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Little is known about interactions between the critically endangered Sumatran tiger Panthera tigris sumatrae and its prey because of the difficulties associated with detecting these species. In this study, we quantify temporal overlap between the Sumatran tiger and five of its presumed prey species from four study areas comprising disturbed lowland to primary submontane forest. Data from 126 camera traps over 8984 camera days were used to estimate species activity patterns and, in turn, their overlap through the coefficient D (ranging from 0 to 1, i.e. no overlap to complete overlap). A newly developed statistical technique was applied to determine confidence intervals associated with respective overlap, which is important, as such measures of precision are usually not estimated in these types of study. Strong temporal overlap was found between tiger and muntjac Muntiacus muntjac (D = 0.80, 95%CI= 0.71-0.84) and tiger and sambar Cervus unicolor (D =0.81, 0.55-0.85), with the latter illustrating the importance of measuring precision. According to the foraging theory, Sumatran tigers should focus on expending lower levels of energy searching for and then capturing larger bodied prey that present the least risk. Hence, surprisingly, there was little overlap between the crepuscular tiger and the largest-bodied prey species available, the nocturnal tapir Tapirus indicus (0.52, 0.44-0.60), suggesting that it is not a principal prey species. This study provides the first insights into Sumatran tiger-prey temporal interactions. The ability to estimate overlap statistics with measures of precision has obvious and wide benefits for other predator-prey and interspecific competition studies.

Count data often show a higher incidence of zero counts than would be expected if the data were Poisson distributed. Zero-inflated Poisson regression models are a useful class of models for such data, but parameter estimates may be seriously biased if the nonzero counts are overdispersed in relation to the Poisson distribution. We therefore provide a score test for testing zero-inflated Poisson regression models against zero-inflated negative binomial alternatives.

Summary 1.Occupancy is an important concept in ecology. To obtain an unbiased estimator of occupancy it is necessary to address the issue of imperfect detection, which requires conducting replicate surveys at the sites being sampled. As the allocation of total effort can be done in different ways, occupancy studies should be designed carefully to ensure an efficient use of available resources. 2. In this paper we address the design of single-season single-species occupancy studies with a focus on: (1) issues relating to small sample sizes and (2) the potential relevance of including the precision of the detectability estimator as a criterion for design. We explore analytically the model with constant probabilities and examine how bias and precision are affected by the numbers of sites and replicates used. 3. We show how, for small sample sizes, the estimator properties depart from those predicted by large sample approximations, emphasize the need to use simulations when designing for small sample sizes and provide a new software tool that can assist in this process. 4. We offer advice on the amount of replication needed when the probability of detection is a quantity of interest and show that, in this case, it is more efficient to reduce the number of sites and increase the amount of replication per site compared with situations where only occupancy is of concern. 5. Synthesis and applications. It is essential to have clearly stated objectives before starting a study and to design the sampling accordingly. As the allocation of effort into replication and sites can be done in different ways, occupancy studies should be designed carefully to ensure an efficient use of available resources. To avoid waste, it is crucial to anticipate the quality of the estimates that can be expected from a particular study design. The discussion and guidance provided here is of special interest for those designing occupancy studies with small sample sizes, something not uncommon in the context of ecology and conservation.

This paper reviews many different estimators of intraclass correlation that have been proposed for binary data and compares them in an extensive simulation study. Some of the estimators are very specific, while others result from general methods such as pseudo-likelihood and extended quasi-likelihood estimation. The simulation study identifies several useful estimators, one of which does not seem to have been considered previously for binary data. Estimators based on extended quasi-likelihood are found to have a substantial bias in some circumstances.

The N-mixture model is widely used to estimate the abundance of a population in the presence of unknown detection probability from only a set of counts subject to spatial and temporal replication (Royle, 2004, Biometrics 60, 105–115). We explain and exploit the equivalence of N-mixture and multivariate Poisson and negative-binomial models, which provides powerful new approaches for fitting these models. We show that particularly when detection probability and the number of sampling occasions are small, infinite estimates of abundance can arise. We propose a sample covariance as a diagnostic for this event, and demonstrate its good performance in the Poisson case. Infinite estimates may be missed in practice, due to numerical optimization procedures terminating at arbitrarily large values. It is shown that the use of a bound, K, for an infinite summation in the N-mixture likelihood can result in underestimation of abundance, so that default values of K in computer packages should be avoided. Instead we propose a simple automatic way to choose K. The methods are illustrated by analysis of data on Hermann's tortoise Testudo hermanni.

Conservationists often complain that their study species are ignored by donors. However, marketing theory could help understand and increase the profile and fundraising potential of these neglected species. We used linear regression with multimodel inference to analyse data on donation behaviour from the World Wildlife Fund-US (WWF-US) and Zoological Society of London's EDGE of Existence programme (EDGE), in order to understand how species traits and marketing campaign characteristics influenced online flagship-based fundraising efforts. Our analysis accounted for species traits through variables such as appeal and familiarity, and marketing campaign characteristics through measuring the order in which the species were presented and the amount of information provided. We found that species traits were key for the WWF-US website, with appealing and threatened nonmammal species the most popular with donors. This was probably because WWF-US used well-known flagship species and so marketing had little impact. The EDGE website used a wider variety of species and in this case both species traits and the marketing campaign characteristics were important, so that appealing species and well-promoted species did best. We then predicted outcomes for a hypothetical EDGE fundraising campaign with varying degrees of marketing effort. We showed that additional marketing can have a large impact on donor behaviour, increasing the interest of potential donors towards unappealing species by up to 26 times. This increase would more than equal the amount raised by campaigns using appealing species without additional promotion. Our results show marketing can have a large impact on donor behaviour and suggest there is scope for successful marketing campaigns based on a much wider range of species

BackgroundYeast (Saccharomyces cerevisiae) prions are efficiently propagated and the on-going generation and transmission of prion seeds (propagons) to daughter cells during cell division ensures a high degree of mitotic stability. The reversible inhibition of the molecular chaperone Hsp104p by guanidine hydrochloride (GdnHCl) results in cell division-dependent elimination of yeast prions due to a block in propagon generation and the subsequent dilution out of propagons by cell division.Principal FindingsAnalysing the kinetics of the GdnHCl-induced elimination of the yeast [PSI+] prion has allowed us to develop novel statistical models that aid our understanding of prion propagation in yeast cells. Here we describe the application of a new stochastic model that allows us to estimate more accurately the mean number of propagons in a [PSI+] cell. To achieve this accuracy we also experimentally determine key cell reproduction parameters and show that the presence of the [PSI+] prion has no impact on these key processes. Additionally, we experimentally determine the proportion of propagons transmitted to a daughter cell and show this reflects the relative cell volume of mother and daughter cells at cell division.ConclusionsWhile propagon generation is an ATP-driven process, the partition of propagons to daughter cells occurs by passive transfer via the distribution of cytoplasm. Furthermore, our new estimates of n0, the number of propagons per cell (500–1000), are some five times higher than our previous estimates and this has important implications for our understanding of the inheritance of the [PSI +] and the spontaneous formation of prion-free cells.