Christopher L. Merkord

Conserving migratory land birds in the New World: Do we know enough?

Migratory bird needs must be met during four phases of the year: breeding season, fall migration, wintering, and spring migration; thus, management may be needed during all four phases. The bulk of research and management has focused on the breeding season, although several issues remain unsettled, including the spatial extent of habitat influences on fitness and the importance of habitat on the breeding grounds used after breeding. Although detailed investigations have shed light on the ecology and population dynamics of a few avian species, knowledge is sketchy for most species. Replication of comprehensive studies is needed for multiple species across a range of areas, Information deficiencies are even greater during the wintering season, when birds require sites that provide security and food resources needed for survival and developing nutrient reserves for spring migration and, possibly, reproduction. Research is needed on many species simply to identify geographic distributions, wintering sites, habitat use, and basic ecology. Studies are complicated, however, by the mobility of birds and by sexual segregation during winter. Stable-isotope methodology has offered an opportunity to identify linkages between breeding and wintering sites, which facilitates understanding the complete annual cycle of birds. The twice-annual migrations are the poorest-understood events in a birds life. Migration has always been a risky undertaking, with such anthropogenic features as tall buildings, towers, and wind generators adding to the risk. Species such as woodland specialists migrating through eastern North America have numerous options for pausing during migration to replenish nutrients, but some species depend on limited stopover locations. Research needs for migration include identifying pathways and timetables of migration, quality and distribution of habitats, threats posed by towers and other tall structures, and any bottlenecks for migration. Issues such as human population growth, acid deposition, climate change, and exotic diseases are global concerns with uncertain consequences to migratory birds and even less-certain remedies. Despite enormous gaps in our understanding of these birds, research, much of it occurring in the past 30 years, has provided sufficient information to make intelligent conservation efforts but needs to expand to handle future challenges.

Relative roles of temperature and photoperiod as drivers of metabolic flexibility in dark-eyed juncos.

Seasonal phenotypic flexibility in small birds produces a winter phenotype with elevated maximum cold-induced metabolic rates (=summit metabolism, Ṁsum). Temperature and photoperiod are candidates for drivers of seasonal phenotypes, but their relative impacts on metabolic variation are unknown. We examined photoperiod and temperature effects on Ṁsum, muscle masses and activities of key catabolic enzymes in winter dark-eyed juncos (Junco hyemalis). We randomly assigned birds to four treatment groups varying in temperature (cold=3°C; warm=24°C) and photoperiod [short day (SD)=8 h:16 h light:dark; long day (LD)=16 h:8 h light:dark] in a two-by-two design. We measured body mass (Mb), flight muscle width and Ṁsum before and after 3 and 6 weeks of acclimation, and flight muscle and heart masses after 6 weeks. Ṁsum increased for cold-exposed, but not for warm-exposed, birds. LD birds gained more Mb than SD birds, irrespective of temperature. Flight muscle size and mass did not differ significantly among groups, but heart mass was larger in cold-exposed birds. Citrate synthase, carnitine palmitoyl transferase and β-hydroxyacyl Co-A dehydrogenase activities in the pectoralis were generally higher for LD and cold groups. The cold-induced changes in Ṁsum and heart mass parallel winter changes for small birds, but the larger Mb and higher catabolic enzyme activities in LD birds suggest photoperiod-induced changes associated with migratory disposition. Temperature appears to be a primary driver of flexibility in Ṁsum in juncos, but photoperiod-induced changes in Mb and catabolic enzyme activities, likely associated with migratory disposition, interact with temperature to contribute to seasonal phenotypes.

Integrating malaria surveillance with climate data for outbreak detection and forecasting: the EPIDEMIA system

BackgroundEarly indication of an emerging malaria epidemic can provide an opportunity for proactive interventions. Challenges to the identification of nascent malaria epidemics include obtaining recent epidemiological surveillance data, spatially and temporally harmonizing this information with timely data on environmental precursors, applying models for early detection and early warning, and communicating results to public health officials. Automated web-based informatics systems can provide a solution to these problems, but their implementation in real-world settings has been limited.MethodsThe Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) computer system was designed and implemented to integrate disease surveillance with environmental monitoring in support of operational malaria forecasting in the Amhara region of Ethiopia. A co-design workshop was held with computer scientists, epidemiological modelers, and public health partners to develop an initial list of system requirements. Subsequent updates to the system were based on feedback obtained from system evaluation workshops and assessments conducted by a steering committee of users in the public health sector.ResultsThe system integrated epidemiological data uploaded weekly by the Amhara Regional Health Bureau with remotely-sensed environmental data freely available from online archives. Environmental data were acquired and processed automatically by the EASTWeb software program. Additional software was developed to implement a public health interface for data upload and download, harmonize the epidemiological and environmental data into a unified database, automatically update time series forecasting models, and generate formatted reports. Reporting features included district-level control charts and maps summarizing epidemiological indicators of emerging malaria outbreaks, environmental risk factors, and forecasts of future malaria risk.ConclusionsSuccessful implementation and use of EPIDEMIA is an important step forward in the use of epidemiological and environmental informatics systems for malaria surveillance. Developing software to automate the workflow steps while remaining robust to continual changes in the input data streams was a key technical challenge. Continual stakeholder involvement throughout design, implementation, and operation has created a strong enabling environment that will facilitate the ongoing development, application, and testing of the system.

Large, infrequent disturbance on a regulated river: response of floodplain forest birds to the 2011 Missouri River flood

Floodplain forests are dynamic habitats that support a high diversity and abundance of birds. Periodic flood disturbance is important in the establishment and maintenance of the heterogeneous mosaic of vegetation communities across the riverine landscape. Human suppression of disturbance regimes has been implicated in the decline of bird species in these systems. Because few large rivers are not subject to flood control by dams and levees, opportunities to study avian responses to flood disturbance are limited. A large magnitude, long-duration flood event on the Missouri River, USA, during the summer of 2011 provided an opportunity to quantify post-flood changes in forest bird densities and species richness relative to pre-flood conditions on a riverine floodplain impacted by decades of flow regulation. We surveyed 75 forest sites on two segments of remnant floodplain forest along the Missouri National Recreational River (MNRR) in southeastern South Dakota and northeastern Nebraska and examined changes in density for 35 breeding landbird species from pre-flood (2009–2010) to post-flood (2012–2014) periods. We used a repeated measures ANOVA design to test the effects of year on average densities of birds and nesting guilds and confidence intervals to determine changes in densities of individual species and species richness. 19 of 35 focal species declined significantly one year after the flood (2012), but abundances of ten species recovered to pre-flood densities or higher within two years. In 2012, density declines of six species and density increases of two species were significantly correlated with a decrease in woody vegetation density and percent shrub cover. Average bird densities and the density of shrub nesters rebounded in 2013 to pre-flood levels and continued to increase through 2014. There were no significant changes in species richness at the level of forest habitat types between sampling years. Our results demonstrate short-term resilience of floodplain bird species to a major disturbance despite declines in early successional habitat and minimal recovery of woody vegetation.

Minimum longevity estimates for some Neotropical landbirds of southeastern Peru

ABSTRACT Relatively little is known about the longevity of free-living landbirds, especially in the tropics. We used mark-recapture data for birds originally banded in 2005 and 2006, and later recaptured between 2011 and 2016, to estimate minimum longevity for 20 species from southeastern Peru. The oldest recorded longevity was 10 years, 6 months for a Black-billed Treehunter (Thripadectes melanorhynchus). Another notable record was for a Russet-crowned Warbler (Myiothlypis coronata; 9 years, 2 months). Our estimated minimum longevity records generally reflect the findings of other researchers, indicating that tropical birds are often markedly site faithful and long-lived.

Evaluation of environmentally driven models for early warning of malaria: an exploratory study

Abstract Background Remotely-sensed earth observation data have the potential to inform early warning systems for malaria and other environmentally mediated diseases due to the lagged relation between environmental conditions at present and disease transmission potential in the near future. A common approach is to use total rainfall and mean temperature at a specific time lag to forecast malaria incidence, without justification for the choice of predictor variables or the length of the time lag. Here we explore a number of commonly used formulations of models to forecast malaria incidences across multiple districts using a variety of environmental indices derived from near-real-time satellite remote-sensing data and summarized using polynomial distributed lags. Methods We used weekly malaria incidence data from 2012 to 2017 in 47 districts in the Amhara Region of Ethiopia, a region of unstable malaria transmission where epidemics are driven by environmental conditions, combined with district-level rainfall, land surface temperature, and vegetation greenness, and vegetation water content summarised at lags of 1–16 weeks. We fit models containing various combinations of parameters related to trend, seasonality, and transformations of the environmental indices. We assessed model accuracy using time series cross validation. Findings Models containing a linear effect of trend, Fourier components for seasonality, and climatological anomalies of rainfall, daytime land surface temperature, and normalised difference water index (NDWI) produced the most useful forecasts. Optimal distributed lag functions varied geographically, but generally showed the most positive correlations with malaria incidence at lags of 4–6 weeks. Interpretation Time series models used for early warning of malaria outbreaks are improved by incorporating other environmental indices in addition to rainfall and temperature, by using distributed lags for summarising environmental effects, and by using Fourier components for seasonality combined with environmental anomalies rather than raw environmental indices. Funding National Institute of Allergy and Infectious Diseases (grant number R01AI079411).

Integrated surveillance and modelling systems for climate-sensitive diseases: two case studies

Abstract Background Infectious disease surveillance has traditionally focused on tracking human cases along with arthropod vectors and zoonotic hosts. For climate-sensitive diseases, there is potential to strengthen surveillance and predict future outbreaks by monitoring environmental risk factors using broad-scale sensor networks. We aim to highlight the opportunities and challenges of this integration by presenting two case studies of operational surveillance and forecasting systems for mosquito-borne diseases. Methods The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) system integrates malaria case surveillance with remotely sensed environmental data to predict malaria outbreaks in the Amhara region of Ethiopia and has been producing weekly forecasts since 2015. The South Dakota Mosquito Information System (SDMIS) combines entomological surveillance with gridded meteorological data to generate weekly risk maps for West Nile virus in the north-central USA. Both systems use a variety of earth science datasets, including meteorological fields from the North American Land Data Assimilation System (NLDAS); rainfall data from the Global Precipitation Measurement (GPM) mission; and land surface temperature and surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). We assessed these projects by conducting structured interviews and soliciting written reports from stakeholders. Findings Despite differences in disease ecology and geographic setting, feedback from the stakeholders revealed common themes that can inform future efforts at disease early warning based on climatic models. These include the value of assimilating multiple data streams to constrain model predictions with recent observations of infection, the crucial role of automated workflows to facilitate timely data processing and integration, and the challenge of linking forecasts to specific public health responses. Interpretation Information systems that integrate climate data with disease surveillance are critical enabling technologies that support data access, model-based predictions, and continuous evaluation and improvement of forecasts. These systems must also include networks of individuals and institutions that create a broader enabling environment to support disease forecasting. Funding National Institute of Allergy and Infectious Diseases and NASA Applied Sciences Public Health and Air Quality Program.