Bee species richness through time in an urbanizing landscape of the southeastern United States

Compared to non-urban environments, cities host ecological communities with altered taxonomic diversity and functional trait composition. However, we know little about how these urban changes take shape over time. Using historical bee (Apoidea: Anthophila) museum specimens supplemented with online repositories and researcher collections, we investigated whether bee species richness tracked urban and human population growth over the past 118 years. We also determined which species were no longer collected, whether those species shared certain traits, and if collector behavior changed over time. We focused on Wake County, North Carolina, United States where human population size has increased over 16 times over the last century along with the urban area within its largest city, Raleigh, which has increased over four times. We estimated bee species richness with occupancy models, and rarefaction and extrapolation curves to account for imperfect detection and sample coverage. To determine if bee traits correlated with when species were collected, we compiled information on native status, nesting habits, diet breadth, and sociality. We used non-metric multidimensional scaling to determine if individual collectors contributed different bee assemblages over time. In total, there were 328 species collected in Wake County. We found that although bee species richness varied, there was no clear trend in bee species richness over time. However, recent collections (since 2003) were missing 195 species, and there was a shift in trait composition, particularly lost species were below-ground nesters. The top collectors in the dataset differed in how often they collected bee species, but this was not consistent between historic and contemporary time periods; some contemporary collectors grouped closer together than others, potentially due to focusing on urban habitats. Use of historical collections and complimentary analyses can fill knowledge gaps to help understand temporal patterns of species richness in taxonomic groups that may not have planned long-term data.

Assessing the Influence of Anthropogenic Land-Use Changes on Bird Diversity and Feeding Guilds—A Case Study of Kalametiya Lagoon (Southern Sri Lanka)

Kalametiya Lagoon, a highly threatened Sri Lankan wetland, has undergone drastic hydrological changes in recent decades, due to an upstream irrigation project. These changes led to the invasion of the lagoon water by monospecific Sonneratia caseolaris mangrove stands and Typha angustifolia reedbeds. As Kalametiya has been a nationally recognized bird sanctuary since 1984, this invasion is expected to have brought significant changes upon local avifauna. Therefore, this study aimed at determining the lagoon’s current bird diversity and distribution in relation with habitat types and environmental variables. Thirty-seven point-count stations were studied, between January and April 2022. Seventy-nine bird species, including four endemic and ten nationally threatened species, were encountered during the study period. Invertebrate feeders and polyphages were the richest and most diverse guilds. Bird communities were also found richer and more diverse in T. angustifolia reedbeds than in S. caseolaris mangroves. As feeding guild composition was significantly influenced by several environmental variables (i.e., water nitrate content, water TDS, water pH, soil pH), guilds could have great potential as bioindicators of the ecosystem if further studies are done to explore these relationships. Considering the important bird diversity found in the new habitats, this research brings additional proof that a management aiming at restoring the lagoon to its past state would bring significant changes to its avifaunal community. These changes could, in the future, be more precisely defined by a thorough comparison with past inventories of the lagoon’s bird community.

A comparison of monitoring designs to assess wildlife community parameters across spatial scales

Dedicated long-term monitoring at appropriate spatial and temporal scales is necessary to understand biodiversity losses and develop effective conservation plans. Wildlife monitoring is often achieved by obtaining data at a combination of spatial scales, ranging from local to broad, to understand the status, trends, and drivers of individual species or whole communities and their dynamics. However, limited resources for monitoring necessitates tradeoffs in the scope and scale of data collection. Careful consideration of the spatial and temporal allocation of finite sampling effort is crucial for monitoring programs that span multiple spatial scales. Here we evaluate the ability of five monitoring designs-stratified random, weighted effort, indicator unit, rotating panel, and split panel-to recover parameter values that describe the status (occupancy), trends (change in occupancy), and drivers (spatially varying covariate and an autologistic term) of wildlife communities at two spatial scales. Using an amphibian monitoring program that spans a network of US national parks as a motivating example, we conducted a simulation study for a regional community occupancy sampling program to compare the monitoring designs across varying levels of sampling effort (ranging from 10% to 50%). We found that the stratified random design outperformed the other designs for most parameters of interest at both scales and was thus generally preferable in balancing the estimation of status, trends, and drivers across scales. However, we found that other designs had improved performance in specific situations. For example, the rotating panel design performed best at estimating spatial drivers at a regional level. Thus, our results highlight the nuanced scenarios in which various design strategies may be preferred and offer guidance as to how managers can balance common tradeoffs in large-scale and long-term monitoring programs in terms of the specific knowledge gained. Monitoring designs that improve accuracy in parameter estimates are needed to guide conservation policy and management decisions in the face of broad-scale environmental challenges, but the preferred design is sensitive to the specific objectives of a monitoring program.

Sampling errors and variability in video transects for assessment of reef fish assemblage structure and diversity

Video monitoring is a rapidly evolving tool in aquatic ecological research because of its non-destructive ability to assess fish assemblages. Nevertheless, methodological considerations of video monitoring techniques are often overlooked, especially in more complex sampling designs, causing inefficient data collection, processing, and interpretation. In this study, we discuss how video transect sampling designs could be assessed and how the inter-observer variability, design errors and sampling variability should be quantified and accounted for. The study took place in the coastal areas of the Galapagos archipelago and consisted of a hierarchical repeated-observations sampling design with multiple observers. Although observer bias was negligible for the assessment of fish assemblage structure, diversity and counts of individual species, sampling variability caused by simple counting/detection errors, observer effects and instantaneous fish displacement was often important. Especially for the counts of individual species, sampling variability most often exceeded the variability of the transects and sites. An extensive part of the variability in the fish assemblage structure was explained by the different transects (13%), suggesting that a sufficiently high number of transects is required to account for the within-location variability. Longer transect lengths allowed a better representation of the fish assemblages as sampling variability decreased by 33% if transect length was increased from 10 to 50 meters. However, to increase precision, including more repeats was typically more efficient than using longer transect lengths. The results confirm the suitability of the technique to study reef fish assemblages, but also highlight the importance of a sound methodological assessment since different biological responses and sampling designs are associated with different levels of sampling variability, precision and ecological relevance. Therefore, besides the direct usefulness of the results, the procedures to establish them may be just as valuable for researchers aiming to optimize their own sampling technique and design.

Revision of the endemic African genus Dinapsis (Dinapsini, Megalyridae, Hymenoptera) with description of seven new species

The endemic Afrotropical genus Dinapsis is revised, and seven new species are described and illustrated: D.bicolor van Noort & Shaw, sp. nov., D.gamka van Noort & Shaw, sp. nov., D.igneus van Noort & Shaw, sp. nov., D.spinitibia van Noort & Shaw, sp. nov., D.taita van Noort & Shaw, sp. nov., D.tricolor Shaw & van Noort, sp. nov., D.zulu Shaw & van Noort, sp. nov. The distribution of the Central African Republican species D.centralis Shaw & van Noort, 2009 is extended to include Cameroon, Kenya and Uganda. Dinapsisturneri Waterston, 1922, previously only known from the poorly preserved holotype female, is redescribed based on newly collected specimens. The distribution of this Western Cape species is extended to include the Eastern and Northern Cape provinces of South Africa. Four distinct species groups within the genus are proposed and diagnosed. An illustrated identification key to all described species of Dinapsis is provided. Online interactive Lucid keys to Afrotropical megalyrid genera and Dinapsis species are available at http://www.waspweb.org.

Variation in herpetofauna detection probabilities: implications for study design

Population monitoring is fundamental for informing management decisions aimed at reducing the rapid rate of global biodiversity decline. Herpetofauna are experiencing declines worldwide and include species that are challenging to monitor. Raw counts and associated metrics such as richness indices are common for monitoring populations of herpetofauna; however, these methods are susceptible to bias as they fail to account for varying detection probabilities. Our goal was to develop a program for efficiently monitoring herpetofauna in southern Texas. Our objectives were to (1) estimate detection probabilities in an occupancy modeling framework using trap arrays for a diverse group of herpetofauna and (2) to evaluate the relative effectiveness of funnel traps, pitfall traps, and cover boards. We collected data with 36 arrays at 2 study sites in 2015 and 2016, for 2105 array-days resulting in 4839 detections of 51 species. We modeled occupancy for 21 species and found support for the hypothesis that detection probability varied over our sampling duration for 10 species and with rainfall for 10 species. For herpetofauna in our study, we found 14 and 12 species were most efficiently captured with funnel traps and pitfall traps, respectively, and no species were most efficiently captured with cover boards. Our results show that using methods that do not account for variations in detection probability are highly subject to bias unless the likelihood of false absences is minimized with exceptionally long capture durations. For monitoring herpetofauna in southern Texas, we recommend using arrays with funnel and pitfall traps and an analytical method such as occupancy modeling that accounts for variation in detection.

The hidden side of diversity: Effects of imperfect detection on multiple dimensions of biodiversity

Studies on ecological communities often address patterns of species distribution and abundance, but few consider uncertainty in counts of both species and individuals when computing diversity measures.We evaluated the extent to which imperfect detection may influence patterns of taxonomic, functional, and phylogenetic diversity in ecological communities.We estimated the true abundance of fruit-feeding butterflies sampled in canopy and understory strata in a subtropical forest. We compared the diversity values calculated by observed and estimated abundance data through the hidden diversity framework. This framework evaluates the deviation of observed diversity when compared with diversities derived from estimated true abundances and whether such deviation represents a bias or a noise in the observed diversity pattern.The hidden diversity values differed between strata for all diversity measures, except for functional richness. The taxonomic measure was the only one where we observed an inversion of the most diverse stratum when imperfect detection was included. Regarding phylogenetic and functional measures, the strata showed distinct responses to imperfect detection, despite the tendency to overestimate observed diversity. While the understory showed noise for the phylogenetic measure, since the observed pattern was maintained, the canopy had biased diversity for the functional metric. This bias occurred since no significant differences were found between strata for observed diversity, but rather for estimated diversity, with the canopy being more clustered.We demonstrate that ignore imperfect detection may lead to unrealistic estimates of diversity and hence to erroneous interpretations of patterns and processes that structure biological communities. For fruit-feeding butterflies, according to their phylogenetic position or functional traits, the undetected individuals triggered different responses in the relationship of the diversity measures to the environmental factor. This highlights the importance to evaluate and include the uncertainty in species detectability before calculating biodiversity measures to describe communities.

Why a landscape view is important: nearby urban and agricultural land affects bird abundances in protected areas

Protected areas are one of the primary conservation tools used worldwide. However, they are often embedded in a landscape that is intensely used by people, such as for agriculture or urban development. The proximity of these land-use types to protected areas can potentially affect the ecological effectiveness (or conservation effectiveness) of protected areas. In this article, we examine to what degree adjacent agricultural and urban land uses affect the ecological effectiveness of protected areas over the greater Gauteng region of South Africa. We selected 198 common, resident bird species, and analysed detection/non-detection data for these species collected over regular grid cells (approximately 61 km² in area). For each species, we estimated abundance per grid cell with the Royle-Nichols model in relation to the proportion of protected area as a covariate. Our study focused on how this relationship between proportion of protected area and abundance (which we term the ‘protection–abundance relationship’) changed as a function of other land-use types in the grid cell. Specifically, we examined the interaction effects between protected area and both urban and agricultural land-use type per grid cell on bird abundance. We assigned each species to one of seven guilds, namely: frugivores, gleaners, granivores, ground-feeders, hawkers, predators and vegivores, and examined how the protection–abundance relationship varied across guilds in relation to agriculture and urban area. As urban area within a grid cell increased, the protection–abundance relationship became more positive for 58% of all species. At the level of guilds, the protection–abundance relationship became more positive for two guilds (granivores and ground-feeders), more negative for frugivores, and remained unchanged for the other four guilds (gleaners, hawkers, predators and vegivores). As agricultural area within a grid cell increased, the protection–abundance relationship became more positive for 49% of all species. At the guild level, the protection–abundance relationship became more positive for six guilds (frugivores, gleaners, ground-feeders, hawkers, predators and vegivores) and remained unchanged for the granivores. Our results show land-use type near protected areas modified the effect protected areas had on bird abundances, and hence the ecological effectiveness of protected areas. Our results suggest that protected areas should be viewed as constituents within the landscape, rather than islands of protection.

Amazonian mammal monitoring using aquatic environmental DNA

Environmental DNA (eDNA) metabarcoding has emerged as one of the most efficient methods to assess aquatic species presence. While the method can in theory be used to investigate nonaquatic fauna, its development for inventorying semi-aquatic and terrestrial fauna is still at an early stage. Here we investigated the potential of aquatic eDNA metabarcoding for inventorying mammals in Neotropical environments, be they aquatic, semi-aquatic or terrestrial. We collected aquatic eDNA in 96 sites distributed along three Guianese watersheds and compared our inventories to expected species distributions and field observations derived from line transects located throughout French Guiana. Species occurrences and emblematic mammalian fauna richness patterns were consistent with the expected distribution of fauna and our results revealed that aquatic eDNA metabarcoding brings additional data to line transect samples for diurnal nonaquatic (terrestrial and arboreal) species. Aquatic eDNA also provided data on species not detectable in line transect surveys such as semi-aquatic, aquatic and nocturnal terrestrial and arboreal species. Although the application of eDNA to inventory mammals still needs some developments to optimize sampling efficiency, it can now be used as a complement to traditional surveys.

Network Analysis: Ten Years Shining Light on Host-Parasite Interactions

Biological interactions are key drivers of ecological and evolutionary processes. The complexity of such interactions hinders our understanding of ecological systems and our ability to make effective predictions in changing environments. However, network analysis allows us to better tackle the complexity of ecosystems because it extracts the properties of an ecological system according to the number and distribution of links among interacting entities. The number of studies using network analysis to solve ecological and evolutionary questions in parasitology has increased over the past decade. Here, we synthesise the contribution of network analysis toward disentangling host-parasite processes. Furthermore, we identify current trends in mainstream ecology and novel applications of network analysis that present opportunities for research on host-parasite interactions.

Comparing detectability patterns of bird species using multi-method occupancy modelling

A robust knowledge of biodiversity distribution is essential for designing and developing effective conservation actions. The choice of a suitable sampling method is key to obtaining sufficiently accurate information of species distribution and consequently to improve biodiversity conservation. This study applies multi-method occupancy models to 36 common bird species associated with small ponds in the province of Murcia (south-eastern Spain), one of the most arid regions of Europe, in order to compare their effectiveness for detecting different bird species: direct observation, combined observation and video monitoring and mist netting captures. The results showed that the combined method and direct observation were similar and most effective than mist netting for detecting species occupancy, although detection rates ranged widely among bird groups, while some large species were poorly detected by all the methods used. Average detectability did not increase during the breeding period. The chosen approach is particularly applicable to both single- and multi-species bird monitoring programmes. However, we recommend evaluating the cost-effectiveness of all the available methods in order to reduce costs and improve the success of sampling designs.

A simulation study of the use of temporal occupancy for identifying core and transient species

Transient species, which do not maintain self-sustaining populations in a system where they are observed, are ubiquitous in nature and their presence often impacts the interpretation of ecological patterns and processes. Identifying transient species from temporal occupancy, the proportion of time a species is observed at a given site over a time series, is subject to classification errors as a result of imperfect detection and source-sink dynamics. We use a simulation-based approach to assess how often errors in detection or classification occur in order to validate the use of temporal occupancy as a metric for inferring whether a species is a core or transient member of a community. We found that low detection increases error in the classification of core species, while high habitat heterogeneity and high detection increase error in classification of transient species. These findings confirm that temporal occupancy is a valid metric for inferring whether a species can maintain a self-sustaining population, but imperfect detection, low abundance, and highly heterogeneous landscapes may yield high misclassification rates.

Listening forward: approaching marine biodiversity assessments using acoustic methods

Ecosystems and the communities they support are changing at alarmingly rapid rates. Tracking species diversity is vital to managing these stressed habitats. Yet, quantifying and monitoring biodiversity is often challenging, especially in ocean habitats. Given that many animals make sounds, these cues travel efficiently under water, and emerging technologies are increasingly cost-effective, passive acoustics (a long-standing ocean observation method) is now a potential means of quantifying and monitoring marine biodiversity. Properly applying acoustics for biodiversity assessments is vital. Our goal here is to provide a timely consideration of emerging methods using passive acoustics to measure marine biodiversity. We provide a summary of the brief history of using passive acoustics to assess marine biodiversity and community structure, a critical assessment of the challenges faced, and outline recommended practices and considerations for acoustic biodiversity measurements. We focused on temperate and tropical seas, where much of the acoustic biodiversity work has been conducted. Overall, we suggest a cautious approach to applying current acoustic indices to assess marine biodiversity. Key needs are preliminary data and sampling sufficiently to capture the patterns and variability of a habitat. Yet with new analytical tools including source separation and supervised machine learning, there is substantial promise in marine acoustic diversity assessment methods.

Dimensions of Phyllostomid Bat Diversity and Assemblage Composition in a Tropical Forest-Agricultural Landscape

Tropical rainforests are suffering rapid habitat loss with large extensions of land transformed into agriculture. We wanted to know whether the type of agricultural activity in forest-agricultural landscapes affects how species composition as well as taxonomic and functional dimensions of diversity respond. We worked in the Amazon forests of southeast Peru and used bats as model organisms. We sampled mosaics characterized by forest adjacent to papaya plantations or cattle pastures. At each sampling site we established a transect in each of the three different vegetation types: forest interior, forest edge and agricultural land. We found that vegetation type was a better predictor of species composition than the type of agricultural land present. Vegetation structure characteristics explained differences in bat species composition between forest interior and edge. Agricultural land type chosen was not irrelevant as we found higher estimated species richness in papaya than in pasture sites. Agricultural land type present in a site and vegetation type affected functional diversity, with both agricultural land types showing a lower number of functionally distinct species than forests. We found papaya plantation sites showed species more evenly dispersed in trait space, suggesting they do better at conserving functional diversity when compared to cattle pasture sites. We demonstrate that sites that harbor agricultural activities can maintain a considerable proportion of the expected bat diversity. We note that this region still has large tracts of intact forest adjacent to agricultural lands, which may explain their ability to maintain relatively high levels bat diversity.

Institutional protocols for the oral administration (gavage) of chemicals and microscopic microbial communities to mice: Analytical consensus

IMPACT STATEMENT

Institutional protocols designed for the oral administration of live microbial communities, either complex or microscopic (microcosmic), to mice do not exist. However, this approach is increasingly employed by investigators focusing on the gut microbiome in experimental research. Herein, we propose two analytically Kappa-based consensus protocols to promote reproducibility and standardization in research practices and describe biologically relevant factors in achieving optimal microbial engraftment of communities in germ-free mice.

Assessing species richness trends: Declines of bees and bumblebees in the Netherlands since 1945

Estimating and predicting temporal trends in species richness is of general importance, but notably difficult because detection probabilities of species are imperfect and many datasets were collected in an opportunistic manner. We need to improve our capabilities to assess richness trends using datasets collected in unstandardized procedures with potential collection bias. Two methods are proposed and applied to estimate richness change, which both incorporate models for sampling effects and detection probability: (a) nonlinear species accumulation curves with an error variance model and (b) Pradel capture-recapture models. The methods are used to assess nationwide temporal trends (1945-2018) in the species richness of wild bees in the Netherlands. Previously, a decelerating decline in wild bee species richness was inferred for part of this dataset. Among the species accumulation curves, those with nonconstant changes in species richness are preferred. However, when analyzing data subsets, constant changes became selected for non-Bombus bees (for samples in collections) and bumblebees (for spatial grid cells sampled in three periods). Smaller richness declines are predicted for non-Bombus bees than bumblebees. However, when relative losses are calculated from confidence intervals limits, they overlap and touch zero loss. Capture-recapture analysis applied to species encounter histories infers a constant colonization rate per year and constant local species survival for bumblebees and other bees. This approach predicts a 6% reduction in non-Bombus species richness from 1945 to 2018 and a significant 19% reduction for bumblebees. Statistical modeling to detect species richness time trends should be systematically complemented with model checking and simulations to interpret the results. Data inspection, assessing model selection bias, and comparisons of trends in data subsets were essential model checking strategies in this analysis. Opportunistic data will not satisfy the assumptions of most models and this should be kept in mind throughout.

A re-examination of the relationship between Steller sea lion (Eumetopias jubatus) diet and population trend using data from the Aleutian Islands

Prey diversity and energy density have been linked to each other and to population trends in many studies of bird and mammal diets. We re-examined these relationships in Steller sea lions (Eumetopias jubatus (Schreber, 1776)) using data collected from the Aleutian Islands, where there has been a strong longitudinal gradient in population trend. Diet diversity and energy density metrics were similar in the western Aleutians, where sea lion counts declined consistently, and in the easternmost Aleutian area, where population trends improved significantly. We compared traditional deterministic diet diversity metrics with diversity scores based on an occupancy model that accounts for differences in sample size and uncertainty in prey group detection. This analysis indicated that there was no significant change in diet diversity over the 23-year study period or any significant differences across the Aleutian Islands. These results are consistent with prey abundance data from nine groundfish bottom trawl surveys conducted over the same period. While diet studies detail what Steller sea lions eat and provide an estimate of their energy intake, they provide only limited information on the energy expended to obtain their food or the consequences of their diet and foraging ecology on individual or population fitness.

Estimating the biodiversity of terrestrial invertebrates on a forested island using DNA barcodes and metabarcoding data

Invertebrates are a major component of terrestrial ecosystems, however, estimating their biodiversity is challenging. We compiled an inventory of invertebrate biodiversity along an elevation gradient on the temperate forested island of Hauturu, New Zealand, by DNA barcoding of specimens obtained from leaf litter samples and pitfall traps. We compared the barcodes and biodiversity estimates from this data set with those from a parallel DNA metabarcoding analysis of soil from the same locations, and with pre-existing sequences in reference databases, before exploring the use of combined data sets as a basis for estimating total invertebrate biodiversity. We obtained 1,282 28S and 1,610 COI barcodes from a total of 1,947 invertebrate specimens, which were clustered into 247 (28S) and 366 (COI) OTUs, of which ≤ 10% were represented in GenBank. Coleoptera were most abundant (730 sequenced specimens), followed by Hymenoptera, Diptera, Lepidoptera, and Amphipoda. The most abundant OTU from both the 28S (153 sequences) and COI (140 sequences) data sets was an undescribed beetle from the family Salpingidae. Based on the occurrences of COI OTUs along the elevation gradient, we estimated there are ~1,000 arthropod species (excluding mites) on Hauturu, including 770 insects, of which 344 are beetles. A DNA metabarcoding analysis of soil DNA from the same sites resulted in the identification of similar numbers of OTUs in most invertebrate groups compared with the DNA barcoding, but less than 10% of the DNA barcoding COI OTUs were also detected by the metabarcoding analysis of soil DNA. A mark-recapture analysis based on the overlap between these data sets estimated the presence of approximately 6,800 arthropod species (excluding mites) on the island, including ~3,900 insects. Estimates of New Zealand-wide biodiversity for selected arthropod groups based on matching of the COI DNA barcodes with pre-existing reference sequences suggested over 13,200 insect species are present, including 4,000 Coleoptera, 2,200 Diptera, and 2,700 Hymenoptera species, and 1,000 arachnid species (excluding mites). These results confirm that metabarcoding analyses of soil DNA tends to recover different components of terrestrial invertebrate biodiversity compared to traditional invertebrate sampling, but the combined methods provide a novel basis for estimating invertebrate biodiversity.

Inferring species richness using multispecies occupancy modeling: Estimation performance and interpretation

Multispecies occupancy models can estimate species richness from spatially replicated multispecies detection/non-detection survey data, while accounting for imperfect detection. A model extension using data augmentation allows inferring the total number of species in the community, including those completely missed by sampling (i.e., not detected in any survey, at any site). Here we investigate the robustness of these estimates. We review key model assumptions and test performance via simulations, under a range of scenarios of species characteristics and sampling regimes, exploring sensitivity to the Bayesian priors used for model fitting. We run tests when assumptions are perfectly met and when violated. We apply the model to a real dataset and contrast estimates obtained with and without predictors, and for different subsets of data. We find that, even with model assumptions perfectly met, estimation of the total number of species can be poor in scenarios where many species are missed (>15%-20%) and that commonly used priors can accentuate overestimation. Our tests show that estimation can often be robust to violations of assumptions about the statistical distributions describing variation of occupancy and detectability among species, but lower-tail deviations can result in large biases. We obtain substantially different estimates from alternative analyses of our real dataset, with results suggesting that missing relevant predictors in the model can result in richness underestimation. In summary, estimates of total richness are sensitive to model structure and often uncertain. Appropriate selection of priors, testing of assumptions, and model refinement are all important to enhance estimator performance. Yet, these do not guarantee accurate estimation, particularly when many species remain undetected. While statistical models can provide useful insights, expectations about accuracy in this challenging prediction task should be realistic. Where knowledge about species numbers is considered truly critical for management or policy, survey effort should ideally be such that the chances of missing species altogether are low.

Responses of aerial insectivorous bats to local and landscape-level features of coffee agroforestry systems in Western Ghats, India

Shade coffee has shown great promise in providing crucial habitats for biodiversity outside formal protected areas. Insectivorous bats have been understudied in coffee, although they may provide pest control services. We investigated the influence of local and landscape-level features of coffee farms on aerial insectivorous bats in Chikmagalur district in the Western Ghats biodiversity hotspot, India. Bats were monitored in 20 farm sites using ultrasound detectors, and the response of bat species richness and activity to changes in tree density, proportion of built-up area in the neighborhood, and distance of farm from forest areas quantified. We examined if models built to explain the species richness and activity could also predict them in nine additional sites. We detected nine phonic types/species in the study area. The quantified predictors had no effect on assemblage-level species richness and activity of bats. Responses of edge-space and cluttered-space forager guilds mirrored those of the overall assemblage, but some species vulnerable to forest conversion like Rhinolophus beddomei were detected rarely. Best models explained up to 20% and 15% variation in assemblage-level species richness and activity respectively, and were poor predictors of both response variables. We conclude that coffee farms in our study area offer an important commuting space for insectivorous bats across a gradient of shade management. Further research should include species-specific responses to management decisions for at-risk species and quantification of ecosystem services like natural pest control to inform biodiversity conservation initiatives in the Western Ghats coffee landscapes.

Assessing the impacts of imperfect detection on estimates of diversity and community structure through multispecies occupancy modeling

Detecting all species in a given survey is challenging, regardless of sampling effort. This issue, more commonly known as imperfect detection, can have negative impacts on data quality and interpretation, most notably leading to false absences for rare or difficult‐to‐detect species. It is important that this issue be addressed, as estimates of species richness are critical to many areas of ecological research and management. In this study, we set out to determine the impacts of imperfect detection, and decisions about thresholds for inclusion in occupancy, on estimates of species richness and community structure. We collected data from a stream fish assemblage in Algonquin Provincial Park to be used as a representation of ecological communities. We then used multispecies occupancy modeling to estimate species‐specific occurrence probabilities while accounting for imperfect detection, thus creating a more informed dataset. This dataset was then compared to the original to see where differences occurred. In our analyses, we demonstrated that imperfect detection can lead to large changes in estimates of species richness at the site level and summarized differences in the community structure and sampling locations, represented through correspondence analyses.

Forecasting biodiversity in breeding birds using best practices

Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertainty, and do not use time-series data that captures the actual dynamics being studied. We addressed these limitations by using best practices to explore our ability to forecast the species richness of breeding birds in North America. We used hindcasting to evaluate six different modeling approaches for predicting richness. Hindcasts for each method were evaluated annually for a decade at 1,237 sites distributed throughout the continental United States. All models explained more than 50% of the variance in richness, but none of them consistently outperformed a baseline model that predicted constant richness at each site. The best practices implemented in this study directly influenced the forecasts and evaluations. Stacked species distribution models and "naive" forecasts produced poor estimates of uncertainty and accounting for this resulted in these models dropping in the relative performance compared to other models. Accounting for observer effects improved model performance overall, but also changed the rank ordering of models because it did not improve the accuracy of the "naive" model. Considering the forecast horizon revealed that the prediction accuracy decreased across all models as the time horizon of the forecast increased. To facilitate the rapid improvement of biodiversity forecasts, we emphasize the value of specific best practices in making forecasts and evaluating forecasting methods.

The impact of strain-specific immunity on Lyme disease incidence is spatially heterogeneous

Lyme disease, caused by the bacterium Borrelia burgdorferi, is the most common tick-borne infection in the US. Recent studies have demonstrated that the incidence of human Lyme disease would have been even greater were it not for the presence of strain-specific immunity, which protects previously infected patients against subsequent infections by the same B. burgdorferi strain. Here, spatial heterogeneity is incorporated into epidemiological models to accurately estimate the impact of strain-specific immunity on human Lyme disease incidence. The estimated reduction in the number of Lyme disease cases is greater in epidemiologic models that explicitly include the spatial distribution of Lyme disease cases reported at the county level than those that utilize nationwide data. strain-specific immunity has the greatest epidemiologic impact in geographic areas with the highest Lyme disease incidence due to the greater proportion of people that have been previously infected and have developed strain-specific immunity.

Predicting cryptic links in host-parasite networks

Networks are a way to represent interactions among one (e.g., social networks) or more (e.g., plant-pollinator networks) classes of nodes. The ability to predict likely, but unobserved, interactions has generated a great deal of interest, and is sometimes referred to as the link prediction problem. However, most studies of link prediction have focused on social networks, and have assumed a completely censused network. In biological networks, it is unlikely that all interactions are censused, and ignoring incomplete detection of interactions may lead to biased or incorrect conclusions. Previous attempts to predict network interactions have relied on known properties of network structure, making the approach sensitive to observation errors. This is an obvious shortcoming, as networks are dynamic, and sometimes not well sampled, leading to incomplete detection of links. Here, we develop an algorithm to predict missing links based on conditional probability estimation and associated, node-level features. We validate this algorithm on simulated data, and then apply it to a desert small mammal host-parasite network. Our approach achieves high accuracy on simulated and observed data, providing a simple method to accurately predict missing links in networks without relying on prior knowledge about network structure.

Multiple methods increase detection of large and medium-sized mammals: working with volunteers in south-eastern Oman

We compared the effectiveness of various methods for surveying medium and large wild mammals in southern Oman. Working with volunteers recruited by Biosphere Expeditions, wildlife professionals and local rangers, we used direct observation, camera traps, sign surveys (tracks and/or dung) and molecular scatology to study 66 sampling units of 2 × 2 km (grid cells) in an area of 32 × 36 km during a 4-week period in February–March 2011. Sixteen mammal species were recorded, and the largest numbers of species were recorded by sign surveys and camera traps (both n = 9); sign surveys, direct sightings and DNA scatology recorded species across the largest number of grid cells. For species with a sample size large enough for comparison (i.e. detected in ≥ 8 grid cells), DNA scatology proved most effective for detecting caracal Caracal caracal, signs for hyaena Hyaena hyaena, ibex Capra nubiana, porcupine Hystrix indica and hyrax Procavia capensis, and signs and direct sightings for mountain gazelle Gazella gazella. Clustering, in which records from multiple methods are either adjacent or overlapping, was highest (≥ 76%) for the wolf Canis lupus, porcupine, ibex and gazelle. Our results indicate the best methods to detect and record the distributions of individual species in the study area, and demonstrate the advantage of using multiple methods to reduce the risk of false absences or partial detections. Our findings also highlight the potential of clustering as a means of cross-checking results of observations that are skill-dependent, which is particularly useful when employing a large workforce.

Taxonomic groups with lower movement capacity may present higher beta diversity

ABSTRACT Diversity analysis by partition is an approach employed in order to understand how communities spatially structure themselves and the factors that operate in the generation and maintenance of distribution patterns. We examined the spatial structure of species diversity of four taxonomic groups, with different dispersal abilities, in 16 forest fragments in the southern region of the state of Minas Gerais, Brazil. Specifically, we tested: i) if the similarity in species composition would be negatively related to geographical distance between the 16 fragments; and ii) if the beta diversity of the different groups could be negatively related to their dispersal abilities. Alpha diversity and the compositional similarity between localities were both low. Beta diversity was not correlated with distance for any of the groups. Primates, followed by birds, showed a higher tendency of forming similarity groupings, although in a manner that was independent from distance between fragments, as well as showed the lowest beta diversity relative values. Spermatophytes and amphibians did not define groupings and presented the highest values of beta diversity. We interpreted such results as indications that the groups with higher dispersal ability (primates and birds) tend to reach, on average, farther localities and, therefore, to define more similar groupings (low beta diversity). The groups with lower dispersal ability (spermatophytes and amphibians) showed the opposite tendency. Although most of the species were restricted to few localities, contributing to the low similarity, beta and gamma diversity values showed the extent which the localities are, respectively, different and complementary to each other in terms of species composition. Such features reinforce and justify future conservation initiatives, both in local and regional levels.