Species-habitat Relationships Research Articles

Pelagic habitat of seabirds in the eastern tropical Pacific: effects of foraging ecology on habitat selection

A central tenet of ecology is the quantification of species-habitat relationships in order to explain spatial variability in the distribution and abundance patterns of animals. We quantified habitat preferences for 6 tropical seabird species representing a phylogenetically and ecologically diverse group within the eastern tropical Pacific (ETP). Seabird censuses were conducted aboard NOAA research vessels from August to November of 1989 and 1990 using 300 m strip transect meth- ods. Simultaneously with the seabird censuses and from the same ships, oceanic habitat was quanti- fied by measuring sea surface temperature, salinity, and chlorophyll, as well as thermocline depth and strength. We quantified seabird habitat using generalized additive models fitted with forward and backward selection algorithms based on minimizing the Akaike information criterion (AIC). In general, seabird habitat models performed well in explaining spatial variability in abundance, reduc- ing the null deviance to ranges between 42.8 and 73.5%, and predicting seabird density patterns with an accuracy ranging from 56.6 to 80.5%. Relative abundance of the species modeled affected the outcome: the higher the abundance, the more robust the fit. Seabirds feeding on fishes and squids associated with habitats characterized by deep (>100 m) and strong (>2°C 10 m -1 ) thermoclines, while planktivorous species preferred habitat characterized by shallower thermoclines with cooler surface temperatures (<25°C) and a less stratified water column. Thus, seabirds in different feeding guilds have clear and distinct habitat preferences within the ETP. We propose thermocline topo- graphy as a key variable in predicting distribution and abundance of seabirds in this area, probably due to its influence on the availability of seabird prey.

Oceanographic influences on seabirds and cetaceans of the eastern tropical Pacific: A review

This paper is part of a comprehensive review of the oceanography of the eastern tropical Pacific, the oceanic region centered on the eastern Pacific warm pool, but also including the equatorial cold tongue and equatorial current system, and summarizes what is known about oceanographic influences on seabirds and cetaceans there. The eastern tropical Pacific supports on the order of 50 species of seabirds and 30 species of cetaceans as regular residents; these include four endemic species, the world’s largest populations for several others, three endemic sub-species, and a multi-species community that is relatively unique to this ecosystem. Three of the meso-scale physical features of the region are particularly significant to seabirds and cetaceans: the Costa Rica Dome for blue whales and short-beaked common dolphins, the Equatorial Front for planktivorous seabirds, and the countercurrent thermocline ridge for flocking seabirds that associate with mixed-species schools of spotted and spinner dolphins and yellowfin tuna. A few qualitative studies of meso- to macro-scale distribution patterns have indicated that some seabirds and cetaceans have species-specific preferences for surface currents. More common are associations with distinct water masses; these relationships have been quantified for a number of species using several different analytical methods. The mechanisms underlying tropical species–habitat relationships are not well understood, in contrast to a number of higher-latitude systems. This may be due to the fact that physical variables have been used as proxies for prey abundance and distribution in species–habitat research in the eastern tropical Pacific. Though seasonal and interannual patterns tend to be complex, species–habitat relationships appear to remain relatively stable over time, and distribution patterns co-vary with patterns of preferred habitat for a number of species. The interactions between seasonal and interannual variation in oceanographic conditions with seasonal patterns in the biology of seabirds and cetaceans may account for some of the complexity in species–habitat relationship patterns. Little work has been done to investigate effects of El Niño-Southern Oscillation cycles on cetaceans, and results of the few studies focusing on oceanic seabirds are complex and not easy to interpret. Although much has been made of the detrimental effects of El Niño events on apex predators, more research is needed to understand the magnitude, and even direction, of these effects on seabirds and cetaceans in space and time.

Associations between Surficial Sediments and Groundfish Distributions in the Gulf of Maine–Georges Bank Region

AbstractThe delineation of essential fish habitat is an important element of contemporary fisheries management. Although local‐scale species–habitat relationships have been established for some managed species, we lack an understanding of these associations at the synoptic spatial scales on which fish populations and their associated fisheries operate. Interest in habitat delineations has been elevated further by an increased awareness of ongoing habitat degradation caused by mobile fishing gears and by the advancement of spatial management tools. Here we examine the associations between surficial sediment grain size and groundfish distributions in the Gulf of Maine–Georges Bank region. The mean abundances for 58 demersal fish species were determined for a spatial cell grid (185.2 km2 per cell), which was subsequently joined to a spatially referenced sediment database in a geographical information systems environment. Multivariate statistical methods were then used to examine how fish distribution and abundance varied with substrate grain size. Of the 58 species examined, 12 were consistently associated with particular substrate types. Atlantic cod Gadus morhua, longhorn sculpin Myoxocephalus octodecemspinosus, sea raven Hemitripterus americanus, and winter flounder Pseudopleuronectes americanus were consistently abundant in large‐grained substrate types, whereas white hake Urophycis tenuis, goosefish Lophius americanus, red hake U. chuss, silver hake Merluccius bilinearis, witch flounder Glyptocephalus cynoglossus, and American plaice Hippoglossoides platessoides were consistently abundant in fine‐grained substrates. Little skate Leucoraja erinacea was most abundant in sediments of intermediate grain size. Although broadly distributed, spring dogfish Squalus acanthias consistently distinguished assemblages in fine‐grained sediments. Given that we were able to detect even weak associations and that these relationships were consistent with local‐scale studies, we recommend using these relationships to further refine essential fish habitat and that they be given more weight in this and similar temperate ecosystems.

Unionid Habitat and Assemblage Composition in Coastal Plain Tributaries of Flint River (Georgia)

Effective conservation of mussels in streams of the lower Flint River basin, southwest Georgia, requires more rigorous understanding of mussel-habitat associations and factors shaping assemblage composition in stream reaches. We surveyed mussels and habitat conditions at 46 locations, and used regression, correlation and multivariate direct gradient analysis (Canonical Correspondence Analyses) to identify species-habitat relationships and characteristic species-assemblage types in Flint basin streams. Riparian wetland and catchment forest cover, average mid-channel depth, and drainage network position accounted for 49% of the variability in mussel species richness, 36% of the variability in unionid abundance, and 32% of the variability observed in Shannon-Wiener diversity across survey sites. Species were grouped into four assemblage types based on their habitat associations: large-river-riffle associates, slackwater associates, habitat generalists, and stream-run associates. Results are broadly concordant with anecdotal reports of mussel-habitat relationships and provide insight into the habitat conservation needs of mussels.

Spatial Heterogeneity and Characteristic Scales of Species–Habitat Relationships

Abstract Determining the characteristic spatial scales at which species respond most strongly to the amount of available habitat is crucial for developing cross-species scaling rules and for predicting species' responses to landscape modification. A Biologist's Toolbox article by Holland and colleagues (“Determining the Spatial Scale of Species' Response to Habitat,” BioScience 54: 227–233) presents a multiscale approach and computer program (Focus) for detecting characteristic scales using a resampling procedure, species–habitat regression models, and nonoverlapping sampling sites. Holland and colleagues refer to these nonoverlapping areas as “spatially independent sites,” when in fact spatial independence includes additional concerns not addressed by the Focus approach. Here I discuss issues of spatial heterogeneity—spatial autocorrelation and spatial dependence—as they relate to measuring the spatial scaling of organism–environment relationships with regression models. I present an empirical example wi...

Species Dynamics in Disturbed Landscapes: When does a Shifting Habitat Mosaic Enhance Connectivity?

Although landscape ecology emphasizes the effects of spatial pattern on ecological processes, most neutral models of species–habitat relationships have treated habitat as a static constraint. Do the working hypotheses derived from these models extend to real landscapes where disturbances create a shifting mosaic? A spatial landscape simulator incorporating vegetation dynamics and a metapopulation model was used to compare species in static and dynamic landscapes with identical habitat amounts and spatial patterns. The main drivers of vegetation dynamics were stand-replacing disturbances, followed by gradual change from early-successional to old-growth habitats. Species dynamics were based on a simple occupancy model, with dispersal simulated as a random walk. As the proportion of available habitat (p) decreased from 1.0, species occupancy generally declined more rapidly and reached extinction at higher habitat levels in dynamic than in static landscapes. However, habitat occupancy was sometimes actually higher in dynamic landscapes than in static landscapes with similar habitat amounts and patterns. This effect was most pronounced at intermediate amounts of habitat (p = 0.3−0.6) for mobile species that had high colonization rates, but were unable to cross non-habitat patches. Differences between static and dynamic landscapes were contingent upon the initial metapopulation size and the shapes of disturbances and the resulting habitat patterns. Overall, the results demonstrate that dispersal-limited species exhibit more pronounced critical behavior in dynamic landscapes than is predicted by simple neutral models based on static landscapes. Thus, caution should be exercised in extending generalizations derived from static landscape models to disturbance-driven landscape mosaics.

A review of statistical methods for the evaluation of aquatic habitat suitability for instream flow assessment

Habitat models serve three main purposes: First, to predict species occurrences on the basis of abiotic and biotic variables, second to improve the understanding of species-habitat relationships and third, to quantify habitat requirements. The use of statistical models to predict the likely occurrence or distribution of species based on relevant variables is becoming an increasingly important tool in conservation planning and wildlife management. This article aims to provide an overview of the current status of development and application of statistical methodologies for analysing the species-environment association, with a clear emphasis on aquatic habitat. It describes the main types of univariate and multivariate techniques available for analysis of species-environment association, and specifically focuses on the assessment of the strengths and weaknesses of the available statistical methods to estimate habitat suitability. A second objective of this article is to propose new approaches using existing statistical methods. A wide array of habitat statistical models has been developed to analyse habitat-species relationship. Generally, physical habitat is dependent on more than one variable (e.g. depth, velocity, substrate, cover) and several suitability indices must be combined to define a composite index. Multivariate approaches are more appropriate for the analysis of aquatic habitat as they inherently consider the interrelation and correlation structure of the environmental variables. Ordinary multiple linear regression and logistic regression are popular methods often used for modelling of species and their relationships with environment. Ridge regression and Principal component regression are particularly useful when the independent variables are highly correlated. More recent regression modelling paradigms like generalized linear models (GLMs) present advantages in dealing with non-normal environmental variables. Generalized additive models (GAMs) and artificial neural networks are better suited for analysis of non-linear relationships between species distribution and environmental variables. The fuzzy logic approach presents advantages in dealing with uncertainties that often exist in habitat modelling. Appropriate methods for analysis of multi-species data are also presented. Finally, the few existing comparative studies for predictive modelling are reviewed, and advantages and disadvantages of different methods are discussed. Copyright © 2006 John Wiley & Sons, Ltd.

Wetland and Microhabitat Use by Nesting Four-Toed Salamanders in Maine

Little is known of Four-Toed Salamander (Hemidactylium scutatum) habitat use, despite the species' extensive range and elevated conservation status. We investigated species-habitat relationships that predict H. scutatum nesting presence in Maine at wetland and microhabitat scales by comparing microhabitats with and without nests. We created logistic regression models, selected models with AIC, and evaluated models with reserve data. Wetlands with nests were best predicted by shoreline microhabitat of Sphagnum spp., wood substrate, water flow, blue-joint reed grass (Calamagrostis canadensis), meadowsweet (Spiraea alba), steeplebush (Spiraea tomentosa), sensitive fern (Onoclea sensibilis), and absence of sheep laurel (Kalmia angustifolia) or deciduous forest canopy. Within occupied wetlands, shoreline microhabitat where nests occurred was best distinguished from available, unoccupied shoreline microhabitat by steeper shore, greater near-shore and basin water depth, deeper nesting vegetation, presence of moss spp. and winterberry (Ilex verticillata), and a negative association with S. alba, leatherleaf (Chamaedaphne calyculata), and K. angustifolia. These models of wetland and microhabitat use by H. scutatum may assist ecologists and managers in detecting and conserving this species.

Constrain to perform: Regularization of habitat models

Predictive habitat models are an important tool for ecological research and conservation. A major cause of unreliable models is excessive model complexity, and regularization methods aim to improve the predictive performance by adequately constraining model complexity. We compare three regularization methods for logistic regression: variable selection, lasso, and ridge. They differ in the way model complexity is measured: variable selection uses the number of estimated parameters, the lasso uses the sum of the absolute values of the parameter estimates, and the ridge uses the sum of the squared values of the parameter estimates. We performed a simulation study with environmental data of a real landscape and artificial species occupancy data. We investigated the effect of three factors on relative model performance: (1) the number of parameters (16, 10, 6, 2) in the ‘true’ model that determined the distribution of the artificial species, (2) the prevalence, i.e. the proportion of sites occupied by the species, and (3) the sample size (measured in events per variable, EPV). Regularization improved model discrimination and calibration. However, no regularization method performed best under all circumstances: the ridge generally performed best in the 16-parameter scenario. The lasso generally performed best in the 10-parameter scenario. Variable selection with AIC was best at large sample sizes ( EPV ≥ 10 ) when less than half of the variables influenced the species distribution. However, at low sample sizes ( EPV < 10 ), ridge and lasso always performed best, regardless of the parameter scenario or prevalence. Overall, calibration was best in ridge models. Other methods showed overconfidence, particularly at low sample sizes. The percentage of correctly identified models was low for both lasso and variable selection. Variable selection should be used with caution. Although it can produce the best performing models under certain conditions, these situations are difficult to infer from the data. Ridge and lasso are risk-averse model strategies that can be expected to perform well under a wide range of underlying species–habitat relationships, particularly at small sample sizes.

Pattern in the Co-occurrence of Fishes Inhabiting the Coral Reefs of Bonaire, Netherlands Antilles

We conducted an analysis of species associations using fish diversity and abundance surveys conducted in Bonaire Marine Park by recreational divers. We used data from the REEF (Reef Environmental Education Foundation) Fish Survey Project to compute Bray–Curtis similarity coefficients for all species pairs for the 100 most abundant species. We quantified relationships between species using hierarchical agglomerative clustering and non-metric multidimensional scaling (MDS) of the matrix of Bray–Curtis similarity coefficients. We identified three clusters of species from the analysis. MDS results showed species clusters occupied distinct regions across a continuous gradient of species in two-dimensional space, rather than form distinct clusters. While differences in habitat requirements can explain some of the pattern in pairwise species interactions, these results suggest that there are significant direct and indirect behavioral interactions mediating the distribution and abundance of species. Studies conducted to elucidate patterns of species-habitat relationships have been central to conservation planning for marine protected areas (MPAs). However, the role of behavioral interactions between species driving the dynamics of species composition within MPA networks, designed for representation of biological diversity, should be considered when selecting sites in order to be effective.

A rapid approach to modeling species–habitat relationships

A basic element in the success of managing species of conservation concern is knowledge of the species’ habitat occupancy. Often, predictive species–habitat models are developed from GIS data sources that were intended for purposes other than predicting species habitat occupancy and are of inappropriate scale. In addition, the techniques used to quantify predictor variables from such data sources are often time consuming and cannot be repeated efficiently to reflect changing conditions. We used digital orthophotos and a grid cell classification scheme to develop an efficient technique to quantify predictor variables to model Florida scrub-jay habitat occupancy. We combined our classification scheme with a priori hypothesis development using expert knowledge and a previously published habitat suitability index and used an objective model selection procedure to choose candidate models. We classified a large area (43,000 ha) in a fraction of the time that would be required to map vegetation classes and were able to test models at varying scales using a grid-cell windowing process. Interpretation of the selected models confirmed existing knowledge of factors important to Florida scrub-jay habitat occupancy. The potential uses and advantages of using a grid cell classification scheme in conjunction with expert knowledge and an objective model selection procedure are discussed.

The Importance of Spatial Scale in Habitat Models: Capercaillie in the Swiss Alps

The role of scale in ecology is widely recognized as being of vital importance for understanding ecological patterns and processes. The capercaillie (Tetrao urogallus) is a forest grouse species with large spatial requirements and highly specialized habitat preferences. Habitat models at the forest stand scale can only partly explain capercaillie occurrence, and some studies at the landscape scale have emphasized the role of large-scale effects. We hypothesized that both the ability of single variables and multivariate models to explain capercaillie occurrence would vary with the spatial scale of the analysis. To test this hypothesis, we varied the grain size of our analysis from 1 to just over 1100 hectares and built univariate and multivariate habitat suitability models for capercaillie in the Swiss Alps. The variance explained by the univariate models was found to vary among the predictors and with spatial scale. Within the multivariate models, the best single-scale model (using all predictor variables at the same scale) worked at a scale equivalent to a small annual home range. The multi-scale model, in which each predictor variable was entered at the scale at which it had performed best in the univariate model, did slightly better than the best single-scale model. Our results confirm that habitat variables should be included at different spatial scales when species-habitat relationships are investigated.

Evaluating vertebrate species risk on an industrial forest landscape

We describe a new landscape-specific procedure for ranking vertebrate forest wildlife species for their relative risk of extirpation, and apply it to a ca. 189,000 ha intensively managed industrial-forest landscape in northwestern New Brunswick, Canada (J.D. Irving, Ltd., Black Brook District). A list of 157 vertebrate species that potentially occur on the landbase was compiled based on published range maps and expert consultation. Each species was assessed for risk of extirpation using a categorical ranking system termed the ‘Species-Sorting Algorithm’ (SSA). The SSA places each species into one of four relative risk categories (Class I = ‘potential high risk or management concern’, II, III and Unknown), based on four variables: (1) potential abundance, (2) proportion of the landscape suitable for occupancy, (3) species-specific habitat connectivity, and (4) population growth potential. These variables use a mix of spatial and non-spatial data derived from a spatial analysis of the landscape and a review of published life-history parameters. A total of 26 (17%) species were rated as Class I, 14 of which were due at least partly to low habitat availability. Eight species were Class I due to Provincial or National ‘at risk’ listing, but only two of these would have been Class I based on the four SSA variables alone. An assessment of the robustness of the ranking variables indicated that the percentage of suitable landscape had the largest effect on SSA results, and a logistic regression model showed estimated provincial abundance and body size to be significant predictors of Class I categorization. The SSA is dependent upon stand structure-based species–habitat relationships and species area–sensitivity relationships, which were uncertain for some species. The SSA was useful in highlighting data gaps and in providing a framework for incorporating new knowledge.

Salmonids on the Fringe: Abundance, Species Composition, and Habitat Use of Salmonids in High-Gradient Headwater Streams, Southeast Alaska

Abstract We evaluated the species distribution, abundance, and habitat relationships of salmonids in small first- to second-order headwater streams in southeast Alaska. Streams were separated into three zones based on gradient and sampled during the spring, summer, and fall. Dolly Varden Salvelinus malma were found in all streams where fish were present. They were the dominant species in moderate- (mean gradient = 5.5%) and high-gradient (mean gradient = 12.9%) zones. Coho salmon Oncorhynchus kisutch fry and parr were the dominant species in the low-gradient zone (mean gradient = 3.1%) but were present in higher-gradient zones. Small numbers of steelhead O. mykiss parr were present in all three zones in the spring and fall. Few were captured during the summer. Coastal cutthroat trout O. clarkii were found primarily in one stream and in all three zones. The density of all species decreased as gradient increased. Anadromous Dolly Varden in spawning condition were observed in the fall up to the highest acces...

Fire and forest landscapes in the Georgia Piedmont: an assessment of spatial modeling assumptions

Landscape simulation models are widely used to study the behavior of ecological systems. As computing power has increased, these models have become more complex and incorporated more realistic spatial representations of landscape patterns and ecological processes. The goal of this research was to examine the sensitivity of simulated landscape patterns to fundamental spatial modeling assumptions. The LANDIS simulator was parameterized for forests of the Georgia Piedmont and used to model landscape-scale community dynamics at fire return intervals from 20 to 100 years. A base scenario incorporating localized seed dispersal along with landform-related variation in species establishment rates and disturbance regimes was contrasted with three alternative scenarios. The uniform habitat scenario applied the same set of species establishment coefficients across all landforms. The uniform dispersal scenario removed the effects of seed source abundance and pattern on species establishment. The uniform disturbance scenario assumed identical disturbance regimes on all landforms. At the shortest fire return intervals, fire severities were low and the stand age distribution was dominated by older forests. At longer fire return intervals, fire severities were high and the stand age distribution was skewed toward younger forests. Species composition generally followed a gradient from fire-resistant species at short fire return intervals to fire-sensitive species at longer fire return intervals. However, some species exhibited bimodal distributions with high abundances at both short and long fire return intervals. Landscape responses to fire were similar in the uniform habitat scenario and the base scenario. Communities were less sensitive to fire return interval and had more fire-sensitive species in the uniform dispersal scenario than in the base scenario. Species composition in the uniform disturbance scenario was similar to the base scenario for the longest fire-intervals, but was more sensitive to changes in the fire regime at shorter fire return intervals. In models of Piedmont forest landscapes, accurate spatial representations of dispersal and fire regime heterogeneity are essential for predicting landscape-scale species composition under changing fire regimes. In contrast, the precise spatial representation of species–habitat relationships may be considerably less important.

Earrthworm diversity and habitat preferences in arid regions of Rajasthan

Manuscript 1074; Received 18 August 2003; Revised finally accepted 15 May 2004; © Zoo Outreach Organisation 1515 ABSTRACT Earthworms were surveyed in different habitats of Jodhpur District, Rajasthan, India. A total of nine earthworm species belonging to four different families, viz., Glossoscolecidae, Megascolecidae, Ocnerodrilidae and Octochaetidae were identified, of which six are first records for Jodhpur. The earthworm species differed in their eco-morphological characteristics and in relative abundance in each of the habitats sampled. Metaphire posthuma and Lampito mauritii were present in all the observed pedoecosystems. Ocnerodrilus occidentalis was found in all systems except garden soil, whereas Dichogaster boluai inhabited cultivated, non-cultivated and sewage soil. Pontoscolex corethururs, Amynthas morrisi and Ramiella bishambari were recorded from only sewage, garden and cultivated fields, respectively. The occurrence of most of the species in sewage soil as compared to other pedoecosystems may be related to high organic carbon and much higher nitrogen of the sewage system. This showed a remarkable species-habitat relationship. The relative density, frequency and species diversity index of some abundantly found earthworm species inhabiting particular habitat were also calculated. The entire observations clearly indicate the richness of earthworm biodiversity in the arid region of Rajasthan.

PROJECTING WILDLIFE RESPONSES TO ALTERNATIVE FUTURE LANDSCAPES IN OREGON'S WILLAMETTE BASIN

Increasingly, environmental quality is becoming recognized as a critical factor that should constrain land use planning. One important measure of a landscape's quality is its capacity to support viable populations of wildlife species. But the ability of land managers to balance conservation with other competing objectives is limited by a shortage of methodologies for assessing landscape quality. In response to this shortage, the research community has begun developing a variety of multispecies, landscape‐level, assessment models. Useful models must strike a balance between parsimony and biological realism and must be designed to make the most of limited life history data. This paper applies two such assessments to an examination of wildlife responses to scenarios of landscape change within Oregon's Willamette River Basin. The study uses GIS maps of pre‐European settlement and circa 1990 habitat conditions, and three possible realizations of how the Basin might appear in the year 2050. Our simpler assessment generated statistics of landscape change from the GIS imagery and species–habitat relationships for all 279 amphibian, reptile, bird, and mammal species in the basin. Our more complex assessment used an individual‐based life history simulator to estimate population sizes for a small subset of this fauna. These two assessments offer complementary kinds of information about wildlife responses to landscape change: estimates of habitat changes for a large number of species representing a region's biodiversity, and estimates of changes in the persistence of populations of key species. We found both good and poor correlations between our two assessments, depending upon the species and landscape. Both assessments agreed in their overall ranking of the landscapes' quality for wildlife. In most cases, the percentage change in habitat quality underestimated the percentage change in population size. In a few cases, small gains in habitat quality were accompanied by very large increases in wildlife populations. We attribute discrepancies in our two assessments to the influence habitat fragmentation had on our individual‐based model. As such, our study provides a methodology for separating the influences of habitat quality and quantity from those of habitat pattern.

Habitat-based conservation priorities for carabid beetles within the Picos de Europa National Park, northern Spain

Quick biodiversity studies on poorly studied taxa and areas are increasingly popular for setting conservation priorities over a wide range of spatial scales. However, the implementation of such studies is complicated by the variable extent to which the different criteria used in prioritisation are correlated to each other. Using methods of constrained ordination, we examined the species-habitat relationships of carabid beetles based on ground beetle assemblages from 22 sites in the Picos de Europa National Park, northern Spain. We found characteristic species assemblages for subalpine meadows, Genista shrublands, and pastures, whereas mown meadows, heathlands, beech and riparian woodlands were occupied by more habitat generalist species. Species associated with subalpine meadows and Genista shrublands tended to be mostly brachypterous and to have geographic ranges restricted to northern Spain. In contrast, we found no relationship between the degree of species' association with pastures and geographic range-wing size type. Although the species richness was higher in riparian woodlands and mown meadows, we suggest a higher conservation value for subalpine meadows and Genista shrublands across the landscape because they sustain characteristic assemblages dominated by species with restricted ranges and reduced powers of dispersal. Our study suggests that preserving areas in the landscape supporting higher biodiversity will not necessarily preserve those species potentially more susceptible to habitat loss and fragmentation. It also supports the feasibility of biodiversity studies based on multivariate techniques for setting conservation priorities over complex landscapes.

Predicting Species Occurrences: Issues of Accuracy and Scale

J. M. Scott, J. H. Heglund, M. L. Morrison, J. B. Haufler, M. G. Raphael, W. A. Wall, F. B. Samson (eds.). 2002. Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Washington, D.C., 868 pp. ISBN 1-55963-787-0, price (hardcover), $95.00. In biodiversity conservation and management of natural resources, from policy decisions under the Convention for Biological Diversity to the implementation of national and local legislation, there is hardly a project where information on species occurrence is not needed. But animal and plant species are mobile, ranges shift over time, and individual animals move within their range and on a variety of scales. Representing complex ecological patterns such as species occurrences on a map inevitably presents a gross simplification of the real world, and models have always been the only tool available to researchers. The black blotches on the maps of many atlases of species distribution are merely the earliest and simplest models, worked out by experts on the basis of available data and their personal experience. In spite of their often-rough approximation, much conservation and management continues to be based on such simple models, which remain the only available means for representing the distribution of many species at a global scale. Species—habitat relationships were a great improvement for exploring the internal composition of species distributions, and they launched the new field of predicting species occurrences. The widespread application of computers offered a vast array of new tools, such as GIS and statistical packages and their ever-increasing ability to crunch large quantities of data, and remote sensing, which facilitated the collection of large amounts of environmental data. Ecologists did not miss these opportunities. However, we are still far from having solved all problems of predicting species occurrences. Spatial and temporal variations in the processes determining species occurrence still pose enormous challenges to modelers, and it is possible that accurate modeling will never be satisfactorily accomplished. In spite of the well-known axiom that ecological patterns should be studied at a variety of scales (Levin 1992), modelers often struggle for the magic model …

Effects of logging and non-native tree proliferation on the birds overwintering in the upland forests of north-western Italy

Factors associated with management and logging practices are of particular interest in the perspective of biodiversity management. In this study we focused on overwintering birds of two close and contrasting forest habitats: a 60–120 years old oak forest and a secondary 10–20 years old wood that has lost most of its original vegetation because of continuous logging and is now dominated by an introduced species, black locust Robinia pseudoacacia. We examined bird use of the forests over two levels: species–habitat relationships and foraging niches. The former were assessed by means of point counts centred in 50 m radius plots, whereas the latter by observations of foraging behaviour and plant species exploitation. Mean species richness, diversity and abundance of bark foragers was significantly greater in the old-growth stand, where trees were higher and larger but stem density was lower. Almost no wintering bird species occurred at higher density in the second-growth than in old-growth forest, and no foraging birds positively selected the black locust as substrate. Despite the observed differences in biodiversity metrics and plant species exploitation, most birds of the two stands showed few shifts in their foraging behaviour (in terms of foraging technique, substrate, relative horizontal and vertical position) and niche metrics (breadth and overlap). By considering results obtained with the two approaches, we suggest that biodiversity of altered secondary woods can be increased if current silvicultural practices are modified towards (1) maintaining oaks or trees prone to snag formation such as old poplars and (2) preventing black locust establishment in post-clearcut communities.