Merging DNA metabarcoding and ecological network analysis to understand and build resilient terrestrial ecosystems

Summary 1. Significant advances in both mathematical and molecular approaches in ecology offer unprecedented opportunities to describe and understand ecosystem functioning. Ecological networks describe interactions between species, the underlying structure of communities and the function and stability of ecosystems. They provide the ability to assess the robustness of complex ecological communities to species loss, as well as a novel way of guiding restoration. However, empirically quantifying the interactions between entire communities remains a significant challenge. 2. Concomitantly, advances in DNA sequencing technologies are resolving previously intractable questions in functional and taxonomic biodiversity and provide enormous potential to determine hitherto difficult to observe species interactions. Combining DNA metabarcoding approaches with ecological network analysis presents important new opportunities for understanding large-scale ecological and evolutionary processes, as well as providing powerful tools for building ecosystems that are resilient to environmental change. 3. We propose a novel ‘nested tagging’ metabarcoding approach for the rapid construction of large, phylogenetically structured species-interaction networks. Taking tree–insect–parasitoid ecological networks as an illustration, we show how measures of network robustness, constructed using DNA metabarcoding, can be used to determine the consequences of tree species loss within forests, and forest habitat loss within wider landscapes. By determining which species and habitats are important to network integrity, we propose new directions for forest management. 4. Merging metabarcoding with ecological network analysis provides a revolutionary opportunity to construct some of the largest, phylogenetically structured species-interaction networks to date, providing new ways to: (i) monitor biodiversity and ecosystem functioning; (ii) assess the robustness of interacting communities to species loss; and (iii) build ecosystems that are more resilient to environmental change

Merging DNA metabarcoding and ecological network analysis to understand and build resilient terrestrial ecosystems

1. Significant advances in both mathematical and molecular approaches in ecology offer unprecedented opportunities to describe and understand ecosystem functioning. Ecological networks describe interactions between species, the underlying structure of communities and the function and stability of ecosystems. They provide the ability to assess the robustness of complex ecological communities to species loss, as well as a novel way of guiding restoration. However, empirically quantifying the interactions between entire communities remains a significant challenge. 2. Concomitantly, advances in DNA sequencing technologies are resolving previously intractable questions in functional and taxonomic biodiversity and provide enormous potential to determine hitherto difficult to observe species interactions. Combining DNA metabarcoding approaches with ecological network analysis presents important new opportunities for understanding large-scale ecological and evolutionary processes, as well as providing powerful tools for building ecosystems that are resilient to environmental change. 3. We propose a novel ‘nested tagging’ metabarcoding approach for the rapid construction of large, phylogenetically structured species-interaction networks. Taking tree–insect–parasitoid ecological networks as an illustration, we show how measures of network robustness, constructed using DNA metabarcoding, can be used to determine the consequences of tree species loss within forests, and forest habitat loss within wider landscapes. By determining which species and habitats are important to network integrity, we propose new directions for forest management. 4. Merging metabarcoding with ecological network analysis provides a revolutionary opportunity to construct some of the largest, phylogenetically structured species-interaction networks to date, providing new ways to: (i) monitor biodiversity and ecosystem functioning; (ii) assess the robustness of interacting communities to species loss; and (iii) build ecosystems that are more resilient to environmental change

Comparative review of human and canine osteosarcoma: morphology, epidemiology, prognosis, treatment and genetics

Osteosarcoma (OSA) is a rare cancer in people. However OSA incidence rates in dogs are 27 times higher than in people. Prognosis in both species is poor, with five year osteosarcoma survival rates in people not having improved in decades. For dogs, one year survival rates are only around ~45%. Improved and novel treatment regimens are urgently required to improve survival in both humans and dogs with OSA. Utilising information from genetic studies could assist in this in both species, with the higher incidence rates in dogs contributing to the dog population being a good model of human disease. This review compares the clinical characteristics, gross morphology and histopathology, aetiology, epidemiology, and genetics of canine and human osteosarcoma. Finally, the current position of canine osteosarcoma genetic research is discussed and areas for additional work within the canine population are identified

The relationship between pheromone trap catch and local population density of the oak processionary moth Thaumetopoea processionea (Lepidoptera: Thaumetopoeidae)

1. Oak processionary moth (OPM) was introduced into the U.K. in 2004–2005 and pheromone traps have been used to monitor its spread and provide an early warning of the colonization of new areas. 2. The traps capture adult male OPM, although catches are highly variable and it has proved difficult to establish a relationship between the numbers of males caught and local population densities. 3. Surveys carried out around 260 pheromone traps as part of the U.K. OPM control programme, however, reveal a consistent linear relationship between square‐root transformed adult males per trap and cube‐root (or log10) transformed numbers of larval nests (r2 = 0.47; P < 0.001) 4. In 91% of cases where traps captured no adult males, there were no OPM nests within 250 m and, where nests were present, the numbers of nests were low. Traps that captured more than 10–20 males were associated with counts of ≥ 50 larval nests. 5. Defoliation and risks to human health from OPM are more closely related to nest density (i.e. the numbers of nests per tree). Consequently, identifying trap catches that might initiate a management response also requires information on the number of oak trees in the surrounding area

Detecting host-parasitoid interactions in an invasive Lepidopteran using nested tagging DNA metabarcoding

Determining the host-parasitoid interactions and parasitism rates for invasive species entering novel environments is an important first step in assessing potential routes for biocontrol and integrated pest management. Conventional insect rearing techniques followed by taxonomic identification are widely used to obtain such data, but this can be time-consuming and prone to biases. Here, we present a next-generation sequencing approach for use in ecological studies which allows for individual-level metadata tracking of large numbers of invertebrate samples through the use of hierarchically organised molecular identification tags. We demonstrate its utility using a sample data set examining both species identity and levels of parasitism in late larval stages of the oak processionary moth (Thaumetopoea processionea-Linn. 1758), an invasive species recently established in the United Kingdom. Overall, we find that there are two main species exploiting the late larval stages of oak processionary moth in the United Kingdom with the main parasitoid (Carcelia iliaca-Ratzeburg, 1840) parasitising 45.7% of caterpillars, while a rare secondary parasitoid (Compsilura concinnata-Meigen, 1824) was also detected in 0.4% of caterpillars. Using this approach on all life stages of the oak processionary moth may demonstrate additional parasitoid diversity. We discuss the wider potential of nested tagging DNA metabarcoding for constructing large, highly resolved species interaction networks.</p