The dilemma of the selfish herd: the search for a realistic movement rule

The selfish herd hypothesis predicts that aggregations form because individuals move toward one another to minimize their own predation risk. The "dilemma of the selfish herd" is that movement rules that are easy for individuals to follow, fail to produce true aggregations, while rules that produce aggregations require individual behavior so complex that one may doubt most animals can follow them. If natural selection at the individual level is responsible for herding behavior, a solution to the dilemma must exist. Using computer simulations, we examined four different movement rules. Relative predation risk was different for all four movement rules (p<0.05). We defined three criteria for measuring the quality of a movement rule. A good movement rule should (a) be statistically likely to benefit an individual that follows it, (b) be something we can imagine most animals are capable of following, and (c) result in a centrally compact flock. The local crowded horizon rule, which allowed individuals to take the positions of many flock-mates into account, but decreased the influence of flock-mates with distance, best satisfied these criteria. The local crowded horizon rule was very sensitive to the animal's perceptive ability. Therefore, the animal's ability to detect its neighbors is an important factor in the dynamics of group formation.     

Optimization of Landscape Services under Uncoordinated Management by Multiple Landowners

Landscapes are often patchworks of private properties, where composition and configuration patterns result from cumulative effects of the actions of multiple landowners. Securing the delivery of services in such multi-ownership landscapes is challenging, because it is difficult to assure tight compliance to spatially explicit management rules at the level of individual properties, which may hinder the conservation of critical landscape features. To deal with these constraints, a multi-objective simulation-optimization procedure was developed to select non-spatial management regimes that best meet landscape-level objectives, while accounting for uncoordinated and uncertain response of individual landowners to management rules. Optimization approximates the non-dominated Pareto frontier, combining a multi-objective genetic algorithm and a simulator that forecasts trends in landscape pattern as a function of management rules implemented annually by individual landowners. The procedure was demonstrated with a case study for the optimum scheduling of fuel treatments in cork oak forest landscapes, involving six objectives related to reducing management costs (1), reducing fire risk (3), and protecting biodiversity associated with mid- and late-successional understories (2). There was a trade-off between cost, fire risk and biodiversity objectives, that could be minimized by selecting management regimes involving ca. 60% of landowners clearing the understory at short intervals (around 5 years), and the remaining managing at long intervals (ca. 75 years) or not managing. The optimal management regimes produces a mosaic landscape dominated by stands with herbaceous and low shrub understories, but also with a satisfactory representation of old understories, that was favorable in terms of both fire risk and biodiversity. The simulation-optimization procedure presented can be extended to incorporate a wide range of landscape dynamic processes, management rules and quantifiable objectives. It may thus be adapted to other socio-ecological systems, particularly where specific patterns of landscape heterogeneity are to be maintained despite imperfect management by multiple landowners.     

The sleeping policeman: understanding issues of enforcement and compliance in conservation

Rules governing human behaviour are at the heart of every system of natural resource management. Without compliance, however, rules are meaningless so effective enforcement is essential if conservation is to be successful. There is a large body of theory concerning enforcement and compliance with rules spread over several disciplines, including psychology, economics and sociology. However, there have been few attempts to extend this theory to conservation applications and there is little practical guidance for managers and conservation planners on the optimal design of enforcement programmes. We review approaches to understanding why individuals break rules and how optimal policy choices can reduce rule-breaking, highlighting research which has specifically dealt with natural resources. Because of the difficulty of studying rule-breaking behaviour directly, modelling approaches have been particularly important and have been used to explore behaviour at the individual, group and institutional levels. We illustrate the application of models of enforcement and compliance to conservation using the African elephant Loxodonta africana as a case study. Further work is needed to create practical tools which can be applied to the design of enforcement measures in conservation. Particular challenges include understanding the importance of violations of rationality assumptions and incorporating intertemporal choice in models of decision making. In conclusion, we argue that a new field of robust theory and practice is urgently needed to ensure that issues of enforcement and compliance do not undermine conservation initiatives.     

Decision Rules and Group Rationality: Cognitive Gain or Standstill?

Recent research in group cognition points towards the existence of collective cognitive competencies that transcend individual group members’ cognitive competencies. Since rationality is a key cognitive competence for group decision making, and group cognition emerges from the coordination of individual cognition during social interactions, this study tests the extent to which collaborative and consultative decision rules impact the emergence of group rationality. Using a set of decision tasks adapted from the heuristics and biases literature, we evaluate rationality as the extent to which individual choices are aligned with a normative ideal. We further operationalize group rationality as cognitive synergy (the extent to which collective rationality exceeds average or best individual rationality in the group), and we test the effect of collaborative and consultative decision rules in a sample of 176 groups. Our results show that the collaborative decision rule has superior synergic effects as compared to the consultative decision rule. The ninety one groups working in a collaborative fashion made more rational choices (above and beyond the average rationality of their members) than the eighty five groups working in a consultative fashion. Moreover, the groups using a collaborative decision rule were closer to the rationality of their best member than groups using consultative decision rules. Nevertheless, on average groups did not outperformed their best member. Therefore, our results reveal how decision rules prescribing interpersonal interactions impact on the emergence of collective cognitive competencies. They also open potential venues for further research on the emergence of collective rationality in human decision-making groups.     

Self-amplification as a source of interindividual variability: Shelter selection in cockroaches

Although group effect and collective decisions have been described in many insect species, the behavioral mechanisms involved in the process remain poorly documented at the individual level. We examined how individual behavior depends on the environmental context and we precisely characterized the behavioral rules leading to settlement of individual cockroaches in resting site. We focused on the spatial and temporal distribution of individuals in absence of conspecifics. Using isolated adult males of the cockroach Periplaneta americana, we showed that the quality of resting sites and the duration of the settlement exerted an influence on the individual decision-making: the probability of leaving a resting site decreased with the time spent under a shelter. A numerical model derived from experimental data suggested that this simple rule of self-amplification can also account for the interindividual variability.     

Interspecific pairwise relationships among body size, clutch size and latitude: deconstructing a macroecological triangle in birds

Aim Ecogeographical ‘rules’, large‐scale patterns in ecological variables across geographical space, can provide important insights into the mechanisms of evolution and ecological assembly. However, interactions between rules could obscure both the observation of large‐scale patterns and their interpretation. Here, we examine a system of three variables interrelated by ecogeographical rules – the latitudinal increase in body size within closely related homeotherms (Bergmann’s rule), the negative allometry of clutch size (Calder’s rule) and the latitudinal increase in clutch size (Lack’s rule) – in a global dataset of birds. Location Global. Methods We used linear regressions and meta‐analysis techniques to quantify the three rules across clades and through the taxonomic hierarchy. Path analysis was used to quantify interactions between rules at multiple taxonomic levels, as a function of both phylogenetic inheritance of traits and indirect feedbacks between the three rules. Independent contrasts analyses were performed on four clades with available phylogenies, and the taxonomic partitioning of variation in each trait was quantified. Results Standardizing across all clades, Lack’s and Bergmann’s rules were supported at all taxonomic levels, with Calder’s rule being supported at the order level. Lack’s rule was consistently stronger and more often detected than the other two rules. Path analysis showed that the indirect effects often outweighed the direct effects of Calder’s rule at the genus level and Bergmann’s rule at the order level. Strong interactions between Calder’s and Bergmann’s rules led to a trade‐off between the rules depending on taxonomic resolution. Main conclusions We found strong interactions between Bergmann’s, Lack’s and Calder’s rules in birds, and these interactions varied in strength and direction over the taxonomic hierarchy and among avian clades. Ecogeographical rules may be masked by feedbacks from other, correlated variables, even when the underlying selective mechanism is operating. The apparently conflicting pairwise relationships among clutch size, body size and latitude illustrate the difficulty of interpreting individual pairwise correlations without recognition of interdependence with other variables.     

Linking Moose Population and Plant Growth Models with a Moose Energetics Model

Selective foraging by large mammals can change ecosystem properties such as plant species composition, nutrient cycling rates, and soil fertility. These changes, in turn, alter the availability of forage and could affect the relative efficiencies of foraging strategies used by these animals. We used a simulation model to predict how alternate foraging strategies affected the net annual energy balance of moose (Alces alces), moose density, and distribution of browse across the landscape. The model simulates the spatial distribution of vegetation in an 8-ha landscape of 1-m² cells with seasonal changes in the energetic needs of free-ranging moose and plant phenology. The energetics model was integrated with a moose population model and a plant-growth model for long-term simulations. Changes in bite density in each feeding station are predicted with height and biomass logistic curves modified by a quadratic response to browsing. We tested foraging strategies using random, fractional, and marginal value theorem (MVT) algorithms on landscapes with a range of bite densities and differing spatial distributions. Small-scale disturbances (that is, tree-fall gaps) were required to maintain browse supply and prevent moose population extinction under all foraging strategies. Populations using a fractional stopping rule survived the 100-year simulations because moose browsed across much of the landscape and did not overbrowse patches with high bite density. Populations using random and MVT stopping rules became extinct in about 25 and about 50 years, respectively. Moose using a random stopping rule were in negative energy balance because travel time was high and the net energy intake rate was low on an annual basis. Moose using the MVT stopping rule were initially in positive energy balance, but as the high-density browse patches were overbrowsed and low-density unbrowsed patches grew out of reach, bite density decreased, and energy balance became negative in subsequent years. Thus, the foraging strategy used by individual moose resulted in creation of landscapes that strongly affected browse density, browse distribution, moose population density, and moose survival. Received 30 April 1997; accepted 5 August 1997.     

Management strategy evaluation: a powerful tool for conservation?

The poor management of natural resources has led in many cases to the decline and extirpation of populations. Recent advances in fisheries science could revolutionize management of harvested stocks by evaluating management scenarios in a virtual world by including stakeholders and by assessing its robustness to uncertainty. These advances have been synthesized into a framework, management strategy evaluation (MSE), which has hitherto not been used in terrestrial conservation. We review the potential of MSE to transform terrestrial conservation, emphasizing that the behavior of individual harvesters must be included because harvester compliance with management rules has been a major challenge in conservation. Incorporating resource user decision-making required to make MSEs relevant to terrestrial conservation will also advance fisheries science.     

Integrated assessment of ecological status and misclassification of lakes: The role of uncertainty and index combination rules

The European Water Framework Directive (WFD) requires that the ecological status of waterbodies is assessed using multiple biological quality elements (BQEs) that are combined into a single status class. The recommended combination rule (the “one-out, all-out” rule; OOAO) has been criticised for being unreasonably conservative and for being sensitive to uncertainty. In this study, the objective was to compare the sensitivity to uncertainty of four different combination rules: (1) OOAO, (2) OOAO with exclusion of one element, (3) average and (4) weighted average. Index values for 5 BQEs (phytoplankton, phytobenthos, macrophytes, macroinvertebrates and fish) sampled from 10 lakes in the Wel River catchment in Poland were used to classify the lakes according to the OOAO and the three alternative combination rules. Based on the mean and (where possible) standard deviation of these index values, we modelled the risk of misclassification by simulating 10,000 resamples for each BQEs in each lake, classifying each resample and calculating the proportion of misclassified resamples under each combination rule. For individual BQEs, the risk of misclassification increased both with higher uncertainty (standard deviation) and with the proximity of the index value to a class boundary. Under the OOAO rule, the risk of misclassification was more biased towards worse status (“underclassification”) than towards better status. Furthermore, risk of underclassification was more affected by uncertainty under the OOAO rule compared with the alternative combination rules. This analysis has demonstrated the weaknesses associated with the OOAO rule for integration of BQEs for lake classification. However, the alternative combination rules are associated with other shortcomings, such as the need for subjective judgement, and involve a higher risk of not protecting the most sensitive BQE and thus the whole ecosystem. We recommend that future versions of instructions for WFD implementation consider alternatives to the OOAO combination rule, and provide guidelines for weighting of individual BQEs.     

Performance of random forest when SNPs are in linkage disequilibrium

Background

Proteases of human pathogens are becoming increasingly important drug targets, hence it is necessary to understand their substrate specificity and to interpret this knowledge in practically useful ways. New methods are being developed that produce large amounts of cleavage information for individual proteases and some have been applied to extract cleavage rules from data. However, the hitherto proposed methods for extracting rules have been neither easy to understand nor very accurate. To be practically useful, cleavage rules should be accurate, compact, and expressed in an easily understandable way.

Results

A new method is presented for producing cleavage rules for viral proteases with seemingly complex cleavage profiles. The method is based on orthogonal search-based rule extraction (OSRE) combined with spectral clustering. It is demonstrated on substrate data sets for human immunodeficiency virus type 1 (HIV-1) protease and hepatitis C (HCV) NS3/4A protease, showing excellent prediction performance for both HIV-1 cleavage and HCV NS3/4A cleavage, agreeing with observed HCV genotype differences. New cleavage rules (consensus sequences) are suggested for HIV-1 and HCV NS3/4A cleavages. The practical usability of the method is also demonstrated by using it to predict the location of an internal cleavage site in the HCV NS3 protease and to correct the location of a previously reported internal cleavage site in the HCV NS3 protease. The method is fast to converge and yields accurate rules, on par with previous results for HIV-1 protease and better than previous state-of-the-art for HCV NS3/4A protease. Moreover, the rules are fewer and simpler than previously obtained with rule extraction methods.

Conclusion

A rule extraction methodology by searching for multivariate low-order predicates yields results that significantly outperform existing rule bases on out-of-sample data, but are more transparent to expert users. The approach yields rules that are easy to use and useful for interpreting experimental data.     

生物技术的商业化原则及其未来

生物技术就是应用自然科学及工程学的原理 ,依靠微生物、动物、植物作为反应器 ,将物料进行加工以提高产品来为社会服务的技术。文章在重点分析了世界生物技术研究开发、产业发展状况及其管理策略基础上 ,探讨了生物技术及其产业的商业化系统模型以及系统各要素之间的关系 ,阐明了建立生物技术商业化系统的 4项原则 ,即相对优势的竞争原则 ,行业的乘数效应原则 ,投资的获得与运营原则和协调管理的价值实现原则 ,并提出了生物技术未来发展的设想。     

Scalable rules for coherent group motion in a gregarious vertebrate

Individuals of gregarious species that initiate collective movement require mechanisms of cohesion in order to maintain advantages of group living. One fundamental question in the study of collective movement is what individual rules are employed when making movement decisions. Previous studies have revealed that group movements often depend on social interactions among individual members and specifically that collective decisions to move often follow a quorum-like response. However, these studies either did not quantify the response function at the individual scale (but rather tested hypotheses based on group-level behaviours), or they used a single group size and did not demonstrate which social stimuli influence the individual decision-making process. One challenge in the study of collective movement has been to discriminate between a common response to an external stimulus and the synchronization of behaviours resulting from social interactions. Here we discriminate between these two mechanisms by triggering the departure of one trained Merino sheep (Ovis aries) from groups containing one, three, five and seven naïve individuals. Each individual was thus exposed to various combinations of already-departed and non-departed individuals, depending on its rank of departure. To investigate which individual mechanisms are involved in maintaining group cohesion under conditions of leadership, we quantified the temporal dynamic of response at the individual scale. We found that individuals'' decisions to move do not follow a quorum response but rather follow a rule based on a double mimetic effect: attraction to already-departed individuals and attraction to non-departed individuals. This rule is shown to be in agreement with an adaptive strategy that is inherently scalable as a function of group size.     

XCSc: a novel approach to clustering with extended classifier system

In this paper, we propose a novel approach to clustering noisy and complex data sets based on the eXtend Classifier Systems (XCS). The proposed approach, termed XCSc, has three main processes: (a) a learning process to evolve the rule population, (b) a rule compacting process to remove redundant rules after the learning process, and (c) a rule merging process to deal with the overlapping rules that commonly occur between the clusters. In the first process, we have modified the clustering mechanisms of the current available XCS and developed a new accelerate learning method to improve the quality of the evolved rule population. In the second process, an effective rule compacting algorithm is utilized. The rule merging process is based on our newly proposed agglomerative hierarchical rule merging algorithm, which comprises the following steps: (i) all the generated rules are modeled by a graph, with each rule representing a node; (ii) the vertices in the graph are merged to form a number of sub-graphs (i.e. rule clusters) under some pre-defined criteria, which generates the final rule set to represent the clusters; (iii) each data is re-checked and assigned to a cluster that it belongs to, guided by the final rule set. In our experiments, we compared the proposed XCSc with CHAMELEON, a benchmark algorithm well known for its excellent performance, on a number of challenging data sets. The results show that the proposed approach outperforms CHAMELEON in the successful rate, and also demonstrates good stability.     

A note on the selection of priority rules in software packages for project management

Various software packages for project management include a procedure for resource-constrained scheduling. In several packages, the user can influence this procedure by selecting a priority rule. However, the resource-allocation methods that are implemented in the procedures are proprietary information; therefore, the question of how the priority-rule selection impacts the performance of the procedures arises. We experimentally evaluate the resource-allocation methods of eight recent software packages using the 600 instances of the PSPLIB J120 test set. The results of our analysis indicate that applying the default rule tends to outperform a randomly selected rule, whereas applying two randomly selected rules tends to outperform the default rule. Applying a small set of more than two rules further improves the project durations considerably. However, a large number of rules must be applied to obtain the best possible project durations.     

Reconciling ecogeographical rules: rainfall and temperature predict global colour variation in the largest bird radiation

Ecogeographical rules that associate climate with organismal form and function can reveal patterns of climatic adaptation. Two rules link animal coloration with climate: Gloger's rule (darker coloration where wet and warm), and Bogert's rule (darker coloration where cold). Whereas Gloger's rule was proposed for endotherms, and Bogert's rule for ectotherms, both rules may apply more broadly, despite their seemingly opposing effects. Here, we test this contradiction on a global scale across passerine birds. Consistent with Gloger's rule, birds were darker in wetter areas and, following Bogert's rule, lighter where warm, although birds became lighter again at very low temperatures. Rainfall and temperature had antagonistic or additive effects depending on their pattern of covariation, and this predicted whether birds followed the rules. We integrate both rules into a general framework to explain heterogeneity in climatic effects on coloration, which has implications to understand patterns of diversification, climatic adaptation and climate change impacts.     

A rule is not a rule if it changes from case to case (a reply to Marshall's comment)

This is a reply to “Queller's rule ok: Comment on van Veelen ‘when inclusive fitness is right and when it can be wrong’ ” by James Marshall in the Journal of Theoretical Biology, in this issue.In order to circumvent the disagreement about the Price equation and focus on the issue of the predictive power of inclusive fitness for group selection models, I derive Queller's and Marshall's rule without the Price equation. Both rules however need a translation step in order to be able to link them to the group selection model in van Veelen (2009). Queller's rule applies to games with 2 players and 2 strategies, and is general. Marshall's rule on the other hand applies only to a small subset of 3-player games. His rule is correct, but for other, similarly small subsets we would get other rules. This implies that if we want a rule that applies to all symmetric games with 3 players and 2 strategies, it will have to use a vector of dimension 2 that represents population structure. More in general: for group selection models with groups of size n, a correct and general prediction will need to use a vector of dimension n−1 that represents population structure.     

Stopover strategies in passerine bird migration: a simulation study

Long-distance bird migration consists of a series of stopovers (for refuelling) and flights, with flights taking little time compared to stopovers. Therefore, it has been hypothesized that birds minimize the total time taken for migration through efficient stopover behaviour. Current optimality models for stopover include (1) the fixed expectation rule and (2) the global update rule. These rules maximize the speed of migration by determining the optimal departure fuel load for a given fuel deposition rate. We were interested in simple behavioural rules approaching the stopover behaviour of real birds and how these rules compare to the time minimizing models above with respect to the total time taken for migration. The simple strategies were to stay at a site (1) until a fixed fuel load was reached or (2) for a constant number of days. We simulated migration of small nocturnal passerine birds across an environment of continuously distributed but variable fuel deposition rates, and investigated the influence of different stopover strategies on the duration of migration. Staying for a constant number of days at each stopover site, irrespective of the fuel deposition rate, resulted in only slightly longer than minimum values for migration duration. Additionally, the constant stopover duration, e.g. 10 days, may change by a day or two (per stopover) without having a large effect on total migration duration. There is therefore a possibility that real birds may be close to optimal migration speed without the need for very complex behaviour. When assessing the sensitivity of migration duration to factors other than stopover duration, we found that flight costs, search and settling time, mean fuel deposition rate and the accuracy in the choice of flight direction were the factors with the largest influence. Our results suggest that migrating birds can approximate optimal stopover duration relatively easy with a simple rule, and that other factors, e.g. those above, are more relevant for travel time.     

Regulatory Influences on Environmental Protection: Why Shipping Companies Comply and When They Don't

This article reports the findings of an empirical study on the regulation of ship-source pollution at one United Kingdom-based global ship management company. In examining the corporate response of the case-study company, particular attention is given to the regulatory influences promoting such compliance as expressed in the views of company executives. The findings show that both legal regulatory pressures and customer demands are important factors in encouraging the company to comply with environmental requirements. However, the study also revealed that compliance with environmental requirements ultimately depends on the way in which individual companies adapt to different national regulatory and enforcement regimes.     

Modeling collective animal behavior with a cognitive perspective: a methodological framework

The last decades have seen an increasing interest in modeling collective animal behavior. Some studies try to reproduce as accurately as possible the collective dynamics and patterns observed in several animal groups with biologically plausible, individual behavioral rules. The objective is then essentially to demonstrate that the observed collective features may be the result of self-organizing processes involving quite simple individual behaviors. Other studies concentrate on the objective of establishing or enriching links between collective behavior researches and cognitive or physiological ones, which then requires that each individual rule be carefully validated. Here we discuss the methodological consequences of this additional requirement. Using the example of corpse clustering in ants, we first illustrate that it may be impossible to discriminate among alternative individual rules by considering only observational data collected at the group level. Six individual behavioral models are described: They are clearly distinct in terms of individual behaviors, they all reproduce satisfactorily the collective dynamics and distribution patterns observed in experiments, and we show theoretically that it is strictly impossible to discriminate two of these models even in the limit of an infinite amount of data whatever the accuracy level. A set of methodological steps are then listed and discussed as practical ways to partially overcome this problem. They involve complementary experimental protocols specifically designed to address the behavioral rules successively, conserving group-level data for the overall model validation. In this context, we highlight the importance of maintaining a sharp distinction between model enunciation, with explicit references to validated biological concepts, and formal translation of these concepts in terms of quantitative state variables and fittable functional dependences. Illustrative examples are provided of the benefits expected during the often long and difficult process of refining a behavioral model, designing adapted experimental protocols and inversing model parameters.     

Jordan's and other ecogeographical rules, and the vertebral number in fishes

Aim  To explore variation in the number of vertebrae in fishes in the context of Jordan's rule and other ecogeographical rules.
Location  Global.
Methods  The study is based on literature review.
Results  The number of vertebrae varies very widely across the diversity of fishes. Jordan's rule states that vertebral number increases with latitude, and this is widely attributed to ambient temperatures during ontogeny of individual fishes. However, the number of vertebrae may depend on both the ontogenetic environment and inheritance. Diverse other aspects of fish development and ecology are suggested as influencing vertebral number, including fish size, phyletic position, body shape and swimming mode.
Main conclusions  The number of different factors that influence the number of vertebrae in fishes makes for highly complex patterns of variation, and means that unravelling causes is difficult. The question needs to be addressed at the population/species/species group scale; moreover, the lack of discrimination between environmental and inherited causes of variation adds to the complexity.