Mafalda Viana

A review of cephalopod—environment interactions in European Seas

Cephalopods are highly sensitive to environmental conditions and changes at a range of spatial and temporal scales. Relationships documented between cephalopod stock dynamics and environmental conditions are of two main types: those concerning the geographic distribution of abundance, for which the mechanism is often unknown, and those relating to biological processes such as egg survival, growth, recruitment and migration, where mechanisms are sometimes known and in a very few cases demonstrated by experimental evidence. Cephalopods seem to respond to environmental variation both ‘actively’ (e.g. migrating to areas with more favoured environmental conditions for feeding or spawning) and ‘passively’ (growth and survival vary according to conditions experienced, passive migration with prevailing currents). Environmental effects on early life stages can affect life history characteristics (growth and maturation rates) as well as distribution and abundance. Both large-scale atmospheric and oceanic processes and local environmental variation appear to play important roles in species–environment interactions. While oceanographic conditions are of particular significance for mobile pelagic species such as the ommastrephid squids, the less widely ranging demersal and benthic species may be more dependent on other physical habitat characteristics (e.g. substrate and bathymetry). Coastal species may be impacted by variations in water quality and salinity (related to rainfall and river flow). Gaps in current knowledge and future research priorities are discussed. Key research goals include linking distribution and abundance to environmental effects on biological processes, and using such knowledge to provide environmental indicators and to underpin fishery management.

On the dimensionality of ecological stability

Ecological stability is touted as a complex and multifaceted concept, including components such as variability, resistance, resilience, persistence and robustness. Even though a complete appreciation of the effects of perturbations on ecosystems requires the simultaneous measurement of these multiple components of stability, most ecological research has focused on one or a few of those components analysed in isolation. Here, we present a new view of ecological stability that recognises explicitly the non-independence of components of stability. This provides an approach for simplifying the concept of stability. We illustrate the concept and approach using results from a field experiment, and show that the effective dimensionality of ecological stability is considerably lower than if the various components of stability were unrelated. However, strong perturbations can modify, and even decouple, relationships among individual components of stability. Thus, perturbations not only increase the dimensionality of stability but they can also alter the relationships among components of stability in different ways. Studies that focus on single forms of stability in isolation therefore risk underestimating significantly the potential of perturbations to destabilise ecosystems. In contrast, application of the multidimensional stability framework that we propose gives a far richer understanding of how communities respond to perturbations.

Assembling evidence for identifying reservoirs of infection

Many pathogens persist in multihost systems, making the identification of infection reservoirs crucial for devising effective interventions. Here, we present a conceptual framework for classifying patterns of incidence and prevalence, and review recent scientific advances that allow us to study and manage reservoirs simultaneously. We argue that interventions can have a crucial role in enriching our mechanistic understanding of how reservoirs function and should be embedded as quasi-experimental studies in adaptive management frameworks. Single approaches to the study of reservoirs are unlikely to generate conclusive insights whereas the formal integration of data and methodologies, involving interventions, pathogen genetics, and contemporary surveillance techniques, promises to open up new opportunities to advance understanding of complex multihost systems.

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

Significance Morbilliviruses are a growing concern because of their ability to infect multiple species. The spill-over of canine distemper virus (CDV) from domestic dogs has been associated with severe declines in wild carnivores worldwide, and therefore mass dog vaccination has been suggested as a potential control strategy. Focusing on three decades of CDV exposure data in dogs and lions of the Serengeti, we show that cyclic infection dynamics in lions initially driven by dogs became more frequent and asynchronous, suggesting that the wider dog population and other wildlife species drive CDV dynamics. Hence, although widespread dog vaccination reduced the infection in dogs, transmission to lion populations still occurred, warranting further investigation into effective management options of CDV in this species-rich ecosystem. 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.

Dynamics of a morbillivirus at the domestic -wildlife interface

Significance Morbilliviruses are a growing concern because of their ability to infect multiple species. The spill-over of canine distemper virus (CDV) from domestic dogs has been associated with severe declines in wild carnivores worldwide, and therefore mass dog vaccination has been suggested as a potential control strategy. Focusing on three decades of CDV exposure data in dogs and lions of the Serengeti, we show that cyclic infection dynamics in lions initially driven by dogs became more frequent and asynchronous, suggesting that the wider dog population and other wildlife species drive CDV dynamics. Hence, although widespread dog vaccination reduced the infection in dogs, transmission to lion populations still occurred, warranting further investigation into effective management options of CDV in this species-rich ecosystem. 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.

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

Significance Insecticide resistance poses one of the greatest challenges to the control of malaria and other vector-borne diseases. Quantifying the magnitude of its impact is essential to ensure the sustainability of future control programs. Mosquito vectors are defined as “resistant” when insecticides are no longer able to kill them on contact. However, they may suffer longer-term impairment following insecticide exposure that reduces their ability to transmit disease. We show that even highly resistant strains of the major malaria vector Anopheles gambiae have their life span cut by ∼50% after exposure to long-lasting insecticidal nets (LLINs). These delayed effects are sufficient to reduce their malaria transmission potential by two-thirds and could partially explain why insecticide resistance is not inextricably associated with LLIN failure. 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.

Cooperative secretions facilitate host range expansion in bacteria

The majority of emergent human pathogens are zoonotic in origin, that is, they can transmit to humans from other animals. Understanding the factors underlying the evolution of pathogen host range is therefore of critical importance in protecting human health. There are two main evolutionary routes to generalism: organisms can tolerate multiple environments or they can modify their environments to forms to which they are adapted. Here we use a combination of theory and a phylogenetic comparative analysis of 191 pathogenic bacterial species to show that bacteria use cooperative secretions that modify their environment to extend their host range and infect multiple host species. Our results suggest that cooperative secretions are key determinants of host range in bacteria, and that monitoring for the acquisition of secreted proteins by horizontal gene transfer can help predict emerging zoonoses.

Importance of long-term cycles for predicting water level dynamics in natural lakes.

Lakes are disproportionately important ecosystems for humanity, containing 77% of the liquid surface freshwater on Earth and comprising key contributors to global biodiversity. With an ever-growing human demand for water and increasing climate uncertainty, there is pressing need for improved understanding of the underlying patterns of natural variability of water resources and consideration of their implications for water resource management and conservation. Here we use Bayesian harmonic regression models to characterise water level dynamics and study the influence of cyclic components in confounding estimation of long-term directional trends in water levels in natural Irish lakes. We found that the lakes were characterised by a common and well-defined annual seasonality and several inter-annual and inter-decadal cycles with strong transient behaviour over time. Importantly, failing to account for the longer-term cyclic components produced a significant overall underestimation of the trend effect. Our findings demonstrate the importance of contextualising lake water resource management to the specific physical setting of lakes.

Ignoring discards biases the assessment of fisheries' ecological fingerprint

Understanding the pressures of fisheries on the ecosystem is crucial for effective management. Fishery removals, or catch, are composed of both landings and discards. However, the use of discards data in studies investigating the effect of the fishing pressures is sparse. Here, we explore the individual contribution of both these catch components to the overall pressure of fisheries on the ecosystem metrics. Using Irish observer data, we compare the linear relationship between several ecological metrics calculated for landings and discards with those of catch. Our results show that in fisheries with high discarding rates, discards can drive the fisheries’ ecological fingerprint and highlight the need to rectify landings-based estimates to make them representative of those of catch in order to gain a robust picture of the impact of fisheries.

Integrating serological and genetic data to quantify cross-species transmission: brucellosis as a case study.

SUMMARY Epidemiological data are often fragmented, partial, and/or ambiguous and unable to yield the desired level of understanding of infectious disease dynamics to adequately inform control measures. Here, we show how the information contained in widely available serology data can be enhanced by integration with less common type-specific data, to improve the understanding of the transmission dynamics of complex multi-species pathogens and host communities. Using brucellosis in northern Tanzania as a case study, we developed a latent process model based on serology data obtained from the field, to reconstruct Brucella transmission dynamics. We were able to identify sheep and goats as a more likely source of human and animal infection than cattle; however, the highly cross-reactive nature of Brucella spp. meant that it was not possible to determine which Brucella species (B. abortus or B. melitensis) is responsible for human infection. We extended our model to integrate simulated serology and typing data, and show that although serology alone can identify the host source of human infection under certain restrictive conditions, the integration of even small amounts (5%) of typing data can improve understanding of complex epidemiological dynamics. We show that data integration will often be essential when more than one pathogen is present and when the distinction between exposed and infectious individuals is not clear from serology data. With increasing epidemiological complexity, serology data become less informative. However, we show how this weakness can be mitigated by integrating such data with typing data, thereby enhancing the inference from these data and improving understanding of the underlying dynamics.