Annual cycles are the most common reproductive strategy in African tropical tree communities

Abstract We present the first cross‐continental comparison of the flowering and fruiting phenology of tropical forests across Africa. Flowering events of 5446 trees from 196 species across 12 sites and fruiting events of 4595 trees from 191 species across 11 sites were monitored over periods of 6 to 29 years and analyzed to describe phenology at the continental level. To study phenology, we used Fourier analysis to identify the dominant cycles of flowering and fruiting for each individual tree and we identified the time of year African trees bloom and bear fruit and their relationship to local seasonality. Reproductive strategies were diverse, and no single regular cycle was found in >50% of individuals across all 12 sites. Additionally, we found annual flowering and fruiting cycles to be the most common. Sub‐annual cycles were the next most common for flowering, whereas supra‐annual patterns were the next most common for fruiting. We also identify variation in different subsets of species, with species exhibiting mainly annual cycles most common in West and West Central African tropical forests, while more species at sites in East Central and East African forests showed cycles ranging from sub‐annual to supra‐annual. Despite many trees showing strong seasonality, at most sites some flowering and fruiting occurred all year round. Environmental factors with annual cycles are likely to be important drivers of seasonal periodicity in trees across Africa, but proximate triggers are unlikely to be constant across the continent.Additional co-authors: Roman M. Wittig, Thomas Breuer, Mireille Breuer‐Ndoundou Hockemba, Crickette M. Sanz, David B. Morgan, Anne E. Pusey, Badru Mugerwa, Baraka Gilagiza, Caroline Tutin, Corneille E. N. Ewango, Douglas Sheil, Edmond Dimoto, Fidèle Baya, Flort Bujo, Fredrick Ssali, Jean‐Thoussaint Dikangadissi, Kim Valenta, Michel Masozera, Michael L. Wilson, Robert Bitariho, Sydney T. Ndolo Ebika, Sylvie Gourlet‐Fleury, Felix Mulindahabi, Colin M. Beal

Annual cycles are the most common reproductive strategy in African tropical tree communities

We present the first cross continental comparison of the flowering and fruiting phenology of tropical forests across Africa. Flowering events of 5,446 trees from 196 species across 12 sites, and fruiting events of 4,595 trees from 191 species, across 11 sites were monitored over periods of 6 to 29 years, and analysed to describe phenology at the continental level. To study phenology we used Fourier analysis to identify the dominant cycles of flowering and fruiting for each individual tree and we identified the time of year African trees bloom and bear fruit and their relationship to local seasonality. Reproductive strategies were diverse and no single regular cycle was found in >50% of individuals across all 12 sites. Additionally, we found annual flowering and fruiting cycles to be the most common. Sub-annual cycles were the next most common for flowering whereas supra-annual patterns were the next most common for fruiting. We also identify variation in different subsets of species, with species exhibiting mainly annual cycles most common in West and West-Central African tropical forests, while more species at sites in East-Central and Eastern African forests showed cycles ranging from sub-annual to supra-annual. Despite many trees showing strong seasonality, at most sites some flowering and fruiting occurred all year round. Environmental factors with annual cycles are likely to be important drivers of seasonal periodicity in trees across Africa, but proximate triggers are unlikely to be constant across the continen

Disentangling risks to an endangered fish: using a state-space life cycle model to separate natural mortality from anthropogenic losses

State-space population models are becoming a common tool to guide natural resource management, because they address the statistical challenges arising from high observation error and process variation while improving inference by integrating multiple, disparate datasets. A hierarchical state-space life cycle model was developed, motivated by delta smelt (Hypomesus transpacificus), an estuarine fish experiencing simultaneous risks of entrainment mortality from out-of-basin water export and natural mortality. Notable model features included a covariate-dependent instantaneous rates formulation of survival, allowing estimation of multiple sources of mortality, and inclusion of relative observation bias parameters, allowing integration of differently scaled abundance indices and entrainment estimates. Simulation testing confirmed that two sources of mortality, process variation, and data integration parameters could be estimated. Delta smelt entrainment mortality was associated with environmental conditions used to manage entrainment, and recruitment and natural mortality were related to temperature, outflow, food, and predators. Although entrainment mortality was reduced in recent years, ecosystem conditions did not appear to support robust spawning or over-summer survival of new recruits, manifesting as a 98% reduction of adults during 1995-2015.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Likelihood ridges and multimodality in population growth rate models

A central problem in population ecology is to use time series data to estimate the form of density dependence in the per capita growth rate (pgr). This is often accomplished with phenomenological models such as the theta-Ricker or generalized Beverton-Holt. Using the theta-Ricker model as a simple but flexible description of density dependence, we apply theory and simulations to show how multimodality and ridges in the likelihood surface can emerge even in the absence of model misspecification or observation error. The message for model fitting of real data is to consider the likelihood surface in detail, check whether the bestfit model is located on a likelihood ridge and, if so, evaluate predictive differences of biologically plausible models along the ridge. We present a detailed analysis of a focal data set showing how multimodality and ridges emerge in practice for fits of several parametric models, including a state–space model with explicit accommodation of observation error. Best-fit models for these data are biologically dubious beyond the range of the data, and likelihood ratio confidence regions include a wide range of more biologically plausible models. We demonstrate the broad relevance of these findings by presenting analyses of 25 additional data sets spanning a wide range of taxa. The results here are relevant to information-theoretic and Bayesian methods, which also rely on likelihoods. Beyond presentation of best-fit models and confidence regions around individual parameters, effort toward understanding features of the likelihood surface will help ensure the most robust translation from statistical analysis to biological interpretation

From moonlight to movement and synchronized randomness : Fourier and wavelet analyses of animal location time series data

High-resolution animal location data are increasingly available, requiring analytical approaches and statistical tools that can accommodate the temporal structure and transient dynamics (non-stationarity) inherent in natural systems. Traditional analyses often assume uncorrelated or weakly correlated temporal structure in the velocity (net displacement) time series constructed using sequential location data. We propose that frequency and time–frequency domain methods, embodied by Fourier and wavelet transforms, can serve as useful probes in early investigations of animal movement data, stimulating new ecological insight and questions. We introduce a novel movement model with time-varying parameters to study these methods in an animal movement context. Simulation studies show that the spectral signature given by these methods provides a useful approach for statistically detecting and characterizing temporal dependency in animal movement data. In addition, our simulations provide a connection between the spectral signatures observed in empirical data with null hypotheses about expected animal activity. Our analyses also show that there is not a specific one-to-one relationship between the spectral signatures and behavior type and that departures from the anticipated signatures are also informative. Box plots of net displacement arranged by time of day and conditioned on common spectral properties can help interpret the spectral signatures of empirical data. The first case study is based on the movement trajectory of a lion (Panthera leo) that shows several characteristic daily activity sequences, including an active–rest cycle that is correlated with moonlight brightness. A second example based on six pairs of African buffalo (Syncerus caffer) illustrates the use of wavelet coherency to show that their movements synchronize when they are within ;1 km of each other, even when individual movement was best described as an uncorrelated random walk, providing an important spatial baseline of movement synchrony and suggesting that local behavioral cues play a strong role in driving movement patterns. We conclude with a discussion about the role these methods may have in guiding appropriately flexible probabilistic models connecting movement with biotic and abiotic covariates

Appendix A. Further discussion on the theta-Ricker and generalized Beverton-Holt density-dependent models, a complete description of likelihood equations and methods of parameter estimation, elaboration on the simulation experiment, additional analyses of the Accipiter nisus data set, TRPN best-fit and ALT models for 25 additional time series from the GPDD, and a presentation of the joint profile likelihood surface of a Columba oenas data set for comparison with Bayesian posterior densities.

Further discussion on the theta-Ricker and generalized Beverton-Holt density-dependent models, a complete description of likelihood equations and methods of parameter estimation, elaboration on the simulation experiment, additional analyses of the Accipiter nisus data set, TRPN best-fit and ALT models for 25 additional time series from the GPDD, and a presentation of the joint profile likelihood surface of a Columba oenas data set for comparison with Bayesian posterior densities

A framework for understanding the architecture of collective movements using pairwise analyses of animal movement data

The study of collective or group-level movement patterns can provide insight regarding the socio-ecological interface, the evolution of self-organization and mechanisms of inter-individual information exchange. The suite of drivers influencing coordinated movement trajectories occur across scales, resulting from regular annual, seasonal and circadian stimuli and irregular intra- or interspecific interactions and environmental encounters acting on individuals. Here, we promote a conceptual framework with an associated statistical machinery to quantify the type and degree of synchrony, spanning absence to complete, in pairwise movements. The application of this framework offers a foundation for detailed understanding of collective movement patterns and causes. We emphasize the use of Fourier and wavelet approaches of measuring pairwise movement properties and illustrate them with simulations that contain different types of complexity in individual movement, correlation in movement stochasticity, and transience in movement relatedness. Application of this framework to movements of free-ranging African elephants (Loxodonta africana) provides unique insight on the separate roles of sociality and ecology in the fission–fusion society of these animals, quantitatively characterizing the types of bonding that occur at different levels of social relatedness in a movement context. We conclude with a discussion about expanding this framework to the context of larger (greater than three) groups towards understanding broader population and interspecific collective movement patterns and their mechanisms