Dynamic species co‐occurrence networks require dynamic biodiversity surrogates

In conservation it is inevitable that surrogates be selected to represent the occurrence of hard‐to‐find species and find priority locations for management. However, species co‐occurrence can vary over time. Here we demonstrate how temporal dynamics in species co‐occurrence influence the ability of managers to choose the best surrogate species. We develop an efficient optimisation formulation that selects the optimal set of complementary surrogate species from any co‐occurrence network. We apply it to two Australian datasets on successional bird responses to disturbances of revegetation and fire. We discover that a surprisingly small number of species are required to represent the majority of species co‐occurrences at any one time. Because co‐occurrence patterns are temporally dynamic, the optimal set of surrogates, and the number of surrogates required to achieve a desired surrogacy power, depend on sampling effort and the successional state of a system. Overlap in optimal sets of surrogates for representing 70% of co‐occurring species ranges from zero to 57% depending on when the surrogacy decision is made. Surrogate sets representing early successional communities over‐estimate the power of surrogacy decisions at later times. Our results show that in dynamic systems, optimal surrogates might be selected in different ways: 1) use short‐term monitoring to choose a larger number of static less‐informative surrogates; 2) use long‐term monitoring to choose a smaller number of static high‐power surrogates that may poorly represent early successional co‐occurrence; 3) develop adaptive surrogate selection frameworks with high short‐term and long‐term surrogacy power that update surrogate sets and capture temporal dynamics in species co‐occurrence. Our results suggest vigilance is needed when selecting surrogates for other co‐occurring species in dynamic landscapes, as selected surrogates from one time may have reduced effectiveness at a different time. Ultimately, decisions that fail to acknowledge dynamic species co‐occurrence will lead to uninformative or redundant surrogates.     

Best Practicable Aggregation of Species: a step forward for species surrogacy in environmental assessment and monitoring

The available taxonomic expertise and knowledge of species is still inadequate to cope with the urgent need for cost‐effective methods to quantifying community response to natural and anthropogenic drivers of change. So far, the mainstream approach to overcome these impediments has focused on using higher taxa as surrogates for species. However, the use of such taxonomic surrogates often limits inferences about the causality of community patterns, which in turn is essential for effective environmental management strategies. Here, we propose an alternative approach to species surrogacy, the “Best Practicable Aggregation of Species” (BestAgg), in which surrogates exulate from fixed taxonomic schemes. The approach uses null models from random aggregations of species to minimizing the number of surrogates without causing significant losses of information on community patterns. Surrogate types are then selected in order to maximize ecological information. We applied the approach to real case studies on natural and human‐driven gradients from marine benthic communities. Outcomes from BestAgg were also compared with those obtained using classic taxonomic surrogates. Results showed that BestAgg surrogates are effective in detecting community changes. In contrast to classic taxonomic surrogates, BestAgg surrogates allow retaining significantly higher information on species‐level community patterns than what is expected to occur by chance and a potential time saving during sample processing up to 25% higher. Our findings showed that BestAgg surrogates from a pilot study could be used successfully in similar environmental investigations in the same area, or for subsequent long‐term monitoring programs. BestAgg is virtually applicable to any environmental context, allowing exploiting multiple surrogacy schemes beyond stagnant perspectives strictly relying on taxonomic relatedness among species. This prerogative is crucial to extend the concept of species surrogacy to ecological traits of species, thus leading to ecologically meaningful surrogates that, while cost effective in reflecting community patterns, may also contribute to unveil underlying processes. A specific R code for BestAgg is provided.     

Effectiveness of biological surrogates for predicting patterns of marine biodiversity: a global meta-analysis

The use of biological surrogates as proxies for biodiversity patterns is gaining popularity, particularly in marine systems where field surveys can be expensive and species richness high. Yet, uncertainty regarding their applicability remains because of inconsistency of definitions, a lack of standard methods for estimating effectiveness, and variable spatial scales considered. We present a Bayesian meta-analysis of the effectiveness of biological surrogates in marine ecosystems. Surrogate effectiveness was defined both as the proportion of surrogacy tests where predictions based on surrogates were better than random (i.e., low probability of making a Type I error; P) and as the predictability of targets using surrogates (R(2)). A total of 264 published surrogacy tests combined with prior probabilities elicited from eight international experts demonstrated that the habitat, spatial scale, type of surrogate and statistical method used all influenced surrogate effectiveness, at least according to either P or R(2). The type of surrogate used (higher-taxa, cross-taxa or subset taxa) was the best predictor of P, with the higher-taxa surrogates outperforming all others. The marine habitat was the best predictor of R(2), with particularly low predictability in tropical reefs. Surrogate effectiveness was greatest for higher-taxa surrogates at a <10-km spatial scale, in low-complexity marine habitats such as soft bottoms, and using multivariate-based methods. Comparisons with terrestrial studies in terms of the methods used to study surrogates revealed that marine applications still ignore some problems with several widely used statistical approaches to surrogacy. Our study provides a benchmark for the reliable use of biological surrogates in marine ecosystems, and highlights directions for future development of biological surrogates in predicting biodiversity.     

Dynamic role and importance of surrogate species for assessing potential adverse environmental impacts of genetically engineered insect-resistant plants on non-target organisms

Surrogate species have a long history of use in research and regulatory settings to understand the potentially harmful effects of toxic substances including pesticides. More recently, surrogate species have been used to evaluate the potential effects of proteins contained in genetically engineered insect resistant (GEIR) crops. Species commonly used in GEIR crop testing include beneficial organisms such as honeybees, arthropod predators, and parasitoids. The choice of appropriate surrogates is influenced by scientific factors such as the knowledge of the mode of action and the spectrum of activity as well as societal factors such as protection goals that assign value to certain ecosystem services such as pollination or pest control. The primary reasons for using surrogates include the inability to test all possible organisms, the restrictions on using certain organisms in testing (e.g., rare, threatened, or endangered species), and the ability to achieve greater sensitivity and statistical power by using laboratory testing of certain species. The acceptance of surrogate species data can allow results from one region to be applied or “transported” for use in another region. On the basis of over a decade of using surrogate species to evaluate potential effects of GEIR crops, it appears that the current surrogates have worked well to predict effects of GEIR crops that have been developed (Carstens et al. GM Crops Food 5:1–5, 2014), and it is expected that they should work well to predict effects of future GEIR crops based on similar technologies.     

A test for assessment of saproxylic beetle biodiversity using subsets of “monitoring species”

In European forests, large scale biodiversity monitoring networks need to be implemented – networks which include components such as taxonomical groups that are at risk and that depend directly on forest stand structure. In this context, monitoring the species-rich group of saproxylic beetles is challenging. In the absence of sufficient resources to comprehensively survey a particular group, surrogates of species richness can be meaningful tools in biodiversity evaluations. In search of restricted subsets of species to use as surrogates of saproxylic beetle richness, we led a case study in Western Europe.Beetle data were compiled from 67 biodiversity surveys and ecological studies carried out from 1999 to 2010 with standardised trapping methods in France and Belgium. This large-scale dataset contains 642 forest plots, 1521 traps and 856 species. Twenty-two simplified species subsets were identified as potential surrogates, as well as the number of genera, a higher taxonomic level, taking into account, for each surrogate, the effort required for species identification, the practical monitoring experience necessary, the species conservation potential or the frequency of species occurrence. The performance of each surrogate was analyzed based on the following parameters: overall surrogacy (correlation between subset richness and total species richness), surrogacy vs. identification cost balance, surrogacy variation over a wide range of ecological conditions (forest type, altitude, latitude and bio-geographical area) and consistency with spatial scale. Ecological representativeness and ability to monitor rare species were supplementary criteria used to assess surrogate performance.The subsets consisting of the identifiable (or only easy-to-identify species) could easily be applied in practice and appear to be the best performing subsets, from a global point of view.The number of genera showed good prediction at the trap level and its surrogacy did not vary across wide environmental gradients. However, the subset of easy-to-identify species and the genus number were highly sensitive to spatial scale, which limits their use in large-scale studies. The number of rare species or the species richness of single beetle families (even the best single-family subset, the Cerambycidae) was very weak surrogates for total species richness. Conversely, the German list of monitoring species had high surrogacy, low identification costs and was not strongly influenced by the main geographical parameters, even with our French and Belgian data.In European-wide monitoring networks, such internationally validated subsets could be very useful with regard to the timing and cost-efficiency of field inventories.     

Spatial conservation priorities are highly sensitive to choice of biodiversity surrogates and species distribution model type

Pressure to conserve biodiversity with limited resources has led to increasing use of species distribution models (SDMs) for spatial conservation prioritization. Published spatial prioritization exercises often focus on well‐studied groups, with data compiled from on‐line databases of ad‐hoc collections. Conservation plans generally aim to protect all components of biodiversity, and it is implied that the species used in prioritization act as surrogates. Here, we assess the sensitivity of spatial priorities to model and surrogate choice using a case study from a fragmented agricultural area of south eastern Australia that is poorly represented in the national reserve system. We model the distributions of 30 species of bird, microbat and bee using two types of SDM; generalised linear models based on systematic surveys that yield presence and absence observations, and MaxEnt models based on biodiversity database records. Eight prioritization scenarios were tested using Zonation software, and were based on either the presence–background or presence–absence SDMs and combinations of surrogacy among the three taxa. We found low correlations between SDMs generated for the same species using different modelling frameworks (μ = 0.18, n = 26). Area under the receiver operating characteristic curve (AUC) estimates generated by MaxEnt were optimistic; on average 1.36 times higher than when tested against the systematic survey data. Conservation priorities were sensitive to the choice of surrogate and type of data used to fit SDMs, and though bats and birds formed moderately good surrogates for each other, there was less compelling evidence of surrogacy for bees. Because valid surrogacy is unlikely with most existing data sets, investment in high quality data for less‐surveyed groups prior to planning should still be a priority. If this is not possible, then it is advisable to analyse the sensitivity of conservation plans to the assumed surrogacy and quality of data available.     

Ecosystem classification and inventory maps as surrogates for ground beetle assemblages in boreal forest

Aims We compare performance of ecosystem classification maps and provincial forest inventory data derived from air photography in reflecting ground beetle (Coleoptera: Carabidae) biodiversity patterns that are related to the forest canopy mosaic. Our biodiversity surrogacy model based on remotely sensed tree canopy cover is validated against field-collected ground data.Methods We used a systematic sampling grid of 198 sites, covering 84 km 2 of boreal mixedwood forest in northwestern Alberta, Canada. For every site, we determined tree basal area, characterized the ground beetle assemblage and obtained corresponding provincial forest inventory and ecosystem classification information. We used variation partitioning, ordination and misclassification matrices to compare beetle biodiversity patterns explained by alternative databases and to determine model biases originating from air photo-interpretation.Important findings Ecosystem classification data performed better than canopy cover derived from forest inventory maps in describing ground beetle biodiversity patterns. The biodiversity surrogacy models based on provincial forest inventory maps and field survey generally detected similar patterns but inaccuracies in air photo-interpretation of relative canopy cover led to differences between the two models. Compared to field survey data, air photo-interpretation tended to confuse two Picea species and two Populus species present and homogenize stand mixtures. This generated divergence in models of ecological association used to predict the relationship between ground beetle assemblages and tree canopy cover. Combination of relative canopy cover from provincial inventory with other geo-referenced land variables to produce the ecosystem classification maps improved biodiversity predictive power. The association observed between uncommon surrogates and uncommon ground beetle species emphasizes the benefits of detecting these surrogates as a part of landscape management. In order to complement conservation efforts established in protected areas, accurate, high resolution, wide ranging and spatially explicit knowledge of landscapes under management is primordial in order to apply effective biodiversity conservation strategies at the stand level as required in the extensively harvested portion of the boreal forest. In development of these strategies, an in-depth understanding of vegetation is key.     

Direct Measurement Versus Surrogate Indicator Species for Evaluating Environmental Change and Biodiversity Loss

The enormity and complexity of problems like environmental degradation and biodiversity loss have led to the development of indicator species and other surrogate approaches to track changes in environments and/or in biodiversity. Under these approaches particular species or groups of species are used as proxies for other biota, particular environmental conditions, or for environmental change. The indicator species approach contrasts with a direct measurement approach in which the focus is on a single entity or a highly targeted subset of entities in a given ecosystem but no surrogacy relationships with unmeasured entities are assumed. Here, we present a broad philosophical discussion of the indicator species and direct measurement approaches because their relative advantages and disadvantages are not well understood by many researchers, resource managers and policy makers. A goal of the direct measurement approach is to demonstrate a causal relationship between key attributes of the target ecosystem system (for example, particular environmental conditions) and the entities selected for measurement. The key steps in the approach are based on the fundamental scientific principles of hypothesis testing and associated direct measurement that drive research activities, management activities and monitoring programs. The direct measurement approach is based on four critical assumptions:(1) the ‘right’ entities to measure have been selected, (2) these entities are well known, (3) there is sufficient understanding about key ecological processes and (4) the entities selected can be accurately measured. The direct measurement approach is reductionist and many elements of the biota, many biotic processes and environmental factors must be ignored because of practical considerations. The steps in applying the indicator species approach are broadly similar to the direct measurement approach, except surrogacy relationships also must be quantified between a supposed indicator species or indicator group and the factors for which it is purported to be a proxy. Such quantification needs to occur via: (1) determining the taxonomic, spatial and temporal bounds for which a surrogacy relationship does and does not hold. That is, the extent of transferability of a given surrogate such as an indicator species to other biotic groups, to landscapes, ecosystems, environmental circumstances or over time in the same location can be determined; and (2) determining the ecological mechanisms underpinning a surrogacy relationship (for example, through fundamental studies of community structure). Very few studies have rigorously addressed these two tasks, despite the extremely widespread use of the indicator species approach and similar kinds of surrogate schemes in virtually all fields of environmental, resource and conservation management. We argue that this has the potential to create significant problems; thus, the use of an indicator species approach needs to be better justified. Attempts to quantify surrogacy relationships may reveal that, in some circumstances, the alternative of direct measurement of particular entities of environmental or conservation interest will be the best option.     

The history and future of fungi as biodiversity surrogates in forests

Biodiversity surrogates are commonly used in conservation biology. Here we review how fungi have been used as such in forest conservation, emphasizing proposed surrogate roles and practical applications. We show that many fungal surrogates have been suggested based on field experience and loose concepts, rather than on rigorously collected scientific data. Yet, they have played an important role, not only in forest conservation, but also in inspiring research in fungal ecology and forest history. We argue that, even in times of ecosystem oriented conservation planning and molecular tools to analyze fungal communities, fruit bodies of macrofungi have potential as convenient conservation shortcuts and easy tools to communicate complex biodiversity for a broader audience. To improve the reliability of future fungal surrogates we propose a three step protocol for developing evidence based schemes for practical application in forest conservation.     

Biodiversity change under adaptive community dynamics

Compositional change is a ubiquitous response of ecological communities to environmental drivers of global change, but is often regarded as evidence of declining “biotic integrity” relative to historical baselines. Adaptive compositional change, however, is a foundational idea in evolutionary biology, whereby changes in gene frequencies within species boost population-level fitness, allowing populations to persist as the environment changes. Here, we present an analogous idea for ecological communities based on core concepts of fitness and selection. Changes in community composition (i.e., frequencies of genetic differences among species) in response to environmental change should normally increase the average fitnessof community members. We refer to compositional changes that improve the functional match, or “fit,” between organisms' traits and their environment as adaptive community dynamics. Environmental change (e.g., land-use change) commonly reduces the fit between antecedent communities and new environments. Subsequent change in community composition in response to environmental changes, however, should normally increase community-level fit, as the success of at least some constituent species increases. We argue that adaptive community dynamics are likely to improve or maintain ecosystem function (e.g., by maintaining productivity). Adaptive community responses may simultaneously produce some changes that are considered societally desirable (e.g., increased carbon storage) and others that are undesirable (e.g., declines of certain species), just as evolutionary responses within species may be deemed desirable (e.g., evolutionary rescue of an endangered species) or undesirable (e.g., enhanced virulence of an agricultural pest). When assessing possible management interventions, it is important to distinguish between drivers of environmental change (e.g., undesired climate warming) and adaptive community responses, which may generate some desirable outcomes. Efforts to facilitate, accept, or resist ecological change require separate consideration of drivers and responses, and may highlight the need to reconsider preferences for historical baseline communities over communities that are better adapted to the new conditions.     

Zoo animals as “proxy species” for threatened sister taxa: Defining a novel form of species surrogacy

The vast number of species threatened with extinction, coupled with the limited resources to support them, results in the need to prioritize species for conservation action. Similarly, zoo collection managers must prioritize species for inclusion at their institutions, which are also limited by space and resources. While conservation status is one factor considered by zoos, weight is also given to qualitative features and practical considerations when evaluating the fit of different species. Resultantly, the species prioritized by zoos have limited overlap with those prioritized for conservation. Several recent studies have highlighted that the majority of species maintained in zoos are ranked globally as least concern. Given the centrality of conservation to the modern mission of zoos, there is value in identifying clear connections between non‐threatened species in zoos and the roles they can play in conservation. Surrogate species approaches have been used in many instances to facilitate indirect conservation, and several distinctive types of surrogacy have been formally described. The aim of this study is to define a novel form of species surrogacy (i.e., “proxy species”) that draws utility from non‐threatened species maintained in zoos. A proxy species is here defined as a non‐threatened species managed ex situ that can be used as a flagship for a related threatened species that is morphologically similar but not otherwise represented in zoos. The benefits of this approach and opportunities for its application are here reviewed. This concept will provide opportunities to enhance the value of pre‐existing zoo collections, and ultimately, support conservation objectives.     

Assessing the mechanisms behind successful surrogates for biodiversity in conservation planning

Limited by the availability of data, conservation planners must use surrogates for biodiversity when selecting conservation areas. Although several methods have been proposed for selecting surrogates, no clear set of species attributes have been described that allow for the efficient a priori selection of surrogate groups. We used a database of 1449 species in two regions of the United States to (1) examine the consistency in the performance of simple taxonomic-based surrogates of biodiversity and (2) test five hypotheses proposed to explain surrogate performance. First, we compared the ability of sites selected to protect members of seven surrogate groups to protect non-surrogate species in the north-western United States and in the Middle-Atlantic region of the eastern United States. Then, in a separate analysis, we tested whether surrogate performance could be explained by (1) taxonomic diversity; (2) nested species distributions; (3) hotspots of biodiversity; (4) species range sizes; (5) environmental diversity. Our first analysis revealed little consistency in the performance of surrogates in the two different study regions. For example, butterflies provided protection for 76% of all other species in the north-western United States but only 56% of all other species in the eastern United States. Our second analysis revealed only weak associations between species characteristics and surrogate performance. Furthermore, these associations proved inadequate for selecting successful surrogates across study regions. Overall, our results suggest that in lieu of searching for optimal surrogate groups, research efforts will be better spent by developing alternative methods for assessing conservation value in areas where data on species distributions are limited.     

Suitability of Molluscs as Bioindicators for Meadow‐ and Flood‐Channels of the Elbe‐Floodplains

The goals of the subproject “molluscs” within the inter‐disciplinary research project “Indicator systems for the characterisation and prediction of ecological changes in floodplain systems” were: – develop further existing mollusc‐based indicator systems of site quality and to test their transferability, – characterise grassland sites within the recent floodplains of three study areas along the Elbe River, – analyse the relationships between indicator species‐/groups and abiotic parameters, – compile and use selected species traits in the analytical process. The results clearly show several characteristic species groups related to the hydrology of the sites (i.e. inundation and desiccation regime) and on to the degree of agricultural use. These dependencies can be interpreted by the simultaneous analysis of the species traits. “Models” are proposed, that are applicable to nature protection measures at the landscape scale. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Different surrogacy approaches for stream macroinvertebrates in discriminating human disturbances in Central China

Due to the difficulty of identifying many taxa of freshwater invertebrates to species, many researchers have assessed the utility of surrogates for species-level identifications (e.g. higher taxa) in bioassessment programs. Here, we examined the efficiency of two different approaches to species surrogacy, one using coarser taxonomic resolution and a second approach based on random aggregation (“Best practicable aggregation of species”, BestAgg), in portraying patterns of stream macroinvertebrates in Central China. The main objectives were: (1) to compare the discriminatory power of biodiversity indices and assemblage structure for different levels of human disturbances based on different taxonomic resolution and on BestAgg; (2) to identify the congruence of assemblage-environment and biodiversity-indices-environment relationships for datasets at the species level versus those at surrogate levels. We found that genus-level and BestAgg datasets accurately reproduced the pattern of species-level communities, whereas family- and order-level datasets did not. Specifically, both genus-level and BestAgg approaches performed almost as well as species-level data in distinguishing sites subjected to different disturbance levels. Most of the environmental variables that were important for species-level assemblages, also emerged as significant when analyzing genera and BestAgg surrogates, as shown by both analyses of indices and assemblage composition according to distance-based ordination models. Our results suggest that genus-level taxonomy, which resulted in the least loss of ecological information relative to species-level identification, is sufficient in studies of community ecology and bioassessment of stream macroinvertebrates in Central China. In addition, the BestAgg approach, which required identification of fewer taxa than genus-level analysis, has a similar ability to depict multivariate patterns of macroinvertebrate assemblages and differentiate different disturbance levels. Applying our results could enhance speed and cost-effectiveness of freshwater biomonitoring and bioassessment programs; however, independent determination of best taxonomic level and BestAgg will be required whenever a new geographic area or habitat type is assessed.     

Habitats as surrogates of taxonomic and functional fish assemblages in coral reef ecosystems: a critical analysis of factors driving effectiveness

Species check-lists are helpful to establish Marine Protected Areas (MPAs) and protect local richness, endemicity, rarity, and biodiversity in general. However, such exhaustive taxonomic lists (i.e., true surrogate of biodiversity) require extensive and expensive censuses, and the use of estimator surrogates (e.g., habitats) is an appealing alternative. In truth, surrogate effectiveness appears from the literature highly variable both in marine and terrestrial ecosystems, making it difficult to provide practical recommendations for managers. Here, we evaluate how the biodiversity reference data set and its inherent bias can influence effectiveness. Specifically, we defined habitats by geomorphology, rugosity, and benthic cover and architecture criteria, and mapped them with satellite images for a New-Caledonian site. Fish taxonomic and functional lists were elaborated from Underwater Visual Censuses, stratified according to geomorphology and exposure. We then tested if MPA networks designed to maximize habitat richness, diversity and rarity could also effectively maximize fish richness, diversity, and rarity. Effectiveness appeared highly sensitive to the fish census design itself, in relation to the type of habitat map used and the scale of analysis. Spatial distribution of habitats (estimator surrogate's distribution), quantity and location of fish census stations (target surrogate's sampling), and random processes in the MPA design all affected effectiveness to the point that one small change in the data set could lead to opposite conclusions. We suggest that previous conclusions on surrogacy effectiveness, either positive or negative, marine or terrestrial, should be considered with caution, except in instances where very dense data sets were used without pseudo-replication. Although this does not rule out the validity of using surrogates of species lists for conservation planning, the critical joint examination of both target and estimator surrogates is needed for every case study.     

Learning from clinical medicine to improve the use of surrogates in ecology

Surrogates are used widely in ecology to detect or monitor changes in the environment that are too difficult or costly to assess directly. Yet most work on surrogates to date has been correlative, with little work on their predictive capacity or the circumstances under which they work. Our suggestion is to revisit and learn from research in the clinical medical sciences, including the causal statistical frameworks available to validate relationships between treatments, surrogate variables, and the outcome of interest. We adapt this medical thinking to ecology by providing a new framework that involves specification of the surrogate model, statistical validation, and subsequent evaluation in a range of spatial and temporal contexts. An inter‐disciplinary surrogate concept will allow for a more rigorous approach to validating and evaluating proxy variables, thus advancing the selection and application of surrogates in ecology. Synthesis We draw together ideas from the medical sciences to define an explicit surrogate concept that has not previously been used in ecology. We present a new framework for specifying surrogate models involving validation using a causal framework, and subsequent re‐evaluation in different spatial and temporal contexts – an approach closely aligned with that used by researchers in the clinical medical sciences. This rigorous method can advance the science underpinning the application of surrogates in ecology by shifting the focus away from correlative understanding to one that focuses instead on causation and prediction. An improved use of surrogates is imperative if we are to meet the challenge of properly measuring and understanding the multifarious and complex problems in contemporary ecology.     

Monitoring marine macroalgae: the influence of spatial scale on the usefulness of biodiversity surrogates

Aim To examine the influence of spatial scale on the usefulness of commonly employed biodiversity surrogates in subtidal macroalgae assemblages. Location South‐west Australia. Methods The relationship between biodiversity surrogates and univariate and multivariate species‐level patterns was tested at multiple spatial scales, ranging from metres (between quadrats) to hundreds of kilometres (between regions), using samples collected from almost 2000 km of temperate coastline that represented almost 300 species. Biodiversity surrogates included commonly used cost‐effective alternatives to species‐level sampling, such as those derived from functional groups and from taxonomic aggregation. Results Overall, surrogates derived from taxonomic aggregation to genus or family level correlated strongly with species‐level patterns, although the family‐level surrogate was a less effective predictor of species richness at large spatial scales. Surrogates derived from aggregation to coarser taxonomic levels and functional groups performed poorly, while the effectiveness of a surrogate measure derived from canopy‐forming species improved with increasing spatial scale. Main conclusions A critical, but rarely examined, assumption of biodiversity surrogates is that the relationship between surrogate and species‐level patterns is consistent in both space and time, and across a range of spatial and temporal scales. As the performance of all surrogates was, to some degree, scale‐dependent, this work empirically demonstrated the need to consider the spatial extent and design of any biodiversity monitoring programme when choosing cost‐effective alternatives to species‐level data collection.     

Recommendations for Assessing the Effectiveness of Surrogate Species Approaches

Surrogate species approaches, including flagship, focal, keystone, indicator, and umbrella, are considered an effective means of conservation planning. For conservation biologists to apply surrogates with confidence, they must have some idea of the effectiveness of surrogates for the circumstances in which they will be applied. We reviewed tests of the effectiveness of surrogate species planning to see if research supports the development of generalized rules for (1) determining when and where surrogate species are an effective conservation tool and (2) how surrogate species should be selected such that the resulting conservation plan will effectively protect biodiversity or achieve other conservation goals. The context and methods of published studies were so diverse that we could not draw general conclusions about the spatial or temporal scales, or ecosystems or taxonomic groups for which surrogate species approaches will succeed. The science of surrogate species can progress by (1) establishing methods to compare diverse measures of effectiveness; (2) taking advantage of data-rich regions to examine the potential effectiveness of surrogate approaches; (3) incorporating spatial scale as an explanatory variable; (4) evaluating surrogate species approaches at broader temporal scales; (5) seeking patterns that will lead to hypothesis driven research; and (6) monitoring surrogate species and their target species.     

Toward an integrated ecosystem perspective of invasive species impacts

Progress in the study of ecosystem impacts of invasive species can be facilitated by moving from the evaluation of invasive species impacts on particular processes to the analysis of their overall effects on ecosystem functioning. Here we propose an integrative ecosystem-based approach to the analysis of invasive species impacts that is based on an understanding of the general mechanistic links between biotic factors, abiotic factors, and processes in ecosystems. Two general kinds of biotic mediation – direct and indirect – and two general mechanisms of invasive species impact – assimilatory–dissimilatory (uptake and release of energy and materials) and physical ecosystem engineering (physical environmental modification by organisms) – are most relevant. By combining the biotic mediation pathways and the general mechanisms, four general situations emerge that characterize a great many of the impacts invasive species can have on ecosystem processes. We propose ways to integrate these distinctive impacts into general mechanistic representations that link ecosystem processes with changes in biotic and abiotic states (changes in structure, composition, amount, process rates, etc.). In turn, these help generate predictions about the interplay of invasive species and other drivers of ecosystem processes that are of particular relevance to ecosystems where invasive species co-occur with other anthropogenic impacts.     

Evaluation of five clustering algorithms for biodiversity surrogates

Conservation planning requires knowledge of the distribution of all species in the area of interest. Surrogates for biodiversity are considered as a possible solution. The two major types are biological and environmental surrogates. Here, we evaluate four different methods of hierarchical clustering, as well as one non-hierarchical method, in the context of producing surrogates for biodiversity. Each clustering method was used to produce maps of both surrogate types. We evaluated the representativeness of each clustering method by finding the average number of species represented in a set of sites, one site of each domain, which was carried out with Monte-Carlo permutations procedure. We propose an additional measure of surrogate performance, which is the degree of evenness of the different domains, e.g., by calculating Simpson's diversity index. Surrogates with low evenness leave little flexibility in site selection since often some of the domains may be represented by a single or very few sites, and thus surrogate maps with a high Simpson's index value may be more relevant for actual decision making. We found that there is a trade-off between species representativeness and evenness. Centroid clustering represented the most species, but had very low values of evenness. Ward's method of minimum variance represented more species than a random choice, and had high evenness values. Using the typical evaluation measures, the Centroid clustering method was most efficient for surrogate production. However, when Simpson's index is also considered, Ward's method of minimum variance is more appropriate for managers.