Preliminary prioritization based on partial order theory and R software for compositional complexes in landscape ecology,with applications to restoration,remediation, and enhancement

The present purpose is to provide convenient computational capability and visualizations for preliminary partial or progressive prioritization based largely on concepts of partial order theory and implemented in R software as illustrated in a context of conservation and sustainable stewardship across landscapes with ecosystem services as a complex multidimensional domain that must be placed in public and private perspective in pursuit of multi-resource management. Practical perspective is promoted by graphic visualization with local partial order modeling (LPOM) methods for screening of settings and scenarios involving interactions of ecosystem elements as evidenced by environmental indicators. ORDIT ordering and precedence plots arise from ascribed advantage as an outcome of a rating regime. Representative ranks constitute criteria drawn from the rank distribution for the case in question. Distal data are determined with regard to remediation and retention. Median mismatches reflect interplay of indicators appearing as isolated instances in plotting patterns. A suggested strategy to circumvent computational constraints is partitioning the pool of cases into collectives by clustering, pursuing classes of partitions, and then prioritizing in particular partitions. When prime prospects have been obtained, detailed determinations can be done with partial ordering procedures involving Hasse diagrams and similarly complex constructs that are difficult to apply with many cases and/or indicator criteria.     

Incorporating geographical and evolutionary rarity into conservation prioritization

Key goals of conservation are to protect both species and the functional and genetic diversity they represent. A strictly species-based approach may underrepresent rare, threatened, or genetically distinct species and overrepresent widespread species. Although reserves are created for a number of reasons, including economic, cultural, and ecological reasons, their efficacy has been measured primarily in terms of how well species richness is protected, and it is useful to compare how well they protect other measures of diversity. We used Proteaceae species-occurrence data in the Cape Floristic Region of South Africa to illustrate differences in the spatial distribution of species and evolutionary diversity estimated from a new maximum-likelihood molecular phylogeny. We calculated species richness, phylogenetic diversity (i.e., summed phylogenetic branch lengths in a site), and a site-aggregated measure of biogeographically weighted evolutionary distinctiveness (i.e., an abundance weighted measure that captures the unique proportion of the phylogenetic tree a species represents) for sites throughout the Cape Floristic Region. Species richness and phylogenetic diversity values were highly correlated for sites in the region, but species richness was concentrated at a few sites that underrepresented the much more spatially extensive distribution of phylogenetic diversity. Biogeographically weighted evolutionary diversity produced a scheme of prioritization distinct from the other 2 metrics and highlighted southern sites as conservation priorities. In these sites, the high values of biogeographically weighted evolutionary distinctiveness were the result of a nonrandom relation between evolutionary distinctiveness and geographical rarity, where rare species also tended to have high levels of evolutionary distinctiveness. Such distinct and rare species are of particular concern, but are not captured by conservation schemes that focus on species richness or phylogenetic diversity alone.     

Application of partial order to stream channel assessment at bridge infrastructure for mitigation management

Many environmental systems and infrastructure systems are monitored using a set of indicator values that assess several aspects of site condition. The values of different indicators often convey different comparative messages for the study sites. The comparability between sites is analyzed within the theory of partially-ordered sets and visualized with Hasse diagrams. This paper demonstrates that properties of partially-ordered sets and the conversion of indicator scores into a rank matrix provide a manager or decision-maker with valuable information that would be lost if the monitored indicator data were aggregated only into a single index. Stream stability assessment data from 49 bridge crossing sites in the United States are used to demonstrate these techniques in prioritization and identification of restoration and maintenance needs of stream channels at bridge crossings.     

A genoscape-network model for conservation prioritization in a migratory bird

Migratory animals are declining worldwide and coordinated conservation efforts are needed to reverse current trends. We devised a novel genoscape-network model that combines genetic analyses with species distribution modeling and demographic data to overcome challenges with conceptualizing alternative risk factors in migratory species across their full annual cycle. We applied our method to the long distance, Neotropical migratory bird, Wilson's Warbler (Cardellina pusilla). Despite a lack of data from some wintering locations, we demonstrated how the results can be used to help prioritize conservation of breeding and wintering areas. For example, we showed that when genetic, demographic, and network modeling results were considered together it became clear that conservation recommendations will differ depending on whether the goal is to preserve unique genetic lineages or the largest number of birds per unit area. More specifically, if preservation of genetic lineages is the goal, then limited resources should be focused on preserving habitat in the California Sierra, Basin Rockies, or Coastal California, where the 3 most vulnerable genetic lineages breed, or in western Mexico, where 2 of the 3 most vulnerable lineages overwinter. Alternatively, if preservation of the largest number of individuals per unit area is the goal, then limited conservation dollars should be placed in the Pacific Northwest or Central America, where densities are estimated to be the highest. Overall, our results demonstrated the utility of adopting a genetically based network model for integrating multiple types of data across vast geographic scales and better inform conservation decision-making for migratory animals.     

Mainstreaming the social sciences in conservation

Despite broad recognition of the value of social sciences and increasingly vocal calls for better engagement with the human element of conservation, the conservation social sciences remain misunderstood and underutilized in practice. The conservation social sciences can provide unique and important contributions to society's understanding of the relationships between humans and nature and to improving conservation practice and outcomes. There are 4 barriers—ideological, institutional, knowledge, and capacity—to meaningful integration of the social sciences into conservation. We provide practical guidance on overcoming these barriers to mainstream the social sciences in conservation science, practice, and policy. Broadly, we recommend fostering knowledge on the scope and contributions of the social sciences to conservation, including social scientists from the inception of interdisciplinary research projects, incorporating social science research and insights during all stages of conservation planning and implementation, building social science capacity at all scales in conservation organizations and agencies, and promoting engagement with the social sciences in and through global conservation policy‐influencing organizations. Conservation social scientists, too, need to be willing to engage with natural science knowledge and to communicate insights and recommendations clearly. We urge the conservation community to move beyond superficial engagement with the conservation social sciences. A more inclusive and integrative conservation science—one that includes the natural and social sciences—will enable more ecologically effective and socially just conservation. Better collaboration among social scientists, natural scientists, practitioners, and policy makers will facilitate a renewed and more robust conservation. Mainstreaming the conservation social sciences will facilitate the uptake of the full range of insights and contributions from these fields into conservation policy and practice.     

Infant mortality and social environment in Georgia: an application of hotspot detection and prioritization

Recent years have witnessed the growth of new information technologies and their applications to various disciplines. The goal of this paper is to demonstrate how the two innovative methods, upper level set scan (ULS) hotspot detection and the multicriteria prioritization scheme, facilitate population health and break new ground in public health surveillance. It is believed that the social environment (i.e. social conditions and social capital) is one of the determinants of human health. Using infant health data and 10 additional indicators of social environment in the 159 counties of Georgia, ULS identified 52 counties that are in double jeopardy (high infant mortality and a high rate of low infant birth weight). The multicriteria ranking scheme suggested that there was no conspicuous spatial cluster of ranking orders, which improved the traditional decision making by visual geographic cluster. Both hotspot detection and ranking methods provided an empirical basis for re-allocating limited resources and several policy implications could be drawn from these analytic results.     

Multiple indicators, partially ordered sets, and linear extensions: Multi-criterion ranking and prioritization

This paper is concerned with the question of ranking a finite collection of objects when a suite of indicator values is available for each member of the collection. The objects can be represented as a cloud of points in indicator space, but the different indicators (coordinate axes) typically convey different comparative messages and there is no unique way to rank the objects while taking all indicators into account. A conventional solution is to assign a composite numerical score to each object by combining the indicator information in some fashion. Consciously or otherwise, every such composite involves judgments (often arbitrary or controversial) about tradeoffs or substitutability among indicators. Rather than trying to combine indicators, we take the view that the relative positions in indicator space determine only a partial ordering and that a given pair of objects may not be inherently comparable. Working with Hasse diagrams of the partial order, we study the collection of all rankings that are compatible with the partial order (linear extensions). In this way, an interval of possible ranks is assigned to each object. The intervals can be very wide, however. Noting that ranks near the ends of each interval are usually infrequent under linear extensions, a probability distribution is obtained over the interval of possible ranks. This distribution, called the rank-frequency distribution, turns out to be unimodal (in fact, log-concave) and represents the degree of ambiguity involved in attempting to assign a rank to the corresponding object. Stochastic ordering of probability distributions imposes a partial order on the collection of rank-frequency distributions. This collection of distributions is in one-to-one correspondence with the original collection of objects and the induced ordering on these objects is called the cumulative rank-frequency (CRF) ordering; it extends the original partial order. Although the CRF ordering need not be linear, it can be iterated to yield a fixed point of the CRF operator. We hypothesize that the fixed points of the CRF operator are exactly the linear orderings. The CRF operator treats each linear extension as an equal voter in determining the CRF ranking. It is possible to generalize to a weighted CRF operator by giving linear extensions differential weights either on mathematical grounds (e.g., number of jumps) or empirical grounds (e.g., indicator concordance). Explicit enumeration of all possible linear extensions is computationally impractical unless the number of objects is quite small. In such cases, the rank-frequencies can be estimated using discrete Markov chain Monte Carlo (MCMC) methods.     

Effects of connectivity and spatial resolution of analyses on conservation prioritization across large extents

The outcome of analyses that prioritize locations for conservation on the basis of distributions of species, land cover, or other elements is influenced by the spatial resolution of data used in the analyses. We explored the influence of data resolution on prioritization of Finnish forests with Zonation, a software program that ranks the priority of cells in a landscape for conservation. We used data on the distribution of different forest types that were aggregated to nine different resolutions ranging from 0.1 × 0.1 km to 25.6 × 25.6 km. We analyzed data at each resolution with two variants of Zonation that had different criteria for prioritization, with and without accounting for connectivity and with and without adjustment for the effect on the analysis of edges between areas at the project boundary and adjacent areas for which data do not exist. Spatial overlap of the 10% of cells ranked most highly when data were analyzed at different resolutions varied approximately from 15% to 60% and was greatest among analyses with similar resolutions. Inclusion of connectivity or edge adjustment changed the location of areas that were prioritized for conservation. Even though different locations received high priority for conservation in analyses with and without accounting for connectivity, accounting for connectivity did not reduce the representation of different forest types. Inclusion of connectivity influenced most the outcome of fine-resolution analyses because the connectivity extents that we based on dispersal distances of typical forest species were small. When we kept the area set aside for conservation constant, representation of the forest types increased as resolution increased. We do not think it is necessary to avoid use of high-resolution data in spatial conservation prioritization. Our results show that large extent, fine-resolution analyses are computationally feasible, and we suggest they can give more flexibility to implementation of well-connected reserve networks.     

Importance of deepening integration of crime and conservation sciences

Conservation crime is a globally distributed societal problem. Conservation crime science, an emerging interdisciplinary field, has the potential to help address this problem. However, its utility depends on serious reflection on the transposition of crime science approaches to conservation contexts, which may differ in meaningful ways from traditional crime contexts. We considered the breadth of crime science approaches being used in conservation as well as the depth of crime science integration in conservation. We used the case of sea cucumber (Holothuria floridana, Isostichopus badionotus) trafficking in Mexico as an example of why the interdisciplinarity of crime and conservation sciences should be deepened and how integration can help ideate new solutions. We first conducted a review of literature to capture the range of interdisciplinarity applications. We identified 6 crime science approaches being applied to the conservation contexts of illegal, unreported, and unregulated fishing; wildlife and plant crime; and illegal logging. We then compared this knowledge base to the case of illegal sea cucumber fishing in Mexico. We identified 5 challenges in the application of these approaches to conservation contexts: the relative diffusion of harms and victims in conservation crimes; scalar mismatches in crime, authority, and the conservation issue itself; interactions between legal and illegal networks; communities and their authority to define and control crime; and the role of natural science in the rule of law. Considering these 5 factors may enhance the depth of interdisciplinarity between crime and conservation sciences. Nurturing interdisciplinary crime and conservation science will expand innovation and help accelerate successful risk management programs and other policy agendas.     

Social network theory in the behavioural sciences: potential applications

Social network theory has made major contributions to our understanding of human social organisation but has found relatively little application in the field of animal behaviour. In this review, we identify several broad research areas where the networks approach could greatly enhance our understanding of social patterns and processes in animals. The network theory provides a quantitative framework that can be used to characterise social structure both at the level of the individual and the population. These novel quantitative variables may provide a new tool in addressing key questions in behavioural ecology particularly in relation to the evolution of social organisation and the impact of social structure on evolutionary processes. For example, network measures could be used to compare social networks of different species or populations making full use of the comparative approach. However, the networks approach can in principle go beyond identifying structural patterns and also can help with the understanding of processes within animal populations such as disease transmission and information transfer. Finally, understanding the pattern of interactions in the network (i.e. who is connected to whom) can also shed some light on the evolution of behavioural strategies.     

CUSUM environmental monitoring in time and space

We consider the situation where there are n sampling sites in an area, with an environmental variable measured at some or all of the sites at m sample times. We assume that there is interest in knowing whether the environmental variable displays systematic changes over time at the sites. A cumulative sum type of analysis with associated randomization tests has been proposed before for this situation, when there is negligible correlation between the observations in different times at one site, and no correlation between the results at different sites. A modification that allows for serial correlation at the individual sites but with no correlation between sites has also been proposed before. In the present paper we discuss how the method can be modified further to allow for spatial correlation between the sites, by applying it only to a reduced set of sites that are far enough apart to give effectively independent results. Simulation results indicate that this strategy is effective providing that the level of spatial correlation is not too high.     

Double-dipping in environmental markets

There is an increasing tendency to use markets to induce the provision of environmental services. As such markets increase in scope, potential market participants might sell multiple environmental services. The question we consider here is whether participants in such markets should be allowed to sell credits in more than one market simultaneously. Some have argued in favor of such “double-dipping”, because it would make the provision of environmental services more profitable. In practice however, most programs do not allow double-dipping. We show that if the optimal level of pollution abatement is sought, then double-dipping maximizes societal net benefits. However, if pollution policies are set in a piecemeal fashion, then the caps for each market are unlikely to be optimal and, in this second-best setting, a policy prohibiting double-dipping can lead to greater social net benefits. We explore conditions under which a single-market policy is preferred, or equivalently, where piecemeal policies are likely to yield particularly inefficient outcomes.     

结构性环境问题——我国环境评价遭遇的"结构"困境

近年来 "结构性环境问题"在我国频发,尤其是结合项目环境影响评价(EIA)制度而突出表现为一种困境--"符合环保先进标准的高环境风险项目".当前学界对于环境问题的认识逐渐从物理层面转向社会层面,然而,对环境评价的研究还停留在基于环境要素功能特征的方法改进和制度完善,当前的结构性环境问题反映出的环境资源在不同利益群体间的不合理性分配还没有被充分认识到.由此,文章借助析出的环境问题两个主要影响变量:环境资源的稀缺性和配置结构的合理性,对"结构性环境问题"的产生过程和特征进行了分析.进而,文章借助系统论的功能-结构理论,结合厦门PX项目事件,认为现有环境评价主要定位于"功能性"特征,还不能针对性地把握结构性环境问题,由此面临结构性困境.为了避免这种困境,有必要进一步展开针对结构性环境问题的环境影响评价方法和制度研究,而且环境影响评价的"结构性"转化也具备着基础理论的支持.