Publications by authors named "Jason Matthiopoulos"

48 Publications

A protocol for a longitudinal, observational cohort study of infection and exposure to zoonotic and vector-borne diseases across a land-use gradient in Sabah, Malaysian Borneo: a socio-ecological systems approach.

Wellcome Open Res 2022 16;7:63. Epub 2022 Feb 16.

Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia.

Landscape changes disrupt environmental, social and biological systems, altering pathogen spillover and transmission risks. This study aims to quantify the impact of specific land management practices on spillover and transmission rates of zoonotic and vector-borne diseases within Malaysian Borneo. This protocol describes a cohort study with integrated ecological sampling to assess how deforestation and agricultural practices impact pathogen flow from wildlife and vector populations to human infection and detection by health facilities. This will focus on malaria, dengue and emerging arboviruses (Chikungunya and Zika), vector-borne diseases with varying contributions of simian reservoirs within this setting. A prospective longitudinal observational cohort study will be established in communities residing or working within the vicinity of the Stability of Altered Forest Ecosystems (SAFE) Project, a landscape gradient within Malaysian Borneo encompassing different plantation and forest types. The primary outcome of this study will be transmission intensity of selected zoonotic and vector-borne diseases, as quantified by changes in pathogen-specific antibody levels. Exposure will be measured using paired population-based serological surveys conducted at the beginning and end of the two-year cohort study. Secondary outcomes will include the distribution and infection rates of and mosquito vectors, human risk behaviours and clinical cases reported to health facilities. Longitudinal data on human behaviour, contact with wildlife and GPS tracking of mobility patterns will be collected throughout the study period. This will be integrated with entomological surveillance to monitor densities and pathogen infection rates of and mosquitoes relative to land cover. Within surrounding health clinics, continuous health facility surveillance will be used to monitor reported infections and febrile illnesses. Models will be developed to assess spillover and transmission rates relative to specific land management practices and evaluate abilities of surveillance systems to capture these risks.
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http://dx.doi.org/10.12688/wellcomeopenres.17678.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8886174PMC
February 2022

Widespread extinction debts and colonization credits in United States breeding bird communities.

Nat Ecol Evol 2022 03 10;6(3):324-331. Epub 2022 Feb 10.

Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK.

Species extinctions and colonizations in response to land cover change often occur with time lags rather than instantaneously, leading to extinction debts and colonization credits. These debts and credits can lead to erroneous predictions of future biodiversity. Recent attempts to measure debts and credits have been limited to small geographical areas and have not considered multiple land cover types, or the directionality of land cover change. Here we quantify the relative contribution of past and current landscapes on the current effective number of species of 2,880 US bird communities, explicitly measuring the response of biodiversity to increases and decreases in five land cover types. We find that the current effective number of species is still largely explained by the past landscape composition (legacy effect), depending on the type, magnitude and directionality of recent land cover change. This legacy effect leads to widespread extinction debts and colonization credits. Specifically, we reveal debts across 52% of the United States, particularly in recently urbanized areas, and colonization credits in the remaining 48%, which are primarily associated with grassland decrease. We conclude that biodiversity policy targets risk becoming rapidly obsolete unless past landscapes are considered and debts and credits accounted for.
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http://dx.doi.org/10.1038/s41559-021-01653-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913367PMC
March 2022

Insecticide resistance and behavioural adaptation as a response to long-lasting insecticidal net deployment in malaria vectors in the Cascades region of Burkina Faso.

Sci Rep 2021 09 2;11(1):17569. Epub 2021 Sep 2.

Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Graham Kerr Building, Glasgow, G12 8QQ, UK.

The decline in malaria across Africa has been largely attributed to vector control using long-lasting insecticidal nets (LLINs). However, this intervention has prompted widespread insecticide resistance (IR) and been associated with changes in mosquito behaviour that reduce their contact with LLINs. The relative importance and rate at which IR and behavioural adaptations emerge are poorly understood. We conducted surveillance of mosquito behaviour and IR at 12 sites in Burkina Faso to assess the magnitude and temporal dynamics of insecticide, biting and resting behaviours in vectors in the 2-year period following mass LLIN distribution. Insecticide resistance was present in all vector populations and increased rapidly over the study period. In contrast, no longitudinal shifts in LLIN-avoidance behaviours (earlier or outdoor biting and resting) were detected. There was a moderate but statistically significant shift in vector species composition from Anopheles coluzzii to Anopheles gambiae which coincided with a reduction in the proportion of bites preventable by LLINs; possibly driven by between-species variation in behaviour. These findings indicate that adaptations based on insecticide resistance arise and intensify more rapidly than behavioural shifts within mosquito vectors. However, longitudinal shifts in mosquito vector species composition were evident within 2 years following a mass LLIN distribution. This ecological shift was characterized by a significant increase in the exophagic species (An. gambiae) and coincided with a predicted decline in the degree of protection expected from LLINs. Although human exposure fell through the study period due to reducing vector densities and infection rates, such ecological shifts in vector species along with insecticide resistance were likely to have eroded the efficacy of LLINs. While both adaptations impact malaria control, the rapid increase of the former indicates this strategy develops more quickly in response to selection from LLINS. However, interventions targeting both resistance strategies will be needed.
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http://dx.doi.org/10.1038/s41598-021-96759-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413378PMC
September 2021

Individual-Level Memory Is Sufficient to Create Spatial Segregation among Neighboring Colonies of Central Place Foragers.

Am Nat 2021 08 24;198(2):E37-E52. Epub 2021 Jun 24.

AbstractCentral place foragers often segregate in space, even without signs of direct agonistic interactions. Using parsimonious individual-based simulations, we show that for species with spatial cognitive abilities, individual-level memory of resource availability can be sufficient to cause spatial segregation in the foraging ranges of colonial animals. The shapes of the foraging distributions are governed by commuting costs, the emerging distribution of depleted resources, and the fidelity of foragers to their colonies. When colony fidelity is weak and foragers can easily switch to colonies located closer to favorable foraging grounds, this leads to space partitioning with equidistant borders between neighboring colonies. In contrast, when colony fidelity is strong-for example, because larger colonies provide safety in numbers or individuals are unable to leave-it can create a regional imbalance between resource requirements and resource availability. This leads to nontrivial space-use patterns that propagate through the landscape. Interestingly, while better spatial memory creates more defined boundaries between neighboring colonies, it can lower the average intake rate of the population, suggesting a potential trade-off between an individual's attempt for increased intake and population growth rates.
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http://dx.doi.org/10.1086/715014DOI Listing
August 2021

COVID-19 - exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study.

Wellcome Open Res 2020 1;5:75. Epub 2021 Mar 1.

University of Glasgow, Glasgow, UK.

 COVID-19 is responsible for increasing deaths globally. As most people dying with COVID-19 are older with underlying long-term conditions (LTCs), some speculate that YLL are low. We aim to estimate YLL attributable to COVID-19, before and after adjustment for number/type of LTCs, using the limited data available early in the pandemic.  We first estimated YLL from COVID-19 using WHO life tables, based on published age/sex data from COVID-19 deaths in Italy. We then used aggregate data on number/type of LTCs in a Bayesian model to estimate likely combinations of LTCs among people dying with COVID-19. We used routine UK healthcare data from Scotland and Wales to estimate life expectancy based on age/sex/these combinations of LTCs using Gompertz models from which we then estimate YLL.  Using the standard WHO life tables, YLL per COVID-19 death was 14 for men and 12 for women. After adjustment for number and type of LTCs, the mean YLL was slightly lower, but remained high (11.6 and 9.4 years for men and women, respectively). The number and type of LTCs led to wide variability in the estimated YLL at a given age (e.g. at ≥80 years, YLL was >10 years for people with 0 LTCs, and <3 years for people with ≥6).  Deaths from COVID-19 represent a substantial burden in terms of per-person YLL, more than a decade, even after adjusting for the typical number and type of LTCs found in people dying of COVID-19. The extent of multimorbidity heavily influences the estimated YLL at a given age. More comprehensive and standardised collection of data (including LTC type, severity, and potential confounders such as socioeconomic-deprivation and care-home status) is needed to optimise YLL estimates for specific populations, and to understand the global burden of COVID-19, and guide policy-making and interventions.
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http://dx.doi.org/10.12688/wellcomeopenres.15849.3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7927210.3PMC
March 2021

Fitness characteristics of the malaria vector Anopheles funestus during an attempted laboratory colonization.

Malar J 2021 Mar 12;20(1):148. Epub 2021 Mar 12.

Department of Environmental Health and Ecological Sciences, Ifakara Health Institute, P.O. Box 53, Ifakara, Tanzania.

Background: The malaria vector Anopheles funestus is increasingly recognized as a dominant vector of residual transmission in many African settings. Efforts to better understand its biology and control are significantly impeded by the difficulties of colonizing it under laboratory conditions. To identify key bottlenecks in colonization, this study compared the development and fitness characteristics of wild An. funestus from Tanzania (FUTAZ) and their F offspring during colonization attempts. The demography and reproductive success of wild FUTAZ offspring were compared to that of individuals from one of the only An. funestus strains that has been successfully colonized (FUMOZ, from Mozambique) under similar laboratory conditions.

Methods: Wild An. funestus (FUTAZ) were collected from three Tanzanian villages and maintained inside an insectary at 70-85% RH, 25-27 °C and 12 h:12 h photoperiod. Eggs from these females were used to establish three replicate F laboratory generations. Larval development, survival, fecundity, mating success, percentage pupation and wing length were measured in the F -FUTAZ offspring and compared with wild FUTAZ and FUMOZ mosquitoes.

Results: Wild FUTAZ laid fewer eggs (64.1; 95% CI [63.2, 65.0]) than FUMOZ females (76.1; 95% CI [73.3, 79.1]). Survival of F-FUTAZ larvae under laboratory conditions was low, with an egg-to-pupae conversion rate of only 5.9% compared to 27.4% in FUMOZ. The median lifespan of F-FUTAZ females (32 days) and males (33 days) was lower than FUMOZ (52 and 49 for females and males respectively). The proportion of female F-FUTAZ inseminated under laboratory conditions (9%) was considerably lower than either FUMOZ (72%) or wild-caught FUTAZ females (92%). This resulted in nearly zero viable F-FUTAZ eggs produced. Wild FUTAZ wings appear to be larger compared to the lab reared F-FUTAZ and FUMOZ.

Conclusions: This study indicates that poor larval survival, mating success, low fecundity and shorter survival under laboratory conditions all contribute to difficulties in colonizing of An. funestus. Future studies should focus on enhancing these aspects of An. funestus fitness in the laboratory, with the biggest barrier likely to be poor mating.
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http://dx.doi.org/10.1186/s12936-021-03677-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955623PMC
March 2021

Interspecific competition between resident and wintering birds: experimental evidence and consequences of coexistence.

Ecology 2021 02 24;102(2):e03208. Epub 2021 Jan 24.

Migratory Bird Center, Smithsonian Conservation Biology Institute, National Zoological 7 Park, P.O. Box 37012, Washington, D.C., 20013-7012, USA.

The contribution of interspecific competition to structuring population and community dynamics remains controversial and poorly tested. Interspecific competition has long been thought to influence the structure of migrant-resident bird communities in winter, yet experimental evidence remains elusive. The arrival of billions of songbirds into Neotropical habitats, where they co-exist with residents, provides a unique opportunity to assess interspecific competition and its consequences. Working in 15 ha of Jamaican black mangrove forest, we used removal experiments to test whether dominant resident Yellow Warblers compete interspecifically with subordinate wintering American Redstarts; we also used observational evidence (interspecific territorial overlap) to understand whether this coexistence influences physical condition, spring departure dates or annual return rates. Consistent with interspecific competition, after experimental removal of the resident, yearling male Redstarts (but not females or adult males) immediately moved into vacated Yellow Warbler territories, increasing their overlap with the space by 7.3%. Yearling Redstarts also appeared to adjust their territorial space use by actively avoiding Yellow Warblers; for example, Redstarts departing the wintering grounds as yearlings and returning the following winter shifted such that their territories overlapped 32% less with those of Yellow Warblers. Adult Redstarts showed no such territorial flexibility. Adult male Redstarts also showed evidence supporting the consequences of coexistence: territorial overlap with Yellow Warblers was negatively correlated with body condition and annual return rates. Adult male Redstarts with <25% territorial overlap with Yellow Warblers were more than three times as likely to return between seasons than those with 100% overlap. We propose that the territorial inflexibility of adult male Redstarts produces these consequences, which may be due to their years-long investment in that particular territory. More generally, the temporary nature of migrant-resident interspecific competition is likely what allows coexistence during winter, the most resource-poor time of year. Interspecific competition and the consequences of coexistence are likely age- and sex-specific and the product of intraspecific dominance hierarchy in Redstarts. Our observations suggest that interspecific coexistence has measurable consequences, and our experiments support the long-held, but previously untested belief that resident birds compete interspecifically with wintering migrants.
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http://dx.doi.org/10.1002/ecy.3208DOI Listing
February 2021

Local rabies transmission and regional spatial coupling in European foxes.

PLoS One 2020 29;15(5):e0220592. Epub 2020 May 29.

Institute of Biodiversity, Animal Health, and Comparative Medicine, University of Glasgow, Glasgow, Scotland.

Infectious diseases are often transmitted through local interactions. Yet, both surveillance and control measures are implemented within administrative units. Capturing local transmission processes and spatial coupling between regions from aggregate level data is therefore a technical challenge that can shed light on both theoretical questions and practical decisions. Fox rabies has been eliminated from much of Europe through oral rabies vaccination (ORV) programmes. The European Union (EU) co-finances ORV to maintain rabies freedom in EU member and border states via a cordon sanitaire. Models to capture local transmission dynamics and spatial coupling have immediate application to the planning of these ORV campaigns and to other parts of the world considering oral vaccination. We fitted a hierarchical Bayesian state-space model to data on three decades of fox rabies cases and ORV campaigns from Eastern Germany. Specifically, we find that (i) combining regional spatial coupling and heterogeneous local transmission allows us to capture regional rabies dynamics; (ii) incursions from other regions account for less than 1% of cases, but allow for re-emergence of disease; (iii) herd immunity achieved through bi-annual vaccination campaigns is short-lived due to population turnover. Together, these findings highlight the need for regular and sustained vaccination efforts and our modelling approach can be used to provide strategic guidance for ORV delivery. Moreover, we show that biological understanding can be gained from inference from partially observed data on wildlife disease.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0220592PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7259497PMC
July 2020

Within Reach? Habitat Availability as a Function of Individual Mobility and Spatial Structuring.

Am Nat 2020 06 21;195(6):1009-1026. Epub 2020 Apr 21.

Organisms need access to particular habitats for their survival and reproduction. However, even if all necessary habitats are available within the broader environment, they may not all be easily reachable from the position of a single individual. Many species distribution models consider populations in environmental (or niche) space, hence overlooking this fundamental aspect of geographical accessibility. Here, we develop a formal way of thinking about habitat availability in environmental spaces by describing how limitations in accessibility can cause animals to experience a more limited or simply different mixture of habitats than those more broadly available. We develop an analytical framework for characterizing constrained habitat availability based on the statistical properties of movement and environmental autocorrelation. Using simulation experiments, we show that our general statistical representation of constrained availability is a good approximation of habitat availability for particular realizations of landscape-organism interactions. We present two applications of our approach, one to the statistical analysis of habitat preference (using step-selection functions to analyze harbor seal telemetry data) and a second that derives theoretical insights about population viability from knowledge of the underlying environment. Analytical expressions for habitat availability, such as those we develop here, can yield gains in analytical speed, biological realism, and conceptual generality by allowing us to formulate models that are habitat sensitive without needing to be spatially explicit.
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http://dx.doi.org/10.1086/708519DOI Listing
June 2020

Distance sampling for epidemiology: an interactive tool for estimating under-reporting of cases from clinic data.

Int J Health Geogr 2020 04 20;19(1):16. Epub 2020 Apr 20.

University of Glasgow, Institute of Biodiversity Animal Health and Comparative Medicine, Glasgow, UK.

Background: Distance sampling methods are widely used in ecology to estimate and map the abundance of animal and plant populations from spatial survey data. The key underlying concept in distance sampling is the detection function, the probability of detecting the occurrence of an event as a function of its distance from the observer, as well as other covariates that may influence detection. In epidemiology, the burden and distribution of infectious disease is often inferred from cases that are reported at clinics and hospitals. In areas with few public health facilities and low accessibility, the probability of detecting a case is also a function of the distance between an infected person and the "observer" (e.g. a health centre). While the problem of distance-related under-reporting is acknowledged in public health; there are few quantitative methods for assessing and correcting for this bias when mapping disease incidence. Here, we develop a modified version of distance sampling for prediction of infectious disease incidence by relaxing some of the framework's fundamental assumptions. We illustrate the utility of this approach using as our example malaria distribution in rural Burkina Faso, where there is a large population at risk but relatively low accessibility of health facilities.

Results: The modified distance-sampling framework was used to predict the probability of reporting malaria infection at 8 rural clinics, based on road-travel distances from villages. The rate at which reporting probability dropped with distance varied between clinics, depending on road and clinic positions. The probability of case detection was estimated as 0.3-1 in the immediate vicinity of the clinic, dropping to 0.1-0.6 at a travel distance of 10 km, and effectively zero at distances > 30-40 km.

Conclusions: To enhance the method's strategic impact, we provide an interactive mapping tool (as a self-contained R Shiny app) that can be used by non-specialists to interrogate model outputs and visualize how the overall probability of under-reporting and the catchment area of each clinic is influenced by changing the number and spatial allocation of health centres.
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http://dx.doi.org/10.1186/s12942-020-00209-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171748PMC
April 2020

Evaluation of mosquito electrocuting traps as a safe alternative to the human landing catch for measuring human exposure to malaria vectors in Burkina Faso.

Malar J 2019 Dec 2;18(1):386. Epub 2019 Dec 2.

Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Graham Kerr Building, Glasgow, G12 8QQ, UK.

Background: Measuring human exposure to mosquito bites is a crucial component of vector-borne disease surveillance. For malaria vectors, the human landing catch (HLC) remains the gold standard for direct estimation of exposure. This method, however, is controversial since participants risk exposure to potentially infected mosquito bites. Recently an exposure-free mosquito electrocuting trap (MET) was developed to provide a safer alternative to the HLC. Early prototypes of the MET performed well in Tanzania but have yet to be tested in West Africa, where malaria vector species composition, ecology and behaviour are different. The performance of the MET relative to HLC for characterizing mosquito vector population dynamics and biting behaviour in Burkina Faso was evaluated.

Methods: A longitudinal study was initiated within 12 villages in Burkina Faso in October 2016. Host-seeking mosquitoes were sampled monthly using HLC and MET collections over 14 months. Collections were made at 4 households on each night, with METs deployed inside and outside at 2 houses, and HLC inside and outside at another two. Malaria vector abundance, species composition, sporozoite rate and location of biting (indoor versus outdoor) were recorded.

Results: In total, 41,800 mosquitoes were collected over 324 sampling nights, with the major malaria vector being Anopheles gambiae sensu lato (s.l.) complex. Overall the MET caught fewer An. gambiae s.l. than the HLC (mean predicted number of 0.78 versus 1.82 indoors, and 1.05 versus 2.04 outdoors). However, MET collections gave a consistent representation of seasonal dynamics in vector populations, species composition, biting behaviour (location and time) and malaria infection rates relative to HLC. As the relative performance of the MET was somewhat higher in outdoor versus indoor settings, this trapping method slightly underestimated the proportion of bites preventable by LLINs compared to the HLC (MET = 82.08%; HLC = 87.19%).

Conclusions: The MET collected proportionately fewer mosquitoes than the HLC. However, estimates of An. gambiae s.l. density in METs were highly correlated with HLC. Thus, although less sensitive, the MET is a safer alternative than the HLC. Its use is recommended particularly for sampling vectors in outdoor environments where it is most sensitive.
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http://dx.doi.org/10.1186/s12936-019-3030-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889701PMC
December 2019

Environmental Predictability as a Cause and Consequence of Animal Movement.

Trends Ecol Evol 2020 02 5;35(2):163-174. Epub 2019 Nov 5.

Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK.

The impacts of environmental predictability on the ecology and evolution of animal movement have been the subject of vigorous speculation for several decades. Recently, the swell of new biologging technologies has further stimulated their investigation. This advancing research frontier, however, still lacks conceptual unification and has so far focused little on converse effects. Populations of moving animals have ubiquitous effects on processes such as nutrient cycling and seed dispersal and may therefore shape patterns of environmental predictability. Here, we synthesise the main strands of the literature on the feedbacks between environmental predictability and animal movement and discuss how they may react to anthropogenic disruption, leading to unexpected threats for wildlife and the environment.
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http://dx.doi.org/10.1016/j.tree.2019.09.009DOI Listing
February 2020

Inference in MCMC step selection models.

Biometrics 2020 06 9;76(2):438-447. Epub 2019 Dec 9.

Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.

Habitat selection models are used in ecology to link the spatial distribution of animals to environmental covariates and identify preferred habitats. The most widely used models of this type, resource selection functions, aim to capture the steady-state distribution of space use of the animal, but they assume independence between the observed locations of an animal. This is unrealistic when location data display temporal autocorrelation. The alternative approach of step selection functions embed habitat selection in a model of animal movement, to account for the autocorrelation. However, inferences from step selection functions depend on the underlying movement model, and they do not readily predict steady-state space use. We suggest an analogy between parameter updates and target distributions in Markov chain Monte Carlo (MCMC) algorithms, and step selection and steady-state distributions in movement ecology, leading to a step selection model with an explicit steady-state distribution. In this framework, we explain how maximum likelihood estimation can be used for simultaneous inference about movement and habitat selection. We describe the local Gibbs sampler, a novel rejection-free MCMC scheme, use it as the basis of a flexible class of animal movement models, and derive its likelihood function for several important special cases. In a simulation study, we verify that maximum likelihood estimation can recover all model parameters. We illustrate the application of the method with data from a zebra.
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http://dx.doi.org/10.1111/biom.13170DOI Listing
June 2020

1980s-2010s: The world's largest mangrove ecosystem is becoming homogeneous.

Biol Conserv 2019 Aug;236:79-91

Boyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom.

Knowledge gaps in spatiotemporal changes in mangrove diversity and composition have obstructed mangrove conservation programs across the tropics, but particularly in the Sundarbans (10,017 km), the world's largest remaining natural mangrove ecosystem. Using mangrove tree data collected from Earth's largest permanent sample plot network at four historical time points (1986, 1994, 1999 and 2014), this study establishes spatially explicit baseline biodiversity information for the Sundarbans. We determined the spatial and temporal differences in alpha, beta, and gamma diversity in three ecological zones (hypo-, meso-, and hypersaline) and also uncovered changes in the mangroves' overall geographic range and abundances therein. Spatially, the hyposaline mangrove communities were the most diverse and heterogeneous in species composition while the hypersaline communities were the least diverse and most homogeneous at all historical time points. Since 1986, we detect an increasing trend of compositional homogeneity (between-site similarity in species composition) and a significant spatial contraction of distinct and diverse areas over the entire ecosystem. Temporally, the western and southern hypersaline communities have undergone radical shifts in species composition due to population increase and range expansion of the native invasive species and local extinction or range contraction of specialists including the globally endangered . The surviving biodiversity hotspots are distributed outside the legislated protected area network. In addition to suggesting the immediate coverage of these hotspots under protected area management, our novel biodiversity insights and spatial maps can form the basis for spatial conservation planning, biodiversity monitoring and protection initiatives for the Sundarbans.
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http://dx.doi.org/10.1016/j.biocon.2019.05.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6716549PMC
August 2019

Global reconstruction of life-history strategies: A case study using tunas.

J Appl Ecol 2019 Apr 1;56(4):855-865. Epub 2019 Feb 1.

Institute of Biodiversity, Animal Health & Comparative Medicine University of Glasgow Glasgow UK.

Measuring the demographic parameters of exploited populations is central to predicting their vulnerability and extinction risk. However, current rates of population decline and species loss greatly outpace our ability to empirically monitor all populations that are potentially threatened.The scale of this problem cannot be addressed through additional data collection alone, and therefore it is a common practice to conduct population assessments based on surrogate data collected from similar species. However, this approach introduces biases and imprecisions that are difficult to quantify. Recent developments in hierarchical modelling have enabled missing values to be reconstructed based on the correlations between available life-history data, linking similar species based on phylogeny and environmental conditions.However, these methods cannot resolve life-history variability among populations or species that are closely placed spatially or taxonomically. Here, theoretically motivated constraints that align with life-history theory offer a new avenue for addressing this problem. We describe a Bayesian hierarchical approach that combines fragmented, multispecies and multi-population data with established life-history theory, in order to objectively determine similarity between populations based on trait correlations (life-history trade-offs) obtained from model fitting.We reconstruct 59 unobserved life-history parameters for 23 populations of tuna that sustain some of the world's most valuable fisheries. Testing by cross-validation across different scenarios indicated that life-histories were accurately reconstructed when information was available for other populations of the same species. The reconstruction of several traits was also accurate for species represented by a single population, although credible intervals increased dramatically. . The described Bayesian hierarchical method provides access to life-history traits that are difficult to measure directly and reconstructs missing life-history information useful for assessing populations and species that are directly or indirectly affected by human exploitation of natural resources. The method is particularly useful for examining populations that are spatially or taxonomically similar, and the reconstructed life-history strategies described for the principal market tunas have immediate application to the world-wide management of these fisheries.
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http://dx.doi.org/10.1111/1365-2664.13327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6559282PMC
April 2019

Achieving explanatory depth and spatial breadth in infectious disease modelling: Integrating active and passive case surveillance.

Stat Methods Med Res 2020 05 18;29(5):1273-1287. Epub 2019 Jun 18.

Institute of Biodiversity Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK.

Ideally, the data used for robust spatial prediction of disease distribution should be both high-resolution and spatially expansive. However, such in-depth and geographically broad data are rarely available in practice. Instead, researchers usually acquire either detailed epidemiological data with high resolution at a small number of active sampling sites, or more broad-ranging but less precise data from passive case surveillance. We propose a novel inferential framework, capable of simultaneously drawing insights from both passive and active data types. We developed a Bayesian latent point process approach, combining active data collection in a limited set of points, where in-depth covariates are measured, with passive case detection, where error-prone, large-scale disease data are accompanied only by coarse or remotely-sensed covariate layers. Using the example of malaria, we tested our method's efficiency under several hypothetical scenarios of reported incidence in different combinations of imperfect detection and spatial complexity of the environmental variables. We provide a simple solution to a widespread problem in spatial epidemiology, combining latent process modelling and spatially autoregressive modelling. By using active sampling and passive case detection in a complementary way, we achieved the best-of-both-worlds, in effect, a formal calibration of spatially extensive, error-prone data by localised, high-quality data.
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http://dx.doi.org/10.1177/0962280219856380DOI Listing
May 2020

Optimizing spatial and seasonal deployment of vaccination campaigns to eliminate wildlife rabies.

Philos Trans R Soc Lond B Biol Sci 2019 07;374(1776):20180280

1 Boyd Orr Centre for Population and Ecosystem Health, Institute for Biodiversity, Animal Health and Comparative Medicine, University of Glasgow , Glasgow G12 8QQ , UK.

Understanding how the spatial deployment of interventions affects elimination time horizons and potential for disease re-emergence has broad application to control programmes targeting human, animal and plant pathogens. We previously developed an epidemiological model that captures the main features of rabies spread and the impacts of vaccination based on detailed records of fox rabies in eastern Germany during the implementation of an oral rabies vaccination (ORV) programme. Here, we use simulations from this fitted model to determine the best vaccination strategy, in terms of spatial placement and timing of ORV efforts, for three epidemiological scenarios representative of current situations in Europe. We found that consecutive and comprehensive twice-yearly vaccinations across all regions rapidly controlled and eliminated rabies and that the autumn campaigns had the greater impact on increasing the probability of elimination. This appears to result from the need to maintain sufficient herd immunity in the face of large birth pulses, as autumn vaccinations reach susceptible juveniles and therefore a larger proportion of the population than spring vaccinations. Incomplete vaccination compromised time to elimination requiring the same or more vaccination effort to meet similar timelines. Our results have important practical implications that could inform policies for rabies containment and elimination in Europe and elsewhere. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
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http://dx.doi.org/10.1098/rstb.2018.0280DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6558560PMC
July 2019

Predicting population change from models based on habitat availability and utilization.

Proc Biol Sci 2019 04;286(1901):20182911

1 Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow , Room 312, Graham Kerr Building, Glasgow G12 8QQ , UK.

The need to understand the impacts of land management for conservation, agriculture and disease prevention are driving demand for new predictive ecology approaches that can reliably forecast future changes in population size. Currently, although the link between habitat composition and animal population dynamics is undisputed, its function has not been quantified in a way that enables accurate prediction of population change in nature. Here, using 12 house sparrow colonies as a proof-of-concept, we apply recent theoretical advances to predict population growth or decline from detailed data on habitat composition and habitat selection. We show, for the first time, that statistical population models using derived covariates constructed from parametric descriptions of habitat composition and habitat selection can explain an impressive 92% of observed population variation. More importantly, they provide excellent predictive power under cross-validation, anticipating 81% of variability in population change. These models may be embedded in readily available generalized linear modelling frameworks, allowing their rapid application to field systems. Furthermore, we use optimization on our sample of sparrow colonies to demonstrate how such models, linking populations to their habitats, permit the design of practical and environmentally sound habitat manipulations for managing populations.
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http://dx.doi.org/10.1098/rspb.2018.2911DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6501931PMC
April 2019

Mesocosm experiments reveal the impact of mosquito control measures on malaria vector life history and population dynamics.

Sci Rep 2018 09 17;8(1):13949. Epub 2018 Sep 17.

Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, United Kingdom.

The impact of control measures on mosquito vector fitness and demography is usually estimated from bioassays or indirect variables in the field. Whilst indicative, neither approach is sufficient to quantify the potentially complex response of mosquito populations to combined interventions. Here, large replicated mesocosms were used to measure the population-level response of the malaria vector Anopheles arabiensis to long-lasting insecticidal nets (LLINs) when used in isolation, or combined with insecticidal eave louvers (EL), or treatment of cattle with the endectocide Ivermectin (IM). State-space models (SSM) were fit to these experimental data, revealing that LLIN introduction reduced adult mosquito survival by 91% but allowed population persistence. ELs provided no additional benefit, but IM reduced mosquito fecundity by 59% and nearly eliminated all populations when combined with LLINs. This highlights the value of IM for integrated vector control, and mesocosm population experiments combined with SSM for identifying optimal combinations for vector population elimination.
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http://dx.doi.org/10.1038/s41598-018-31805-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141522PMC
September 2018

Linking resource selection and step selection models for habitat preferences in animals.

Ecology 2019 01 28;100(1):e02452. Epub 2018 Nov 28.

IBAHCM, University of Glasgow, Graham Kerr, Glasgow, G12 8QQ, UK.

The two dominant approaches for the analysis of species-habitat associations in animals have been shown to reach divergent conclusions. Models fitted from the viewpoint of an individual (step selection functions), once scaled up, do not agree with models fitted from a population viewpoint (resource selection functions [RSFs]). We explain this fundamental incompatibility, and propose a solution by introducing to the animal movement field a novel use for the well-known family of Markov chain Monte Carlo (MCMC) algorithms. By design, the step selection rules of MCMC lead to a steady-state distribution that coincides with a given underlying function: the target distribution. We therefore propose an analogy between the movements of an animal and the movements of an MCMC sampler, to guarantee convergence of the step selection rules to the parameters underlying the population's utilization distribution. We introduce a rejection-free MCMC algorithm, the local Gibbs sampler, that better resembles real animal movement, and discuss the wide range of biological assumptions that it can accommodate. We illustrate our method with simulations on a known utilization distribution, and show theoretically and empirically that locations simulated from the local Gibbs sampler give rise to the correct RSF. Using simulated data, we demonstrate how this framework can be used to estimate resource selection and movement parameters.
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http://dx.doi.org/10.1002/ecy.2452DOI Listing
January 2019

Overcoming the Data Crisis in Biodiversity Conservation.

Trends Ecol Evol 2018 09 7;33(9):676-688. Epub 2018 Jul 7.

Institute of Biodiversity, Animal Health and Comparative Medicine, Graham Kerr Building, University of Glasgow, Glasgow G12 8QQ, UK.

How can we track population trends when monitoring data are sparse? Population declines can go undetected, despite ongoing threats. For example, only one of every 200 harvested species are monitored. This gap leads to uncertainty about the seriousness of declines and hampers effective conservation. Collecting more data is important, but we can also make better use of existing information. Prior knowledge of physiology, life history, and community ecology can be used to inform population models. Additionally, in multispecies models, information can be shared among taxa based on phylogenetic, spatial, or temporal proximity. By exploiting generalities across species that share evolutionary or ecological characteristics within Bayesian hierarchical models, we can fill crucial gaps in the assessment of species' status with unparalleled quantitative rigor.
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http://dx.doi.org/10.1016/j.tree.2018.06.004DOI Listing
September 2018

Variations in household microclimate affect outdoor-biting behaviour of malaria vectors.

Wellcome Open Res 2017 24;2:102. Epub 2017 Oct 24.

Department of Environmental Health and Ecological Sciences, Ifakara Health Institute, Ifakara, Tanzania.

: Mosquito behaviours including the degree to which they bite inside houses or outside is a crucial determinant of human exposure to malaria. Whilst seasonality in mosquito vector abundance is well documented, much less is known about the impact of climate on mosquito behaviour. We investigated how variations in household microclimate affect outdoor-biting by malaria vectors, and . : Mosquitoes were sampled indoors and outdoors weekly using human landing catches at eight households in four villages in south-eastern Tanzania, resulting in 616 trap-nights over 12 months. Daily temperature, relative humidity and rainfall were recorded. Generalized additive mixed models (GAMMs) were used to test associations between mosquito abundance and the microclimatic conditions. Generalized linear mixed models (GLMMs) were used to investigate the influence of microclimatic conditions on the tendency of vectors to bite outdoors (proportion of outdoor biting). :  abundance peaked during high rainfall months (February-May), whilst density remained stable into the dry season (May-August) Across the range of observed household temperatures, a rise of 1 C marginally increased nightly abundance (~11%), but more prominently increased abundance (~66%). The abundance of and showed strong positive associations with time-lagged rainfall (2-3 and 3-4 weeks before sampling). The degree of outdoor biting in was significantly associated with the relative temperature difference between indoor and outdoor environments, with exophily increasing as temperature inside houses became relatively warmer. The exophily of did not vary with temperature differences.   : This study demonstrates that malaria vector shifts the location of its biting from indoors to outdoors in association with relative differences in microclimatic conditions. These environmental impacts could give rise to seasonal variation in mosquito biting behaviour and degree of protection provided by indoor-based vector control strategies.
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http://dx.doi.org/10.12688/wellcomeopenres.12928.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829465PMC
October 2017

Avoidance of wind farms by harbour seals is limited to pile driving activities.

J Appl Ecol 2016 12 23;53(6):1642-1652. Epub 2016 May 23.

Sea Mammal Research Unit University of St Andrews St Andrews Fife KY16 8LB UK.

As part of global efforts to reduce dependence on carbon-based energy sources there has been a rapid increase in the installation of renewable energy devices. The installation and operation of these devices can result in conflicts with wildlife. In the marine environment, mammals may avoid wind farms that are under construction or operating. Such avoidance may lead to more time spent travelling or displacement from key habitats. A paucity of data on at-sea movements of marine mammals around wind farms limits our understanding of the nature of their potential impacts.Here, we present the results of a telemetry study on harbour seals in The Wash, south-east England, an area where wind farms are being constructed using impact pile driving. We investigated whether seals avoid wind farms during operation, construction in its entirety, or during piling activity. The study was carried out using historical telemetry data collected prior to any wind farm development and telemetry data collected in 2012 during the construction of one wind farm and the operation of another.Within an operational wind farm, there was a close-to-significant increase in seal usage compared to prior to wind farm development. However, the wind farm was at the edge of a large area of increased usage, so the presence of the wind farm was unlikely to be the cause.There was no significant displacement during construction as a whole. However, during piling, seal usage (abundance) was significantly reduced up to 25 km from the piling activity; within 25 km of the centre of the wind farm, there was a 19 to 83% (95% confidence intervals) decrease in usage compared to during breaks in piling, equating to a mean estimated displacement of 440 individuals. This amounts to significant displacement starting from predicted received levels of between 166 and 178 dB re 1 μPa. Displacement was limited to piling activity; within 2 h of cessation of pile driving, seals were distributed as per the non-piling scenario. . Our spatial and temporal quantification of avoidance of wind farms by harbour seals is critical to reduce uncertainty and increase robustness in environmental impact assessments of future developments. Specifically, the results will allow policymakers to produce industry guidance on the likelihood of displacement of seals in response to pile driving; the relationship between sound levels and avoidance rates; and the duration of any avoidance, thus allowing far more accurate environmental assessments to be carried out during the consenting process. Further, our results can be used to inform mitigation strategies in terms of both the sound levels likely to cause displacement and what temporal patterns of piling would minimize the magnitude of the energetic impacts of displacement.
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http://dx.doi.org/10.1111/1365-2664.12678DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5111737PMC
December 2016

Inference of the drivers of collective movement in two cell types: Dictyostelium and melanoma.

J R Soc Interface 2016 10;13(123)

School of Mathematics and Statistics, College of Science and Engineering, University of Glasgow, Glasgow, UK.

Collective cell movement is a key component of many important biological processes, including wound healing, the immune response and the spread of cancers. To understand and influence these movements, we need to be able to identify and quantify the contribution of their different underlying mechanisms. Here, we define a set of six candidate models-formulated as advection-diffusion-reaction partial differential equations-that incorporate a range of cell movement drivers. We fitted these models to movement assay data from two different cell types: Dictyostelium discoideum and human melanoma. Model comparison using widely applicable information criterion suggested that movement in both of our study systems was driven primarily by a self-generated gradient in the concentration of a depletable chemical in the cells' environment. For melanoma, there was also evidence that overcrowding influenced movement. These applications of model inference to determine the most likely drivers of cell movement indicate that such statistical techniques have potential to support targeted experimental work in increasing our understanding of collective cell movement in a range of systems.
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http://dx.doi.org/10.1098/rsif.2016.0695DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5095226PMC
October 2016

Seabird diversity hotspot linked to ocean productivity in the Canary Current Large Marine Ecosystem.

Biol Lett 2016 Aug;12(8)

Environment and Sustainability Institute, University of Exeter, Penryn, Cornwall TR10 9EZ, UK

Upwelling regions are highly productive habitats targeted by wide-ranging marine predators and industrial fisheries. In this study, we track the migratory movements of eight seabird species from across the Atlantic; quantify overlap with the Canary Current Large Marine Ecosystem (CCLME) and determine the habitat characteristics that drive this association. Our results indicate the CCLME is a biodiversity hotspot for migratory seabirds; all tracked species and more than 70% of individuals used this upwelling region. Relative species richness peaked in areas where sea surface temperature averaged between 15 and 20°C, and correlated positively with chlorophyll a, revealing the optimum conditions driving bottom-up trophic effects for seabirds. Marine vertebrates are not confined by international boundaries, making conservation challenging. However, by linking diversity to ocean productivity, our research reveals the significance of the CCLME for seabird populations from across the Atlantic, making it a priority for conservation action.
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http://dx.doi.org/10.1098/rsbl.2016.0024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5014014PMC
August 2016

Delayed mortality effects cut the malaria transmission potential of insecticide-resistant mosquitoes.

Proc Natl Acad Sci U S A 2016 08 11;113(32):8975-80. Epub 2016 Jul 11.

Boyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom;

Malaria transmission has been substantially reduced across Africa through the distribution of long-lasting insecticidal nets (LLINs). However, the emergence of insecticide resistance within mosquito vectors risks jeopardizing the future efficacy of this control strategy. The severity of this threat is uncertain because the consequences of resistance for mosquito fitness are poorly understood: while resistant mosquitoes are no longer immediately killed upon contact with LLINs, their transmission potential may be curtailed because of longer-term fitness costs that persist beyond the first 24 h after exposure. Here, we used a Bayesian state-space model to quantify the immediate (within 24 h of exposure) and delayed (>24 h after exposure) impact of insecticides on daily survival and malaria transmission potential of moderately and highly resistant laboratory populations of the major African malaria vector Anopheles gambiae Contact with LLINs reduced the immediate survival of moderately and highly resistant An. gambiae strains by 60-100% and 3-61%, respectively, and delayed mortality impacts occurring beyond the first 24 h after exposure further reduced their overall life spans by nearly one-half. In total, insecticide exposure was predicted to reduce the lifetime malaria transmission potential of insecticide-resistant vectors by two-thirds, with delayed effects accounting for at least one-half of this reduction. The existence of substantial, previously unreported, delayed mortality effects within highly resistant malaria vectors following exposure to insecticides does not diminish the threat of growing resistance, but posits an explanation for the apparent paradox of continued LLIN effectiveness in the presence of high insecticide resistance.
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http://dx.doi.org/10.1073/pnas.1603431113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987804PMC
August 2016

Defining the scale of habitat availability for models of habitat selection.

Ecology 2016 May;97(5):1113-22

Statistical models of habitat preference and species distribution (e.g., Resource Selection Functions and Maximum Entropy approaches) perform a quantitative comparison of the use of space with the availability of all habitats in an animal's environment. However, not all of space is accessible all of the time to all individuals, so availability is in fact determined by limitations in animal perception and mobility. Therefore, measuring habitat availability at biologically relevant scales is essential for understanding preference, but herein lies a trade-off: Models fitted at large spatial scales, will tend to average across the responses of different individuals that happen to be in regions with contrasting habitat compositions. We suggest that such models may fail to capture local extremes (hotspots and coldspots) in animal usage and call this potential problem, homogenization. In contrast, models fitted at smaller scales will vary stochastically depending on the particular habitat composition of their narrow spatial neighborhood, and hence fail to describe responses when predicting for different sampling instances. This is the now well-documented issue of non-transferability of habitat models. We illustrate this tradeoff, using a range of simulated experiments, incorporating variations in environmental gradients, richness and fragmentation. We propose diagnostics for detecting the two issues of homogenization and non-transferability and show that these scale-related symptoms are likely to be more pronounced in highly fragmented or steeply graded landscapes. Further, we address these problems by treating the neighborhood of each cell in the landscape grid as an individual sampling instance (with its own neighborhood), hence allowing coefficients to respond to the local expectations of environmental variables according to a Generalized Functional Response (GFR). Under simulation this approach is consistently better at estimating robust (i.e., transferable) habitat models at smaller scales, and less susceptible to homogenization at larger scales. At the same time, it represents the first application of a GFR to continuous space (rather than multiple, spatially distinct datasets), allowing the predictive advantages of this extension of species distribution models to become available to data from large-scale but single-site field studies.
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http://dx.doi.org/10.1890/14-2241.1DOI Listing
May 2016

Are we failing to protect threatened mangroves in the Sundarbans world heritage ecosystem?

Sci Rep 2016 Feb 16;6:21234. Epub 2016 Feb 16.

Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow G12 8QQ, United Kingdom.

The Sundarbans, the largest mangrove ecosystem in the world, is under threat from historical and future human exploitation and sea level rise. Limited scientific knowledge on the spatial ecology of the mangroves in this world heritage ecosystem has been a major impediment to conservation efforts. Here, for the first time, we report on habitat suitability analyses and spatial density maps for the four most prominent mangrove species--Heritiera fomes, Excoecaria agallocha, Ceriops decandra and Xylocarpus mekongensis. Globally endangered H. fomes abundances declined as salinity increased. Responses to nutrients, elevation, and stem density varied between species. H. fomes and X. mekongensis preferred upstream habitats. E. agallocha and C. decandra preferred down-stream and mid-stream habitats. Historical harvesting had negative influences on H. fomes, C. decandra and X. mekongensis abundances. The established protected area network does not support the most suitable habitats of these threatened species. We therefore recommend a reconfiguration of the network to include these suitable habitats and ensure their immediate protection. These novel habitat insights and spatial predictions can form the basis for future forest studies and spatial conservation planning, and have implications for more effective conservation of the Sundarbans mangroves and the many other species that rely on them.
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http://dx.doi.org/10.1038/srep21234DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4754640PMC
February 2016

Indirect effects of primary prey population dynamics on alternative prey.

Theor Popul Biol 2015 Aug 27;103:44-59. Epub 2015 Apr 27.

Centre for Research into Ecological and Environmental Modelling, University of St-Andrews, United Kingdom; Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, United Kingdom.

We develop a theory of generalist predation showing how alternative prey species are affected by changes in both mean abundance and variability (coefficient of variation) of their predator's primary prey. The theory is motivated by the indirect effects of cyclic rodent populations on ground-breeding birds, and developed through progressive analytic simplifications of an empirically-based model. It applies nonetheless to many other systems where primary prey have fast life-histories and can become superabundant, thus facilitating impact on alternative prey species and generating highly asymmetric interactions. Our results suggest that predator effects on alternative prey should generally decrease with mean primary prey abundance, and increase with primary prey variability (low to high CV)-unless predators have strong aggregative responses, in which case these results can be reversed. Approximations of models including predator dynamics (general numerical response with possible delays) confirm these results but further suggest that negative temporal correlation between predator and primary prey is harmful to alternative prey. Finally, we find that measurements of predator numerical responses are crucial to predict-even qualitatively-the response of ecosystems to changes in the dynamics of outbreaking prey species.
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http://dx.doi.org/10.1016/j.tpb.2015.04.002DOI Listing
August 2015

Dynamics of a morbillivirus at the domestic-wildlife interface: Canine distemper virus in domestic dogs and lions.

Proc Natl Acad Sci U S A 2015 Feb 20;112(5):1464-9. Epub 2015 Jan 20.

Boyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom;

Morbilliviruses cause many diseases of medical and veterinary importance, and although some (e.g., measles and rinderpest) have been controlled successfully, others, such as canine distemper virus (CDV), are a growing concern. A propensity for host-switching has resulted in CDV emergence in new species, including endangered wildlife, posing challenges for controlling disease in multispecies communities. CDV is typically associated with domestic dogs, but little is known about its maintenance and transmission in species-rich areas or about the potential role of domestic dog vaccination as a means of reducing disease threats to wildlife. We address these questions by analyzing a long-term serological dataset of CDV in lions and domestic dogs from Tanzania's Serengeti ecosystem. Using a Bayesian state-space model, we show that dynamics of CDV have changed considerably over the past three decades. Initially, peaks of CDV infection in dogs preceded those in lions, suggesting that spill-over from dogs was the main driver of infection in wildlife. However, despite dog-to-lion transmission dominating cross-species transmission models, infection peaks in lions became more frequent and asynchronous from those in dogs, suggesting that other wildlife species may play a role in a potentially complex maintenance community. Widespread mass vaccination of domestic dogs reduced the probability of infection in dogs and the size of outbreaks but did not prevent transmission to or peaks of infection in lions. This study demonstrates the complexity of CDV dynamics in natural ecosystems and the value of long-term, large-scale datasets for investigating transmission patterns and evaluating disease control strategies.
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http://dx.doi.org/10.1073/pnas.1411623112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4321234PMC
February 2015
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