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Funding was funded by National Science Foundation (US) (Grant Nos. 0614334, 0741450, 1354511), Svenska Forskningsrådet Formas (Grant No. 2016-02045), H2020 European Research Council (Grant No. AdG 250189) and Instituto Nacional de Ciência e Tecnologia de Ciência Animal (Grant No. 306455/2014-5). Freshwater ecosystems provide irreplaceable services for both nature and society. The quality and quantity of freshwater affect biogeochemical processes and ecological dynamics that determine biodiversity, ecosystem productivity, and human health and welfare at local, regional and global scales. Freshwater ecosystems and their associated riparian habitats are amongst the most biologically diverse on Earth, and have inestimable economic, health, cultural, scientific and educational values. Yet human impacts to lakes, rivers, streams, wetlands and groundwater are dramatically reducing biodiversity and robbing critical natural resources and services from current and future generations. Freshwater biodiversity is declining rapidly on every continent and in every major river basin on Earth, and this degradation is occurring more rapidly than in terrestrial ecosystems. Currently, about one third of all global freshwater discharges pass through human agricultural, industrial or urban infrastructure. About one fifth of the Earth’s arable land is now already equipped for irrigation, including all the most productive lands, and this proportion is projected to surpass one third by midcentury to feed the rapidly expanding populations of humans and commensal species, especially poultry and ruminant livestock. Less than one fifth of the world’s preindustrial freshwater wetlands remain, and this proportion is projected to decline to under one tenth by midcentury, with imminent threats from water transfer megaprojects in Brazil and India, and coastal wetland drainage megaprojects in China. The Living Planet Index for freshwater vertebrate populations has declined to just one third that of 1970, and is projected to sink below one fifth by midcentury. A linear model of global economic expansion yields the chilling prediction that human utilization of critical freshwater resources will approach one half of the Earth’s total capacity by midcentury. Although the magnitude and growth of the human freshwater footprint are greater than is generally understood by policy makers, the news media, or the general public, slowing and reversing dramatic losses of freshwater species and ecosystems is still possible. We recommend a set of urgent policy actions that promote clean water, conserve watershed services, and restore freshwater ecosystems and their vital services. Effective management of freshwater resources and ecosystems must be ranked amongst humanity’s highest priorities. Postprint

Habitat loss can alter animal movements and disrupt animal seed dispersal mutualisms; however, its effects on spatial patterns of seed dispersal are not well understood. To explore the effects of habitat loss on seed dispersal distances and seed dispersion (aggregation), we created a spatially explicit, individual‐based model of an animal dispersing seeds (SEADS—Spatially Explicit Animal Dispersal of Seeds) in a theoretical landscape of 0%–90% habitat loss based on three animal traits: movement distance, gut retention time, and time between movements. Our model design had three objectives: to determine the effects of (1) animal traits and (2) habitat loss on seed dispersal distances and dispersion and (3) determine how animal traits could mitigate the negative effects of habitat loss on these variables. SEADS results revealed a complex interaction involving all animal traits and habitat loss on dispersal distances and dispersion, driven by a novel underlying mechanism of fragment entrapment. Unexpectedly, intermediate habitat loss could increase dispersal distances and dispersion relative to low and high habitat loss for some combinations of animal traits. At intermediate habitat loss, movement between patches was common, and increased dispersal distances and dispersion compared to continuous habitats because animals did not stop in spaces between fragments. However, movement between patches was reduced at higher habitat loss as animals became trapped in fragments, often near the parent plant, and dispersed seeds in aggregated patterns. As movement distance increased, low time between movements and high gut retention time combinations permitted more movement to adjacent patches than other combinations of animal traits. Because habitat loss affects movement in a nonlinear fashion under some conditions, future empirical tests would benefit from comparisons across landscapes with more than two levels of fragmentation.

Landscape composition and structure influence animal movement, which in turn can affect transmission of their diseases. Spatio-temporal variation in host diffusion, caused by landscape heterogeneity, is thus expected to generate corresponding phylogeographic patterns in the pathogen. However, establishing causative links between genetic structure in pathogen populations and environmental variation does require appropriate null models. Here, we present an empirical example of the emergence and multi-decade persistence of phylogeographic structure on a homogeneous landscape in a rapidly diversifying pathogen in the absence of any apparent landscape heterogeneity. By applying phylogeographic inference to 173 sequences of a raccoon-specific strain of rabies virus, we reconstruct patterns of the virus’ evolution and diffusion on the Florida peninsula, USA, from its first emergence in the 1940’s to the present. Consistent with a lack of significant landscape heterogeneity relevant to raccoon movement in Florida, we found that the speed of rabies virus diffusion was spatially homogeneous across the peninsula. In contrast, we document the emergence of strong phylogeographic structure in the virus, in the form of five monophyletic lineages that diverged during the early years of colonization and now each occupy a distinct sub-region of Florida. Based on samples taken over multiple decades, we show that the spatial distribution of these lineages has changed little over the past four decades. This phylogeographic stability allowed us to retrospectively identify a small set of counties within Florida as the likely source of the virus strain that seeded a much larger rabies outbreak in the northeastern USA in the 1970s. Our results provide a rare empirical demonstration that spatial genetic structure can arise and be maintained in the absence of landscape heterogeneity, which has wider implications for the interpretation of phylogeographic data and the reconstruction of historical colonization patterns from molecular data.

Aim To investigate the effects of river capture on the biogeographical history of South American freshwater fishes. Location Western Amazon and La Plata basins, and adjacent river drainages. Methods We used a species-dense time-calibrated phylogeny of long-whiskered catfishes (Siluriformes, Pimelodidae) to calculate likelihoods for 16 biogeographical scenarios of river capture, each differing in details of (1) landscape evolution and/or (2) models of species range evolution. We designed eight alternative landscape evolution models (LEMs) to represent distinct palaeogeographical river capture histories between the Western Amazon and La Plata drainages during the formation of the Central Andean (Bolivian) orocline (43.0–15.0 Ma). The LEMs differed only in patterns of area-connectivity constraints through time, and otherwise had the same geographical areas, time durations and dispersal probabilities. We used the DEC and DECj models of species range evolution under these eight LEM constraints to calculate likelihood values for ancestral area estimates. Results Divergence time estimates indicated that crown-group pimelodids emerged during the Late Cretaceous or Palaeogene (c. 72.9 ± 20 Ma) and model-selection recovered a best-fit palaeogeographical scenario with (1) a LEM with three river capture events, and (2) a DECj model of species range evolution. These results were quantitatively replicated using Lagrange and BayArea-like methods. Main conclusions The taxon–area chronogram of pimelodids exhibits the characteristic biogeographical signature of river capture; i.e. several non-monophyletic regional (basin-wide) species assemblages coupled with the presence of many species inhabiting more than one basin. These phylogenetic and biogeographical patterns are consistent with the effects of three large-scale river capture events during the formation of the Bolivian orocline.

We have developed a computer model of plant community dynamics for Louisiana’s coastal wetland ecosystems. The model was improved as a part of the Louisiana Coastal Master Plan of 2017 and is one of several linked models used to evaluate the potential effects of climate change and sea levels rise as well as the potential effects of alternative approaches to managing the region’s natural resources to mitigate the effects of sea level rise. The model we describe here incorporates a number of improvements over the previous version of the model developed for the 2012 Master Plan, including an expansion of the number of species and habitat types represented, the inclusion of bottomland forests and barrier islands, and the incorporation of additional ecological processes such as dispersal. Here, we present results from the model used to evaluate large scale ecosystem restoration projects, as well as three alternative management scenarios to illustrate the utility of the model and the ability of current management plans to address the threats that sea level rise pose to Louisiana’s coastal wetland ecosystems.

Visser, J.M.; Duke-Sylvester, S.M.; Carter, J., and Broussard, W.P., III, 2013. A computer model to forecast wetland vegetation changes resulting from restoration and protection in coastal Louisiana. In: Peyronnin, N. and Reed, D. (eds.), Louisiana’s 2012 Coastal Master Plan Technical Analysis, Journal of Coastal Research, Special Issue No. 67, 51–59. Coconut Creek (Florida), ISSN 0749-0208. The coastal wetlands of Louisiana are a unique ecosystem that supports a diversity of wildlife as well as a diverse community of commercial interests of both local and national importance. The state of Louisiana has established a 5-year cycle of scientific investigation to provide up-to-date information to guide future legislation and regulation aimed at preserving this critical ecosystem. Here we report on a model that projects changes in plant community distribution and composition in response to environmental conditions. This model is linked to a suite of other models and requires input from those that simulate the hydrology and morphology of coastal Louisiana. Collectively, these models are used to assess how alternative management plans may affect the wetland ecosystem through explicit spatial modeling of the physical and biological processes affected by proposed modifications to the ecosystem. We have also taken the opportunity to advance the state-of-the-art in wetland plant community modeling by using a model that is more speciesbased in its description of plant communities instead of one based on aggregated community types such as brackish marsh and saline marsh. The resulting model provides an increased level of ecological detail about how wetland communities are expected to respond. In addition, the output from this model provides critical inputs for estimating the effects of management on higher trophic level species though a more complete description of the shifts in habitat.

Macroevolutionary theory posits three processes leading to lineage diversification and the formation of regional biotas: dispersal (species geographic range expansion), speciation (species lineage splitting), and extinction (species lineage termination). The Theory of Island Biogeography (TIB) predicts species richness values using just two of these processes; dispersal and extinction. Yet most species on Earth live on continents or continental shelves, and the dynamics of evolutionary diversification at regional and continental scales are qualitatively different from those that govern the formation of species richness on biogeographic islands. Certain geomorphological processes operating perennially on continental platforms displace barriers to gene flow and organismal dispersal, and affect all three terms of macroevolutionary diversification. For example, uplift of a dissected landscape and river capture both merge and separate portions of adjacent areas, allowing dispersal and larger geographic ranges, vicariant speciation and smaller geographic ranges, and extinction when range sizes are subdivided below a minimum persistence threshold. The TIB also does not predict many biogeographic and phylogenetic patterns widely observed in continentally distributed taxa, including: (i) power function-like species-area relationships; (ii) log-normal distribution of species geographic range sizes, in which most species have restricted ranges (are endemic) and few species have broad ranges (are cosmopolitan); (iii) mid-domain effects with more species toward the geographic center, and more early-branching, species-poor clades toward the geographic periphery; (iv) exponential rates of net diversification with log-linear accumulation of lineages through geological time; and (v) power function-like relationships between species-richness and clade diversity, in which most clades are species-poor and few clades are species-rich. Current theory does not provide a robust mechanistic framework to connect these seemingly disparate patterns. Here we present SEAMLESS (Spatially Explicit Area Model of Landscape Evolution by SimulationS) that generates clade diversification by moving geographic barriers on a continuous, neutral landscape. SEAMLESS is a neutral Landscape Evolution Model (LEM) that treats species and barriers as functionally equivalent with respect to model parameters. SEAMLESS differs from other model-based biogeographic methods (e.g., Lagrange, GeoSSE, BayArea, and BioGeoBEARS) by modeling properties of dispersal barriers rather than areas, and by modeling the evolution of species lineages on a continuous landscape, rather than the evolution of geographic ranges along branches of a phylogeny. SEAMLESS shows how dispersal is required to maintain species richness and avoid clade-wide extinction, demonstrates that ancestral range size does not predict species richness, and provides a unified explanation for the suite of commonly observed biogeographic and phylogenetic patterns listed above. SEAMLESS explains how a simple barrier-displacement mechanism affects lineage diversification under neutral conditions, and is advanced here toward the formulation of a general theory of continental biogeography. [Diversification, extinction, geodispersal, macroevolution, river capture, vicariance.].

Numerical simulation models play important roles in assessing the potential effects of climate change on coastal ecosystems and developing management strategies aimed at minimizing risks to sensitive habitats, species, and people living along the coasts. Numerical models also provide a quantitative framework to disentangle the synergistic influences of multiple factors and isolate the effects of individual stressors. This chapter provides a brief overview of numerical simulation models used to assess the potential effects of climate change on coastal ecosystems. Four selected case studies from diverse coastal ecosystems are presented, illustrating the power of modeling in addressing important environmental issues in the context of climate change.

A system of ordinary differential equations describes the population dynamics of a rabies epidemic in raccoons. The model accounts for the dynamics of a vaccine, including loss of vaccine due to animal consumption and loss from factors other than racoon uptake. A control method to reduce the spread of disease is introduced through temporal distribution of vaccine packets. This work incorporates the effect of the seasonal birth pulse in the racoon population and the attendant increase in new-borns which are susceptible to the diseases, analysing the impact of the timing and length of this pulse on the optimal distribution of vaccine packets. The optimization criterion is to minimize the number of infected raccoons while minimizing the cost of distributing the vaccine. Using an optimal control setting, numerical results illustrate strategies for distributing the vaccine depending on the timing of the infection outbreak with respect to the birth pulse.

Computational models have been successfully applied to a wide variety of research areas including infectious disease epidemiology. Especially for questions that are difficult to examine in other ways, computational models have been used to extend the range of epidemiological issues that can be addressed, advance theoretical understanding of disease processes and help identify specific intervention strategies. We explore each of these contributions to epidemiology research through discussion and examples. We also describe in detail models for raccoon rabies and methicillin-resistant Staphylococcus aureus, drawn from our own research, to further illustrate the role of computation in epidemiological modeling.

We document patterns of coordinated dispersal over evolutionary time frames in heroine cichlids and poeciliine live-bearers, the two most species-rich clades of freshwater fishes in the Caribbean basin. Observed dispersal rate (DO) values were estimated from time-calibrated molecular phylogenies in Lagrange+, a modified version of the ML-based parametric biogeographic program Lagrange. DO is measured in units of “wallaces” (wa) as the number of biogeographic range-expansion events per million years. DO estimates were generated on a dynamic paleogeographic landscape of five areas over three time intervals from Upper Cretaceous to Recent. Expected dispersal rate (DE) values were generated from alternative paleogeographic models, with dispersal rates proportional to target area and source-river discharge volume, and inversely proportional to paleogeographic distance. Correlations between DO and DE were used to assess the relative contributions of these three biogeographic parameters. DO estimates imply a persistent dispersal corridor across the Eastern (Antillean) margin of the Caribbean plate, under the influence of prevailing and perennial riverine discharge vectors such as the Proto–Orinoco–Amazon river. Ancestral area estimation places the earliest colonizations of the Greater Antilles and Central America during the Paleocene–Eocene (ca. 58–45 Ma), potentially during the existence of an incomplete Paleogene Arc (∼59 Ma) or Lesser Antilles Arc (∼45 Ma), but predating the GAARlandia land bridge (∼34–33 Ma). Paleogeographic distance is the single best predictor of DO. The Western (Central American) plate margin did not serve as a dispersal corridor until the Late Neogene (12–0 Ma), and contributed relatively little to the formation of modern distributions.

Background The use of intermittent preventive treatment in pregnant women (IPTp), children (IPTc) and infant (IPTi) is an increasingly popular preventive strategy aimed at reducing malaria risk in these vulnerable groups. Studies to understand how this preventive intervention can affect the spread of anti-malarial drug resistance are important especially when there is human movement between neighbouring low and high transmission areas. Because the same drug is sometimes utilized for IPTi and for symptomatic malaria treatment, distinguishing their individual roles on accelerating the spread of drug resistant malaria, with or without human movement, may be difficult to isolate experimentally or by analysing data. A theoretical framework, as presented here, is thus relevant as the role of IPTi on accelerating the spread of drug resistance can be isolated in individual populations and when the populations are interconnected and interact. Methods A previously published model is expanded to include human movement between neighbouring high and low transmission areas, with focus placed on the malaria parasites. Parasite fitness functions, determined by how many humans the parasites can infect, are used to investigate how fast resistance can spread within the neighbouring communities linked by movement, when the populations are at endemic equilibrium. Results Model simulations indicate that population movement results in resistance spreading fastest in high transmission areas, and the more complete the anti-malarial resistance the faster the resistant parasite will tend to spread through a population. Moreover, the demography of infection in low transmission areas tends to change to reflect the demography of high transmission areas. Additionally, when regions are strongly connected the rate of spread of partially resistant parasites (R1) relative to drug sensitive parasites (RS), and fully resistant parasites (R2) relative to partially resistant parasites (R1) tend to behave the same in both populations, as should be expected. Conclusions In fighting anti-malarial drug resistance, different drug resistance monitoring and management policies are needed when the area in question is an isolated high or low transmission area, or when it is close and interacting with a neighbouring high or low transmission area, with human movement between them. Electronic supplementary material The online version of this article (doi:10.1186/1475-2875-13-428) contains supplementary material, which is available to authorized users.

Models for infectious diseases usually assume a fixed demographic structure. Yet, a disease can spread over a region encountering different local demographic variations that may significantly alter local dynamics. Spatial heterogeneity in the resulting dynamics can lead to important differences in the design of surveillance and control strategies. We illustrate this by exploring the north–south gradient in the seasonal demography of raccoon rabies over the eastern USA. We find that the greater variance in the timing of spring births characteristic of southern populations can lead to the spatial synchronization of southern epidemics, while the narrow birth-pulse associated with northern populations can lead to an irregular patchwork of epidemics. These results indicate that surveillance in the southern states can be reduced relative to northern locations without loss of detection ability. This approach could yield significant savings in vaccination programmes. The importance of seasonality in many widely distributed diseases indicates that our findings will find applications beyond raccoon rabies.

To effectively manage large natural reserves, resource managers must prepare for future contingencies while balancing the often conflicting priorities of different stakeholders. To deal with these issues, managers routinely employ models to project the response of ecosystems to different scenarios that represent alternative management plans or environmental forecasts. Scenario analysis is often used to rank such alternatives to aid the decision making process. However, model projections are subject to uncertainty in assumptions about model structure, parameter values, environmental inputs, and subcompo- nent interactions. We introduce an approach for testing the robustness of model-based management decisions to the uncertainty inherent in complex ecological models and their inputs. We use relative assessment to quantify the relative impacts of uncertainty on scenario ranking. To illustrate our approach we consider uncertainty in parameter values and uncertainty in input data, with specific examples drawn from the Florida Everglades restoration project. Our examples focus on two alternative 30-year hydrologic management plans that were ranked according to their overall impacts on wildlife habitat potential. We tested the assumption that varying the parameter settings and inputs of habitat index models does not change the rank order of the hydrologic plans. We compared the average projected index of habitat potential for four endemic species and two wading-bird guilds to rank the plans, accounting for variations in parameter settings and water level inputs associated with hypothetical future climates. Indices of habitat potential were based on projections from spatially explicit models that are closely tied to hydrology. For the American alligator, the rank order of the hydrologic plans was unaffected by substantial variation in model parameters. By contrast, simulated major shifts in water levels led to reversals in the ranks of the hydrologic plans in 24.1-30.6% of the projections for the wading bird guilds and several individual species. By exposing the differential effects of uncertainty, relative assessment can help resource managers assess the robustness of scenario choice in model-based policy decisions.

Agent-based or individual-based models allow for variation in the state and behavior of the basic objects that interact within the model. Modeling each individual as a separate entity allows for spatially explicit components to be included so that the individuals can interact with a heterogeneous landscape and with each other. Realism is added to the models by incorporating spatially explicit data for the area of interest. Integrating spatial data into an agent-based system requires that a significant level of geographic information systems (GIS) functionality from traditional GIS be incorporated into the modeling system. This approach may seem redundant and costly, but current GIS systems do not offer a framework for building dynamic agent-based models. The across-trophic-level system simulation (ATLSS) is characterized by the integration of several distinct agent-based models and spatially explicit data into a single modeling system. One of the goals of the ATLSS (pronounced like “atlas”) project is to investigate the relative response of various interconnected trophic levels of the South Florida (SF) Everglades to different hydrologic scenarios over a thirty-year planning horizon. The ATLSS approach consists of several distinct component models, each of which represents different biotic components of the Everglades system, linked together as a multimodel. Currently, ATLSS includes component models for the Florida Panther, the Cape Sable Sea Side Sparrow, white tail deer, fresh water fish, wading birds, the Snail kite, and vegetation biomass. Additional models for alligators and various reptiles and amphibians are in development and will be added as they are completed. The list above by no means enumerates all of the species in SF. It reflects instead the initial attempt to include key components that biologists with many years of field experience in SF believed were critical to include. It also reflects the time and funding limitations to carry out empirical studies and develop both the theory and software needed to model each system component. The Florida Panther, the Cape Sable Seaside Sparrow, the Snail Kite and several wading bird species of SF are all listed as endangered species. The fish, deer, and vegetation on the other hand are included since they are critical resources for the endangered species.