Grassland intensification effects cascade to alter multifunctionality of wetlands within metaecosystems

Sustainable agricultural intensification could improve ecosystem service multifunctionality, yet empirical evidence remains tenuous, especially regarding consequences for spatially coupled ecosystems connected by flows across ecosystem boundaries (i.e., metaecosystems). Here we aim to understand the effects of land-use intensification on multiple ecosystem services of spatially connected grasslands and wetlands, where management practices were applied to grasslands but not directly imposed to wetlands. We synthesize long-term datasets encompassing 53 physical, chemical, and biological indicators, comprising >11,000 field measurements. Our results reveal that intensification promotes high-quality forage and livestock production in both grasslands and wetlands, but at the expense of water quality regulation, methane mitigation, non-native species invasion resistance, and biodiversity. Land-use intensification weakens relationships among ecosystem services. The effects on grasslands cascade to alter multifunctionality of embedded natural wetlands within the metaecosystems to a similar extent. These results highlight the importance of considering spatial flows of resources and organisms when studying land-use intensification effects on metaecosystems as well as when designing grassland and wetland management practices to improve landscape multifunctionality.

Individual-level patterns of resource selection do not predict hotspots of contact

Contact among animals is crucial for various ecological processes, including social behaviors, disease transmission, and predator-prey interactions. However, the distribution of contact events across time and space is heterogeneous, influenced by environmental factors and biological purposes. Previous studies have assumed that areas with abundant resources and preferred habitats attract more individuals and, therefore, lead to more contact. To examine the accuracy of this assumption, we used a use-available framework to compare landscape factors influencing the location of contacts between wild pigs (Sus scrofa) in two study areas in Florida and Texas (USA) from those influencing non-contact space use. We employed a contact-resource selection function (RSF) model, where contact locations were defined as used points and locations without contact as available points. By comparing outputs from this contact RSF with a general, population-level RSF, we assessed the factors driving both habitat selection and contact. We found that the landscape predictors (e.g., wetland, linear features, and food resources) played different roles in habitat selection from contact processes for wild pigs in both study areas. This indicated that pigs interacted with their landscapes differently when choosing habitats compared to when they encountered other individuals. Consequently, relying solely on the spatial overlap of individual or population-level RSF models may lead to a misleading understanding of contact-related ecology. Our findings challenge prevailing assumptions about contact and introduce innovative approaches to better understand the ecological drivers of spatially explicit contact. By accurately predicting the spatial distribution of contact events, we can enhance our understanding of contact based ecological processes and their spatial dynamics.

Deriving spatially explicit direct and indirect interaction networks from animal movement data

Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from animal tracking technologies (Global Positioning Systems [“GPS”]) can circumvent longstanding challenges in the estimation of spatiotemporally explicit interactions, but the discrete nature and coarse temporal resolution of data mean that ephemeral interactions that occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual and spatial patterns of interaction using continuous‐time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs to infer the full movement trajectories at an arbitrarily fine temporal scale before estimating interactions, thus allowing inference of interactions occurring between observed GPS locations. Our framework then infers indirect interactions—individuals occurring at the same location, but at different times—while allowing the identification of indirect interactions to vary with ecological context based on CTMM outputs. We assessed the performance of our new method using simulations and illustrated its implementation by deriving disease‐relevant interaction networks for two behaviorally differentiated species, wild pigs (Sus scrofa) that can host African Swine Fever and mule deer (Odocoileus hemionus) that can host chronic wasting disease. Simulations showed that interactions derived from observed GPS data can be substantially underestimated when temporal resolution of movement data exceeds 30‐min intervals. Empirical application suggested that underestimation occurred in both interaction rates and their spatial distributions. CTMM‐Interaction method, which can introduce uncertainties, recovered majority of true interactions. Our method leverages advances in movement ecology to quantify fine‐scale spatiotemporal interactions between individuals from lower temporal resolution GPS data. It can be leveraged to infer dynamic social networks, transmission potential in disease systems, consumer–resource interactions, information sharing, and beyond. The method also sets the stage for future predictive models linking observed spatiotemporal interaction patterns to environmental drivers.

Optimizing response to an introduction of African swine fever in wild pigs

African swine fever virus (ASFv) is a virulent pathogen that threatens domestic swine industries globally and persists in wild boar populations in some countries. Persistence in wild boar can challenge elimination and prevent disease-free status, making it necessary to address wild swine in proactive response plans. In the U.S., invasive wild pigs are abundant and found across a wide range of ecological conditions that could drive different epidemiological dynamics among populations. Information on size of control areas required to rapidly eliminate ASFv in wild pigs and how this area should change with management constraints and local ecology are needed to optimize response planning. We developed a spatially-explicit disease transmission model contrasting wild pig movement and contact ecology in two ecosystems in southeastern U.S. We simulated ASFv spread and determined optimal response area (reported as radius of a circle) for eliminating ASFv rapidly over a range of detection times (when ASFv is detected relative to true date of introduction), culling capacities (proportion of wild pigs in the culling zone removed weekly), and wild pig densities. Large radii for response areas (14 km) were needed under most conditions but could be shortened with early detection (≤ 8 weeks) and high culling capacities (≥ 15% weekly). Under most conditions ASFv was eliminated in less than 22 weeks using optimal control radii, although ecological conditions with high rates of wild pig movement required higher culling capacities (≥ 10% weekly) for elimination within one year. Results highlight the importance of adjusting response plans based on local ecology and show wild pig movement is a better predictor of optimal response area than numbers of ASFv cases early in the outbreak trajectory. Our framework provides a tool for determining optimal control plans in different areas, guiding expectations of response impacts, and planning resources needed for rapid elimination. This article is protected by copyright. All rights reserved.

A model for leveraging animal movement to understand spatio-temporal disease dynamics

The ongoing explosion of fine-resolution movement data in animal systems provides a unique opportunity to empirically quantify spatial, temporal and individual variation in transmission risk and improve our ability to forecast disease outbreaks. However, we lack a generalizable model that can leverage movement data to quantify transmission risk and how it affects pathogen invasion and persistence on heterogeneous landscapes. We developed a flexible model 'Movement-driven modelling of spatio-temporal infection risk' (MoveSTIR) that leverages diverse data on animal movement to derive metrics of direct and indirect contact by decomposing transmission into constituent processes of contact formation and duration and pathogen deposition and acquisition. We use MoveSTIR to demonstrate that ignoring fine-scale animal movements on actual landscapes can mis-characterize transmission risk and epidemiological dynamics. MoveSTIR unifies previous work on epidemiological contact networks and can address applied and theoretical questions at the nexus of movement and disease ecology.

Systemic humoral immunity in beef bulls following therapeutic vaccination against Tritrichomonas foetus

The utility of therapeutic vaccination of bulls against Tritrichomonas foetus has been advocated in previous studies, but anecdotal reports suggest this practice does not clear infections and may additionally confound diagnostic testing by reducing parasite burdens below detectable limits. The objective of this study was to characterize the systemic humoral immune response to therapeutic vaccination in T. foetus-infected bulls over a period of four months using an indirect ELISA and to compare the dynamics of this response to culture and PCR results to establish the existence of a relationship (or lack thereof) between immunization and infection status. A study population of 4- to 6-year-old T. foetus-infected beef bulls (n = 20) was divided equally into a treatment group and a control group. The treatment group received two doses of commercially prepared whole cell killed vaccine 2 weeks apart while the control group received injections of vaccine diluent. Blood samples were collected at each injection and at 4 subsequent dates every 4 weeks thereafter (i.e. 0, 2, 6, 10, 14, and 18 wks) to measure IgG₁ and IgG₂ antibody subisotype response via an indirect ELISA. Preputial smegma samples were collected at the four monthly intervals following vaccination for diagnosis of infection via InPouch™ culture, Modified Diamond's Medium (MDM) culture, and PCR. Humoral response for both IgG isotypes from week 2 through week 18 were significantly increased in vaccinates compared to controls. No significant decrease in infection prevalence was detected in the treatment group for any of the diagnostic methods used. The apparent lack of pathogen clearance during a stimulated immune response suggests that therapeutic vaccination may not be a useful T. foetus management practice.

Quantifying drivers of wild pig movement across multiple spatial and temporal scales

BACKGROUND

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management.

METHODS

We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season.

RESULTS

We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales.

CONCLUSIONS

The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

Inhaled albuterol, but not intravenous lidocaine, protects against intubation-induced bronchoconstriction in asthma

BACKGROUND

The ability of intravenous lidocaine to prevent intubation-induced bronchospasm is unclear. The authors performed a prospective, randomized, double-blind, placebo-controlled trial to test the ability of intravenous lidocaine and inhaled albuterol to attenuate airway reactivity after tracheal intubation in asthmatic patients undergoing general anesthesia.

METHODS

Sixty patients were randomized to receive either 1.5 mg/kg intravenous lidocaine or saline, 3 min before tracheal intubation. An additional 50 patients were randomized to receive 4 puffs of inhaled albuterol or placebo 15-20 min before tracheal intubation. Anesthesia was induced with propofol. Immediately after intubation and at 5-min intervals, transpulmonary pressure and airflow were recorded, and lower pulmonary resistance (RL) was calculated. Isoflurane was administered after the initial two measurements to assess reversibility of bronchoconstriction. A bronchoconstrictor response to intubation was defined as RL greater than or equal to 5 cm H2O. l-1. s-1 in the first two measurements after intubation and RL subsequently decreasing by 50% or more after isoflurane.

RESULTS

The lidocaine and placebo groups were not different in the peak RL before administration of isoflurane (8.2 cm H2O. l-1. s-1 vs. 7.6 cm H2O. l-1. s-1) or frequency of airway response to intubation (lidocaine 6 of 30 vs. placebo 5 of 27). In contrast, the albuterol group had lower peak RL (5.3 cm H2O. l-1. s-1 vs. 8.9 cm H2O. l-1. s-1; P < 0.05) and a lower frequency of airway response (1 of 25 vs. 8 of 23; P < 0.05) than the placebo group.

CONCLUSIONS

Inhaled albuterol blunted airway response to tracheal intubation in asthmatic patients, whereas intravenous lidocaine did not.

Epidermolysis bullosa--a review of 15 years' experience, including experience with combined general and regional anaesthetic techniques

Eight patients with epidermolysis bullosa received a total of 60 anaesthetics for 67 procedures over the fifteen-year period 1972 to 1986. On twenty-three occasions patients were intubated. On thirteen occasions general anaesthesia was supplemented by regional blockade, involving a total of thirty-four local anaesthetic blocks. Complications from intubation were minimal and none were seen related to regional blockade.

Lack of agreement between subjective ratings of instructors and objective testing of knowledge acquisition in a urological continuing medical education course

Objective scores from multiple-choice questions before and after a postgraduate course were compared to subjective ratings of the instructors at a 3-day seminar. The objective mean scores after the course were significantly higher than the scores before the course (p less than 0.0001). There was no correlation between test results and subjective ratings of instructors.