Kin discrimination in the spotted hyena (<Emphasis Type="Italic">Crocuta crocuta</Emphasis>): nepotism among siblings

We examined patterns of affiliation, association, and aggression to inquire whether spotted hyenas (Crocuta crocuta) can distinguish among various groups of maternal and paternal siblings. If so, and if these animals conform to predictions of kin selection theory, then behavioral interactions among hyenas should vary with relatedness. We also considered familiarity-based recognition and phenotype matching as mechanisms hyenas might use to recognize kin. Patterns of affiliative behavior indicated that hyenas favored full-sibling littermates over half-sibling littermates or any other group of half-siblings. Rates of dyadic aggression generally did not vary with kinship. Hyenas associated more closely with half-sibling littermates than with non-littermate half-siblings, and hyenas affiliated more with maternal half-siblings than with paternal half-siblings, suggesting that familiarity-based cues might mediate discrimination among these sibling classes. In addition, operation of a phenotype-matching mechanism was suggested by the preference hyenas demonstrated during affiliative interactions for full- over half-sibling littermates, and by their lack of preference in these interactions for half-sibling littermates over non-littermate half-siblings. Phenotype matching was also suggested by our observation that paternal half-siblings cooperated more, and fought less, than did non-kin. Our data indicate that hyenas can discriminate among various types of siblings, that their social behavior conforms to predictions of kin selection theory, and that they recognize kin using mechanisms of both familiarity and phenotype matching.Communicated by S. Alberts     

The influence of productivity on the species richness of plants: a critical assessment

Despite much scrutiny the relationship between productivity and species richness remains controversial, and there is little agreement about causal processes. We present the results of a survey of 159 productivity-plant species richness (P-PSR) relationships from 131 published studies. We critically assessed each study with respect to experimental design and for the appropriateness of the surrogates used for productivity. We were able to accept only 60 of the reported relationships as robust tests of the P-PSR relationship and a further 18 as robust tests of the biomass species richness relationship. Previous analyses have found that unimodal P-PSR relationships predominate. In contrast, we found that, in studies that used data of continental to global extent, all P-PSR relationships were positive regardless of grain, that almost all were also positive in data sets of regional extent, and that unimodal relationships were not dominant even in studies of fine grain or small spatial extent. Our results differ substantially from previous meta-analyses because previous studies have included a large number of studies that do not meet basic experimental design criteria for objectively testing P-PSR relationships. These results have important implications for theory that attempts to explain species richness patterns. We critically review four dominant theories in light of our results and develop new falsifiable predictions of relationship from these theories at both small and large spatial scales.     

Elevated land runoff after European settlement perturbs persistent foraminiferal assemblages on the Great Barrier Reef

Coral reefs are under pressure from a variety of human-induced disturbances, but demonstration of ecosystem changes and identification of stressors are often difficult. We tested whether global change or increased agricultural runoff after European settlement of Northeast Australia (ca. 1860) has affected inshore reefs of the Great Barrier Reef. Eleven sediment cores were retrieved from inner reefs, intermediate reefs, and outer-island reefs, and benthic foraminiferal assemblages were analyzed in dated (14C, 210Pb, 137Cs) core sections (N = 82 samples). Data were grouped into six age bands (< 55, 55-150, 150-500, 500-1000, 1000-1500, and > 1500 yr). Principal component analysis and two-factor (Zone and Age) permutational analysis of variance (PERMANOVA) suggested that assemblages from the three zones were significantly different from each other over several millennia, with symbiont-bearing (mixotrophic) species dominating the outer reefs. A significant interaction term indicated that within-zone patterns varied. Assemblages in outer reefs unaffected from increased land runoff were persistent until present times. In both other zones, assemblages were also persistent until 150 yr ago, suggesting that benthic foraminiferal assemblages are naturally highly persistent over long (> 2000 yr) timescales. Assemblages in core sections < 55 yr old from inner reefs were significantly (post hoc t test) different from those older than 150 yr. Similarly, assemblages < 55 yr old from intermediate reefs were significantly different compared to older assemblages. A multivariate regression tree (environmental variables: Zone and Age) explained 56.8% of the variance in foraminiferal assemblages and confirmed patterns identified by PERMANOVA. With some exceptions, changes on the inner and intermediate reefs were consistent with a model predicting that increased nutrients and higher turbidity enhance relative abundance of heterotrophic species. Given that assemblages did not change in outer-island reefs (not impacted by runoff) we argue that changes in assemblages due to global change can be rejected as an explanation. Thus, the findings are more consistent with the hypothesis that agricultural runoff since European settlement altered foraminiferal assemblages than with the hypothesis that global forcing caused changes.     

The maximum likelihood based intensity estimate for circular point processes

Identifying the geometrical nature of spatial point patterns plays an important role in many areas of scientific research. Common types of spatial point processes involve random, regular, and cluster patterns. However, some point patterns suggest identifiable geometrical shapes such as a circular or other conic patterns. These patterns may be recognized as either a specific clustered shape or an inhomogeneous point pattern. Less noisy conic shapes, including circular patterns, are heavily discussed in the pattern recognition literature, but the goodness-of-fit of conic-fitting algorithms is rarely discussed for very noisy data. This study addresses a parameter estimation technique for noisy circular point patterns using the maximum likelihood principle. Additionally, a spatial statistical tool known as the L-function is used to investigate whether the fitted location pattern is reasonably attributable to a circular shape. A novel quantity named ‘relative log-error’ (\(\gamma \)) is introduced to quantify the goodness-of-fit for circular model fits. An iteratively re-weighted least squares procedure is introduced and robustness is evaluated under several error structures. Computational efficiency of the current and novel circle-fitting methods is also discussed. The findings are applied to two environmental science data sets.     

Combining Strategies to Select Reserves in Fragmented Landscapes

Abstract:  In the identification of reserve networks in fragmented landscapes with limited species-specific data at hand, one approach is to use selection criteria, such as patch size, to rank the habitat patches' conservation value and evaluate reserve-network alternatives. These criteria are assumed to be reasonable surrogates for the true network objectives. Caution is warranted, however, because the relationships between the selection criteria and the reserve-network objectives may be inconsistent. Conflicts are also likely to arise because no single reserve network will be optimal with respect to multiple objectives (or selection criteria) simultaneously. Instead, reserve planners must compromise between conflicting demands. We field tested the relationships between a variety of selection criteria and the objectives of a reserve network for the sandplain natural communities on Martha's Vineyard Island, Massachusetts (U.S.A.). Selection criteria that correlated with the reserve-network objectives were used in a multi-objective integer program to identify the 10-patch reserve networks that were optimal with each objective independently and those that offered optimal tradeoffs between the reserve-network objectives. From these 10-patch networks, one can select a final reserve network that provides the preferred compromise between the objectives.     

Savviness of prey to introduced predators

The prey naivety hypothesis posits that prey are vulnerable to introduced predators because many generations in slow gradual coevolution are needed for appropriate avoidance responses to develop. It predicts that prey will be more responsive to native than introduced predators and less responsive to introduced predators that differ substantially from native predators and from those newly established. To test these predictions, we conducted a global meta-analysis of studies that measured the wariness responses of small mammals to the scent of sympatric mammalian mesopredators. We identified 26 studies that met our selection criteria. These studies comprised 134 experiments reporting on the responses of 36 small mammal species to the scent of six introduced mesopredators and 12 native mesopredators. For each introduced mesopredator, we measured their phylogenetic and functional distance to local native mesopredators and the number of years sympatric with their prey. We used predator and prey body mass as a measure of predation risk. Globally, small mammals were similarly wary of the scent of native and introduced mesopredators; phylogenetic and functional distance between introduced mesopredators and closest native mesopredators had no effect on wariness; and wariness was unrelated to the number of prey generations, or years, since first contact with introduced mesopredators. Small mammal wariness was associated with predator-prey body mass ratio, regardless of the nativity. The one thing animals do not seem to recognize is whether their predators are native.     

The influence of intraguild predation on prey suppression and prey release: a meta-analysis

Intraguild predation (IGP) occurs when one predator species consumes another predator species with whom it also competes for shared prey. One question of interest to ecologists is whether multiple predator species suppress prey populations more than a single predator species, and whether this result varies with the presence of IGP. We conducted a meta-analysis to examine this question, and others, regarding the effects of IGP on prey suppression. When predators can potentially consume one another (mutual IGP), prey suppression is greater in the presence of one predator species than in the presence of multiple predator species; however, this result was not found for assemblages with unidirectional or no IGP. With unidirectional IGP, intermediate predators were generally more effective than the top predator at suppressing the shared prey, in agreement with IGP theory. Adding a top predator to an assemblage generally caused prey to be released from predation, while adding an intermediate predator caused prey populations to be suppressed. However, the effects of adding a top or intermediate predator depended on the effectiveness of these predators when they were alone. Effects of IGP varied across different ecosystems (e.g., lentic, lotic, marine, terrestrial invertebrate, and terrestrial vertebrate), with the strongest patterns being driven by terrestrial invertebrates. Finally, although IGP theory is based on equilibrium conditions, data from short-term experiments can inform us about systems that are dominated by transient dynamics. Moreover, short-term experiments may be connected in some way to equilibrium models if the predator and prey densities used in experiments approximate the equilibrium densities in nature.     

Detecting Extinction Risk from Climate Change by IUCN Red List Criteria

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow‐acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short‐lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions. Detección del Riesgo de Extinción a partir del Cambio Climático por medio del Criterio de la Lista Roja de la UICNKeith et al.     

Conservation Genetics at the Species Boundary

Abstract: Conservation genetics has expanded its purview such that molecular techniques are now used routinely to prioritize populations for listing and protection and infer their historical relationships in addition to addressing more traditional questions of heterozygosity and inbreeding depression. Failure to specify whether molecular data are being used for diagnosis-related questions or for population viability questions, however, can lead either to misinterpretation of character data as adaptive information or to misinterpretation of frequency or distance data as diagnostic or historical information. Each of these misinterpretations will confound conservation programs. The character-based approach to delimiting phylogenetic species is both operationally and logically superior to "diagnostic" methods that involve distance- or frequency-based routines, which are unstable over time. Tree-based criteria for the diagnosis of conservation "units" are also inappropriate because they can depend on patterns inferred without reference to diagnostic characters. Intraspecific studies, conservation-related or otherwise, that adopt terminology and methods designed to infer nested hierarchic relationships confuse diagnosis with historical inferences by treating diagnoses as outcomes rather than as precursors to phylogeny reconstruction. A character-based diagnostic approach recognizes the analytical dichotomy between species hierarchies and population statistics and provides a framework for the understanding of each. No species concept, however, should be viewed as an absolute criterion for protecting populations, but as part of a framework from within which identification of protection and management goals can be achieved effectively and defensibly.     

整合分析中的非参数检验:重复取样检验法的实例应用

整合分析(meta-analysis)是对同一主题下多个独立实验结果进行综合的统计学方法。非参数检验整合分析——重复取样检验(resampling test)不考虑原文献数据的分布形式，故可在不知原文献数据分布形式时使用。其中的靴襻法(bootstrap)可用来给出总效应值的置信区间，但不能检验组内异质性是否显著。靴襻法与随机检验法(randomization test)可以有效弥补这一缺失，判断出组间差异性是否显著。实例应用表明，重复取样检验没有参数检验保守，又与参数检验的结果差异较小。     

Active density-dependent habitat selection in a controlled population of small mammals

Density-dependent habitat selection has numerous and far-reaching implications to population dynamics and evolutionary processes. Although several studies suggest that organisms choose and occupy high-quality habitats over poorer ones, definitive experiments demonstrating active selection, by the same individuals at the appropriate population scale, are lacking. We conducted a reciprocal food supplementation experiment to assess whether voles would first occupy a habitat receiving extra food, then change their preference to track food supplements moved to another habitat. Meadow voles, as predicted, were more abundant in food-supplemented habitat than in others. Density declined when food supplements ceased because the voles moved to the new habitat receiving extra food. Although males and females appeared to follow different strategies, meadow-vole densities reflected habitat quality because voles actively selected the best habitat available. It is thus clear that behavioral decisions on habitat use can motivate patterns of abundance, frequency, and gene flow that have widespread effects on subsequent evolution.     

Meta-analyses and mega-mistakes: calling time on meta-analysis of the species richness-productivity relationship

The form of the species richness-productivity relationship (SRPR) is both theoretically important and contentious. In an effort to distill general patterns, ecologists have undertaken meta-analyses, within which each SRPR data set is first classified into one of five alternative forms: positive, humped (unimodal), negative, U-shaped (unimodal), and no relationship. Herein, I first provide a critique of this approach, based on 68 plant data sets/ studies used in three meta-analyses published in Ecology. The meta-analyses are shown to have resulted in highly divergent outcomes, inconsistent and often highly inappropriate classification of data sets, and the introduction and multiplication of errors from one meta-analysis to the next. I therefore call on the ecological community at large to adopt a far more rigorous and critical attitude to the use of meta-analysis. Second, I develop the argument that the literature on the SRPR continues to be bedeviled by a common failing to appreciate the fundamental importance of the scale of analysis, beginning with the confusion evident between concepts of grain, focus, and extent. I postulate that variation in the form of the SRPR at fine scales of analysis owes much to artifacts of the sampling regime adopted. An improved understanding may emerge from combining sampling theory with an understanding of the factors controlling the form of species abundance distributions and species accumulation curves.     

Spatial proximity loggers for recording animal social networks: consequences of inter-logger variation in performance

Social network analysis has become an increasingly popular method to link individual behaviour to population level patterns (and vice versa). Technological advances of recent years, such as the development of spatial proximity loggers, have enhanced our abilities to record contact patterns between animals. However, loggers are often deployed without calibration which may lead to sampling biases and spurious results. In particular, loggers may differ in their performance (i.e., some loggers may over-sample and other loggers may under-sample social associations). However, the consequences of inter-logger variation in logging performance has not been thoroughly considered or quantified. In this study, proximity loggers made by Sirtrack Ltd. were fitted to 20 dairy cows over a 3-week period. Contact records resulting from field deployment demonstrated variability in logger performance when recording contact duration, which was highly consistent for each logger over time. Testing loggers under standardised conditions suggested that inter-logger variation observed in the field was due to a combination of intrinsic variation in devices, and environmental/behavioural effects. We demonstrate the potential consequences that inter-logger variation in logging performance can have for social network analysis; particularly how measures of connectivity can be biased by logging performance. Finally, we suggest some approaches to correct data generated by proximity loggers with imperfect performance, that should be used to improve the robustness of future analyses.     

Sensitivity of Systematic Reserve Selection to Decisions about Scale, Biological Data, and Targets: Case Study from Southern British Columbia

Abstract:  The identification of conservation areas based on systematic reserve-selection algorithms requires decisions related to both spatial and ecological scale. These decisions may affect the distribution and number of sites considered priorities for conservation within a region. We explored the sensitivity of systematic reserve selection by altering values of three essential variables. We used a 1:20,000–scale terrestrial ecosystem map and habitat suitability data for 29 threatened vertebrate species in the Okanagan region of British Columbia, Canada. To these data we applied a reserve-selection algorithm to select conservation sites while altering selection unit size and shape, features of biodiversity (i.e., vertebrate species), and area conservation targets for each biodiversity feature. The spatial similarity, or percentage overlap, of selected sets of conservation sites identified (1) with different selection units was ≤40%, (2) with different biodiversity features was 59%, and (3) with different conservation targets was ≥94%. Because any selected set of sites is only one of many possible sets, we also compared the conservation value (irreplaceability) of all sites in the region for each variation of the data. The correlations of irreplaceability were weak for different selection units (0.23 ≤ r ≤ 0.67), strong for different biodiversity features ( r = 0.84), and mixed for different conservation targets ( r = 0.16; 0.16; 1.00). Because of the low congruence of selected sites and weak correlations of irreplaceability for different selection units, recommendations from studies that have been applied at only one spatial scale must be considered cautiously.     

Evolving metacommunities: toward an evolutionary perspective on metacommunities

The metacommunity framework predicts that local coexistence depends on the outcome of local species interactions and regional migration. In analogous fashion, spatial structure among populations can shape species interactions through evolutionary mechanisms. Yet, most metacommunity theories assume that populations do not evolve. Here, we evaluate how evolution shapes local species coexistence and exclusion within the multiscale and multispecies context embodied by the metacommunity framework. In general, coexistence in joint ecological-evolutionary models requires low to intermediate dispersal rates that can promote maintenance of both regional species and genetic diversity. These conditions support a set of key mechanisms that modify patterns of species coexistence including local adaptation, gene storage effects, genetic rescue effects, spatial genetic subsidies, and metacommunity evolution. Multispecies extensions indicate that correlated selection can further alter the outcome of interspecific interactions depending on the magnitude and direction of correlations and shape of fitness trade-offs. We suggest that an evolving metacommunity perspective has the potential to generate novel predictions about community structure and function by incorporating the genetic and species diversity that characterize natural communities. In adopting such a perspective, we seek to facilitate understanding about the interactions between evolutionary and metacommunity dynamics.     

Mechanistic analysis of interspecific competition using foraging trade-offs: implications for duck assemblages

The role of interspecific competition and resource partitioning in determining the composition of species assemblages is often controversial. In many cases data on species co-occurrence or resource use (prey or habitat) have been interpreted without a clear understanding of how, or even whether, phenotypic differences constrain performance to allow resource partitioning or how these constraints and the density of resources and competitors should shape resource selection by each species. Instead, predictions have been based on assumed constraints, possibly leading to conflicting results. One such controversy involves the role of bill morphology in mediating resource partitioning among dabbling ducks (Anas spp.). To determine whether incorrect assumptions may have contributed to this controversy, I constructed mechanistic models that predict filter-feeding performance for seven species of ducks directly from bill morphology and kinetics and compared these predictions to those of earlier studies that tested the bill morphology hypothesis. The models predicted that species should share a preference for their most profitable (primary) prey while partitioning their less profitable (secondary) prey by size. Consequently, ducks should forage in the same habitats and exhibit high overlap in prey size when competitor/resource ratios are either high or low. In contrast, earlier studies expected that resource partitioning should always be evident, which implicitly assumes that species partition their primary resources. The models also predicted that the ecological similarity of species in assemblages should increase as prey abundance and size variability declines, contrary to the expectations of an earlier study. A more consistent understanding of the mechanisms regulating assemblages of dabbling ducks, and other species, might emerge if patterns of resource use and species co-occurrence were predicted directly from a mechanistic understanding of how performance trade-offs affect resource selection in the context of varying resource and competitor densities.     

Adaptive phenotypic differentiation across the intertidal gradient in the alga Silvetia compressa

Populations of intertidal species span a steep environmental gradient driven by differences in emersion time. In spite of strong differential selection on traits related to this gradient, the small spatial scale over which differences occur may prevent local adaptation, and instead may favor a single intermediate phenotype, or nongenetic mechanisms of differentiation. Here I examine whether a common macroalga, Silvetia compressa, exhibits phenotypic differentiation across the intertidal gradient and evaluate how local adaptation, developmental plasticity, and maternal effects may interact to shape individual phenotypes. Reciprocal transplants of both adults and embryos showed a "home-height advantage" in two of the three populations tested. In laboratory trials, the progeny of upper-limit individuals survived exposure to air significantly better than lower-limit progeny from the same population. I compared the emersion tolerance of full-sib families generated from gametes produced in the field to those produced under common garden conditions. The relative advantage of upper-limit lineages was robust to maternal environment during gametogenesis; this pattern is consistent with genetic differentiation. The possible role of local adaptation has historically been ignored in studies of intertidal zonation. In S. compressa, phenotypic differentiation may have important consequences for vertical range, both within and among sites.     

Selecting pseudo-absence data for presence-only distribution modeling: How far should you stray from what you know?

An important decision in presence-only species distribution modeling is how to select background (or pseudo-absence) localities for model parameterization. The selection of such localities may influence model parameterization and thus, can influence the appropriateness and accuracy of the model prediction when extrapolating the species distribution across time and space. We used 12 species from the Australian Wet Tropics (AWT) to evaluate the relationship between the geographic extent from which pseudo-absences are taken and model performance, and shape and importance of predictor variables using the MAXENT modeling method. Model performance is lower when pseudo-absence points are taken from either a restricted or broad region with respect to species occurrence data than from an intermediate region. Furthermore, variable importance (i.e., contribution to the model) changed such that, models became increasingly simplified, dominated by just two variables, as the area from which pseudo-absence points were drawn increased. Our results suggest that it is important to consider the spatial extent from which pseudo-absence data are taken. We suggest species distribution modeling exercises should begin with exploratory analyses evaluating what extent might provide both the most accurate results and biologically meaningful fit between species occurrence and predictor variables. This is especially important when modeling across space or time—a growing application for species distributional modeling.     

The triple helix of Plantago lanceolata: genetics and the environment interact to determine population dynamics

The theory of evolution via natural selection predicts that the genetic composition of wild populations changes over time in response to the environment. Different genotypes should exhibit different demographic patterns, but genetic variation in demography is often impossible to separate from environmental variation. Here, we asked if genetic variation is important in determining demographic patterns. We answer this question using a long-term field experiment combined with general linear modeling of deterministic population growth rates (lambda), deterministic life table response experiment (LTRE) analysis, and stochastic simulation of demography by paternal lineage in a short-lived perennial plant, Plantago lanceolata, in which we replicated genotypes across four cohorts using a standard breeding design. General linear modeling showed that growth rate varied significantly with year, spatial block, and sire. In LTRE analysis of all cohorts, the strongest influences on growth rate were from year x spatial block, and cohort x year x spatial block interactions. In analysis of genetics vs. temporal environmental variation, the strongest impacts on growth rate were from year and year x sire. Finally, stochastic simulation suggested different genetic composition among cohorts after 100 years, and different population growth rates when genetic differences were accounted for than when they were not. We argue that genetic variation, genotype x environment interactions, natural selection, and cohort effects should be better integrated into population ecological studies, as these processes should result in deviations from projected deterministic and stochastic population parameters.