Evidence for the Role of Infectious Disease in Species Extinction and Endangerment

Inefficient global nutrient (i.e., phosphorus (P) and nitrogen (N)) management leads to an increase in nutrient delivery to freshwater and coastal ecosystems and induces eutrophication in these aquatic environments. This process threatens the various species inhabiting these ecosystems. In this study, we developed regionalized characterization factors (CFs) for freshwater eutrophication at 0.5 × 0.5-degree resolution, considering different fates for direct emissions to freshwater, diffuse emissions, and increased erosion due to agricultural land use. The CFs were provided for global and regional species loss of freshwater fish. CFs for global species loss were quantified by integrating global extinction probabilities. Results showed that the CFs for P and N impacts on freshwater fish are higher in densely populated regions that encompass either large lakes or the headwaters of large rivers. Focusing on nutrient-limited areas increases country-level CFs in 51.9 % of the countries for P and 49.5 % of the countries for N compared to not considering nutrient limitation. This study highlights the relevance of considering freshwater eutrophication impacts via both P and N emissions and identifying the limiting nutrient when performing life cycle impact assessments.

Characterisation of ranaviral infection and its management in Australian lizards

The idea that Earth is currently experiencing a sixth mass extinction is widespread. We critically evaluate this claim. Very few studies have tested this idea. Some studies showed that recent extinction rates are faster than fossil background rates, but extinction rates can exceed background rates outside mass extinctions. Other studies extrapolated from recent extinctions to project 75% global species loss. But these recent extinctions were mostly of island species. No cause was specified for these future extinctions, and >50% of assessed species are considered non-threatened. We find numerous other issues. Proponents of the sixth mass extinction have made invaluable contributions by highlighting recent extinctions, but these extinctions may not be equivalent to past mass extinctions or relevant to current threats.

Strengthening the BTWC: The role of the Biological and Toxin Weapons Convention in combating natural and deliberate disease outbreaks

Infectious disease, especially virulent infectious disease, is commonly regarded as a cause of fluctuation or decline in biological populations. However, it is not generally considered as a primary factor in causing the actual endangerment or extinction of species. We review here the known historical examples in which disease has, or has been assumed to have had, a major deleterious impact on animal species, including extinction, and highlight some recent cases in which disease is the chief suspect in causing the outright endangerment of particular species. We conclude that the role of disease in historical extinctions at the population or species level may have been underestimated. Recent methodological breakthroughs may lead to a better understanding of the past and present roles of infectious disease in influencing population fitness and other parameters.

Recent increases in the magnitude and rate of environmental change, including habitat loss, climate change and overexploitation, have been directly linked to the global loss of biodiversity. Wildlife extinction rates are estimated to be 100–1000 times greater than the historical norm, and up to 50% of higher taxonomic groups are critically endangered. While many types of environmental changes threaten the survival of species all over the planet, infectious disease has rarely been cited as the primary cause of global species extinctions. There is substantial evidence, however, that diseases can greatly impact local species populations by causing temporary or permanent declines in abundance. More importantly, pathogens can interact with other driving factors, such as habitat loss, climate change, overexploitation, invasive species and environmental pollution to contribute to local and global extinctions. Regrettably, our current lack of knowledge about the diversity and abundance of pathogens in natural systems has made it difficult to establish the relative importance of disease as a significant driver of species extinction, and the context when this is most likely to occur. Here, we review the role of infectious diseases in biological conservation. We summarize existing knowledge of disease‐induced extinction at global and local scales and review the ecological and evolutionary forces that may facilitate disease‐mediated extinction risk. We suggest that while disease alone may currently threaten few species, pathogens may be a significant threat to already‐endangered species, especially when disease interacts with other drivers. We identify control strategies that may help reduce the negative effects of disease on wildlife and discuss the most critical challenges and future directions for the study of infectious diseases in the conservation sciences.

Leaf litter decomposition is a major ecosystem process that can link aquatic to terrestrial ecosystems by flows of nutrients. Biodiversity and ecosystem functioning research hypothesizes that the global loss of species leads to impaired decomposition rates and thus to slower recycling of nutrients. Especially in aquatic systems, an understanding of diversity effects on litter decomposition is still incomplete.Here we conducted an experiment to test two main factors associated with global species loss that might influence leaf litter decomposition. First, we tested whether mixing different leaf species alters litter decomposition rates compared to decomposition of these species in monoculture. Second, we tested the effect of the size structure of a lotic decomposer community on decomposition rates.Overall, leaf litter identity strongly affected decomposition rates, and the observed decomposition rates matched measures of metabolic activity and microbial abundances. While we found some evidence of a positive leaf litter diversity effect on decomposition, this effect was not coherent across all litter combinations and the effect was generally additive and not synergistic.Microbial communities, with a reduced functional and trophic complexity, showed a small but significant overall reduction in decomposition rates compared to communities with the naturally complete functional and trophic complexity, highlighting the importance of a complete microbial community on ecosystem functioning.Our results suggest that top‐down diversity effects of the decomposer community on litter decomposition in aquatic systems are of comparable importance as bottom‐up diversity effects of primary producers.Aplain language summaryis available for this article.

Reduced river discharge and flow regulation are significant threats to freshwater biodiversity. An accurate representation of potential damage of water consumption on freshwater biodiversity is required to quantify and compare the environmental impacts of global value chains. The effect of discharge reduction on fish species richness was previously modeled in life cycle impact assessment, but models were limited by the restricted geographical scope of underlying species-discharge relationships and the small number of species data. Here, we propose a model based on a novel regionalized species-discharge relationship (SDR). Our SDR-based model covers 88 % of the global landmass (2320 river basins worldwide excluding deserts and permanently frozen areas) and is based on a global dataset of 11,450 riverine fish species, simulated river discharge, elevation, and climate zones. We performed 10-fold cross-validation to select the best set of predictors and validated the obtained SDRs based on observed discharge data. Our model performed better than previous SDRs employed in life cycle impact assessment (Kling-Gupta efficiency coefficient about 4 times larger). We provide both marginal and average models with their uncertainty ranges for assessing scenarios of small and large-scale water consumption, respectively, and include regional and global species loss. We conducted an illustrative case study to showcase the method's applicability and highlight the differences with the currently used approach. Our models are useful for supporting sustainable water consumption and riverine fish biodiversity conservation decisions. They enable a more specific, reliable, and complete impact assessment by differentiating impacts on regional riverine fish species richness and irreversible global losses, including up-to-date species data, and providing spatially explicit values with high geographical coverage.

Since the early twentieth century, different general laws have been investigated to understand mechanisms driving stability in natural ecosystems, but until today the mechanisms are still generally unexplored. The main goal for ecology is to understand mechanisms driving food web dynamics, to counteract the hazard of global species loss. The studies presented in this thesis investigate the general scaling of different strucural food web (e.g. diversity, connectance, vulnerabilty) and species properties (e.g. body mass, trophic level), and how these properties influence secondary extinctions in food webs. The backbone of this thesis is a database of food webs , including information about predator–prey interactions, the metabolic type, and the species’ body mass. The relationship between diversity and topology is widely discussed, especially the hypothesis that a constant number of species per link leads to a decreasing connectance with increasing number of species. The alternative to this idea has been the ’constant connectance hypothesis’, where connectance is constant with increasing number of species. As part of my thesis (Chapter 2), I analysed the scaling of topological properties based on my compiled database and found power–law scaling relationships with diversity and complexity for most properties. Also, connectance tends to decrease with increasing number of species. The results illustrate the lack of universal constants in food web ecology as a function of diversity and complexity. Furthermore, common measures of bio–complexity (e.g. the fractions of top, intermediate and basal species, and the average trophic level) have been reinvestigated, as scale–dependent on diversity and connectance to. Interestingly, the scale dependence is partly significantly different between ecosystem types. A lot of species’ characteristics depend on body mass (eg. predator–prey interactions, metabolism, mobility) thus nominating body mass as the most important species attribute. Chapter 3 illustrates the distribution of mean population body masses in communities for different ecosystem types. The body masses are often roughly log–normally (terrestrial and stream ecosystems) or multi–modally (lake and marine ecosystems) distributed, and most networks exhibit exponential cumulative degree distributions. An exception are stream networks which most often possess uniform degree distributions. Furthermore, with increasing body mass vulnerability decreases in 70% of the food webs and generality increases in 80% of the food webs. Facing paradigms developed by Elton, I analysed the relationship of predator mass to prey mass and trophic level and the relationship between predator–prey body–mass ratio (hereafter: mass ratio) and trophic level (Chaper 4). In 1927, Elton suggested that (i) the mean prey mass increases with predator mass, (ii) the predators become larger in size with increasing trophic level, and (iii) the mass ratio is constant across trophic levels. After analysing the data base, the result supports the paradigms (i) and (ii). However, consistant with theoretical derivations, I found a systematic decrease in mass ratios with the trophic level of the predator. This result indicates the general pattern that on average predators at the top of the food webs are more similar in size to their prey than those closer to the base. Food–web stability is critically dependent on species loss. In two subsequent projects (Chapter 5, 6), I applied a bioenergetic model approach to simulate species loss in a set of (Chapter 5) 1000 model food webs and (Chapter 6) 30 empirical food webs randomly chosen from the food web data base . I analysed the stability of model food webs in respect of effects of topological, size–based, and dynamical properties. Stabiltiy has been messured as the number of secondary extinctions after removing one species from the network. The results show that food–web robustness is affected by factors from all three groups. However, the most striking effect was related to the body mass–abundance relationship which points to the importance of body mass relationships for food web stability. Additionally to the network–related properties (e.g. diversity, connectance), I analysed species related properties (e.g. body mass, trophic level). Overall, ecosystem-types (lake, stream, marine, and terrestrial ecosystems) react in the same way to species loss. I found food webs with high diversity and a low standard deviation of vulnerability were less affected by secondary extinctions. At the species level, consistent with classical conservation biology findings, I found that the loss of large–bodied top predators increases the extinction–risk for all others species in the ecosystem. The work presented here contributes to the understanding of underlying mechanisms and dynamics between interacting species in ecosystems. It illustrates differences between ecosystem types, where ”streams tend to be different than other ecosystems”. Overall, the studies show how energy fluxes can contribute to the stability of natural communities, how topological properties influence the interplay between animal populations and how complex communities react to species loss.

Previous studies show that conservation actions have prevented extinctions, recovered populations, and reduced declining trends in global biodiversity. However, all studies to date have substantially underestimated the difference conservation action makes because they failed to account fully for what would have happened in the absence thereof. We undertook a scenario-based thought experiment to better quantify the effect conservation actions have had on the extinction risk of the world's 235 recognized ungulate species. We did so by comparing species' observed conservation status in 2008 with their estimated status under counterfactual scenarios in which conservation efforts ceased in 1996. We estimated that without conservation at least 148 species would have deteriorated by one International Union for Conservation of Nature (IUCN) Red List category, including 6 species that now would be listed as extinct or extinct in the wild. The overall decline in the conservation status of ungulates would have been nearly 8 times worse than observed. This trend would have been greater still if not for conservation on private lands. While some species have benefited from highly targeted interventions, such as reintroduction, most benefited collaterally from conservation such as habitat protection. We found that the difference conservation action makes to the conservation status of the world's ungulate species is likely to be higher than previously estimated. Increased, and sustained, investment could help achieve further improvements.

Research on the functional importance of biodiversity, motivated by global species loss, has documented that plant species richness affects many plant‐related ecosystem functions. Less is known about the effects of plant species richness on functions related to higher trophic levels, such as the consumption of biomass by animals, that is, herbivory. Previous studies have shown positive, neutral, or negative effects of plant species richness on herbivory. In the framework of a grassland biodiversity experiment (the Jena Experiment), we investigated herbivory (the proportion of leaf area damaged and the amount of leaf biomass consumed by arthropod herbivores) along two experimental gradients of plant species richness ranging from 1 to 60 species (Main Experiment) and from 1 to 8 species (Trait‐Based Experiment) biannually for five and three years, respectively. Additionally, plant functional diversity, based on traits related to plant growth, was manipulated as the number of functional groups in a community (Main Experiment) or a gradient of functional trait dissimilarity (Trait‐Based Experiment). Herbivory at the level of plant communities ranged from 0% to 31% (0 and 33.8 g/m2) in the Main Experiment and 0% to 8% (0 and 13.7 g/m2) in the Trait‐Based Experiment, and it was on average higher in summer than in spring. For both experimental gradients and all years investigated, we found a consistent increase in damaged leaf area and consumed biomass with increasing plant species richness. As mechanistic explanations for effects of plant species richness, we propose changes in plant quality and herbivore communities. The presence of specific plant functional groups significantly affected herbivory, likely related to traits affecting plant defense and nutritional value, but we found little evidence for effects of plant functional diversity. The general positive relationship between plant species richness and herbivory might contribute to effects of plant species richness on other ecosystem functions such as productivity and nutrient mineralization and can cascade up the food web also affecting higher trophic levels.

Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems. With a focus on integrated sustainability analysis, the book presents a large-scale quadratic programming algorithm to expand high-resolution input-output tables from the national scale to the multinational scale to measure the carbon footprint of the entire trade supply chain. It also quantifies the error or dispersion between different reclassification and aggregation schemas, revealing that aggregation errors have a high concentration over specific regions and sectors. The book summarizes the latest contributions of the data analysis community to climate change research. A profuse amount of climate data of various types is available, providing a rich and fertile playground for future data mining and machine learning research. The book also pays special attention to several critical challenges in the science of climate extremes that are not handled by the current generation of climate models. It discusses potential conceptual and methodological directions to build a close integration between physical understanding, or physics-based modeling, and data-driven insights. The book then covers the conservation of species and ecologically valuable land. A case study on the Pennsylvania Dirt and Gravel Roads Program demonstrates that multiple-objective linear programming is a more versatile and efficient approach than the widely used benefit targeting selection process. Moving on to renewable energy and the need for smart grids, the book explores how the ongoing transformation to a sustainable energy system of renewable sources leads to a paradigm shift from demand-driven generation to generation-driven demand. It shows how to maximize renewable energy as electricity by building a supergrid or mixing renewable sources with demand management and storage. It also presents intelligent data analysis for real-time detection of disruptive events from power system frequency data collected using an existing Internet-based frequency monitoring network as well as evaluates a set of computationally intelligent techniques for long-term wind resource assessment. In addition, the book gives an example of how temporal and spatial data analysis tools are used to gather knowledge about behavioral data and address important social problems such as criminal offenses. It also applies constraint logic programming to a planning problem: the environmental and social impact assessment of the regional energy plan of the Emilia-Romagna region of Italy. Sustainable development problems, such as global warming, resource shortages, global species loss, and pollution, push researchers to create powerful data analysis approaches that analysts can then use to gain insight into these issues to support rational decision making. This volume shows both the data analysis and sustainable development communities how to use intelligent data analysis tools to address practical problems and encourages researchers to develop better methods.

Species turnover is ubiquitous. However, it remains unknown whether certain types of species are consistently gained or lost across different habitats. Here, we analysed the trajectories of 1827 plant species over time intervals of up to 78years at 141sites across mountain summits, forests, and lowland grasslands in Europe. We found, albeit with relatively small effect sizes, displacements of smaller- by larger-ranged species across habitats. Communities shifted in parallel towards more nutrient-demanding species, with species from nutrient-rich habitats having larger ranges. Because these species are typically strong competitors, declines of smaller-ranged species could reflect not only abiotic drivers of global change, but also biotic pressure from increased competition. The ubiquitous component of turnover based on species range size we found here may partially reconcile findings of no net loss in local diversity with global species loss, and link community-scale turnover to macroecological processes such as biotic homogenisation.

Infectious and non-infectious diseases pose a tremendous challenge to global public health. Existing technologies for detecting infectious and non-infectious diseases are mostly tedious, expensive, and do not meet the World Health Organization’s (WHO) ASSURED (affordable, sensitive, specific, user-friendly, rapid and robust, equipment-free, and deliverable to end user) criteria. Early diagnosis of diseases can lead to effective control and early intervention of the patient's condition. Conventional approach for diseases diagnosis are including culture and microscopy, immunology (ELISA, fluorescent immunoassays, magnetic immunoassays, RIA, lateral flow immunoassays) and PCR have drawbacks like these are expensive, inaccurate, and require skilled technicians and time consuming process, especially for the earlier and rapid detection of infectious diseases. Over the past few decades, quantum dot have attracted widespread attention due to its immense potential in the area of diagnostic medicine for early detection of disease without relying on visible symptoms. This is largely due to their unique optical properties such as high brightness, narrow emission band, and resistance to photo bleaching, multiplexing capacity, and high surface-to-volume ratio and this will make them excellent candidates for intracellular tracking, diagnostics, in vivo imaging, and therapeutic delivery. In this mini review, we examine recent advances in the diagnosis of infectious and noninfectious diseases, which has based on quantum dot nanomaterial. The current state-of-the-art and most promising quantum dot based technologies, including, QD based Lateral Flow Immunoassay, Quantum dot-based paper strip devices, QD based biomarkers, QD based biosensor devices etc. Quantum dot based techniques, devices are promising accessories in modern biomedical applications, and these techniques will go to become the future of next-generation diagnostics.

The marine manatee ( Trichechus manatus ) is one of the most endangered marine mammals in Brazil, and is currently classified as vulnerable to extinction. The main risks to the conservation of the species are from natural causes, such as the slow birth rate, human actions and infectious diseases. Among the main objectives of the National Centre for Research and Conservation of Aquatic Mammals, the Chico Mendes Institute for Biodiversity Conservation (CMA/ICMBio) is to promote scientific research and management actions for the conservation and recovery of endangered species of marine mammals, and develop and promote rehabilitation in captivity and release natural environment of the marine manatee. The passage of these individuals for captive is of utmost importance for the conservation of the species. The rehabilitation of captive cubs marine manatees and allow recovery and can return the animal to the natural environment, enables a greater knowledge of the species, referring to biological, behavioral and clinical. Studies on the parasitism of manatee in Brazil are few elucidated, more research related to the topic, it is necessary to better understand the disease and health aspects of the species. This work aims to realize the isolation of the parasite in urine samples of marine manatee kept in the rehabilitation process. All animals included in the study are from the rehabilitation center for wild animals CRAS/CMA/ICMbio , located in Itamaraca, State of Pernambuco. This deal is the first description of parasites in urine manatee in Brazil and can support management actions to be taken to ensure the health of animals in rehabilitation.