Species Occurrence Patterns Research Articles

Temporal and spatial distribution patterns of toothed whales in Massachusetts Bay using passive acoustics from ocean gliders

Basic information on marine mammal habitat use is necessary for informing ecosystem-based management plans and for mitigating human impacts. Massachusetts Bay is an important marine mammal foraging area in the Gulf of Maine and a region of high human activity, but little is known about toothed whale habitat use, particularly during winter months. Passive acoustic monitoring, particularly from autonomous platforms, provides advantages in studying habitat use in unfavorable conditions. The goal of this work is to use acoustic monitoring to investigate temporal and spatial occurrence patterns of toothed whale species in Massachusetts Bay during late fall/early winter using ocean gliders equipped with passive acoustic recorders. Slocum gliders were deployed in western Massachusetts Bay in 2014, 2015, and 2016. Toothed whales were detected on 92 (72%) of 128 deployment days. Detections occurred more often at night. Ongoing work includes acoustic identification of species and assessing relationships between detections and environmental conditions. These data provide the first evidence of a consistent presence of toothed whales in Massachusetts Bay during late fall and winter, and demonstrate the potential for ocean gliders as a tool to detect toothed whales in areas/times that are difficult to survey with traditional visual methods.

Resource use by the dryad butterfly is scale-dependent

The factors shaping the ways in which animals use resources are a key element of conservation biology, but ecological studies on resource use typically neglect to consider how the study’s spatial scale may have affected the outcomes. We used the dryad butterfly, inhabiting xerothermic grassland and wet meadow, to test for differences in its resource use at two scales–habitat patch and landscape. Based on records of plant species composition from random points within four habitat patches and from points in 53 patches along surveyed transects, we compared the microhabitat preferences of the butterfly on the patch scale, and species occurrence and abundance patterns on the landscape scale. We distinguished four main groups of factors related to vegetation structure which affected the butterfly’s resource use—factors having similar effects on both spatial scales, factors operating primarily on one of the scales considered, factors relevant only on a single spatial scale, and factors operating on both scales but with effects differing between the two habitat types. We suggest that invertebrates may respond on two spatial levels or on only one, and conclude that larger-scale studies can meet the challenges of a sophisticated metapopulation approach and can give insight into the habitat characteristics affecting the persistence of species in landscapes. We stress the value of large-scale studies on species’ habitat preferences when planning conservation strategies, while pointing out that small-scale studies provide useful information about species ecology and behavior, especially if conducted in multiple habitats.

Accounting for sampling patterns reverses the relative importance of trade and climate for the global sharing of exotic plants

AbstractAimThe distributions of exotic species reflect patterns of human‐mediated dispersal, species climatic tolerances and a suite of other biotic and abiotic factors. The relative importance of each of these factors will shape how the spread of exotic species is affected by ongoing economic globalization and climate change. However, patterns of trade may be correlated with variation in scientific sampling effort globally, potentially confounding studies that do not account for sampling patterns.LocationGlobal.Time periodMuseum records, generally from the 1800s up to 2015.Major taxa studiedPlant species exotic to the United States.MethodsWe used data from the Global Biodiversity Information Facility (GBIF) to summarize the number of plant species with exotic occurrences in the United States that also occur in each other country world‐wide. We assessed the relative importance of trade and climatic similarity for explaining variation in the number of shared species while evaluating several methods to account for variation in sampling effort among countries.ResultsAccounting for variation in sampling effort reversed the relative importance of trade and climate for explaining numbers of shared species. Trade was strongly correlated with numbers of shared U.S. exotic plants between the United States and other countries before, but not after, accounting for sampling variation among countries. Conversely, accounting for sampling effort strengthened the relationship between climatic similarity and species sharing. Using the number of records as a measure of sampling effort provided a straightforward approach for the analysis of occurrence data, whereas species richness estimators and rarefaction were less effective at removing sampling bias.Main conclusionsOur work provides support for broad‐scale climatic limitation on the distributions of exotic species, illustrates the need to account for variation in sampling effort in large biodiversity databases, and highlights the difficulty in inferring causal links between the economic drivers of invasion and global patterns of exotic species occurrence.

Seasonal and Interannual Changes in Ciliate and Dinoflagellate Species Assemblages in the Arctic Ocean (Amundsen Gulf, Beaufort Sea, Canada)

Recent studies have focused on how climate change could drive changes in phytoplankton communities in the Arctic. In contrast, ciliates and dinoflagellates that can contribute substantially to the mortality of phytoplankton have received less attention. Some dinoflagellate and ciliate species can also contribute to net photosynthesis, which suggests that species composition could reflect food web complexity. To identify potential seasonal and annual species occurrence patterns and to link species with environmental conditions, we first examined the seasonal pattern of microzooplankton and then performed an in-depth analysis of interannual species variability. We used high-throughput amplicon sequencing to identify ciliates and dinoflagellates to the lowest taxonomic level using a curated Arctic 18S rRNA gene database. DNA- and RNA-derived reads were generated from samples collected from the Canadian Arctic from November 2007 to July 2008. The proportion of ciliate reads increased in the surface towards summer, when salinity was lower and smaller phytoplankton prey were abundant, while chloroplastidic dinoflagellate species increased at the subsurface chlorophyll maxima (SCM), where inorganic nutrient concentrations were higher. Comparing communities collected in summer and fall from 2003-2010, and found that microzooplankton community composition change was associated with the record ice minimum in the summer of 2007. Specifically, reads from smaller predatory species like Laboea, Monodinium and Strombidium and several unclassified ciliates increased in the summer after 2007, while the other usually summer-dominant dinoflagellate taxa decreased. The ability to exploit smaller prey, which are predicted to dominate the future Arctic, could be an advantage for these smaller ciliates in the wake of the changing climate.

Effects of landscape composition on the occurrence of a widespread invasive bird species in the Brazilian Atlantic Forest

Despite the growing concern and literature on biological invasions, few studies have adopted an explicit landscape perspective to understand occurrence patterns of invasive species. We investigated how landscape composition influences the occurrence of a widespread invasive bird species, the Monk Parakeet Myiopsitta monachus, across landscapes of the Brazilian Atlantic Forest. We determined occurrence patterns and habitat composition in 24 sites, half of which harboring established populations of the species. Landscape composition had clear effects on species occurrence. Probability of occurrence decreased as the amounts of anthropogenic and agricultural areas in the landscape increased. Landscape composition was mostly strongly related to occurrence patterns when measured at the largest spatial scale considered (search radius=3km). Our results show that landscape composition may affect occurrence patterns of invasive species across landscapes. They also suggest that invasive species are not necessarily favored by habitat disturbance at the landscape level.

The age of lima bean leaves influences the richness and diversity of the endophytic fungal community, but not the antagonistic effect of endophytes against Colletotrichum lindemuthianum

Abstract Phaseolus lunatus (lima bean) has been a model organism to understand direct and indirect defenses against herbivores. We investigated the identity and diversity of endophytic fungi associated with young, mature and old leaves of lima bean in its natural environment. We recovered 758 isolates that were identified and classified in 142 fungal species from 66 genera, with Curvularia , Fusarium , Phomopsis , Alternaria and Colletotrichum being the most abundant and diverse Ascomycota genera. Our data revealed that species richness and diversity increased with leaf age, this factor being also important for the structure of the endophytic community. The occurrence patterns of fungal species was highly heterogeneous among leaves, and only fourteen species were recovered from all three foliar ages investigated. In vitro dual assays between endophytes and the plant pathogen Colletotrichum lindemuthianum revealed that most endophytes tested can inhibit the growth of this pathogen, suggesting their potential as biocontrol agents.

Effect of Environmental and Temporal Factors on Patterns of Rarity of Ephemeroptera in Stream of the Brazilian Cerrado.

Patterns of species' abundance and occurrence over time and space allow division of species into (i) common species, which are abundant, but have a low diversity, and (ii) rare species, which are far more diverse and less abundant. Understanding the relationships among these two species groups and how they are affected by environmental conditions is a major challenge for ecologists, especially considering the distinction between local environmental factors and regional factors and variations in abundance over the course of the year. In this study, we focused on the long-term relationship between the abundance of rare and common ephemeropterans and abiotic factors on local and regional scales. Our hypotheses are that common species will be affected primarily by regional environmental variables (i), whereas rare species will be influenced more by temporal variation (ii). Together, both local and regional abiotic variables, plus temporal variation, best explained the abundance of the common species, whereas temporal variation was the best predictor of rare species. Considering the theoretical aspects and the empirical evidence, we discuss the results based on the plasticity of the common species and the life cycle of the rare ones. We believe that our findings reinforce the need for the deconstruction of communities for a deeper understanding of their relationships with abiotic variables and, in particular, the specific aspects of these relationships in the context of the different guilds of the community.

The importance of motivation, weapons, and foul odors in driving encounter competition in carnivores.

Encounter competition is interference competition in which animals directly contend for resources. Ecological theory predicts the trait that determines the resource holding potential (RHP), and hence the winner of encounter competition, is most often body size or mass. The difficulties of observing encounter competition in complex organisms in natural environments, however, has limited opportunities to test this theory across diverse species. We studied the outcome of encounter competition contests among mesocarnivores at deer carcasses in California to determine the most important variables for winning these contests. We found some support for current theory in that body mass is important in determining the winner of encounter competition, but we found that other factors including hunger and species-specific traits were also important. In particular, our top models were "strength and hunger" and "size and hunger," with models emphasizing the complexity of variables influencing outcomes of encounter competition. In addition, our wins above predicted (WAP) statistic suggests that an important aspect that determines the winner of encounter competition is species-specific advantages that increase their RHP, as bobcats (Lynx rufus) and spotted skunks (Spilogale gracilis) won more often than predicted based on mass. In complex organisms, such as mesocarnivores, species-specific adaptations, including strategic behaviors, aggressiveness, and weapons, contribute to competitive advantages and may allow certain species to take control or defend resources better than others. Our results help explain how interspecific competition shapes the occurrence patterns of species in ecological communities.

Identifying environmental correlates of intraspecific genetic variation.

Genetic variation is critical to the persistence of populations and their capacity to adapt to environmental change. The distribution of genetic variation across a species' range can reveal critical information that is not necessarily represented in species occurrence or abundance patterns. We identified environmental factors associated with the amount of intraspecific, individual-based genetic variation across the range of a widespread freshwater fish species, the Murray cod Maccullochella peelii. We used two different approaches to statistically quantify the relative importance of predictor variables, allowing for nonlinear relationships: a random forest model and a Bayesian approach. The latter also accounted for population history. Both approaches identified associations between homozygosity by locus and both disturbance to the natural flow regime and mean annual flow. Homozygosity by locus was negatively associated with disturbance to the natural flow regime, suggesting that river reaches with more disturbed flow regimes may support larger, more genetically diverse populations. Our findings are consistent with the hypothesis that artificially induced perennial flows in regulated channels may provide greater and more consistent habitat and reduce the frequency of population bottlenecks that can occur frequently under the highly variable and unpredictable natural flow regime of the system. Although extensive river regulation across eastern Australia has not had an overall positive effect on Murray cod numbers over the past century, regulation may not represent the primary threat to Murray cod survival. Instead, pressures other than flow regulation may be more critical to the persistence of Murray cod (for example, reduced frequency of large floods, overfishing and chemical pollution).

Do community-weighted mean functional traits reflect optimal strategies?

The notion that relationships between community-weighted mean (CWM) traits (i.e. plot-level trait values weighted by species abundances) and environmental conditions reflect selection towards locally optimal phenotypes is challenged by the large amount of interspecific trait variation typically found within ecological communities. Reconciling these contrasting patterns is a key to advancing predictive theories of functional community ecology. We combined data on geographical distributions and three traits (wood density, leaf mass per area and maximum height) of 173 tree species in Puerto Rico. We tested the hypothesis that species are more likely to occur where their trait values are more similar to the local CWM trait values (the'CWM-optimality' hypothesis) by comparing species occurrence patterns (as a proxy for fitness) with the functional composition of forest plots across a precipitation gradient. While 70% of the species supported CWM-optimality for at least one trait, nearly 25% significantly opposed it for at least one trait, thereby contributing to local functional diversity. The majority (85%) of species that opposed CWM-optimality did so only for one trait and few species opposed CWM-optimality in multivariate trait space. Our study suggests that constraints to local functional variation act more strongly on multivariate phenotypes than on univariate traits.

Temporal trends in cusk eel sound production at a proposed US wind farm site

Many marine organisms produce sound during key life history events. Identifying and tracking these sounds can reveal spatial and temporal patterns of species occurrence and behaviors. We describe the temporal patterns of striped cusk eel Ophidion marginatum calls across approximately 1 yr in Nantucket Sound, MA, USA, the location of a proposed offshore wind energy installation. Stereotyped calls typical of courtship and spawning were detected from April to October with clear diel, monthly, and seasonal patterns. Acoustic energy increased in the evenings and peaked during crepuscular periods, with the dusk call levels typically higher in energy and more rapid in onset than those from near-dawn periods. Increased call energy and substantial overlap of calls during certain periods suggest that many cusk eels were often calling simultaneously. Call energy (measured in energy flux density) peaked in July and patterns fol- lowed seasonal changes in sunrise and sunset. Sound levels were high (over 150 dB re 1 µPa 2 s) during the summer, indicating that this cusk eel population is a substantial contributor to the local soundscape. The stereotyped cusk eel signals and clear temporal energy patterns potentially pro- vide a bioacoustic signal that can be used to monitor changes to the local environment and its soundscape.

Assessing landscape functional connectivity in a forest carnivore using path selection functions

Understanding connectivity patterns in relation to habitat fragmentation is essential to landscape management. However, connectivity is often judged from expert opinion or species occurrence patterns, with very few studies considering the actual movements of individuals. Path selection functions provide a promising tool to infer functional connectivity from animal movement data, but its practical application remains scanty. We aimed to describe functional connectivity patterns in a forest carnivore using path-level analysis, and to explore how connectivity is affected by land cover patterns and road networks. We radiotracked 22 common genets in a mixed forest-agricultural landscape of southern Portugal. We developed path selection functions discriminating between observed and random paths in relation to landscape variables. These functions were used together with land cover information to map conductance surfaces. Genets moved preferentially within forest patches and close to riparian habitats. Functional connectivity declined with increasing road density, but increased with the proximity of culverts, viaducts and bridges. Functional connectivity was favoured by large forest patches, and by the presence of riparian areas providing corridors within open agricultural land. Roads reduced connectivity by dissecting forest patches, but had less effect on riparian corridors due to the presence of crossing structures. Genet movements were jointly affected by the spatial distribution of suitable habitats, and the presence of a road network dissecting such habitats and creating obstacles in areas otherwise permeable to animal movement. Overall, the study showed the value of path-level analysis to assess functional connectivity patterns in human-modified landscapes.

Citizen Science Program Shows Urban Areas Have Lower Occurrence of Frog Species, but Not Accelerated Declines.

Understanding the influence of landscape change on animal populations is critical to inform biodiversity conservation efforts. A particularly important goal is to understand how urban density affects the persistence of animal populations through time, and how these impacts can be mediated by habitat provision; but data on this question are limited for some taxa. Here, we use data from a citizen science monitoring program to investigate the effect of urbanization on patterns of frog species richness and occurrence over 13 years. Sites surrounded by a high proportion of bare ground (a proxy for urbanization) had consistently lower frog occurrence, but we found no evidence that declines were restricted to urban areas. Instead, several frog species showed declines in rural wetlands with low-quality habitat. Our analysis shows that urban wetlands had low but stable species richness; but also that population trajectories are strongly influenced by vegetation provision in both the riparian zone and the wider landscape. Future increases in the extent of urban environments in our study area are likely to negatively impact populations of several frog species. However, existing urban areas are unlikely to lose further frog species in the medium term. We recommend that landscape planning and management focus on the conservation and restoration of rural wetlands to arrest current declines, and the revegetation of urban wetlands to facilitate the re-expansion of urban-sensitive species.

Idiosyncratic responses of Amazonian birds to primary forest disturbance.

As humans continue to alter tropical landscapes across the world, it is important to understand what environmental factors help determine the persistence of biodiversity in modified ecosystems. Studies on well-known taxonomic groups can offer critical insights as to the fate of biodiversity in these modified systems. Here we investigated species-specific responses of 44 forest-associated bird species with different behavioural traits to forest disturbance in 171 transects distributed across 31 landscapes in two regions of the eastern Brazilian Amazon. We investigated patterns of species occurrence in primary forests varyingly disturbed by selective-logging and fire and examined the relative importance of local, landscape and historical environmental variables in determining species occurrences. Within undisturbed and disturbed primary forest transects, we found that distance to forest edge and the biomass of large trees were the most important predictors driving the occurrence of individual species. However, we also found considerable variation in species responses to different environmental variables as well as inter-regional variation in the responses of the same species to the same environmental variables. We advocate the utility of using species-level analyses to complement community-wide responses in order to uncover highly variable and species-specific responses to environmental change that remain so poorly understood.

Establishing conservation baselines with dynamic distribution models for bat populations facing imminent decline

AbstractAimBat mortality rates from white‐nose syndrome and wind power development are unprecedented. Cryptic and wide‐ranging behaviours of bats make them difficult to survey, and population estimation is often intractable. We advance a model‐based framework for making spatially explicit predictions about summertime distributions of bats from capture and acoustic surveys. Motivated by species‐energy and life‐history theory, our models describe hypotheses about spatio‐temporal variation in bat distributions along environmental gradients and life‐history attributes, providing a statistical basis for conservation decision‐making.LocationOregon and Washington, USA.MethodsWe developed Bayesian hierarchical models for 14 bat species from an 8‐year monitoring dataset across a ~430,000 km2 study area. Models accounted for imperfect detection and were temporally dynamic. We mapped predicted occurrence probabilities and prediction uncertainties as baselines for assessing future declines.ResultsForest cover, snag abundance and cliffs were important predictors for most species. Species occurrence patterns varied along elevation and precipitation gradients, suggesting a potential hump‐shaped diversity–productivity relationship. Annual turnover in occurrence was generally low, and occurrence probabilities were stable among most species. We found modest evidence that turnover covaried with the relative riskiness of bat roosting and migration. The fringed myotis (Myotis thysanodes), canyon bat (Parastrellus hesperus) and pallid bat (Antrozous pallidus) were rare; fringed myotis occurrence probabilities declined over the study period. We simulated anticipated declines to demonstrate that mapped occurrence probabilities, updated over time, provide an intuitive way to assess bat conservation status for a broad audience.Main conclusionsLandscape keystone structures associated with roosting habitat emerged as regionally important predictors of bat distributions. The challenges of bat monitoring have constrained previous species distribution modelling efforts to temporally static presence‐only approaches. Our approach extends to broader spatial and temporal scales than has been possible in the past for bats, making a substantial increase in capacity for bat conservation.

Juxtaposition and Disturbance: Disentangling the Determinants of Lizard Community Structure

AbstractDisturbance alters the structure and dynamics of communities. Here, we examined the effects of seasonal flooding on the lizard community structure by comparing two adjacent habitats, a seasonally flooded and a non‐flooded forest, in a Cerrado–Amazon ecotone area, the Cantão State Park, Tocantins state, Brazil. Despite the strong potential impact of seasonal flooding, the only significant environmental difference detected was more termite mounds in non‐flooded forests. Species richness was significantly higher in the non‐flooded forest. Colobosaura modesta, followed by Mabuya frenata and Anolis brasiliensis, were the only species that differed in number of captures between sites. Colobosaura modesta was exclusively found in the non‐flooded forest, while Anolis brasiliensis was the most captured in the flooded forest. Mabuya frenata is indicated as an indicator species in the flooded forest, and Colobosaura modesta in the non‐flooded forest. We found a significant association between lizard abundances and habitat characteristics, with flooding, canopy cover, and logs being the best predictors. A phylogenetic community structure analysis indicated a lack of structure in both lizard assemblages. Overall, we show that seasonal flooding can strongly impact species richness and species occurrence patterns, but not phylogenetic community structure. The Amazon–Cerrado transition is undergoing pronounced transformations due to deforestation and climate change. Despite being species‐poor compared with central areas in Amazon or Cerrado, this ecotone harbors species with important adaptations that could hold the key to persistence in human‐disturbed landscapes or during periods of climate change.

Using multispecies occupancy models to improve the characterization and understanding of metacommunity structure.

Two of the most prominent frameworks to develop in ecology over the past decade are metacommunity ecology, which seeks to characterize multispecies distributions across space, and occupancy modeling, which corrects for imperfect detection in an effort to better understand species occurrence patterns. Although their goals are complementary, metacommunity theory and statistical occupancy modeling methods have developed independently. For instance, the elements of metacommunity structure (EMS) framework uses species occurrence data to classify metacommunity structure and link it to underlying environmental gradients. While the efficacy of this approach relies on the quality of the data, few studies have considered how imperfect detection, which is widespread in ecological surveys and the major focus of occupancy modeling, affects the outcome. We introduce a framework that integrates multispecies occupancy models with the current EMS framework, detection error-corrected EMS (DECEMS). This method offers two distinct advantages. First, DECEMS reduces bias in characterizing metacommunity structure by using repeated surveys and occupancy models to disentangle species-specific occupancy and detection probabilities, ultimately bringing metacommunity structure classification into a more probabilistic framework. Second, occupancy modeling allows estimation of species-specific responses to environmental covariates, which will increase our ability to link species-level effects to metacommunity-wide patterns. After reviewing the EMS framework, we introduce a simple multispecies occupancy model and show how DECEMS can work in practice, highlighting that detection error often causes EMS to assign incorrect structures. To emphasize the broader applicability of this approach, we further illustrate that DECEMS can reduce the rate of structure misclassification by more than 20% in some cases, even proving useful when detection error rates are quite low (-10%). Integrating occupancy models and the EMS framework will lead to more accurate descriptions of metacommunity structure and to a greater understanding of the mechanisms by which different structures arise.

Cuckoo and biodiversity: Testing the correlation between species occurrence and bird species richness in Europe

The use of biodiversity surrogates is an increasingly popular tool, because it provides strong results while reducing the costs of conservation studies. Here, we hypothesize that cuckoo (Cuculus canorus) occurrence may correlate with high bird species richness based on the assumption that their presence should mirror the richness of their potential avian hosts and the overall bird community. Specifically, we assessed the association between species occurrence and taxonomic diversity patterns on a multi-spatial scale using datasets from seven European countries. Our results show that high bird species richness is a good proxy for cuckoo occurrence, and the best results were based on data from point counts. The species was almost absent at sites with low species richness, suggesting that the presence of cuckoo is an appropriate surrogate of bird biodiversity. The accuracy of the models ranged from 0.68–0.71 (for large spatial scale) to 0.86 (for local spatial scale) and provided valuable indications of bird taxonomic diversity distribution on all different types of environments monitored in each country. These associations are possibly related to co-evolutionary relationships with host species (correlated with overall species richness) and the cuckoo’s preference for sites that are attractive to many other bird species, due to high habitat diversity or abundant food resources. Our findings highlight how conservation planners can use cuckoo occurrence as a surrogate to maximize efficiency when studying bird species richness patterns. These results also demonstrate the advantages of using the cuckoo rather than top predators as a potential surrogacy tool for citizen scientist programs.

FuzzySim: applying fuzzy logic to binary similarity indices in ecology

Summary Binary similarity indices are widely used in ecology, for example for detecting associations between species occurrence patterns, comparing regional and temporal species assemblages, and assessing beta diversity patterns, including spatial and temporal species loss and turnover. Such indices have widespread applications in biogeography, global change biology and biodiversity conservation. Similarity indices are commonly calculated upon binary presence/absence (or sometimes modelled suitable/unsuitable) data, which are generally incomplete and more categorical than their underlying natural patterns. Probable false absences are disregarded, amplifying the effects of data deficiencies and the scale dependence of the results. Fuzzy occurrence data, with a degree of uncertainty attributed to localities where presence or absence cannot be safely assigned, could better reflect species distributions, compensating for incomplete knowledge and methodological errors. Similarity indices would therefore also benefit from accommodating such fuzzy data directly. This study proposes fuzzy versions of the binary similarity indices most commonly used in ecology, so that they can be directly applied to continuous (fuzzy) rather than binary occurrence values, thus producing more realistic similarity assessments. Fuzzy occurrence can be obtained with several methods, some of which are also provided. The procedure is robust to data source disparities, gaps or other errors in species occurrence records, even for restricted species for which slight inaccuracies can affect substantial parts of their range. The method is implemented in a free and open‐source software package, fuzzySim, which is available for the r statistical software and under implementation for the QGIS geographic information system. It is provided with sample data and an illustrated tutorial suitable for non‐experienced users.

Assessment of fish species assemblage on mesohabitat scale: A case of middle stretch of Narmada River, India

In river ecosystems, mesohabitat characteristics (i.e. pool, run, riffle, rapids, etc.) act as proximate variables to fish species occurrence. Fish occurrence and mesohabitat data are very often collected independently for different purposes, which invites challenges to characterize the fish species distribution pattern on mesohabitat scale. The present article delineates quantitative assessment of fish occurrence in relation to mesohabitat using secondary data. Middle stretch of the Narmada River of India has been selected for the study. Geographic information system tools have been used for integration of species and mesohabitat data. Nonmetric multidimensional scaling, cluster analysis and analysis of similarity techniques have been used for similarity analysis. Logistic regression model has been applied for model-based inferences on family-mesohabitat relationship. Two separate mesohabitat types, viz., Pool-Run and Run-Riffle, have been characterized by the fish species occurrence pattern. Dissimilarity of fish species composition between Pool-Run and Run-Riffle was statistically significant (p-value < 0.05). The family-mesohabiat model predicted that the occurrence probability of a fish species was 14.49 times more in the Pool-Run than that in the Run-Riffle. The predictive accuracy of the model was 69.8%.