Synergistic effects of precipitation and groundwater extraction on freshwater wetland inundation.

Wetlands provide essential ecosystem services, including nutrient cycling, flood protection, and biodiversity support, that are sensitive to changes in wetland hydrology. Wetland hydrological inputs come from precipitation, groundwater discharge, and surface run-off. Changes to these inputs via climate variation, groundwater extraction, and land development may alter the timing and magnitude of wetland inundation. Here, we use a long-term (14-year) comparative study of 152 depressional wetlands in west-central Florida to identify sources of variation in wetland inundation during two key time periods, 2005-2009 and 2010-2018. These time periods are separated by the enactment of water conservation policies in 2009, which included regional reductions in groundwater extraction. We investigated the response of wetland inundation to the interactive effects of precipitation, groundwater extraction, surrounding land development, basin geomorphology, and wetland vegetation class. Results show that water levels were lower and hydroperiods were shorter in wetlands of all vegetation classes during the first (2005-2009) time period, which corresponded with low rainfall conditions and high rates of groundwater extraction. Under water conservation policies enacted in the second (2010-2018) time period, median wetland water depths increased 1.35 m and median hydroperiods increased from 46 % to 83 %. Water-level variation was additionally less sensitive to groundwater extraction. The increase in inundation differed among vegetation classes with some wetlands not displaying signs of hydrological recovery. After accounting for effects of several explanatory factors, inundation still varied considerably among wetlands, suggesting a diversity of hydrological regimes, and thus ecological function, among individual wetlands across the landscape. Policies seeking to balance human water demand with the preservation of depressional wetlands would benefit by recognizing the heightened sensitivity of wetland inundation to groundwater extraction during periods of low precipitation.

Land reversion and zoonotic spillover risk.

Deforestation alters wildlife communities and modifies human-wildlife interactions, often increasing zoonotic spillover potential. When deforested land reverts to forest, species composition differences between primary and regenerating (secondary) forest could alter spillover risk trajectory. We develop a mathematical model of land-use change, where habitats differ in their relative spillover risk, to understand how land reversion influences spillover risk. We apply this framework to scenarios where spillover risk is higher in deforested land than mature forest, reflecting higher relative abundance of highly competent species and/or increased human-wildlife encounters, and where regenerating forest has either very low or high spillover risk. We find the forest regeneration rate, the spillover risk of regenerating forest relative to deforested land, and how rapidly regenerating forest regains attributes of mature forest determine landscape-level spillover risk. When regenerating forest has a much lower spillover risk than deforested land, reversion lowers cumulative spillover risk, but instaneous spillover risk peaks earlier. However, when spillover risk is high in regenerating and cleared habitats, landscape-level spillover risk remains high, especially when cleared land is rapidly abandoned then slowly regenerates to mature forest. These results suggest that proactive wildlife management and awareness of human exposure risk in regenerating forests could be important tools for spillover mitigation.

The magnitude, diversity, and distribution of the economic costs of invasive terrestrial invertebrates worldwide.

Invasive alien species (IAS) are a major driver of global biodiversity loss, hampering conservation efforts and disrupting ecosystem functions and services. While accumulating evidence documented ecological impacts of IAS across major geographic regions, habitat types and taxonomic groups, appraisals for economic costs remained relatively sparse. This has hindered effective cost-benefit analyses that inform expenditure on management interventions to prevent, control, and eradicate IAS. Terrestrial invertebrates are a particularly pervasive and damaging group of invaders, with many species compromising primary economic sectors such as forestry, agriculture and health. The present study provides synthesised quantifications of economic costs caused by invasive terrestrial invertebrates on the global scale and across a range of descriptors, using the InvaCost database. Invasive terrestrial invertebrates cost the global economy US$ 712.44 billion over the investigated period (up to 2020), considering only high-reliability source reports. Overall, costs were not equally distributed geographically, with North America (73%) reporting the greatest costs, with far lower costs reported in Europe (7%), Oceania (6%), Africa (5%), Asia (3%), and South America (< 1%). These costs were mostly due to invasive insects (88%) and mostly resulted from direct resource damages and losses (75%), particularly in agriculture and forestry; relatively little (8%) was invested in management. A minority of monetary costs was directly observed (17%). Economic costs displayed an increasing trend with time, with an average annual cost of US$ 11.40 billion since 1960, but as much as US$ 165.01 billion in 2020, but reporting lags reduced costs in recent years. The massive global economic costs of invasive terrestrial invertebrates require urgent consideration and investment by policymakers and managers, in order to prevent and remediate the economic and ecological impacts of these and other IAS groups.

Biological invasion costs reveal insufficient proactive management worldwide.

The global increase in biological invasions is placing growing pressure on the management of ecological and economic systems. However, the effectiveness of current management expenditure is difficult to assess due to a lack of standardised measurement across spatial, taxonomic and temporal scales. Furthermore, there is no quantification of the spending difference between pre-invasion (e.g. prevention) and post-invasion (e.g. control) stages, although preventative measures are considered to be the most cost-effective. Here, we use a comprehensive database of invasive alien species economic costs (InvaCost) to synthesise and model the global management costs of biological invasions, in order to provide a better understanding of the stage at which these expenditures occur. Since 1960, reported management expenditures have totalled at least US$95.3 billion (in 2017 values), considering only highly reliable and actually observed costs - 12-times less than damage costs from invasions ($1130.6 billion). Pre-invasion management spending ($2.8 billion) was over 25-times lower than post-invasion expenditure ($72.7 billion). Management costs were heavily geographically skewed towards North America (54%) and Oceania (30%). The largest shares of expenditures were directed towards invasive alien invertebrates in terrestrial environments. Spending on invasive alien species management has grown by two orders of magnitude since 1960, reaching an estimated $4.2 billion per year globally (in 2017 values) in the 2010s, but remains 1-2 orders of magnitude lower than damages. National management spending increased with incurred damage costs, with management actions delayed on average by 11 years globally following damage reporting. These management delays on the global level have caused an additional invasion cost of approximately $1.2 trillion, compared to scenarios with immediate management. Our results indicate insufficient management - particularly pre-invasion - and urge better investment to prevent future invasions and to control established alien species. Recommendations to improve reported management cost comprehensiveness, resolution and terminology are also made.

Knowledge gaps in economic costs of invasive alien fish worldwide.

Invasive alien fishes have had pernicious ecological and economic impacts on both aquatic ecosystems and human societies. However, a comprehensive and collective assessment of their monetary costs is still lacking. In this study, we collected and reviewed reported data on the economic impacts of invasive alien fishes using InvaCost, the most comprehensive global database of invasion costs. We analysed how total (i.e. both observed and potential/predicted) and observed (i.e. empirically incurred only) costs of fish invasions are distributed geographically and temporally and assessed which socioeconomic sectors are most affected. Fish invasions have potentially caused the economic loss of at least US$37.08 billion (US2017 value) globally, from just 27 reported species. North America reported the highest costs (>85% of the total economic loss), followed by Europe, Oceania and Asia, with no costs yet reported from Africa or South America. Only 6.6% of the total reported costs were from invasive alien marine fish. The costs that were observed amounted to US$2.28 billion (6.1% of total costs), indicating that the costs of damage caused by invasive alien fishes are often extrapolated and/or difficult to quantify. Most of the observed costs were related to damage and resource losses (89%). Observed costs mainly affected public and social welfare (63%), with the remainder borne by fisheries, authorities and stakeholders through management actions, environmental, and mixed sectors. Total costs related to fish invasions have increased significantly over time, from

Economic costs of biological invasions in the United States.

The United States has thousands of invasive species, representing a sizable, but unknown burden to the national economy. Given the potential economic repercussions of invasive species, quantifying these costs is of paramount importance both for national economies and invasion management. Here, we used a novel global database of invasion costs (InvaCost) to quantify the overall costs of invasive species in the United States across spatiotemporal, taxonomic, and socioeconomic scales. From 1960 to 2020, reported invasion costs totaled $4.52 trillion (USD 2017). Considering only observed, highly reliable costs, this total cost reached $1.22 trillion with an average annual cost of $19.94 billion/year. These costs increased from $2.00 billion annually between 1960 and 1969 to $21.08 billion annually between 2010 and 2020. Most costs (73%) were related to resource damages and losses ($896.22 billion), as opposed to management expenditures ($46.54 billion). Moreover, the majority of costs were reported from invaders from terrestrial habitats ($643.51 billion, 53%) and agriculture was the most impacted sector ($509.55 billion). From a taxonomic perspective, mammals ($234.71 billion) and insects ($126.42 billion) were the taxonomic groups responsible for the greatest costs. Considering the apparent rising costs of invasions, coupled with increasing numbers of invasive species and the current lack of cost information for most known invaders, our findings provide critical information for policymakers and managers.

Temporal variability in population and community dynamics.

Populations and communities fluctuate in their overall numbers through time, and the magnitude of fluctuations in individual species may scale to communities. However, the composite variability at the community scale is expected to be tempered by opposing fluctuations in individual populations, a phenomenon often called the portfolio effect. Understanding population variability, how it scales to community variability, and the spatial scaling in this variability are pressing needs given shifting environmental conditions and community composition. We explore evidence for portfolio effects using null community simulations and a large collection of empirical community time series from the BioTIME database. Additionally, we explore the relative roles of habitat type and geographic location on population and community temporal variability. We find strong portfolio effects in our theoretical community model, but weak effects in empirical data, suggesting a role for shared environmental responses, interspecific competition, or a litany of other factors. Furthermore, we observe a clear latitudinal signal - and differences among habitat types - in population and community variability. Together, this highlights the need to develop realistic models of community dynamics, and hints at spatial, and underlying environmental, gradients in variability in both population and community dynamics.

Global economic costs of aquatic invasive alien species.

Much research effort has been invested in understanding ecological impacts of invasive alien species (IAS) across ecosystems and taxonomic groups, but empirical studies about economic effects lack synthesis. Using a comprehensive global database, we determine patterns and trends in economic costs of aquatic IAS by examining: (i) the distribution of these costs across taxa, geographic regions and cost types; (ii) the temporal dynamics of global costs; and (iii) knowledge gaps, especially compared to terrestrial IAS. Based on the costs recorded from the existing literature, the global cost of aquatic IAS conservatively summed to US$345 billion, with the majority attributed to invertebrates (62%), followed by vertebrates (28%), then plants (6%). The largest costs were reported in North America (48%) and Asia (13%), and were principally a result of resource damages (74%); only 6% of recorded costs were from management. The magnitude and number of reported costs were highest in the United States of America and for semi-aquatic taxa. Many countries and known aquatic alien species had no reported costs, especially in Africa and Asia. Accordingly, a network analysis revealed limited connectivity among countries, indicating disparate cost reporting. Aquatic IAS costs have increased in recent decades by several orders of magnitude, reaching at least US$23 billion in 2020. Costs are likely considerably underrepresented compared to terrestrial IAS; only 5% of reported costs were from aquatic species, despite 26% of known invaders being aquatic. Additionally, only 1% of aquatic invasion costs were from marine species. Costs of aquatic IAS are thus substantial, but likely underreported. Costs have increased over time and are expected to continue rising with future invasions. We urge increased and improved cost reporting by managers, practitioners and researchers to reduce knowledge gaps. Few costs are proactive investments; increased management spending is urgently needed to prevent and limit current and future aquatic IAS damages.

Ubiquity and functional uniformity in CO2 concentrating mechanisms in multiple phyla of Bacteria is suggested by a diversity and prevalence of genes encoding candidate dissolved inorganic carbon transporters.

Autotrophic microorganisms catalyze the entry of dissolved inorganic carbon (DIC; = CO2 + HCO3- + CO32-) into the biological component of the global carbon cycle, despite dramatic differences in DIC abundance and composition in their sometimes extreme environments. "Cyanobacteria" are known to have CO2 concentrating mechanisms (CCMs) to facilitate growth under low CO2 conditions. These CCMs consist of carboxysomes, containing enzymes ribulose 1,5-bisphosphate oxygenase and carbonic anhydrase, partnered to DIC transporters. CCMs and their DIC transporters have been studied in a handful of other prokaryotes, but it was not known how common CCMs were beyond "Cyanobacteria". Since it had previously been noted that genes encoding potential transporters were found neighboring carboxysome loci, α-carboxysome loci were gathered from bacterial genomes, and potential transporter genes neighboring these loci are described here. Members of transporter families whose members all transport DIC (CHC, MDT and Sbt) were common in these neighborhoods, as were members of the SulP transporter family, many of which transport DIC. 109 of 115 taxa with carboxysome loci have some form of DIC transporter encoded in their genomes, suggesting that CCMs consisting of carboxysomes and DIC transporters are widespread not only among "Cyanobacteria", but also among members of "Proteobacteria" and "Actinobacteria".

Multiscale model of regional population decline in little brown bats due to white-nose syndrome.

The introduced fungal pathogen Pseudogymnoascus destructans is causing decline of several species of bats in North America, with some even at risk of extinction or extirpation. The severity of the epidemic of white-nose syndrome caused by P. destructans has prompted investigation of the transmission and virulence of infection at multiple scales, but linking these scales is necessary to quantify the mechanisms of transmission and assess population-scale declines.We built a model connecting within-hibernaculum disease dynamics of little brown bats to regional-scale dispersal, reproduction, and disease spread, including multiple plausible mechanisms of transmission.We parameterized the model using the approach of plausible parameter sets, by comparing stochastic simulation results to statistical probes from empirical data on within-hibernaculum prevalence and survival, as well as among-hibernacula spread across a region.Our results are consistent with frequency-dependent transmission between bats, support an important role of environmental transmission, and show very little effect of dispersal among colonies on metapopulation survival.The results help identify the influential parameters and largest sources of uncertainty. The model also offers a generalizable method to assess hypotheses about hibernaculum-to-hibernaculum transmission and to identify gaps in knowledge about key processes, and could be expanded to include additional mechanisms or bat species.

Density-dependent selection on mate search and evolution of Allee effects.

Sexually reproducing organisms require males and females to find each other. Increased difficulty of females finding mates as male density declines is the most frequently reported mechanism of Allee effects in animals. Evolving more effective mate search may alleviate Allee effects, but may depend on density regimes a population experiences. In particular, high-density populations may evolve mechanisms that induce Allee effects which become detrimental when populations are reduced and maintained at a low density. We develop an individual-based, eco-genetic model to study how mating systems and fitness trade-offs interact with changes in population density to drive evolution of the rate at which males or females search for mates. Finite mate search rate triggers Allee effects in our model and we explore how these Allee effects respond to such evolution. We allow a population to adapt to several population density regimes and examine whether high-density populations are likely to reverse adaptations attained at low densities. We find density-dependent selection in most of scenarios, leading to search rates that result in lower Allee thresholds in populations kept at lower densities. This mainly occurs when fecundity costs are imposed on mate search, and provides an explanation for why Allee effects are often observed in anthropogenically rare species. Optimizing selection, where the attained trait value minimizes the Allee threshold independent of population density, depended on the trade-off between search and survival, combined with monogamy when females were searching. Other scenarios led to runaway selection on the mate search rate, including evolutionary suicide. Trade-offs involved in mate search may thus be crucial to determining how density influences the evolution of Allee effects. Previous studies did not examine evolution of a trait related to the strength of Allee effects under density variation. We emphasize the crucial role that mating systems, fitness trade-offs and the evolving sex have in determining the density threshold for population persistence, in particular since evolution need not always take the Allee threshold to its minimum value.

Accuracy of climate-based forecasts of pathogen spread.

Species distribution models (SDMs) are a tool for predicting the eventual geographical range of an emerging pathogen. Most SDMs, however, rely on an assumption of equilibrium with the environment, which an emerging pathogen, by definition, has not reached. To determine if some SDM approaches work better than others for modelling the spread of emerging, non-equilibrium pathogens, we studied time-sensitive predictive performance of SDMs for Batrachochytrium dendrobatidis, a devastating infectious fungus of amphibians, using multiple methods trained on time-incremented subsets of the available data. We split our data into timeline-based training and testing sets, and evaluated models on each set using standard performance criteria, including AUC, kappa, false negative rate and the Boyce index. Of eight models examined, we found that boosted regression trees and random forests performed best, closely followed by MaxEnt. As expected, predictive performance generally improved with the length of time series used for model training. These results provide information on how quickly the potential extent of an emerging disease may be determined, and identify which modelling frameworks are likely to provide useful information during the early phases of pathogen expansion.

Spatiotemporal Fluctuations and Triggers of Ebola Virus Spillover.

Because the natural reservoir of Ebola virus remains unclear and disease outbreaks in humans have occurred only sporadically over a large region, forecasting when and where Ebola spillovers are most likely to occur constitutes a continuing and urgent public health challenge. We developed a statistical modeling approach that associates 37 human or great ape Ebola spillovers since 1982 with spatiotemporally dynamic covariates including vegetative cover, human population size, and absolute and relative rainfall over 3 decades across sub-Saharan Africa. Our model (area under the curve 0.80 on test data) shows that spillover intensity is highest during transitions between wet and dry seasons; overall, high seasonal intensity occurs over much of tropical Africa; and spillover intensity is greatest at high (>1,000/km2) and very low (<100/km2) human population densities compared with intermediate levels. These results suggest strong seasonality in Ebola spillover from wild reservoirs and indicate particular times and regions for targeted surveillance.

Spatial spread of the West Africa Ebola epidemic.

Controlling Ebola outbreaks and planning an effective response to future emerging diseases are enhanced by understanding the role of geography in transmission. Here we show how epidemic expansion may be predicted by evaluating the relative probability of alternative epidemic paths. We compared multiple candidate models to characterize the spatial network over which the 2013-2015 West Africa epidemic of Ebola virus spread and estimate the effects of geographical covariates on transmission during peak spread. The best model was a generalized gravity model where the probability of transmission between locations depended on distance, population density and international border closures between Guinea, Liberia and Sierra Leone and neighbouring countries. This model out-performed alternative models based on diffusive spread, the force of infection, mobility estimated from cell phone records and other hypothesized patterns of spread. These findings highlight the importance of integrated geography to epidemic expansion and may contribute to identifying both the most vulnerable unaffected areas and locations of maximum intervention value.

Global Patterns of Zoonotic Disease in Mammals.

As the frequency and prevalence of zoonotic diseases increase worldwide, investigating how mammal host distributions determine patterns of human disease and predicting which regions are at greatest risk for future zoonotic disease emergence are two goals which both require better understanding of the current distributions of zoonotic hosts and pathogens. We review here the existing data about mammalian host species, comparing and contrasting these patterns against global maps of zoonotic hosts from all 27 orders of terrestrial mammals. We discuss the zoonotic potential of host species from the top six most species-rich mammal groups, and review the literature to identify analytical and conceptual gaps that must be addressed to improve our ability to generate testable predictions about zoonotic diseases originating from wild mammals.

Experimental demonstration of an Allee effect in microbial populations.

Microbial populations can be dispersal limited. However, microorganisms that successfully disperse into physiologically ideal environments are not guaranteed to establish. This observation contradicts the Baas-Becking tenet: 'Everything is everywhere, but the environment selects'. Allee effects, which manifest in the relationship between initial population density and probability of establishment, could explain this observation. Here, we experimentally demonstrate that small populations of Vibrio fischeri are subject to an intrinsic demographic Allee effect. Populations subjected to predation by the bacterivore Cafeteria roenbergensis display both intrinsic and extrinsic demographic Allee effects. The estimated critical threshold required to escape positive density-dependence is around 5, 20 or 90 cells ml(-1)under conditions of high carbon resources, low carbon resources or low carbon resources with predation, respectively. This work builds on the foundations of modern microbial ecology, demonstrating that mechanisms controlling macroorganisms apply to microorganisms, and provides a statistical method to detect Allee effects in data.

The contribution of marine aggregate-associated bacteria to the accumulation of pathogenic bacteria in oysters: an agent-based model.

Bivalves process large volumes of water, leading to their accumulation of bacteria, including potential human pathogens (e.g., vibrios). These bacteria are captured at low efficiencies when freely suspended in the water column, but they also attach to marine aggregates, which are captured with near 100% efficiency. For this reason, and because they are often enriched with heterotrophic bacteria, marine aggregates have been hypothesized to function as important transporters of bacteria into bivalves. The relative contribution of aggregates and unattached bacteria to the accumulation of these cells, however, is unknown. We developed an agent-based model to simulate accumulation of vibrio-type bacteria in oysters. Simulations were conducted over a realistic range of concentrations of bacteria and aggregates and incorporated the dependence of pseudofeces production on particulate matter. The model shows that the contribution of aggregate-attached bacteria depends strongly on the unattached bacteria, which form the colonization pool for aggregates and are directly captured by the simulated oysters. The concentration of aggregates is also important, but its effect depends on the concentration of unattached bacteria. At high bacterial concentrations, aggregates contribute the majority of bacteria in the oysters. At low concentrations of unattached bacteria, aggregates have a neutral or even a slightly negative effect on bacterial accumulation. These results provide the first evidence suggesting that the concentration of aggregates could influence uptake of pathogenic bacteria in bivalves and show that the tendency of a bacterial species to remain attached to aggregates is a key factor for understanding species-specific accumulation.

Ebola cases and health system demand in Liberia.

In 2014, a major epidemic of human Ebola virus disease emerged in West Africa, where human-to-human transmission has now been sustained for greater than 12 months. In the summer of 2014, there was great uncertainty about the answers to several key policy questions concerning the path to containment. What is the relative importance of nosocomial transmission compared with community-acquired infection? How much must hospital capacity increase to provide care for the anticipated patient burden? To which interventions will Ebola transmission be most responsive? What must be done to achieve containment? In recent years, epidemic models have been used to guide public health interventions. But, model-based policy relies on high quality causal understanding of transmission, including the availability of appropriate dynamic transmission models and reliable reporting about the sequence of case incidence for model fitting, which were lacking for this epidemic. To investigate the range of potential transmission scenarios, we developed a multi-type branching process model that incorporates key heterogeneities and time-varying parameters to reflect changing human behavior and deliberate interventions in Liberia. Ensembles of this model were evaluated at a set of parameters that were both epidemiologically plausible and capable of reproducing the observed trajectory. Results of this model suggested that epidemic outcome would depend on both hospital capacity and individual behavior. Simulations suggested that if hospital capacity was not increased, then transmission might outpace the rate of isolation and the ability to provide care for the ill, infectious, and dying. Similarly, the model suggested that containment would require individuals to adopt behaviors that increase the rates of case identification and isolation and secure burial of the deceased. As of mid-October, it was unclear that this epidemic would be contained even by 99% hospitalization at the planned hospital capacity. A new version of the model, updated to reflect information collected during October and November 2014, predicts a significantly more constrained set of possible futures. This model suggests that epidemic outcome still depends very heavily on individual behavior. Particularly, if future patient hospitalization rates return to background levels (estimated to be around 70%), then transmission is predicted to remain just below the critical point around Reff = 1. At the higher hospitalization rate of 85%, this model predicts near complete elimination in March to June, 2015.

Assessing the in situ fertilization status of two marine copepod species, Temora longicornis and Eurytemora herdmani; how common are unfertilized eggs in nature?

We utilized an egg staining technique to measure the in situ fertilization success of two marine copepod species, Temora longicornis and Eurytemora herdmani from May to October 2008 in coastal Maine and correlated fertilization success with environmental conditions in their habitat. T. longicornis is a free spawning species that releases eggs into the ambient seawater after mating. In contrast, E. herdmani carries eggs in an egg sac until they hatch. The proportion of fertilized eggs within E. herdmani egg sacs was significantly higher than the freely spawned clutches of T. longicornis. This may be a result of the asymmetrical costs associated with carrying vs. spawning unfertilized eggs. T. longicornis frequently laid both fertilized and unfertilized eggs within their clutch. T. longicornis fertilization was negatively associated with chlorophyll concentration and positively associated with population density in their local habitat. The fertilization status of E. herdmani egg sacs was high throughout the season, but the proportion of ovigerous females was negatively associated with an interaction between predators and the proportion of females in the population. This study emphasizes that, in addition to population level processes, community and ecosystem level processes strongly influence the fertilization success and subsequent productivity of copepods.