Dynamic occupancy models for analyzing species' range dynamics across large geographic scales

Large‐scale biodiversity data are needed to predict species' responses to global change and to address basic questions in macroecology. While such data are increasingly becoming available, their analysis is challenging because of the typically large heterogeneity in spatial sampling intensity and the need to account for observation processes. Two further challenges are accounting for spatial effects that are not explained by covariates, and drawing inference on dynamics at these large spatial scales. We developed dynamic occupancy models to analyze large‐scale atlas data. In addition to occupancy, these models estimate local colonization and persistence probabilities. We accounted for spatial autocorrelation using conditional autoregressive models and autologistic models. We fitted the models to detection/nondetection data collected on a quarter‐degree grid across southern Africa during two atlas projects, using the hadeda ibis (Bostrychia hagedash) as an example. The model accurately reproduced the range expansion between the first (SABAP1: 1987–1992) and second (SABAP2: 2007–2012) Southern African Bird Atlas Project into the drier parts of interior South Africa. Grid cells occupied during SABAP1 generally remained occupied, but colonization of unoccupied grid cells was strongly dependent on the number of occupied grid cells in the neighborhood. The detection probability strongly varied across space due to variation in effort, observer identity, seasonality, and unexplained spatial effects. We present a flexible hierarchical approach for analyzing grid‐based atlas data using dynamical occupancy models. Our model is similar to a species' distribution model obtained using generalized additive models but has a number of advantages. Our model accounts for the heterogeneous sampling process, spatial correlation, and perhaps most importantly, allows us to examine dynamic aspects of species ranges.     

Band reporting rates of waterfowl: does individual heterogeneity bias estimated survival rates?

In capture–recapture studies, the estimation accuracy of demographic parameters is essential to the efficacy of management of hunted animal populations. Dead recovery models based upon the reporting of rings or bands are often used for estimating survival of waterfowl and other harvested species. However, distance from the ringing site or condition of the bird may introduce substantial individual heterogeneity in the conditional band reporting rates (r), which could cause bias in estimated survival rates (S) or suggest nonexistent individual heterogeneity in S. To explore these hypotheses, we ran two sets of simulations (n = 1000) in MARK using Seber''s dead recovery model, allowing time variation on both S and r. This included a series of heterogeneity models, allowing substantial variation on logit(r), and control models with no heterogeneity. We conducted simulations using two different values of S: S = 0.60, which would be typical of dabbling ducks such as mallards (Anas platyrhynchos), and S = 0.80, which would be more typical of sea ducks or geese. We chose a mean reporting rate on the logit scale of −1.9459 with SD = 1.5 for the heterogeneity models (producing a back-transformed mean of 0.196 with SD = 0.196, median = 0.125) and a constant reporting rate for the control models of 0.196. Within these sets of simulations, estimation models where σ_S = 0 and σ_S > 0 (σ_S is SD of individual survival rates on the logit scale) were incorporated to investigate whether real heterogeneity in r would induce apparent individual heterogeneity in S. Models where σ_S = 0 were selected approximately 91% of the time over models where σ_S > 0. Simulation results showed < 0.05% relative bias in estimating survival rates except for models estimating σ_S > 0 when true S = 0.8, where relative bias was a modest 0.5%. These results indicate that considerable variation in reporting rates does not cause major bias in estimated survival rates of waterfowl, further highlighting the robust nature of dead recovery models that are being used for the management of harvested species.     

Neogene origins and implied warmth tolerance of Amazon tree species

Tropical rain forest has been a persistent feature in South America for at least 55 million years. The future of the contemporary Amazon forest is uncertain, however, as the region is entering conditions with no past analogue, combining rapidly increasing air temperatures, high atmospheric carbon dioxide concentrations, possible extreme droughts, and extensive removal and modification by humans. Given the long‐term Cenozoic cooling trend, it is unknown whether Amazon forests can tolerate air temperature increases, with suggestions that lowland forests lack warm‐adapted taxa, leading to inevitable species losses. In response to this uncertainty, we posit a simple hypothesis: the older the age of a species prior to the Pleistocene, the warmer the climate it has previously survived, with Pliocene (2.6–5 Ma) and late‐Miocene (8–10 Ma) air temperature across Amazonia being similar to 2100 temperature projections under low and high carbon emission scenarios, respectively. Using comparative phylogeographic analyses, we show that 9 of 12 widespread Amazon tree species have Pliocene or earlier lineages (>2.6 Ma), with seven dating from the Miocene (>5.6 Ma) and three >8 Ma. The remarkably old age of these species suggest that Amazon forests passed through warmth similar to 2100 levels and that, in the absence of other major environmental changes, near‐term high temperature‐induced mass species extinction is unlikely.     

Not looking where you are leaping: a novel method of oriented travel in the caterpillar Calindoea trifascialis (Moore) (Lepidoptera: Thyrididae)

The prepupation caterpillar of the Southeast Asian moth Calindoea trifascialis constructs a leaf shelter that jumps across the ground using a jumping method novel among the insects. We found that movement path direction was correlated to the direction opposite to the most intense light. Correlated random walk (CRW) analyses found net squared displacements higher than predicted by a CRW, and fractal dimension analysis indicated straighter paths at large spatial scales. Rearing experiments showed high mortality from predation on the ground, but higher mortality resulted from sun exposure. We interpret jumping path orientation as an efficient search strategy to find shade in a variable landscape, given limited perception, in the presence of overheating and desiccation risks.     

Fungal disease incidence along tree diversity gradients depends on latitude in European forests

European forests host a diversity of tree species that are increasingly threatened by fungal pathogens, which may have cascading consequences for forest ecosystems and their functioning. Previous experimental studies suggest that foliar and root pathogen abundance and disease severity decrease with increasing tree species diversity, but evidences from natural forests are rare. Here, we tested whether foliar fungal disease incidence was negatively affected by tree species diversity in different forest types across Europe. We measured the foliar fungal disease incidence on 16 different tree species in 209 plots in six European countries, representing a forest‐type gradient from the Mediterranean to boreal forests. Forest plots of single species (monoculture plots) and those with different combinations of two to five tree species (mixed species plots) were compared. Specifically, we analyzed the influence of tree species richness, functional type (conifer vs. broadleaved) and phylogenetic diversity on overall fungal disease incidence. The effect of tree species richness on disease incidence varied with latitude and functional type. Disease incidence tended to increase with tree diversity, in particular in northern latitudes. Disease incidence decreased with tree species richness in conifers, but not in broadleaved trees. However, for specific damage symptoms, no tree species richness effects were observed. Although the patterns were weak, susceptibility of forests to disease appears to depend on the forest site and tree type.     

Does stream flow structure woody riparian vegetation in subtropical catchments?

The primary objective of this study was to test the relevance of hydrological classification and class differences to the characteristics of woody riparian vegetation in a subtropical landscape in Queensland, Australia. We followed classification procedures of the environmental flow framework ELOHA – Ecological Limits of Hydrologic Alteration. Riparian surveys at 44 sites distributed across five flow classes recorded 191 woody riparian species and 15, 500 individuals. There were differences among flow classes for riparian species richness, total abundance, and abundance of regenerating native trees and shrubs. There were also significant class differences in the occurrence of three common tree species, and 21 indicator species (mostly native taxa) further distinguished the vegetation characteristics of each flow class. We investigated the influence of key drivers of riparian vegetation structure (climate, depth to water table, stream‐specific power, substrate type, degree of hydrologic alteration, and land use) on riparian vegetation. Patterns were explained largely by climate, particularly annual rainfall and temperature. Strong covarying drivers (hydrology and climate) prevented us from isolating the independent influences of these drivers on riparian assemblage structure. The prevalence of species considered typically rheophytic in some flow classes implies a more substantial role for flow in these classes but needs further testing. No relationships were found between land use and riparian vegetation composition and structure. This study demonstrates the relevance of flow classification to the structure of riparian vegetation in a subtropical landscape, and the influence of covarying drivers on riparian patterns. Management of environmental flows to influence riparian vegetation assemblages would likely have most potential in sites dominated by rheophytic species where hydrological influences override other controls. In contrast, where vegetation assemblages are dominated by a diverse array of typical rainforest species, and other factors including broad‐scale climatic gradients and topographic variables have greater influence than hydrology, riparian vegetation is likely to be less responsive to environmental flow management.     

Accounting for host cell protein behavior in anion‐exchange chromatography

Host cell proteins (HCP) are a problematic set of impurities in downstream processing (DSP) as they behave most similarly to the target protein during separation. Approaching DSP with the knowledge of HCP separation behavior would be beneficial for the production of high purity recombinant biologics. Therefore, this work was aimed at characterizing the separation behavior of complex mixtures of HCP during a commonly used method: anion‐exchange chromatography (AEX). An additional goal was to evaluate the performance of a statistical methodology, based on the characterization data, as a tool for predicting protein separation behavior. Aqueous two‐phase partitioning followed by two‐dimensional electrophoresis provided data on the three physicochemical properties most commonly exploited during DSP for each HCP: pI (isoelectric point), molecular weight, and surface hydrophobicity. The protein separation behaviors of two alternative expression host extracts (corn germ and E. coli) were characterized. A multivariate random forest (MVRF) statistical methodology was then applied to the database of characterized proteins creating a tool for predicting the AEX behavior of a mixture of proteins. The accuracy of the MVRF method was determined by calculating a root mean squared error value for each database. This measure never exceeded a value of 0.045 (fraction of protein populating each of the multiple separation fractions) for AEX. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1453–1463, 2016     

Tree Height Reduction After Selective Logging in a Tropical Forest

By harvesting scattered large trees, selective logging increases light availability and thereby stimulates growth and crown expansion at early‐life stage among remnant trees. We assessed the effects of logging on total and merchantable bole (i.e., lowest branch at crown base) heights on 952 tropical canopy trees in French Guiana. We observed reductions in both total (mean, ?2.3 m) and bole (mean, ?2.0 m) heights more than a decade after selective logging. Depending on local logging intensity, height reductions resulted in 2–13 percent decreases in aboveground tree biomass and 3–17 percent decreases in bole volume. These results highlight the adverse effects of logging at both tree and stand levels. This decrease in height is a further threat to future provision of key environmental services, such as timber production and carbon sequestration.     

Generalist Species Have a Central Role In a Highly Diverse Plant–Frugivore Network

Analysis of plant–frugivore interactions provides a quantitative framework for integrating community structure and ecosystem function in terms of how the roles and attributes of individual species contribute to network structure and resilience. In this study, we used centrality metrics to rank and detect the most important species in a mutualistic network of fruit‐eating birds and plants in a cloud forest in the Colombian Andes. We identified a central core of ten bird and seven plant species in a network of 135 species that perform dual roles as local hubs and connectors. The birds were mostly large forest frugivores, such as cracids, cotingas, and toucans, which consume fruits of all sizes. The plants were species of intermediate successional stages with small‐ to medium‐sized seeds that persist in mature forest or forest borders (e.g., Miconia, Cecropia, Ficus). We found the resilience of our network depends on super‐generalist species, because their elimination makes the network more prone to disassemble than random extinctions, potentially disrupting seed‐dispersal processes. At our study site, extirpation of large frugivores has already been documented, and if this continues, the network might collapse despite its high diversity. Our results suggest that generalist species play critical roles in ecosystem function and should be incorporated into conservation and monitoring programs.     

Land use,fallow period and the recovery of a Caatinga forest

Caatinga vegetation continues to be converted into mosaics of secondary forest stands, but the affect of this process on biodiversity has not yet been examined. We used 35 regenerating and old‐growth stands of Caatinga to examine the recovery of plant assemblages subsequent to slash‐and‐burn agriculture and cattle ranching/pasture in northeastern Brazil. Plant assemblages were contrasted in terms of community structure (stem density/basal area/species richness/diversity), functional (leaf habit/reproductive traits) and taxonomic composition. Soil attributes were also examined to infer potential drivers for cross‐habitat differences. As expected, plant assemblages clearly differed across a large set of community‐level attributes, including all trait categories relative to leaf habit and reproduction (pollination syndrome/floral color, size, type). Overall, old‐growth forest stands supported distinct and more diverse assemblages at the plot and habitat level; e.g., long‐lived tree species were almost exclusively found in old‐growth forest stands. For most attributes, plant assemblages subsequent to pasture exhibited intermediate values between those exhibited by old‐growth forest and those of agriculture‐related stands. Surprisingly, soils exhibited similar fertility‐related scores across habitats. Our results indicate that: (1) sprouting/resprouting represents an important mechanism of forest regeneration; (2) assemblage‐level attributes suggest recovery at distinct rates; (3) forest regeneration implies community‐level changes in both vegetative and reproductive functional attributes, including directional changes; (4) Caatinga is not able to completely recover in a period of 15‐yr following land abandonment; and (5) historical land use affects recovery rates and successional pathways/taxonomic trajectories. Seasonally dry tropical forests may intrinsically cover a wide range of patterns relative to successional model, recovery rates and successional pathways.