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With the expansion in the quantity and types of biodiversity data being collected, there is a need to find ways to combine these different sources to provide cohesive summaries of species' potential and realized distributions in space and time. Recently, model-based data integration has emerged as a means to achieve this by combining datasets in ways that retain the strengths of each. We describe a flexible approach to data integration using point process models, which provide a convenient way to translate across ecological currencies. We highlight recent examples of large-scale ecological models based on data integration and outline the conceptual and technical challenges and opportunities that arise., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Bird ring-recovery data have been widely used to estimate demographic parameters such as survival probabilities since the mid-20th century. However, while the total number of birds ringed each year is usually known, historical information on age at ringing is often not available. A standard ring-recovery model, for which information on age at ringing is required, cannot be used when historical data are incomplete. We develop a new model to estimate age-dependent survival probabilities from such historical data when age at ringing is not recorded; we call this the historical data model. This new model provides an extension to the model of Robinson, 2010, Ibis, 152, 651-795 by estimating the proportion of the ringed birds marked as juveniles as an additional parameter. We conduct a simulation study to examine the performance of the historical data model and compare it with other models including the standard and conditional ring-recovery models. Simulation studies show that the approach of Robinson, 2010, Ibis, 152, 651-795 can cause bias in parameter estimates. In contrast, the historical data model yields similar parameter estimates to the standard model. Parameter redundancy results show that the newly developed historical data model is comparable to the standard ring-recovery model, in terms of which parameters can be estimated, and has fewer identifiability issues than the conditional model. We illustrate the new proposed model using Blackbird and Sandwich Tern data. The new historical data model allows us to make full use of historical data and estimate the same parameters as the standard model with incomplete data, and in doing so, detect potential changes in demographic parameters further back in time.

Due to concerns over negative impacts on insect pollinators, the European Union has implemented a moratorium on the use of three neonicotinoid pesticide seed dressings for mass-flowering crops. We assessed the effectiveness of this policy in reducing the exposure risk to honeybees by collecting 130 samples of honey from bee keepers across the UK before (2014: N = 21) and after the moratorium was in effect (2015: N = 109). Neonicotinoids were present in about half of the honey samples taken before the moratorium, and they were present in over a fifth of honey samples following the moratorium. Clothianidin was the most frequently detected neonicotinoid. Neonicotinoid concentrations declined from May to September in the year following the ban. However, the majority of post-moratorium neonicotinoid residues were from honey harvested early in the year, coinciding with oilseed rape flowering. Neonicotinoid concentrations were correlated with the area of oilseed rape surrounding the hive location. These results suggest mass flowering crops may contain neonicotinoid residues where they have been grown on soils contaminated by previously seed treated crops. This may include winter seed treatments applied to cereals that are currently exempt from EU restrictions. Although concentrations of neonicotinoids were low (<2.0 ng g-1), and posed no risk to human health, they may represent a continued risk to honeybees through long-term chronic exposure.

Insect pollinators such as bumblebees (Bombus spp.) are in global decline. A major cause of this decline is habitat loss due to agricultural intensification. A range of global and national initiatives aimed at restoring pollinator habitats and populations have been developed. However, the success of these initiatives depends critically upon understanding how landscape change affects key population-level parameters, such as survival between lifecycle stages, in target species. This knowledge is lacking for bumblebees, because of the difficulty of systematically finding and monitoring colonies in the wild. We used a combination of habitat manipulation, land-use and habitat surveys, molecular genetics and demographic and spatial modelling to analyse between-year survival of family lineages in field populations of three bumblebee species. Here we show that the survival of family lineages from the summer worker to the spring queen stage in the following year increases significantly with the proportion of high-value foraging habitat, including spring floral resources, within 250-1,000 m of the natal colony. This provides evidence for a positive impact of habitat quality on survival and persistence between successive colony cycle stages in bumblebee populations. These findings also support the idea that conservation interventions that increase floral resources at a landscape scale and throughout the season have positive effects on wild pollinators in agricultural landscapes.

Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species' range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen scientists.

Integrated population models (IPMs) combine data on different aspects of demography with time-series of population abundance. IPMs are becoming increasingly popular in the study of wildlife populations, but their application has largely been restricted to the analysis of single species. However, species exist within communities: sympatric species are exposed to the same abiotic environment, which may generate synchrony in the fluctuations of their demographic parameters over time. Given that in many environments conditions are changing rapidly, assessing whether species show similar demographic and population responses is fundamental to quantifying interspecific differences in environmental sensitivity and highlighting ecological interactions at risk of disruption. In this paper, we combine statistical approaches to study populations, integrating data along two different dimensions: across species (using a recently proposed framework to quantify multi-species synchrony in demography) and within each species (using IPMs with demographic and abundance data). We analyse data from three seabird species breeding at a nationally important long-term monitoring site. We combine demographic datasets with island-wide population counts to construct the first multi-species Integrated Population Model to consider synchrony. Our extension of the IPM concept allows the simultaneous estimation of demographic parameters, adult abundance and multi-species synchrony in survival and productivity, within a robust statistical framework. The approach is readily applicable to other taxa and habitats. Supplementary materials accompanying this paper appear on-line., Electronic Supplementary Material: Supplementary materials for this article are available at 10.1007/s13253-017-0279-4., (© The Author(s) 2017.)

At a time of climate change and major loss of biodiversity, it is important to have efficient tools for monitoring populations. In this context, animal abundance indices play an important rôle. In producing indices for invertebrates, it is important to account for variation in counts within seasons. Two new methods for describing seasonal variation in invertebrate counts have recently been proposed; one is nonparametric, using generalized additive models, and the other is parametric, based on stopover models. We present a novel generalized abundance index which encompasses both parametric and nonparametric approaches. It is extremely efficient to compute this index due to the use of concentrated likelihood techniques. This has particular relevance for the analysis of data from long-term extensive monitoring schemes with records for many species and sites, for which existing modeling techniques can be prohibitively time consuming. Performance of the index is demonstrated by several applications to UK Butterfly Monitoring Scheme data. We demonstrate the potential for new insights into both phenology and spatial variation in seasonal patterns from parametric modeling and the incorporation of covariate dependence, which is relevant for both monitoring and conservation. Associated R code is available on the journal website., (© 2016 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.)

With environmental conditions changing rapidly, there is a need to move beyond single-species models and consider how communities respond to environmental drivers. We present a modeling approach that allows estimation of multispecies synchrony in productivity, or its components, and the contribution of environmental covariates as synchronizing and desynchronizing agents. We apply the model to long-term breeding success data for five seabird species at a North Atlantic colony. Our Bayesian analysis reveals varying degrees of synchrony in overall productivity, with a common signal indicating a significant decline in productivity between 1986 and 2009. Productivity in seabirds reflects conditions in the marine ecosystem so the estimated synchronous component is a useful indicator of local marine environment health. For the two species for which we have most data, the environmental contribution to overall productivity synchrony is driven principally by effects operating at the chick stage rather than during incubation. Our results emphasize the importance of studying together species that coexist in a community. The framework, which accommodates interspecific clutch-size variation, is readily applicable to any species assemblage in any ecosystem where long-term productivity data are available.

Objectives: The 1983 US Orphan Drug Act (ODA) provided incentives to stimulate treatment product development for patients with rare disease. This article highlights a decade of ODA contributions to this goal for children with RDs., Methods: An internal US Food and Drug Administration database was the information source for orphan designations, marketing approvals, and prevalence numbers for 2000 to 2009. Product categorization was based on the disease age of onset for which they received designation. Category 1 products were for diseases with onset exclusively in Childhood; Category 2 products were for diseases with onset at any age; and Category 3 products were for diseases with adult onset only. Disease prevalence distributions were analyzed by using population intervals of 20 000., Results: From 2000 to 2009, 1138 orphan drugs were designated and 148 received marketing approval, of which 38 (26%) were for pediatric diseases. The proportion of approvals for pediatric products increased from 17.5% (10 of 57) in the first half of the decade, to 30.8% (28 of 91) in the second. More products received designation and marketing approval for pediatric diseases with prevalence numbers fewer than 20 000 than for any other prevalence subgroup. The median disease prevalence for all pediatric orphan designations that received marketing approval was 8972. Among the pediatric orphan drug approvals categorized by therapeutic class, the endocrine/metabolic drugs had the largest representation (39%)., Conclusions: The ODA incentives have led to increased product availability for RDs overall, with an increasing number of marketing approvals for children this past decade.

Fungal entomopathogens are ubiquitous within the environment and susceptible insects are predicted to be under strong selection pressure to detect and avoid virulent isolates. Beauveria bassiana is an entomopathogenic fungus with a wide host range including coccinellids. Seven-spot ladybirds, Coccinella septempunctata, overwinter predominantly in leaf litter and B. bassiana is one of their major mortality factors during winter in temperate regions. Behavioural assays were conducted to assess the ability of adult C. septempunctata to avoid lethal densities of B. bassiana conidia in soil or on leaves. Further assays considered avoidance by C. septempunctata of mycosed (B. bassiana) C. septempunctata cadavers compared with uninfected C. septempunctata cadavers or in vitro B. bassiana. Treatments in any bioassays entirely avoided by C. septempunctata were regarded as censored data, to overcome the difficulties associated with zeros in log-ratio analyses. Male and female C. septempunctata avoided contact with leaf surfaces and soil inoculated with B. bassiana and mycosed cadavers. The ability of C. septempunctata to detect and avoid B. bassiana conidia is an adaptation that undoubtedly increases survival and ultimately fitness. We predict that such behavioural responses are widespread and driven by the high cost of fungal infection to a host., (© 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.)

The global decline of insect pollinators, especially bees, is cause for concern, and there is an urgent need for cost-effective conservation measures in agricultural landscapes. While landscape context and habitat quality are known to influence species richness and abundance of bees, there is a lack of evidence from manipulative field experiments on bees' responses to adaptive management across differently structured landscapes. We present the results of a large-scale study that investigated the effects of a targeted agri-environment scheme (AES) on bumble bees (Bombus spp.) over three years in the United Kingdom. Forage patches of different sizes were sown with a conservation flower mixture across eight sites covering a broad range of agricultural land use types. Species richness and worker densities (especially of the longer-tongued Bombus species for which the mixture was targeted) were significantly higher on sown forage patches than on existing non-crop control habitats throughout the three-year study, but the strength of this response depended on both the proportions of arable land and abundance of herbaceous forb species in the surrounding landscape. The size of sown patches also affected worker density, with smaller patches (0.25 ha) attracting higher densities of some species than larger patches (1.0 ha). Our models show that a targeted AES can deliver greater net benefits in more intensively farmed areas, in terms of the number and species richness of bumble bees supported, than in heterogeneous landscapes where other foraging habitats exist. These findings serve to strengthen the evidence base for extending agri-environment schemes to boost declining pollinator populations to a larger number of agricultural landscapes across the globe.

Many neurological diseases or conditions are rare disorders. The Orphan Drug Act (ODA) of 1983 was promulgated to promote the development of products for such conditions. In this Opinion piece, we discuss how the ODA has affected neurological diseases, note how current and future sponsors (any person(s) or entity (i.e., academic, corporate body, individual, manufacturer) that applies for an official regulatory action) of products for rare neurological diseases can take advantage of ODA incentives, identify areas of success and continuing needs, and review data that can help drive the future development of products for rare neurological conditions.

The Orphan Drug Act encourages the development of products for rare diseases and conditions. Many conditions that stand to benefit from stem cell-based products are rare diseases. We address the Orphan Drug Act in relation to the development of stem cell-based products., (Copyright 2010 Elsevier Inc. All rights reserved.)

We have identified the RhoBTB2 putative tumor suppressor gene as a direct target of the E2F1 transcription factor. Overexpression of E2F1 led to up-regulation of RhoBTB2 at the level of mRNA and protein. This also occurred during the induction of E2F1 activity in the presence of cycloheximide, thus indicating that RhoBTB2 is a direct target. RNAi-mediated knockdown of E2F1 resulted in decreased RhoBTB2 protein expression, demonstrating that RhoBTB2 is a physiological target of E2F1. Because E2F1 primarily serves to transcribe genes involved in cell cycle progression and apoptosis, we explored whether RhoBTB2 played roles in either of these processes. We found RhoBTB2 expression highly up-regulated during mitosis, which was partially dependent on the presence of E2F1. Furthermore, overexpression of RhoBTB2 induced a short term increase in cell cycle progression and proliferation, while long term expression had a negative effect on these processes. We similarly found RhoBTB2 up-regulated during drug-induced apoptosis, with this being primarily dependent on E2F1. Finally, we observed that knockdown of RhoBTB2 levels via siRNA delayed the onset of drug-induced apoptosis. Collectively, we describe RhoBTB2 as a novel direct target of E2F1 with roles in cell cycle and apoptosis.

In this article, we consider the U.K. Common Birds Census counts and their use in monitoring bird abundance. We use a state-space modeling approach within a Bayesian framework to describe population level trends over time and contribute to the alert system used by the British Trust for Ornithology. We account for potential overdispersion and excess zero counts by modeling the observation process with a zero-inflated negative binomial, while the system process is described by second-order polynomial growth models. In order to provide a biological motivation for the amount of smoothing applied to the observed series the system variance is related to the demographic characteristics of the species, so as to help the specification of its prior distribution. In particular, the available information on productivity and survival is used to formulate prior expectations on annual percentage changes in the population level and then used to constrain the variance of the system process. We discuss an example of how to interpret alternative choices for the degree of smoothing and how these relate to the classification of species, over time, into conservation lists.

We show how a simple reparameterization can reduce the number of parameters that need to be estimated by numerical maximum likelihood in site occupancy models. Three examples are provided.

A number of methods for joint inference from animal abundance and demographic data have been proposed in recent years, each with its own advantages. A new approach to analyzing panel survey and demographic data simultaneously is described. The approach fits population-dynamics models to the survey data, rather than to a single index of abundance derived from them and thus avoids disadvantages inherent in analyzing such an index. The methodology is developed and illustrated with British Lapwing data, and the results are compared with those obtained from existing approaches. The estimates of demographic parameters and population indices are similar for all methods. The results of a simulation study show that the new method performs well in terms of mean squared error.

E2F1 and E2F4 are known to have opposing roles in cell cycle control. In the present work, we examine the role of both E2F1 and E2F4 in apoptosis induced by three cyclin-dependent kinase inhibitors (roscovitine, BMS-387032, and flavopiridol) as well as by three established chemotherapeutic drugs (VP16, cisplatin and paclitaxel). We find that E2F4 levels are diminished following treatment with cyclin dependent kinase inhibitors (flavopiridol, roscovitine and BMS-387032) or with DNA damaging drugs (cisplatin and VP16). In contrast, each of these drugs induced E2F1. We find that mouse fibroblasts nullizygous for the E2F4 gene are more sensitive to apoptosis induced by roscovitine, flavopiridol, cisplatin, and VP16, whereas E2F1-deficient fibroblasts are less sensitive. Likewise, we find that RNAi-mediated reductions in E2F4 in human cancer cells results in increased drug sensitivity. Taken together, these results support a model in which E2F1 and E2F4 play opposing roles during drug-induced apoptosis.

In studies of wild animals, one frequently encounters both census and mark-recapture-recovery data. We show how a state-space model for census data in combination with the usual multinomial-based models for ring-recovery data provide estimates of productivity not available from either type of data alone. The approach is illustrated on two British bird species. For the lapwing, we calibrate how its recent decline could be due to a decrease in productivity. For the heron, there is no evidence for a decline in productivity, and the combined analysis increases significantly the strength of logistic regressions of survival on winter severity.

Abalone are semimobile marine gastropods that form the basis of Australia's second most valuable fishery. A site off the coast of Port Arthur, Tasmania, was visited on six occasions. On each occasion, any unmarked live abalone found were marked with a unique identification number and were recorded. Any previously marked abalone found had its identification number and whether or not it was still alive recorded. This results in integrated mark-recapture-recovery data, as in Catchpole et al. (1998, Biometrics 54, 33-46). During the study period, abalone grew in size, and we model the survival of individuals as a function of their size, estimated from a fitted growth curve. The shells of dead animals are long lasting, and we extend existing methodology to allow for the possibility that an animal found dead may have been dead but overlooked for several visits.

In this paper we propose a strategy for analysing recovery data from birds ringed as nestlings. The approach advocated starts with a global model, involving calendar year dependence of both reporting and first-year survival rates, and age-dependence of survival rates for older birds. Likelihood ratio tests are then used to choose between a range of submodels. The strategy is illustrated through application to three data sets, on mallards, herring gulls, and blue-winged teal. The effect of age-dependence operating also on reporting rates is examined through matched simulations, since a model with age-dependent reporting rates cannot be fitted directly. This reveals an underestimation of the first-year survival rates, when the probability of recovery for first-year birds is greater than that for older birds. It is argued that this bias may not be serious and indeed may be allowed for in practice. For mallards and teal, comparisons are drawn with the results from other models that additionally analyse recoveries of birds ringed as adults; the same general conclusions are reached.

The effects of cortisol on the inhibition of cell-death processes and suppression of plasminogen-activator (PA) activity during involution of the rat ventral prostate gland were investigated to determine the principal type of PA activated by castration and inhibited by this hormone and whether the mechanism responsible for decreased PA activity involved reductions in enzyme synthesis or increased activity of a PA inhibitor. By using the technique of fibrin-agarose zymography, three bands of PA activity were detected at 4 and 7 days after castration: a major band with a molecular mass of approx. 30 kDa and two minor bands of 48 kDa and 64 kDa. Both the 30 kDa and 48 kDa activities were inhibited with anti-[urokinase-type PA (u-PA)] IgG. The 64 kDa activity was inhibited by anti-[tissue-type PA (t-PA)] IgG. In addition to retarding prostatic involution, daily administration of cortisol to the castrated animals suppressed all three bands of PA activity. A comparison of the pattern of total PA activity and of e.l.i.s.a. estimates of u-PA concentration during the castration-induced rise and after cortisol inhibition indicated a near perfect correlation between the two parameters. Northern-blot analysis using prostatic polyadenylated RNA revealed that the level of u-PA mRNA was highest at 4 and 7 days after castration and that cortisol treatment repressed u-PA mRNA to a level similar to that in non-castrated controls. Neither Northern hybridizations nor reverse zymography detected RNA transcripts or activity corresponding to the PA inhibitor PAI-1 in any of the prostate samples. Western-blot analysis revealed that, although the amount of arginine esterase A, another prostatic proteinase, also increased after castration, the rise in concentration of this protein was not blocked by glucocorticoid administration. Together our findings indicate the following: (1) the predominant form of PA activity induced in the prostate after castration and inhibited by cortisol is a 30 kDa form of u-PA. Although less prominent, t-PA and a 48 kDa form of u-PA follow a similar pattern of induction and inhibition; (2) changes in u-PA activity in response to castration and cortisol treatment are due to alterations in the level of u-PA mRNA and protein rather than in the activity of PAI-1; (3) not all castration-induced proteinases in the prostate are inhibited by cortisol.

The ability of high doses of cortisol to retard the involution process in the rat ventral prostate was related to alterations in the pattern of gene expression. Poly(A)+ RNA preparations from the prostates of noncastrated, castrated, and castrated rats injected daily for 7 days with cortisol were compared by Northern blot hybridizations for the relative expression of genes associated with cell differentiation and maintenance (the C1 prostatic steroid binding protein gene and alpha-tubulin), with cell death (TRPM-2, hsp 70, and c-fos), and with hormone regulation (the androgen and glucocorticoid receptors). As anticipated, the concentration of C1 mRNA in the prostate fell to less than 4% of that in the noncastrated controls within 4 days after castration and was nearly undetectable after 7 days. This decline was retarded by cortisol treatment of 7-day castrated animals which sustained the level of C1 transcripts at approximately 50% of control. While the pattern of expression of alpha-tubulin indicated some minor fluctuations, with the highest level occurring 7 days after castration, the prostates of the cortisol-treated group had essentially the same concentration of this mRNA as the noncastrates. Cortisol also modified the expression of genes associated with prostatic cell death. The large increase in prostatic TRPM-2 mRNA, seen 7 days after castration, was reduced by over 80% after treatment with the glucocorticoid. Although not as abundantly expressed as TRPM-2, the castration-induced levels of transcripts for both hsp 70 and the protooncogene c-fos were substantially reduced by cortisol.(ABSTRACT TRUNCATED AT 250 WORDS)