Model-based control of observer bias for the analysis of presence-only data in ecology

Presence-only data, where information is available concerning species presence but not species absence, are subject to bias due to observers being more likely to visit and record sightings at some locations than others (hereafter "observer bias"). In this paper, we describe and evaluate a model-based approach to accounting for observer bias directly - by modelling presence locations as a function of known observer bias variables (such as accessibility variables) in addition to environmental variables, then conditioning on a common level of bias to make predictions of species occurrence free of such observer bias. We implement this idea using point process models with a LASSO penalty, a new presence-only method related to maximum entropy modelling, that implicitly addresses the "pseudo-absence problem" of where to locate pseudo-absences (and how many). The proposed method of bias-correction is evaluated using systematically collected presence/absence data for 62 plant species endemic to the Blue Mountains near Sydney, Australia. It is shown that modelling and controlling for observer bias significantly improves the accuracy of predictions made using presence-only data, and usually improves predictions as compared to pseudo-absence or "inventory" methods of bias correction based on absences from non-target species. Future research will consider the potential for improving the proposed bias-correction approach by estimating the observer bias simultaneously across multiple species. © 2013 Warton et al

Fitting Log-Gaussian Cox Processes Using Generalized Additive Model Software

While log-Gaussian Cox process regression models are useful tools for modeling point patterns, they can be technically difficult to fit and require users to learn/adopt bespoke software. We show that, for suitably formatted data, we can actually fit these models using generalized additive model software, via a simple line of code, demonstrated on R by the popular mgcv package. We are able to do this because a common and computationally efficient way to fit a log-Gaussian Cox process model is to use a basis function expansion to approximate the Gaussian random field, as is provided by a generic bivariate smoother over geographic space. We further show that if basis functions are parameterized appropriately then we can estimate parameters in the spatial covariance function for the latent random field using a generalized additive model. We use simulation to show that this approach leads to model fits of comparable quality to state-of-the-art software, often more quickly. But we see the main advance from this work as lowering the technology barrier to spatial statistics for applied researchers, many of whom are already familiar with generalized additive model software

Untangling direct species associations from indirect mediator species effects with graphical models

Ecologists often investigate co-occurrence patterns in multi-species data in order to gain insight into the ecological causes of observed co-occurrences. Apart from direct associations between the two species of interest, they may co-occur because of indirect effects, where both species respond to another variable, whether environmental or biotic (e.g. a mediator species). A wide variety of methods are now available for modelling how environmental filtering drives species distributions. In contrast, methods for studying other causes of co-occurence are much more limited. “Graphical” methods, which can be used to study how mediator species impact co-occurrence patterns, have recently been proposed for use in ecology. However, available methods are limited to presence/absence data or methods assuming multivariate normality, which is problematic when analysing abundances. We propose Gaussian copula graphical models (GCGMs) for studying the effect of mediator species on co-occurence patterns. GCGMs are a flexible type of graphical model which naturally accommodates all data types, for example binary (presence/absence), counts, as well as ordinal data and biomass, in a unified framework. Simulations demonstrate that GCGMs can be applied to a much broader range of data types than the methods currently used in ecology, and perform as well as or better than existing methods in many settings. We apply GCGMs to counts of hunting spiders, in order to visualise associations between species. We also analyse abundance data of New Zealand native forest cover (on an ordinal scale) to show how GCGMs can be used analyse large and complex datasets. In these data, we were able to reproduce known species relationships as well as generate new ecological hypotheses about species associations

Tropical plants do not have narrower temperature tolerances, but are more at risk from warming because they are close to their upper thermal limits

Aim: Tropical species are thought to be more susceptible to climate warming than are higher latitude species. This prediction is largely based on the assumption that tropical species can tolerate a narrower range of temperatures. While this prediction holds for some animal taxa, we do not yet know the latitudinal trends in temperature tolerance for plants. We aim to address this knowledge gap and establish if there is a global trend in plant warming risk. Location: Global. Time period: Present–2070. Major taxa studied: Plants. Methods: We used 9,737 records for 1,312 species from the Kew Gardens’ global germination database to quantify global patterns in germination temperature. Results: We found no evidence for a latitudinal gradient in the breadth of temperatures at which plant species can germinate. However, tropical plants are predicted to face the greatest risk from climate warming, because they experience temperatures closer to their upper germination limits. By 2070, over half (79/142) of tropical plant species are predicted to experience temperatures exceeding their optimum germination temperatures, with some even exceeding their maximum germination temperature (41/190). Conversely, 95% of species at latitudes above 45° are predicted to benefit from warming, with environmental temperatures shifting closer to the species’ optimal germination temperatures. Main conclusions: The prediction that tropical plant species would be most at risk under future climate warming was supported by our data, but through a different mechanism to that generally assumed

Bridging reproductive and microbial ecology: a case study in arbuscular mycorrhizal fungi

Offspring size is a key trait for understanding the reproductive ecology of species, yet studies addressing the ecological meaning of offspring size have so far been limited to macro-organisms. We consider this a missed opportunity in microbial ecology and provide what we believe is the first formal study of offspring-size variation in microbes using reproductive models developed for macro-organisms. We mapped the entire distribution of fungal spore size in the arbuscular mycorrhizal (AM) fungi (subphylum Glomeromycotina) and tested allometric expectations of this trait to offspring (spore) output and body size. Our results reveal a potential paradox in the reproductive ecology of AM fungi: while large spore-size variation is maintained through evolutionary time (independent of body size), increases in spore size trade off with spore output. That is, parental mycelia of large-spored species produce fewer spores and thus may have a fitness disadvantage compared to small-spored species. The persistence of the large-spore strategy, despite this apparent fitness disadvantage, suggests the existence of advantages to large-spored species that could manifest later in fungal life history. Thus, we consider that solving this paradox opens the door to fruitful future research establishing the relationship between offspring size and other AM life history traits

When Your Decisions Are Not (Quite) Your Own: Action Observation Influences Free Choices

A growing number of studies have begun to assess how the actions of one individual are represented in an observer. Using a variant of an action observation paradigm, four experiments examined whether one person's behaviour can influence the subjective decisions and judgements of another. In Experiment 1, two observers sat adjacent to each other and took turns to freely select and reach to one of two locations. Results showed that participants were less likely to make a response to the same location as their partner. In three further experiments observers were asked to decide which of two familiar products they preferred or which of two faces were most attractive. Results showed that participants were less likely to choose the product or face occupying the location of their partner's previous reaching response. These findings suggest that action observation can influence a range of free choice preferences and decisions. Possible mechanisms through which this influence occurs are discussed

Neighbour identity hardly affects litter-mixture effects on decomposition rates of New Zealand forest species.

The mass loss of litter mixtures is often different than expected based on the mass loss of the component species. We investigated if the identity of neighbour species affects these litter-mixing effects. To achieve this, we compared decomposition rates in monoculture and in all possible two-species combinations of eight tree species, widely differing in litter chemistry, set out in two contrasting New Zealand forest types. Litter from the mixed-species litter bags was separated into its component species, which allowed us to quantify the importance of litter-mixing effects and neighbour identity, relative to the effects of species identity, litter chemistry and litter incubation environment. Controlling factors on litter decomposition rate decreased in importance in the order: species identity (litter quality) >> forest type >> neighbour species. Species identity had the strongest influence on decomposition rate. Interspecific differences in initial litter lignin concentration explained a large proportion of the interspecific differences in litter decomposition rate. Litter mass loss was higher and litter-mixture effects were stronger on the younger, more fertile alluvial soils than on the older, less-fertile marine terrace soils. Litter-mixture effects only shifted percentage mass loss within the range of 1.5%. There was no evidence that certain litter mixtures consistently showed interactive effects. Contrary to common theory, adding a relatively fast-decomposing species generally slowed down the decomposition of the slower decomposing species in the mixture. This study shows that: (1) species identity, litter chemistry and forest type are quantitatively the most important drivers of litter decomposition in a New Zealand rain forest; (2) litter-mixture effects—although statistically significant—are far less important and hardly depend on the identity and the chemical characteristics of the neighbour species; (3) additive effects predominate in this ecosystem, so that mass dynamics of the mixtures can be predicted from the monocultures

Leaf economics fundamentals explained by optimality principles

The life span of leaves increases with their mass per unit area (LMA). It is unclear why. Here, we show that this empirical generalization (the foundation of the worldwide leaf economics spectrum) is a consequence of natural selection, maximizing average net carbon gain over the leaf life cycle. Analyzing two large leaf trait datasets, we show that evergreen and deciduous species with diverse construction costs (assumed proportional to LMA) are selected by light, temperature, and growing-season length in different, but predictable, ways. We quantitatively explain the observed divergent latitudinal trends in evergreen and deciduous LMA and show how local distributions of LMA arise by selection under different environmental conditions acting on the species pool. These results illustrate how optimality principles can underpin a new theory for plant geography and terrestrial carbon dynamics

Higher fungal diversity is correlated with lower CO2 emissions from dead wood in a natural forest

Wood decomposition releases almost as much CO2 to the atmosphere as does fossil-fuel combustion, so the factors regulating wood decomposition can affect global carbon cycling. We used metabarcoding to estimate the fungal species diversities of naturally colonized decomposing wood in subtropical China and, for the first time, compared them to concurrent measures of CO2 emissions. Wood hosting more diverse fungal communities emitted less CO2, with Shannon diversity explaining 26 to 44% of emissions variation. Community analysis supports a ‘pure diversity’ effect of fungi on decomposition rates and thus suggests that interference competition is an underlying mechanism. Our findings extend the results of published experiments using low-diversity, laboratory-inoculated wood to a high-diversity, natural system. We hypothesize that high levels of saprotrophic fungal biodiversity could be providing globally important ecosystem services by maintaining dead-wood habitats and by slowing the atmospheric contribution of CO2 from the world’s stock of decomposing wood. However, large-scale surveys and controlled experimental tests in natural settings will be needed to test this hypothesis

Anyone with a Long-Face? Craniofacial Evolutionary Allometry (CREA) in a Family of Short-Faced Mammals, the Felidae

Among adults of closely related species, a trend in craniofacial evolutionary allometry (CREA) for larger taxa to be long-faced and smaller ones to have paedomorphic aspects, such as proportionally smaller snouts and larger braincases, has been demonstrated in some mammals and two bird lineages. Nevertheless, whether this may represent a ‘rule’ with few exceptions is still an open question. In this context, Felidae is a particularly interesting family to study because, although its members are short-faced, previous research did suggest relative facial elongation in larger living representatives. Using geometric morphometrics, based on two sets of anatomical landmarks, and traditional morphometrics, for comparing relative lengths of the palate and basicranium, we performed a series of standard and comparative allometric regressions in the Felidae and its two subfamilies. All analyses consistently supported the CREA pattern, with only one minor exception in the geometric morphometric analysis of Pantherinae: the genus Neofelis. With its unusually long canines, Neofelis species seem to have a relatively narrow cranium and long face, despite being smaller than other big cats. In spite of this, overall, our findings strengthen the possibility that the CREA pattern might indeed be a ‘rule’ among mammals, raising questions on the processes behind it and suggesting future directions for its study