Panarchy: opportunities and challenges for ecosystem management

Addressing unexpected events and uncertainty represents one of the grand challenges of the Anthropocene, yet ecosystem management is constrained by existing policy and laws that were not formulated to deal with today's accelerating rates of environmental change. In many cases, managing for simple regulatory standards has resulted in adverse outcomes, necessitating innovative approaches for dealing with complex social–ecological problems. We highlight a project in the US Great Plains where panarchy – a conceptual framework that emerged from resilience – was implemented at project onset to address the continued inability to halt large‐scale transition from grass‐to‐tree dominance in central North America. We review how panarchy was applied, the initial outcomes and evidence for policy reform, and the opportunities and challenges for which it could serve as a useful model to contrast with traditional ecosystem management approaches

Integrating Multiple Biomarkers of Fish Health: A Case Study of Fish Health in Ports

Biomarkers of fish health are recognised as valuable biomonitoring tools that inform on the impact of pollution on biota. The integration of a suite of biomarkers in a statistical analysis that better illustrates the effects of exposure to xenobiotics on living organisms is most informative; however, most published ecotoxicological studies base the interpretation of results on individual biomarkers rather than on the information they carry as a set. To compare the interpretation of results from individual biomarkers with an interpretation based on multivariate analysis, a case study was selected where fish health was examined in two species of fish captured in two ports located in Western Australia. The suite of variables selected included chemical analysis of white muscle, body condition index, liver somatic index (LSI), hepatic ethoxyresorufin-O-deethylase activity, serum sorbitol dehydrogenase activity, biliary polycyclic aromatic hydrocarbon metabolites, oxidative DNA damage as measured by serum 8-oxo-dG, and stress protein HSP70 measured on gill tissue. Statistical analysis of individual biomarkers suggested little consistent evidence of the effects of contaminants on fish health. However, when biomarkers were integrated as a set by principal component analysis, there was evidence that the health status of fish in Fremantle port was compromised mainly due to increased LSI and greater oxidative DNA damage in fish captured within the port area relative to fish captured at a remote site. The conclusions achieved using the integrated set of biomarkers show the importance of viewing biomarkers of fish health as a set of variables rather than as isolated biomarkers of fish health

Accuracy of Using Visual Identification of White Sharks to Estimate Residency Patterns

Determining the residency of an aquatic species is important but challenging and it remains unclear what is the best sampling methodology. Photo-identification has been used extensively to estimate patterns of animals' residency and is arguably the most common approach, but it may not be the most effective approach in marine environments. To examine this, in 2005, we deployed acoustic transmitters on 22 white sharks (Carcharodon carcharias) in Mossel Bay, South Africa to quantify the probability of detecting these tagged sharks by photo-identification and different deployment strategies of acoustic telemetry equipment. Using the data collected by the different sampling approaches (detections from an acoustic listening station deployed under a chumming vessel versus those from visual sightings and photo-identification), we quantified the methodologies' probability of detection and determined if the sampling approaches, also including an acoustic telemetry array, produce comparable results for patterns of residency. Photo-identification had the lowest probability of detection and underestimated residency. The underestimation is driven by various factors primarily that acoustic telemetry monitors a large area and this reduces the occurrence of false negatives. Therefore, we propose that researchers need to use acoustic telemetry and also continue to develop new sampling approaches as photo-identification techniques are inadequate to determine residency. Using the methods presented in this paper will allow researchers to further refine sampling approaches that enable them to collect more accurate data that will result in better research and more informed management efforts and policy decisions

Increasing the Depth of Current Understanding: Sensitivity Testing of Deep-Sea Larval Dispersal Models for Ecologists

Larval dispersal is an important ecological process of great interest to conservation and the establishment of marine protected areas. Increasing numbers of studies are turning to biophysical models to simulate dispersal patterns, including in the deep-sea, but for many ecologists unassisted by a physical oceanographer, a model can present as a black box. Sensitivity testing offers a means to test the models' abilities and limitations and is a starting point for all modelling efforts. The aim of this study is to illustrate a sensitivity testing process for the unassisted ecologist, through a deep-sea case study example, and demonstrate how sensitivity testing can be used to determine optimal model settings, assess model adequacy, and inform ecological interpretation of model outputs. Five input parameters are tested (timestep of particle simulator (TS), horizontal (HS) and vertical separation (VS) of release points, release frequency (RF), and temporal range (TR) of simulations) using a commonly employed pairing of models. The procedures used are relevant to all marine larval dispersal models. It is shown how the results of these tests can inform the future set up and interpretation of ecological studies in this area. For example, an optimal arrangement of release locations spanning a release area could be deduced; the increased depth range spanned in deep-sea studies may necessitate the stratification of dispersal simulations with different numbers of release locations at different depths; no fewer than 52 releases per year should be used unless biologically informed; three years of simulations chosen based on climatic extremes may provide results with 90% similarity to five years of simulation; and this model setup is not appropriate for simulating rare dispersal events. A step-by-step process, summarising advice on the sensitivity testing procedure, is provided to inform all future unassisted ecologists looking to run a larval dispersal simulation

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

for the ANZICS Centre for Outcome and Resource Evaluation (CORE) of the Australian and New Zealand Intensive Care Society (ANZICS)BACKGROUND Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. METHODS Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. RESULTS The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag ₄₀ and 35% had autocorrelation through to lag ₄₀; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. CONCLUSIONS The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.John L Moran, Patricia J Solomo

EBV Tegument Protein BNRF1 Disrupts DAXX-ATRX to Activate Viral Early Gene Transcription

Productive infection by herpesviruses involve the disabling of host-cell intrinsic defenses by viral encoded tegument proteins. Epstein-Barr Virus (EBV) typically establishes a non-productive, latent infection and it remains unclear how it confronts the host-cell intrinsic defenses that restrict viral gene expression. Here, we show that the EBV major tegument protein BNRF1 targets host-cell intrinsic defense proteins and promotes viral early gene activation. Specifically, we demonstrate that BNRF1 interacts with the host nuclear protein Daxx at PML nuclear bodies (PML-NBs) and disrupts the formation of the Daxx-ATRX chromatin remodeling complex. We mapped the Daxx interaction domain on BNRF1, and show that this domain is important for supporting EBV primary infection. Through reverse transcription PCR and infection assays, we show that BNRF1 supports viral gene expression upon early infection, and that this function is dependent on the Daxx-interaction domain. Lastly, we show that knockdown of Daxx and ATRX induces reactivation of EBV from latently infected lymphoblastoid cell lines (LCLs), suggesting that Daxx and ATRX play a role in the regulation of viral chromatin. Taken together, our data demonstrate an important role of BNRF1 in supporting EBV early infection by interacting with Daxx and ATRX; and suggest that tegument disruption of PML-NB-associated antiviral resistances is a universal requirement for herpesvirus infection in the nucleus

The Worker Honeybee Fat Body Proteome Is Extensively Remodeled Preceding a Major Life-History Transition

Honeybee workers are essentially sterile female helpers that make up the majority of individuals in a colony. Workers display a marked change in physiology when they transition from in-nest tasks to foraging. Recent technological advances have made it possible to unravel the metabolic modifications associated with this transition. Previous studies have revealed extensive remodeling of brain, thorax, and hypopharyngeal gland biochemistry. However, data on changes in the abdomen is scarce. To narrow this gap we investigated the proteomic composition of abdominal tissue in the days typically preceding the onset of foraging in honeybee workers

Cloître, Cathedral of the Blessed Virgin Mary, Lincoln, ca 1250

Photographie: Hartill Art Associates. AUk-0620; Date du début des travaux de réalisation : Ca 1250

Engraved portrait of William Hamilton, second duke of Hamilton (1616–1651)

Engraved portrait of William Hamilton, second duke of Hamilton (1616–1651). Line engraving by James Stow after Samuel Cooper. Titled: 'William, Duke of Hamilton, Ob. 1651. From an original in the Collection of William Smith Esqr. at Chelsea.