside the system. Populations of these 'nearly closed to efficient cause' systems can be defined based on the ability to isolate each component in its own 'reaction chamber'. Diagrams from these populations are drawn from a couple of different perspectives, and comments are made on how these diagrams can be related to the more conventional language of chemistry.     

Causality and complexity: the myth of objectivity in science

Two distinctly different worldviews dominate today's thinking in science and in the world of ideas outside of science. Using the approach advocated by Robert M. Hutchins, it is possible to see a pattern of interaction between ideas in science and in other spheres such as philosophy, religion, and politics. Instead of compartmentalizing these intellectual activities, it is worthwhile to look for common threads of mutual influence. Robert Rosen has created an approach to scientific epistemology that might seem radical to some. However, it has characteristics that resemble ideas in other fields, in particular in the writings of George Lakoff, Leo Strauss, and George Soros. Historically, the atmosphere at the University of Chicago during Hutchins' presidency gave rise to Rashevsky's relational biology, which Rosen carried forward. Strauss was writing his political philosophy there at the same time. One idea is paramount in all this, and it is Lakoff who gives us the most insight into how the worldviews differ using this idea. The central difference has to do with causality, the fundamental concept that we use to build a worldview. Causal entailment has two distinct forms in Lakoff 's analysis: direct causality and complex causality. Rosen's writings on complexity create a picture of complex causality that is extremely useful in its detail, grounding in the ideas of Aristotle. Strauss asks for a return to the ancients to put philosophy back on track. Lakoff sees the weaknesses in Western philosophy in a similar way, and Rosen provides tools for dealing with the problem. This introduction to the relationships between the thinking of these authors is meant to stimulate further discourse on the role of complex causal entailment in all areas of thought, and how it brings them together in a holistic worldview. The worldview built on complex causality is clearly distinct from that built around simple, direct causality. One important difference is that the impoverished causal entailment that accompanies the machine metaphor in science is unable to give us a clear way to distinguish living organisms from machines. Complex causality finds a dichotomy between organisms, which are closed to efficient cause, and machines, which require entailment from outside. An argument can be made that confusing living organisms with machines, as is done in the worldview using direct cause, makes religion a necessity to supply the missing causal entailment.     

Effects of spatial scale of sampling on food web structure

This study asks whether the spatial scale of sampling alters structural properties of food webs and whether any differences are attributable to changes in species richness and connectance with scale. Understanding how different aspects of sampling effort affect ecological network structure is important for both fundamental ecological knowledge and the application of network analysis in conservation and management. Using a highly resolved food web for the marine intertidal ecosystem of the Sanak Archipelago in the Eastern Aleutian Islands, Alaska, we assess how commonly studied properties of network structure differ for 281 versions of the food web sampled at five levels of spatial scale representing six orders of magnitude in area spread across the archipelago. Species (S) and link (L) richness both increased by approximately one order of magnitude across the five spatial scales. Links per species (L/S) more than doubled, while connectance (C) decreased by approximately two‐thirds. Fourteen commonly studied properties of network structure varied systematically with spatial scale of sampling, some increasing and others decreasing. While ecological network properties varied systematically with sampling extent, analyses using the niche model and a power‐law scaling relationship indicate that for many properties, this apparent sensitivity is attributable to the increasing S and decreasing C of webs with increasing spatial scale. As long as effects of S and C are accounted for, areal sampling bias does not have a special impact on our understanding of many aspects of network structure. However, attention does need be paid to some properties such as the fraction of species in loops, which increases more than expected with greater spatial scales of sampling.     

On the Possibility of Constructive Neutral Evolution

The neutral theory often is presented as a theory of ``noise' or silent changes at an isolated ``molecular level,' relevant to marking the steady pace of divergence, but not to the origin of biological structure, function, or complexity. Nevertheless, precisely these issues can be addressed in neutral models, such as those elaborated here with regard to scrambled ciliate genes, gRNA-mediated RNA editing, the transition from self-splicing to spliceosomal splicing, and the retention of duplicate genes. All of these are instances of a more general scheme of ``constructive neutral evolution' that invokes biased variation, epistatic interactions, and excess capacities to account for a complex series of steps giving rise to novel structures or operations. The directional and constructive outcomes of these models are due not to neutral allele fixations per se, but to these other factors. Neutral models of this type may help to clarify the poorly understood role of nonselective factors in evolutionary innovation and directionality. Received: 3 September 1998 / Accepted: 15 February 1999