Do wildlife laws work? Species protection and the application of a prey choice model to poaching decisions

Legislation for the protection of species is a global conservation tool. However, in many developing countries lack of resources means that effectiveness relies on voluntary compliance, leading to contradictory assumptions. On one hand, laws introduced without effective enforcement mechanisms carry an implicit assumption that voluntary compliance will occur. On the other hand, it is often openly assumed that, without enforcement, there will in fact be no compliance. Which assumption holds has rarely been rigorously tested. Here we show that laws for the protection of some species of large mammal have no effect on the prey choice patterns of primarily commercial hunters in the Democratic Republic of Congo, confirming the second assumption. We established this result by using an optimal diet model to predict the pattern of prey choice in the absence of regulation. Prey choice patterns predicted by the model were accurate across a range of conditions defined by time, space and type of hunting weapon. Given that hunters will not comply voluntarily, the protection of vulnerable species can only take place through effective enforcement, for example by wildlife authorities restricting access to protected areas, or by traditional authorities restricting the sale of protected species in local markets.     

Impacts of taxonomic inertia for the conservation of African ungulate diversity: an overview

We review the state of African ungulate taxonomy over the last 120 years, with an emphasis on the introduction of the polytypic species concept and the discipline's general neglect since the middle of the 20th century. We single out negative consequences of ‘orthodox’ taxonomy, highlighting numerous cases of neglect of threatened lineages, unsound translocations that led to lineage introgression, and cases of maladaptation to local conditions including parasitic infections. Additionally, several captive breeding programmes have been hampered by chromosome rearrangements caused by involuntary lineage mixing. We advocate that specimen‐based taxonomy should regain its keystone role in mammal research and conservation biology, with its scientific values augmented with genomic evidence. While integration with molecular biology, ecology and behaviour is needed for a full understanding of ungulate alpha diversity, we stress that morphological diversity has been neglected despite its tremendous practical importance for some groups of ‘utilizers’ such as trophy hunters, wildlife tourists and conservationists. We conclude that there is no evidence that purported ‘taxonomic inflation’ has adverse effects on ungulate conservation: rather, it is taxonomic inertia that has such adverse effects. We stress that sound science, founded on robust taxonomy, should underpin effective sustainable management (hunting, ranching, captive breeding and reintroduction programmes) of this unique African natural resource.     

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.     

Optimality models of phage life history and parallels in disease evolution

Optimality models constitute one of the simplest approaches to understanding phenotypic evolution. Yet they have shortcomings that are not easily evaluated in most organisms. Most importantly, the genetic basis of phenotype evolution is almost never understood, and phenotypic selection experiments are rarely possible. Both limitations can be overcome with bacteriophages. However, phages have such elementary life histories that few phenotypes seem appropriate for optimality approaches. Here we develop optimality models of two phage life history traits, lysis time and host range. The lysis time models show that the optimum is less sensitive to differences in host density than suggested by earlier analytical work. Host range evolution is approached from the perspective of whether the virus should avoid particular hosts, and the results match optimal foraging theory: there is an optimal "diet" in which host types are either strictly included or excluded, depending on their infection qualities. Experimental tests of both models are feasible, and phages provide concrete illustrations of many ways that optimality models can guide understanding and explanation. Phage genetic systems already support the perspective that lysis time and host range can evolve readily and evolve without greatly affecting other traits, one of the main tenets of optimality theory. The models can be extended to more general properties of infection, such as the evolution of virulence and tissue tropism.     

Mixing Carrots and Sticks to Conserve Forests in the Brazilian Amazon: A Spatial Probabilistic Modeling Approach

Annual forest loss in the Brazilian Amazon had in 2012 declined to less than 5,000 sqkm, from over 27,000 in 2004. Mounting empirical evidence suggests that changes in Brazilian law enforcement strategy and the related governance system may account for a large share of the overall success in curbing deforestation rates. At the same time, Brazil is experimenting with alternative approaches to compensate farmers for conservation actions through economic incentives, such as payments for environmental services, at various administrative levels. We develop a spatially explicit simulation model for deforestation decisions in response to policy incentives and disincentives. The model builds on elements of optimal enforcement theory and introduces the notion of imperfect payment contract enforcement in the context of avoided deforestation. We implement the simulations using official deforestation statistics and data collected from field-based forest law enforcement operations in the Amazon region. We show that a large-scale integration of payments with the existing regulatory enforcement strategy involves a tradeoff between the cost-effectiveness of forest conservation and landholder incomes. Introducing payments as a complementary policy measure increases policy implementation cost, reduces income losses for those hit hardest by law enforcement, and can provide additional income to some land users. The magnitude of the tradeoff varies in space, depending on deforestation patterns, conservation opportunity and enforcement costs. Enforcement effectiveness becomes a key determinant of efficiency in the overall policy mix.     

On the compositing of samples for qualitative microbiological testing

The introduction of legislative microbiological criteria for foods [Official J L338 (2005) 1] has increased the exposure of enforcement and industrial laboratories to the need to test multiple food samples for organisms such as salmonellae. A consequence has been an increase in the number of organizations, both official and commercial, considering whether it is permissible to composite replicate sample units for the purposes of assessing compliance with the criteria. This note summarizes the statistical and practical aspects of compositing sample units for compliance testing. Provided that the method of choice is 'fit for purpose', then there is no statistical difference between testing, say, 30 x 25 g sample units or 3 x 250 g sample units. However, compositing of sample units should be done only when the method has been demonstrated unequivocally to be sufficiently sensitive to detect potentially lower numbers of target organism(s) in the quantity of composited sample under the conditions of test. Different approaches to compositing of samples are considered.     

生物多样性保护廊道构建方法研究进展

生物多样性保护廊道对遏制生态系统退化及生物多样性丧失,改善生态系统服务功能,消除生境破碎化对生物多样性的影响,恢复珍稀濒危物种的种群数量,维护自然生态系统平衡稳定具有极为重要的作用。在近20年(1997—2017)国内外生物多样性保护廊道的相关研究分析的基础上,对廊道的概念、构建理论及方法应用进行了系统总结与探讨,分析了廊道构建理论的发展过程及适用性,分类总结了现有的廊道构建方法和17种廊道构建模型工具。研究分析表明,廊道作为一种新的生物多样性保护模式,已成为目前国际生态领域研究的热点之一,随着对物种景观运动过程认识的加深,廊道构建理论逐渐趋于成熟,与之匹配的廊道构建方法及模型工具进展迅速。借助遥感与地理信息技术,大范围,高精度的获取廊道模拟数据,并集成综合模型实现目标物种廊道的构建、保护和管理是今后生物多样性保护廊道构建研究的发展方向。最后,对当前该领域的研究现状和不足展开讨论并展望了未来发展,为我国生物多样性保护廊道的应用与实践及国家生态廊道体系的建设完善提供借鉴与参考。     

Supporting Fisheries Management by Means of Complex Models: Can We Point out Isles of Robustness in a Sea of Uncertainty?

Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters.     

Decisions of cattle herdsmen in Burkina Faso and optimal foraging models

Models of optimal foraging theory are used to evaluate the decisions of a sedentary herdsman and his family in Burkina Faso concerning the movement of his cattle from pasture to pasture. Generally, such models describe exploitation at the patch level, but are inadequate at higher levels. The herdsmen in the study area are generally sedentary, and their strategy of exploitation appears to be characterized by planning at least in terms of a whole day and minimizing daily travel time among fields. In conjuction with this conclusion a modified optimization model is proposed. We conclude that optimal foraging models are useful in interpreting and understanding the rules governing the movements of traditional West African herdsmen when so modified, but that more data are needed to develop and test these models further.     

Post-Crackdown Effectiveness of Field-Based Forest Law Enforcement in the Brazilian Amazon

Regulatory enforcement of forest conservation laws is often dismissed as an ineffective approach to reducing tropical forest loss. Yet, effective enforcement is often a precondition for alternative conservation measures, such as payments for environmental services, to achieve desired outcomes. Fair and efficient policies to reducing emissions from deforestation and forest degradation (REDD) will thus crucially depend on understanding the determinants and requirements of enforcement effectiveness. Among potential REDD candidate countries, Brazil is considered to possess the most advanced deforestation monitoring and enforcement infrastructure. This study explores a unique dataset of over 15 thousand point coordinates of enforcement missions in the Brazilian Amazon during 2009 and 2010, after major reductions of deforestation in the region. We study whether local deforestation patterns have been affected by field-based enforcement and to what extent these effects vary across administrative boundaries. Spatial matching and regression techniques are applied at different spatial resolutions. We find that field-based enforcement operations have not been universally effective in deterring deforestation during our observation period. Inspections have been most effective in reducing large-scale deforestation in the states of Mato Grosso and Pará, where average conservation effects were 4.0 and 9.9 hectares per inspection, respectively. Despite regional and actor-specific heterogeneity in inspection effectiveness, field-based law enforcement is highly cost-effective on average and might be enhanced by closer collaboration between national and state-level authorities.     

Urban greenspace composition and landscape context influence natural enemy community composition and function

Conservation research has historically been aimed at preserving high value natural habitats, but urbanization and its associated impacts have prompted broader mandates that include the preservation and promotion of biodiversity in cities. Current efforts within urban landscapes aim to support biodiversity and diverse ecosystem services such as storm water management, sustainable food production, and toxin remediation. Arthropod natural enemies provide biocontrol services important for the ecosystem management of urban greenspaces. Establishing habitat for these and other beneficial arthropods is a growing area of urban conservation. Habitat design, resource inputs, management, and abiotic conditions shape the value of greenspace habitats for arthropods. In general, larger patches with diverse plant communities support a greater abundance and diversity of natural enemies and biocontrol services, yet opposing patterns or no effects have also been documented. The surrounding landscape is likely a contributor to this variation in natural enemy response to patch-scale habitat design and management. Looking across rural–urban landscape gradients, natural enemy communities shift toward dominance by habitat generalists and disturbance tolerant species in urban areas compared to rural or natural communities. These changes have been linked to variation in habitat fragmentation, plant productivity and management intensity. In landscape-scale studies focusing solely within cities, variables such as impervious surface area and greenspace connectivity affect the community assembly of natural enemies within a patch. Given these findings, a greater mechanistic understanding of how both the composition and spatial context of urban greenspaces influence natural enemy biodiversity–biocontrol relationships is needed to advance conservation planning and implementation.     

What is optimal about motor control?

This article poses a controversial question: is optimal control theory useful for understanding motor behavior or is it a misdirection? This question is becoming acute as people start to conflate internal models in motor control and perception (Poeppel et?al., 2008; Hickok et?al., 2011). However, the forward models in motor control are not the generative models used in perceptual inference. This Perspective tries to highlight the differences between internal models in motor control and perception and asks whether optimal control is the right way to think about things. The issues considered here may have broader implications for optimal decision theory and Bayesian approaches to learning and behavior in general.     

Modelling whole-plant allocation in relation to carbon and nitrogen supply: Coordination versus optimization: Opinion

One of the few integrating theories related to allocation is the hypothesis of optimization. While optimization theory has great heuristic appeal and has been used to describe a range of physiological and ecological phenomena, it has major limitations. Optimization is necessarily based on a definite time integral and an optimal control strategy must be specific to the same patterns exhibited by the driving variables over this same period of time. Optimization tends to employ the use of oversimplifications in order to facilitate analytical solutions to the optimal control strategy, i.e. the mechanism governing the response of plants, which is the critical issue of interest. It is difficult to define objective criteria that can account for the natural variability in plants and testing the quantitative predictions of optimality models is also difficult. Thus, we suggest that optimization theory is too limited for practical use in modelling whole plant allocation. In this paper, we introduce the use of coordination theory as a practical alternative. We develop a simple plant growth allocation model using both coordination and optimization approaches and show that coordination theory is easily applied, produces results that are quantitatively similar to optimization, and overcomes the inherent limitations of optimization theory.     

Sane in the membrane: designing systems to modulate membrane proteins

Proteins and lipids make sense in rational approaches to the design of systems for the study of membrane proteins. Lipids surround integral membrane proteins in their natural environment. Although lipids have always formed part of investigations into membrane proteins, it has generally been the proteins themselves that have taken the limelight. As knowledge of membrane proteins has increased, so has that of their interactions with lipids. This increased understanding of the interplay of proteins and lipids, together with existing knowledge of lipid properties, is enabling new approaches to be introduced for membrane protein study. The lipids can be used to control protein behaviour and as novel probes of protein motion.     

Rational design of 13C-labeling experiments for metabolic flux analysis in mammalian cells

ABSTRACT: BACKGROUND: 13C-Metabolic flux analysis (13C-MFA) is a standard technique to probe cellular metabolism and elucidate in vivo metabolic fluxes. 13C-Tracer selection is an important step in conducting 13C-MFA, however, current methods are restricted to trial-and-error approaches, which commonly focus on an arbitrary subset of the tracer design space. To systematically probe the complete tracer design space, especially for complex systems such as mammalian cells, there is a pressing need for new rational approaches to identify optimal tracers. RESULTS: Recently, we introduced a new framework for optimal 13C-tracer design based on elementary metabolite units (EMU) decomposition, in which a measured metabolite is decomposed into a linear combination of so-called EMU basis vectors. In this contribution, we applied the EMU method to a realistic network model of mammalian metabolism with lactate as the measured metabolite. The method was used to select optimal tracers for the two free fluxes in the system, the oxidative pentose phosphate pathway (oxPPP) flux and anaplerosis by pyruvate carboxylase (PC). Our approach was based on sensitivity analysis of EMU basis vector coefficients with respect to free fluxes. Through efficient grouping of coefficient sensitivities, simple tracer selection rules were derived for high-resolution quantification of the fluxes in the mammalian network model. The approach resulted in a significant reduction of the number of possible tracers and the feasible tracers were evaluated using numerical simulations. Two optimal, novel tracers were identified that have not been previously considered for 13C-MFA of mammalian cells, specifically [2,3,4,5,6-13C]glucose for elucidating oxPPP flux and [3,4-13C]glucose for elucidating PC flux. We demonstrate that 13C-glutamine tracers perform poorly in this system in comparison to the optimal glucose tracers. CONCLUSIONS: In this work, we have demonstrated that optimal tracer design does not need to be a pure simulation-based trial-and-error process; rather, rational insights into tracer design can be gained through the application of the EMU basis vector methodology. Using this approach, rational labeling rules can be established a priori to guide the selection of optimal 13C-tracers for high-resolution flux elucidation in complex metabolic network models.     

Evolutionary accounts of human behavioural diversity

Human beings persist in an extraordinary range of ecological settings, in the process exhibiting enormous behavioural diversity, both within and between populations. People vary in their social, mating and parental behaviour and have diverse and elaborate beliefs, traditions, norms and institutions. The aim of this theme issue is to ask whether, and how, evolutionary theory can help us to understand this diversity. In this introductory article, we provide a background to the debate surrounding how best to understand behavioural diversity using evolutionary models of human behaviour. In particular, we examine how diversity has been viewed by the main subdisciplines within the human evolutionary behavioural sciences, focusing in particular on the human behavioural ecology, evolutionary psychology and cultural evolution approaches. In addition to differences in focus and methodology, these subdisciplines have traditionally varied in the emphasis placed on human universals, ecological factors and socially learned behaviour, and on how they have addressed the issue of genetic variation. We reaffirm that evolutionary theory provides an essential framework for understanding behavioural diversity within and between human populations, but argue that greater integration between the subfields is critical to developing a satisfactory understanding of diversity.     

Connecting behavioural biologists and psychologists: Clarifying distinctions and suggestions for further work

This article is a reply to the commentaries on our target article, which relates our group's work on simple heuristics to biological research on rules of thumb. Several commentators contrasted both these approaches with behaviour analysis, in which the patterns of behaviour investigated in the laboratory are claimed to be near-universal attributes, rather than specific to particular appropriate environments. We question this universality. For instance, learning phenomena such Pavlovian or operant conditioning have mostly been studied only in a few generalist species that learn easily; in many natural situations the environment hinders learning as an adaptive strategy. Other supposedly general phenomena such as impulsiveness and matching are outcome models, which several different models of simple cognitive processes might explain. We clarify some confusions about optimisation, optima and optimality modelling. Lastly, we say a little more about how heuristics might be selected, learnt and tuned to suit the current environment.     

Dynamic social behaviour in a bacterium: Pseudomonas aeruginosa partially compensates for siderophore loss to cheats

Cooperation underlies diverse phenomena including the origins of multicellular life, human behaviour in economic markets and the mechanisms by which pathogenic bacteria cause disease. Experiments with microorganisms have advanced our understanding of how, when and why cooperation evolves, but the extent to which microbial cooperation can recapitulate aspects of animal behaviour is debated. For instance, understanding the evolution of behavioural response rules (how should one individual respond to another's decision to cooperate or defect?) is a key part of social evolution theory, but the possible existence of such rules in social microbes has not been explored. In one specific context (biparental care in animals), cooperation is maintained if individuals respond to a partner's defection by increasing their own investment into cooperation, but not so much that this fully compensates for the defector's lack of investment. This is termed ‘partial compensation’. Here, I show that partial compensation for the presence of noncooperating ‘cheats’ is also observed in a microbial social behaviour: the cooperative production of iron‐scavenging siderophores by the bacterium Pseudomonas aeruginosa. A period of evolution in the presence of cheats maintains this response, whereas evolution in the absence of cheats leads to a loss of compensatory behaviour. These results demonstrate (i) the remarkable flexibility of bacterial social behaviour, (ii) the potential generality of partial compensation as a social response rule and (iii) the need for mathematical models to explore the evolution of response rules in multi‐player social interactions.     

Simple rules for complex landscapes: the case of hilltopping movements and topography

Empirical data on the signals and processes that direct animal movement during dispersal in heterogeneous landscapes are scarce. Our understanding could benefit from utilising simulation approaches and searching for simple rules across species and landscapes. This study sought to identify general movement behaviours that optimise butterfly movements during hilltopping. This widespread dispersal‐like phenomenon in butterflies, where males and virgin females ascend to mountain summits for the purpose of mating, benefits from the uniqueness of knowing the purpose (mating) and the orientation signal (topography). We used an individual‐based simulation model to search for movement rules that can optimise mating success, mating time, and the success of mated females in subsequently finding habitat patches across differently structured landscapes. We found that a strong response to topography was optimal for males and virgin females to reach summits, but slight deviation from ‘perfect’, namely a certain level of randomness in response to topography, was inherently essential to avoid the risk of being trapped on local summits. The optimal response of mated females deviated only slightly from a random movement, indicating a potential weak response to topography which could be easily overlooked by field studies. Notably, the parameter values identified by the model as optimal corresponded with the observed behaviour of butterflies in the field. Finally, the optimal movement behaviours were affected by the lifespan of butterflies and the spatial distribution of host plant patches, but less so by landscape structure. We therefore suggest that modelling approaches that build on simple biological rules can facilitate the development and parameterisation of models for understanding and potentially predicting dispersal and connectivity in complex landscapes, also in circumstances where observed patterns seem complex and empirical data are scarce.