Riverine invertebrate assemblages are degraded more by catchment urbanisation than by riparian deforestation

1. Restoration of riparian forests has been promoted as a means of mitigating urban impacts on stream ecosystems. However, conventional urban stormwater drainage may diminish the beneficial effect of riparian forests.
2. The relative effects of riparian deforestation and catchment urbanisation on stream ecosystems have rarely been discriminated because urban land use and riparian degradation usually covary. However, land use at three scales (channel canopy cover along a 100-m site, riparian forest cover within 200 m of the channel for 1 km upstream, and catchment imperviousness) covaried only weakly along the lowland Yarra River, Victoria, Australia.
3. We tested the extent to which each land use measure explained macroinvertebrate assemblage composition on woody debris and in the sediments of pools or runs in the mainstem Yarra River in autumn and spring 1998.
4. Assemblage composition in both habitats and in both seasons was most strongly correlated with proportion of catchment covered by impervious surfaces. Sites with higher imperviousness had fewer sensitive taxa (those having a strong positive influence on indicators of biological integrity) and more taxa typical of degraded urban streams. Sensitive taxa rarely occurred in sites with >4% total imperviousness. However, within sites of similar imperviousness, those with more riparian forest cover had more dipteran taxa. Channel canopy cover did not explain assemblage composition strongly.
5. Riparian forest cover may influence richness of some macroinvertebrate taxa, but catchment urbanisation probably has a stronger effect on sensitive taxa. In catchments with even a small amount of conventionally drained urban land, riparian revegetation is unlikely to have an effect on indicators of stream biological integrity. Reducing the impacts of catchment urbanisation through dispersed, low-impact drainage schemes is likely to be more effective.     

Inconsistency in short-term temporal variability of microgastropods within and between two different intertidal habitats

Small-scale temporal variation in abundances of fauna in marine soft sediments has long been recognised. Many studies on rocky intertidal shores have, however, focused on larger fauna in single habitats and have primarily examined relatively long time-scales. The implications of small-scale variability are frequently not adequately addressed in the studies of changes in fauna over longer time-scales. Without knowledge of the magnitude of variation at smaller scales, comparisons across longer time-scales may be confounded. In this study, the temporal variability of a number of co-existing species of microgastropods in patches of two different intertidal habitats (coralline turf and sediment) in Botany Bay, New South Wales, Australia, was measured using a nested, hierarchical sampling design incorporating temporal scales of weeks, 1 and 3 months. In addition to habitats, there were also spatial scales of metres between plots and 100s of metres between the locations. There was generally a lack of consistency in the trends of variance for the three temporal scales at the smallest spatial scale of plots. In addition, the different species, including those that were closely related, showed different patterns of variation, depending on the habitat and site. These data show the importance of incorporating adequate scales of sampling in different habitats when analysing the distribution and abundance of microbenthos in intertidal habitats.     

Urban catchment hydrology overwhelms reach scale effects of riparian vegetation on organic matter dynamics

1. Urbanisation severely affects stream hydrology, biotic integrity and water quality, but relatively little is known about effects on organic matter dynamics. Coarse particulate organic matter (CPOM) is a source of energy and nutrients in aquatic systems, and its availability has implications for ecosystem productivity and aquatic communities. In undisturbed environments, allochthonous inputs from riparian zones provide critical energy subsidies, but the extent to which this occurs in urbanised streams is poorly understood. 2. We investigated CPOM inputs, standing stocks, retention rates and retention mechanisms in urban and peri‐urban streams in Melbourne, Australia. Six streams were chosen along a gradient of catchment urbanisation, with the presence of reach scale riparian canopy cover as a second factor. CPOM retention was assessed at baseflow via replicate releases of marked Eucalyptus leaves where the retention distance and mechanism were recorded. CPOM and small wood (>1 cm diameter) storage were measured via cores and direct counts, respectively, while lateral and horizontal CPOM inputs were assessed using riparian litter traps. Stream discharge, velocity, depth and width were also measured. 3. CPOM inputs were not correlated with urbanisation, but were significantly higher in ‘closed’ canopy reaches. Urbanisation and riparian cover altered CPOM retention mechanisms, but not retention distances. Urban streams showed greater retention by rocks; while in less urban streams, retention by small wood was considerably higher. CPOM and small wood storage were significantly lower in more urban streams, but we found only a weak effect of riparian cover. 4. These findings suggest that while riparian vegetation increases CPOM inputs and has modest/weak effects on storage, catchment scale urbanisation decreases organic matter availability. Using an organic matter budget approach, it appears likely that the increased frequency and magnitude of high flows associated with catchment urbanisation exerts an overriding influence on organic matter availability. 5. We conclude that to maintain both organic matter inputs and storage, the restoration and protection of streams in urban or rapidly urbanising environments relies on the management of both riparian vegetation and catchment hydrology.     

Estimating the under-five mortality rate using a bayesian hierarchical time series model

Background

Millennium Development Goal 4 calls for a reduction in the under-five mortality rate by two-thirds between 1990 and 2015, which corresponds to an annual rate of decline of 4.4%. The United Nations Inter-Agency Group for Child Mortality Estimation estimates under-five mortality in every country to measure progress. For the majority of countries, the estimates within a country are based on the assumption of a piece-wise constant rate of decline.

Methods and Findings

This paper proposes an alternative method to estimate under-five mortality, such that the underlying rate of change is allowed to vary smoothly over time using a time series model. Information about the average rate of decline and changes therein is exchanged between countries using a Bayesian hierarchical model. Cross-validation exercises suggest that the proposed model provides credible bounds for the under-five mortality rate that are reasonably well calibrated during the observation period. The alternative estimates suggest smoother trends in under-five mortality and give new insights into changes in the rate of decline within countries.

Conclusions

The proposed model offers an alternative modeling approach for obtaining estimates of under-five mortality which removes the restriction of a piece-wise linear rate of decline and introduces hierarchy to exchange information between countries. The newly proposed estimates of the rate of decline in under-5 mortality and the uncertainty assessments would help to monitor progress towards Millennium Development Goal 4.     

Spatial synchrony in the response of a long range migratory species (Salmo salar) to climate change in the North Atlantic Ocean

A major challenge in understanding the response of populations to climate change is to separate the effects of local drivers acting independently on specific populations, from the effects of global drivers that impact multiple populations simultaneously and thereby synchronize their dynamics. We investigated the environmental drivers and the demographic mechanisms of the widespread decline in marine survival rates of Atlantic salmon (Salmo salar) over the last four decades. We developed a hierarchical Bayesian life cycle model to quantify the spatial synchrony in the marine survival of 13 large groups of populations (called stock units, SU) from two continental stock groups (CSG) in North America (NA) and Southern Europe (SE) over the period 1971–2014. We found strong coherence in the temporal variation in postsmolt marine survival among the 13 SU of NA and SE. A common North Atlantic trend explains 37% of the temporal variability of the survivals for the 13 SU and declines by a factor of 1.8 over the 1971–2014 time series. Synchrony in survival trends is stronger between SU within each CSG. The common trends at the scale of NA and SE capture 60% and 42% of the total variance of temporal variations, respectively. Temporal variations of the postsmolt survival are best explained by the temporal variations of sea surface temperature (SST, negative correlation) and net primary production indices (PP, positive correlation) encountered by salmon in common domains during their marine migration. Specifically, in the Labrador Sea/Grand Banks for populations from NA, 26% and 24% of variance is captured by SST and PP, respectively and in the Norwegian Sea for populations from SE, 21% and 12% of variance is captured by SST and PP, respectively. The findings support the hypothesis of a response of salmon populations to large climate‐induced changes in the North Atlantic simultaneously impacting populations from distant continental habitats.     

Legacies of land use and recent climatic change: the small mammal fauna in the mountains of Utah

Climate warming will continue alongside human modification of the landscape. Therefore, studying systems modified by land use may highlight factors that mitigate or exacerbate predicted biological responses to ongoing climate warming. Using historical museum specimen records and recent field surveys, I examine temporal patterns in the ecological dynamics of the small mammal fauna on five mountain ranges in central Utah over time intervals of 27-53 years during the past century. This landscape was heavily modified by livestock grazing early in the twentieth century and since then has witnessed a steady decline in grazing intensity. In general, at regional and landscape scales, species preferring mesic habitats increased in percent abundance, rank abundance, and rank occurrence over time. This result is opposite that predicted from regional climate trends and probably represents the recovery of forest conditions following a release over time from earlier periods of severe overgrazing. Decreased grazing intensity may thus mitigate the predicted biological effects of climatically driven environmental change for small mammals. This work also illustrates that abundance data gleaned from natural history collections can be an appropriate tool for assessing temporal changes in composition, especially when comparisons are drawn using time- and space-averaged data sets.     

Hierarchical Bayesian Estimation for the Number of Species

This paper is concerned with the estimation of the number of species in a population through a fully hierarchical Bayesian model using the Metropolis algorithm. The proposed Bayesian estimator is based on Poisson random variables with means that are distributed according to some prior distributions with unknown hyperparameters. An empirical Bayes approach is considered and compared with the fully Bayesian approach based on biological data.     

Catchment urbanisation and increased benthic algal biomass in streams: linking mechanisms to management

1. Urbanisation is an important cause of eutrophication in waters draining urban areas. We determined whether benthic algal biomass in small streams draining urban areas was explained primarily by small‐scale factors (benthic light, substratum type and nutrient concentrations) within a stream, or by catchment‐scale variables that incorporate the interacting multiple impacts of urbanisation (i.e. variables that describe urban density and the intensity of drainage or septic tank systems). 2. Benthic algal biomass was assessed as chlorophyll a density (chl a) in 16 streams spanning a rural–urban gradient, with both a wide range of urban density and of piped stormwater infrastructure intensity on the eastern fringe of metropolitan Melbourne, Australia. The gradient of urban density among streams was broadly correlated with catchment imperviousness, drainage connection (proportion of impervious areas connected to streams by stormwater pipes), altitude, longitude and median phosphorus concentration. Catchment area, septic tank density, median nitrogen concentration, benthic light (photosynthetically active radiation) and substratum type were not strongly correlated with the urban gradient. 3. Variation in benthic light and substratum type within streams explained a relatively small amount of variation in log chl a (3–11 and 1–13%, respectively) compared with between‐site variation (39–54%). 4. Median chl a was positively correlated with catchment urbanisation, with a large proportion of variance explained jointly (as determined by hierarchical partitioning) by those variables correlated with urban density. Independent of this correlation, the contributions of drainage connection and altitude to the explained variance in chl a were significant. 5. The direct connection of impervious surfaces to streams by stormwater pipes is hypothesised as the main determinant of algal biomass in these streams through its effect on the supply of phosphorus, possibly in interaction with stormwater‐related impacts on grazing fauna. Management of benthic algal biomass in streams of urbanised catchments is likely to be most effective through the application of stormwater management approaches that reduce drainage connection.     

Assessing spatiotemporal variation in abundance: A flexible framework accounting for sampling bias with an application to common pochard (Aythya ferina)

Assessing trends in the relative abundance of populations is a key yet complex issue for management and conservation. This is a major aim of many large‐scale censusing schemes such as the International Waterbird Count (IWC). However, owing to the lack of sampling strategy and standardization, such schemes likely suffer from biases due to spatial heterogeneity in sampling effort. Despite huge improvements of the statistical tools that allow tackling these statistical issues (e.g., GLMM, Bayesian inference), many conservationists still prefer to rely on stand‐alone turn‐key statistical tools, often violating the prerequisites put forward by the developers of these tools. Here, we propose a straightforward and flexible approach to tackle the typical statistical issues one can encounter when analyzing count data of monitoring schemes such as the IWC. We rely on IWC counts of the declining common pochard populations of the Northwest European flyway as a case study (period 2002–2012). To standardize the size of sampling units and mitigate spatial autocorrelation, we grouped sampling sites using a 75 × 75 km grid cells overlaid over the flyway of interest. Then, we used a hierarchical modeling approach, assessing population trends with random effects at two spatial scales (grid cells, and sites within grid cells) in order to derive spatialized values and to compute the average population trend at the whole flyway scale. Our approach allowed to tackle many statistical issues inherent to this type of analysis but often neglected, including spatial autocorrelation. Concerning the case study, our main findings are that: (1) the northwestern population of common pochards experienced a steep decline (4.9% per year over the 2002–2012 period); (2) the decline was more pronounced at high than low latitude (11.6% and 0.5% per year at 60° and 46° of latitude, respectively); and, (3) the decline was independent of the initial number of individuals in a given site (random across sites). Beyond the case study of the common pochard, our study provides a conceptual statistical framework for estimating and assessing potential drivers of population trends at various spatial scales.     

Very-broad-scale assessment of human impacts on river condition

1. Management of whole rivers and river catchments requires a comprehensive set of information about river condition and use, both existing and historical, and the links between them at regional, state or national scales. This paper outlines a new approach to the assessment of river condition, using a small team was able to assess 210 000 km of rivers across more than 3 million km² of Australia in little more than a year. 2. The approach was driven by a hierarchical model of river function, which assumed that broad‐scale catchment characteristics affect local hydrology, habitat features, water quality and, ultimately, aquatic biota. The model provided the basis for selecting important ecologically relevant features that indices should represent. For each reach of each river we derived a biological index and an environmental index based on measures quantifying catchment and hydrological condition, and habitat and water quality condition. Data came from existing state and national databases, satellite images, site measurements and process models. 3. All indices were calculated as deviation from a reference condition, were range‐standardised and were divided into equivalent bands of condition. Amalgamation of index components and of sub‐indices was determined by consideration of their ecological effects; for example, general degradation might be additive, but toxic effects of one component would override all others. 4. Several internal and external validation methods were employed, with the all‐important validation of the final assessments undertaken by comparison with a similar index based on locally measured data. 5. The environmental assessment classified 14% of reaches as largely unmodified, 67% as moderately modified and 19% as substantially modified by human impacts. The biological assessment based on site assessments and modelled data using invertebrates indicated that 70% of reaches were equivalent to reference condition and that 30% were significantly impaired. Catchment disturbance, elevated sediment and nutrient loads, and habitat degradation all contributed to these results. These impacts have all occurred during the last 200 years (post‐European settlement). 6. Partly as a result of the assessments of this study the Australian Government has begun to adopt a more environmentally sustainable approach to broad‐scale water management.     

A Hierarchical Bayesian Model to Quantify Uncertainty of Stream Water Temperature Forecasts

Providing generic and cost effective modelling approaches to reconstruct and forecast freshwater temperature using predictors as air temperature and water discharge is a prerequisite to understanding ecological processes underlying the impact of water temperature and of global warming on continental aquatic ecosystems. Using air temperature as a simple linear predictor of water temperature can lead to significant bias in forecasts as it does not disentangle seasonality and long term trends in the signal. Here, we develop an alternative approach based on hierarchical Bayesian statistical time series modelling of water temperature, air temperature and water discharge using seasonal sinusoidal periodic signals and time varying means and amplitudes. Fitting and forecasting performances of this approach are compared with that of simple linear regression between water and air temperatures using i) an emotive simulated example, ii) application to three French coastal streams with contrasting bio-geographical conditions and sizes. The time series modelling approach better fit data and does not exhibit forecasting bias in long term trends contrary to the linear regression. This new model also allows for more accurate forecasts of water temperature than linear regression together with a fair assessment of the uncertainty around forecasting. Warming of water temperature forecast by our hierarchical Bayesian model was slower and more uncertain than that expected with the classical regression approach. These new forecasts are in a form that is readily usable in further ecological analyses and will allow weighting of outcomes from different scenarios to manage climate change impacts on freshwater wildlife.     

Spatiotemporal variation in mechanisms driving regional‐scale population dynamics of a Threatened grassland bird

To achieve national population targets for migratory birds, landscape‐level conservation approaches are increasingly encouraged. However, knowledge of the mechanisms that drive spatiotemporal patterns in population dynamics are needed to inform scale‐variant policy development. Using hierarchical Bayesian models and variable selection, we determined by which mechanism(s), and to what extent, changes in quantity and quality of surrogate grassland habitats contributed to regional variation in population trends of an obligatory grassland bird, Bobolink (Dolichonyx oryzivorous). We used North American Breeding Bird Survey data to develop spatially explicit models of regional population trends over 25 years across 35 agricultural census divisions in Ontario, Canada. We measured the strength of evidence for effects of land‐use change on population trends over the entire study period and over five subperiods. Over the entire study period, one region (Perth) displayed strong evidence of population decline (95% CI is entirely below 0); four regions displayed strong evidence of population increase (Bruce, Simcoe, Peterborough, and Northumberland). Population trends shifted spatially among subperiods, with more extreme declines later in time (1986–1990: 28% of 35 census divisions, 1991–1995: 46%, 1996–2000: 40%, 2001–2005: 66%, 2006–2010: 82%). Important predictors of spatial patterns in Bobolink population trends over the entire study period were human development and fragmentation. However, factors inferred to drive patterns in population trends were not consistent over space and time. This result underscores that effective threat identification (both spatially and temporally) and implementation of flexible, regionally tailored policies will be critical to realize efficient conservation of Bobolink and similar at‐risk species.     

Landscape fragmentation affects responses of avian communities to climate change

Forecasting the consequences of climate change is contingent upon our understanding of the relationship between biodiversity patterns and climatic variability. While the impacts of climate change on individual species have been well‐documented, there is a paucity of studies on climate‐mediated changes in community dynamics. Our objectives were to investigate the relationship between temporal turnover in avian biodiversity and changes in climatic conditions and to assess the role of landscape fragmentation in affecting this relationship. We hypothesized that community turnover would be highest in regions experiencing the most pronounced changes in climate and that these patterns would be reduced in human‐dominated landscapes. To test this hypothesis, we quantified temporal turnover in avian communities over a 20‐year period using data from the New York State Breeding Atlases collected during 1980–1985 and 2000–2005. We applied Bayesian spatially varying intercept models to evaluate the relationship between temporal turnover and temporal trends in climatic conditions and landscape fragmentation. We found that models including interaction terms between climate change and landscape fragmentation were superior to models without the interaction terms, suggesting that the relationship between avian community turnover and changes in climatic conditions was affected by the level of landscape fragmentation. Specifically, we found weaker associations between temporal turnover and climatic change in regions with prevalent habitat fragmentation. We suggest that avian communities in fragmented landscapes are more robust to climate change than communities found in contiguous habitats because they are comprised of species with wider thermal niches and thus are less susceptible to shifts in climatic variability. We conclude that highly fragmented regions are likely to undergo less pronounced changes in composition and structure of faunal communities as a result of climate change, whereas those changes are likely to be greater in contiguous and unfragmented habitats.     

Evidence of Alaskan Trumpeter Swan Population Growth Using Bayesian Hierarchical Models

ABSTRACT Alaska (USA) contains a large proportion of the breeding population of trumpeter swans (Cygnus buccinator) in the United States. However, tracking population trends in Alaska trumpeter swans is complicated by variables such as an increase in survey effort over time, periodic surveys (1968 and every 5 yr after 1975), and missing data. We therefore constructed Bayesian hierarchical negative binomial models to account for nuisance variables and to estimate population size of trumpeter swans using aerial survey data from all known breeding habitats in Alaska, 1968–2005. We also performed an augmented analysis, where we entered zeroes for missing data. This approach differed from the standard (nonaugmented) analysis where we generated estimates for missing data through simulation. We estimated that adult swan populations in Alaska increased at an average rate of 5.9% annually (95% credibility interval = 5.2–6.6%) and cygnet production increased at 5.3% annually (95% credibility interval = 2.2–8.0%). We also found evidence that cygnet production exhibited higher rates of increase at higher latitudes in later years, which may be a response to warmer spring temperatures. Augmented analyses always produced higher swan population estimates than the nonaugmented estimates and likely overestimate true population abundance. Our results provide evidence that trumpeter swan populations are increasing in Alaska, especially at northern latitudes. Changes in population size and distribution could negatively affect tundra swans (Cygnus columbianus) breeding in Alaska, and biologists should monitor these interactions. We recommend using nonaugmented Bayesian hierarchical analyses to estimate wildlife populations when missing survey data occur.     

A species assemblage approach to comparative phylogeography of birds in southern Australia

We present a novel approach to investigating the divergence history of biomes and their component species using single-locus data prior to investing in multilocus data. We use coalescent-based hierarchical approximate Bayesian computation (HABC) methods (MsBayes) to estimate the number and timing of discrete divergences across a putative barrier and to assign species to their appropriate period of co-divergence. We then apply a coalescent-based full Bayesian model of divergence (IMa) to suites of species shown to have simultaneously diverged. The full Bayesian model results in reduced credibility intervals around divergence times and allows other parameters associated with divergence to be summarized across species assemblages. We apply this approach to 10 bird species that are wholly or patchily discontinuous in semi-arid habitats between Australia's southwest (SW) and southeast (SE) mesic zones. There was substantial support for up to three discrete periods of divergence. HABC indicates that two species wholly restricted to more mesic habitats diverged earliest, between 594,382 and 3,417,699 years ago, three species from semi-arid habitats diverged between 0 and 1,508,049 years ago, and four diverged more recently, between 0 and 396,843 years ago. Eight species were assigned to three periods of co-divergence with confidence. For full Bayesian analyses, we accounted for uncertainty in the two remaining species by analyzing all possible suites of species. Estimates of divergence times from full Bayesian divergence models ranged between 429,105 and 2,006,355; 67,172 and 663,837; and 24,607 and 171,085 for the earliest, middle, and most recent periods of co-divergence, respectively. This single-locus approach uses the power of multitaxa coalescent analyses as an efficient means of generating a foundation for further, targeted research using multilocus and genomic tools applied to an understudied biome.     

Importance of scale,land‐use,and stream network properties for riparian plant communities along an urban gradient

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A geostatistical approach to large-scale disease mapping with temporal misalignment

Summary Temporal boundary misalignment occurs when area boundaries shift across time (e.g., census tract boundaries change at each census year), complicating the modeling of temporal trends across space. Large area-level datasets with temporal boundary misalignment are becoming increasingly common in practice. The few existing approaches for temporally misaligned data do not account for correlation in spatial random effects over time. To overcome issues associated with temporal misalignment, we construct a geostatistical model for aggregate count data by assuming that an underlying continuous risk surface induces spatial correlation between areas. We implement the model within the framework of a generalized linear mixed model using radial basis splines. Using this approach, boundary misalignment becomes a nonissue. Additionally, this disease-mapping framework facilitates fast, easy model fitting by using a penalized quasilikelihood approximation to maximum likelihood estimation. We anticipate that the method will also be useful for large disease-mapping datasets for which fully Bayesian approaches are infeasible. We apply our method to assess socioeconomic trends in breast cancer incidence in Los Angeles between the periods 1988-1992 and 1998-2002.     

Urban stormwater runoff limits distribution of platypus

The platypus (Ornithorhynchus anatinus), like many other stream‐dependent species, is reportedly sensitive to catchment urbanization. However, the primary mechanism limiting its distribution in urban environments has not been identified. We created species distribution models for three platypus demographic classes: adult females (which are exclusively responsible for raising young), adult males (which are more mobile than females), and first‐year juveniles. Using live‐trapping data collected in Melbourne, Australia, we tested whether distributions of the three demographic classes were better predicted by catchment urban density (total imperviousness), by urban stormwater runoff (catchment attenuated imperviousness), or by stream size (catchment area). Two variants of each predictor variable were developed, one that accounted for platypus mobility, and one that did not. Female distribution was most plausibly predicted by stormwater runoff (accounting for mobility), with a steep decline in reporting rate from 0 to 10% attenuated imperviousness. Male distribution was equally plausibly predicted by stormwater runoff and urban density (both accounting for mobility), with a less steep and more uncertain decline with imperviousness than females. Juvenile distribution was most plausibly predicted by stream size (accounting for mobility), but both stormwater runoff and urban density (accounting for mobility) were nearly equally plausible predictors. The superior performance of models that accounted for mobility underscores the importance of accounting for this in species distribution models of highly mobile species. Platypus populations in urban areas are likely to be affected adversely by urban stormwater runoff conveyed by conventional drainage systems, with adult females more limited by runoff‐related impacts than adult males or juveniles. Urban platypus conservation efforts have generally focused on restoring riparian and in‐stream habitats on a local scale. This is unlikely to protect platypus from adverse impacts of urban stormwater runoff, which is most effectively managed at the catchment scale.     

Model‐based integration of observed and expert‐based information for assessing the geographic and environmental distribution of freshwater species

Freshwater ecosystems harbor specialized and vulnerable biodiversity, and the prediction of potential impacts of freshwater biodiversity to environmental change requires knowledge of the geographic and environmental distribution of taxa. To date, however, such quantitative information about freshwater species distributions remains limited. Major impediments include heterogeneity in available species occurrence data, varying detectability of species in their aquatic environment, scarcity of contiguous freshwater‐specific predictors, and methods that support addressing these issues in a single framework. Here we demonstrate the use of a hierarchical Bayesian modeling (HBM) framework that combines disparate species occurrence information with newly‐developed 1 km freshwater‐specific predictors, to account for imperfect species detection and make fine‐grain (1 km) estimates of distributions in freshwater organisms. The approach integrates a Bernoulli suitability and a Binomial observability process into a hierarchical zero‐inflated Binomial model. The suitability process includes point presence observations, records of site visits, 1 km environmental predictors and expert‐derived species range maps integrated with a distance‐decay function along the within‐stream distance as covariates. The observability process uses repeated observations to estimate a probability of observation given that the species was present. The HBM accounts for the spatial autocorrelation in species habitat suitability projections using an intrinsic Gaussian conditional autoregressive model. We used this framework for three fish species native to different regions and habitats in North America. Model comparison shows that HBMs significantly outperformed non‐spatial GLMs in terms of AUC and TSS scores, and that expert information when appropriately included in the model can provide an important refinement. Such ancillary species information and an integrative, hierarchical Bayesian modeling framework can therefore be used to advance fine‐grain habitat suitability predictions and range size estimates in the freshwater realm. Our approach is extendable in terms of data availability and generality and can be used on other freshwater organisms and regions.     

Interactive effects of rising temperatures and urbanisation on birds across different climate zones: A mechanistic perspective

Climate change and urbanisation are among the most pervasive and rapidly growing threats to biodiversity worldwide. However, their impacts are usually considered in isolation, and interactions are rarely examined. Predicting species' responses to the combined effects of climate change and urbanisation, therefore, represents a pressing challenge in global change biology. Birds are important model taxa for exploring the impacts of both climate change and urbanisation, and their behaviour and physiology have been well studied in urban and non-urban systems. This understanding should allow interactive effects of rising temperatures and urbanisation to be inferred, yet considerations of these interactions are almost entirely lacking from empirical research. Here, we synthesise our current understanding of the potential mechanisms that could affect how species respond to the combined effects of rising temperatures and urbanisation, with a focus on avian taxa. We discuss potential interactive effects to motivate future in-depth research on this critically important, yet overlooked, aspect of global change biology. Increased temperatures are a pronounced consequence of both urbanisation (through the urban heat island effect) and climate change. The biological impact of this warming in urban and non-urban systems will likely differ in magnitude and direction when interacting with other factors that typically vary between these habitats, such as resource availability (e.g. water, food and microsites) and pollution levels. Furthermore, the nature of such interactions may differ for cities situated in different climate types, for example, tropical, arid, temperate, continental and polar. Within this article, we highlight the potential for interactive effects of climate and urban drivers on the mechanistic responses of birds, identify knowledge gaps and propose promising future research avenues. A deeper understanding of the behavioural and physiological mechanisms mediating species' responses to urbanisation and rising temperatures will provide novel insights into ecology and evolution under global change and may help better predict future population responses.