Ronen Kadmon

A movement ecology paradigm for unifying organismal movement research.

Movement of individual organisms is fundamental to life, quilting our planet in a rich tapestry of phenomena with diverse implications for ecosystems and humans. Movement research is both plentiful and insightful, and recent methodological advances facilitate obtaining a detailed view of individual movement. Yet, we lack a general unifying paradigm, derived from first principles, which can place movement studies within a common context and advance the development of a mature scientific discipline. This introductory article to the Movement Ecology Special Feature proposes a paradigm that integrates conceptual, theoretical, methodological, and empirical frameworks for studying movement of all organisms, from microbes to trees to elephants. We introduce a conceptual framework depicting the interplay among four basic mechanistic components of organismal movement: the internal state (why move?), motion (how to move?), and navigation (when and where to move?) capacities of the individual and the external factors affecting movement. We demonstrate how the proposed framework aids the study of various taxa and movement types; promotes the formulation of hypotheses about movement; and complements existing biomechanical, cognitive, random, and optimality paradigms of movement. The proposed framework integrates eclectic research on movement into a structured paradigm and aims at providing a basis for hypothesis generation and a vehicle facilitating the understanding of the causes, mechanisms, and spatiotemporal patterns of movement and their role in various ecological and evolutionary processes. ”Now we must consider in general the common reason for moving with any movement whatever.“ (Aristotle, De Motu Animalium, 4th century B.C.)

TEMPORAL ENVIRONMENTAL VARIATION TIPS THE BALANCE BETWEEN FACILITATION AND INTERFERENCE IN DESERT PLANTS

Recently, numerous studies have pointed to the importance of positive interactions in natural communities. There is now a broad consensus that the balance between negative and positive interactions should shift along environmental gradients, with competition prevailing under environmentally benign conditions and positive interactions dominating under harsh conditions. A commonly cited example of the importance of facilitation in harsh environments is the preference of desert annual plants for the areas under the canopy of shrubs. The recognition of apparently positive effects of desert shrubs on annuals, however, has been mostly based on density measurements, while fitness parameters of the understory plants have been ignored. Also, the temporal consistency of such effects has not been previously tested. Based on conceptual ideas about the balance between interference and facilitation, we predicted that positive effects of the shrubs on the understory should dominate in dry years, while in favorable years...

EFFECT OF ROADSIDE BIAS ON THE ACCURACY OF PREDICTIVE MAPS PRODUCED BY BIOCLIMATIC MODELS

Sampling bias is a common phenomenon in records of plant and animal distribution. Yet, models based on such records usually ignore the potential implications of bias in data collection on the accuracy of model predictions. This study was designed to investigate the effect of roadside bias, one of the most common sources of bias in biodiversity databases, on the accuracy of predictive maps produced by bioclimatic models. Using data on the distribution of 129 species of woody plants in Israel, we tested the following hypotheses: (1) that data collected on woody plant distribution in Israel suffer from roadside bias, (2) that such bias affects the accuracy of model predictions, (3) that the road network of Israel is biased with respect to climatic conditions, and (4) that the impact of roadside bias on model predictions depends on the magnitude of climatic bias in the geographic distribution of the road network. As expected, the frequency of plant observations near roads was consistently greater than that ex...

Assessment of alternative approaches for bioclimatic modeling with special emphasis on the Mahalanobis distance

Abstract We introduce the concept of the Mahalanobis distance to bioclimatic modeling. Specifically, we argue that climatic envelopes defined by the Mahalanobis distance produce more accurate predictions of species distribution than standard rectilinear envelopes (e.g. those produced by bioclim ). We base our hypothesis on three rationales: (1) the climatic envelope generated by the Mahalanobis distance is oblique, and therefore, may cope with correlations and interactions among the climatic variables; (2) the Mahalanobis envelope is elliptic, and therefore, better reflects the principle of central tendency as expressed by niche theory; (3) Mahalanobian predictions are based on the whole data rather than on the outermost observations, and are therefore, less sensitive to outliers. We test our hypothesis using data on the distribution of 192 species of woody plants in Israel. Validation tests based on four measures of accuracy (sensitivity, specificity, overall accuracy and the Kappa statistic) support our hypothesis, and suggest that Mahalanobis models produce predictions that are significantly more accurate than those produced by corresponding rectilinear models. Additional simulation experiments demonstrate that the superiority of Mahalanobian models cannot be related to their elliptic shape, or their ability to cope with correlations among the climatic variables. Accordingly, our conclusion is that the prime advantage of Mahalanobian models originates from the fact that their climatic envelopes are defined using all the observations, as opposed to rectilinear envelopes that are founded on the outermost observations.

A SYSTEMATIC ANALYSIS OF FACTORS AFFECTING THE PERFORMANCE OF CLIMATIC ENVELOPE MODELS

Effective application of species distribution models requires some knowledge concerning the accuracy of model predictions. Yet very few studies have attempted to systematically analyze factors affecting the predictive power of distribution models. This study fills this gap for Climatic Envelope Models, which have been applied extensively for a variety of conservation and management purposes. We hypothesized that model predic- tions are influenced by properties of the data (both quantity and quality) and distribution properties of the modeled species. Hypotheses concerning the effects of both types of factors were tested by analyzing distribution patterns of 192 species of woody plants in Israel. Analyses were based on Monte Carlo simulations and standard statistical tests. The total number of observations had a strong positive effect on model performance; but on average, 50-75 observations were sufficient to obtain the maximal accuracy. Climatic bias (the degree of sampling bias with respect to climatic conditions) had a significant negative effect on predictive accuracy. Climatic completeness (the degree to which the climatic range occupied by the species is covered by the observations) had a negative effect on model performance-a result contradicting our original hypothesis. Among the species properties, commonness had a positive effect while niche width had a negative one. Niche position with respect to rainfall and temperature was also important in determining the accuracy of model predictions. The overall results are discussed with respect to trade-offs between commission and omission errors and the potential implications of scale dependency.

Studying Long-Term Vegetation Dynamics Using Digital Processing of Historical Aerial Photographs

Plant ecologists have long recognized the importance of aerial photographs as a data source for studies of vegetation dynamics. Recent advances in computer-aided technology (digital photogrammetry, computerized image processing, and geographical information systems) have opened new possibilities for the extraction of data on vegetation changes from aerial photographs. In this study we describe a computer-based approach for studying landscape-scale, long-term vegetation dynamics, using historical aerial photographs as a major data source. The method we employ consists of four main steps: 1) image scanning and preprocessing (rectification, georeferencing, spectral corrections and mosaicking), 2) image classification and construction of vegetation maps, 3) field validation, and 4) statistical analysis of vegetation changes. We applied our approach by analyzing changes in tree cover over a period of 32 years in a mountainous landscape dominated by Mediterranean maquis in northern Israel and discuss the main limitations and potential error sources of each stage of our analysis. We conclude that digital processing of historical aerial photographs may serve as a powerful tool for the detection, quantification, and analysis of landscape-scale patterns of vegetation dynamics. This conclusion is important because aerial photographs provide the largest source of information available today for research of long-term vegetation dynamics, and are the only source of information on vegetation dynamics that combines high spatial resolution, large spatial extent, and long-term coverage.

Nested species subsets and geographic isolation: a case study.

Insular systems tend to exhibit nonrandom patterns of species composition in which smaller species assemblages contain successive subsets of those found on richer ones. The fact that such nested patterns of species composition have usually been observed in systems where species number is correlated with island size has led to the hypothesis that differences among species in the effect of island size on the probability of extinction represent the main mechanism producing nested patterns of species composition. This study tested the hypothesis that differences among species in dispersal ability may interact with geographic isolation to produce nested subsets of species composition. This hypothesis was tested in a systems of woody plants inhibiting artificial islands that were created by the filling of the Clarks Hill Reservoir, Georgia, USA. All of the studied islands had been logged prior to their separation from the mainland and their species number 34 yr later was found to be negatively correlated with distance to the closest mainland. The results of the present analysis indicated that (1) species occupancy of the whole island system was highly nested, (2) nestedness occurred with respect to geographic isolation but not with respect to island size, (3) only a small portion of the overall species included in the study contributed to the observed nestedness, and (4) the degree to which individual species contributed to the observed nestedness was correlated with their dispersal properties, with wind—dispersed species showing no evidence for nestedness and species lacking adaptations for long—range dispersal showing the strongest patterns of nestedness. These results indicate that isolation effects may interact with species—specific dispersal properties to produce nested subsets of species composition.

Integrating the Effects of Area, Isolation, and Habitat Heterogeneity on Species Diversity: A Unification of Island Biogeography and Niche Theory

We present an analytical model that unifies two of the most influential theories in community ecology, namely, island biogeography and niche theory. Our model captures the main elements of both theories by incorporating the combined effects of area, isolation, stochastic colonization and extinction processes, habitat heterogeneity, and niche partitioning in a unified, demographically based framework. While classical niche theory predicts a positive relationship between species richness and habitat heterogeneity, our unified model demonstrates that area limitation and dispersal limitation (the main elements of island biogeography) may create unimodal and even negative relationships between species richness and habitat heterogeneity. We attribute this finding to the fact that increasing heterogeneity increases the potential number of species that may exist in a given area (as predicted by niche theory) but simultaneously reduces the amount of suitable area available for each species and, thus, increases the likelihood of stochastic extinction. Area limitation, dispersal limitation, and low reproduction rates intensify the latter effect by increasing the likelihood of stochastic extinction. These analytical results demonstrate that the integration of island biogeography and niche theory provides new insights about the mechanisms that regulate the diversity of ecological communities and generates unexpected predictions that could not be attained from any single theory.

Area–heterogeneity tradeoff and the diversity of ecological communities

For more than 50 y ecologists have believed that spatial heterogeneity in habitat conditions promotes species richness by increasing opportunities for niche partitioning. However, a recent stochastic model combining the main elements of niche theory and island biogeography theory suggests that environmental heterogeneity has a general unimodal rather than a positive effect on species richness. This result was explained by an inherent tradeoff between environmental heterogeneity and the amount of suitable area available for individual species: for a given area, as heterogeneity increases, the amount of effective area available for individual species decreases, thereby reducing population sizes and increasing the likelihood of stochastic extinctions. Here we provide a comprehensive evaluation of this hypothesis. First we analyze an extensive database of breeding bird distribution in Catalonia and show that patterns of species richness, species abundance, and extinction rates are consistent with the predictions of the area–heterogeneity tradeoff and its proposed mechanisms. We then perform a metaanalysis of heterogeneity–diversity relationships in 54 published datasets and show that empirical data better fit the unimodal pattern predicted by the area–heterogeneity tradeoff than the positive pattern predicted by classic niche theory. Simulations in which species may have variable niche widths along a continuous environmental gradient are consistent with all empirical findings. The area–heterogeneity tradeoff brings a unique perspective to current theories of species diversity and has important implications for biodiversity conservation.

Island biogeography: effect of geographical isolation on species composition

Island biogeography theory attempts to explain and predict among-island variation in species richness. However, two islands with the same number of species may still differ from each other considerably in their species composition. In this study the authors test the hypothesis that among-island variation in species composition is predictable and can be related to the corresponding differences in distance to the mainland. They focus on woody plants inhabiting islands in the Clarks Hill Lake, a reservoir completed in 1954 on the Savannah River, between Georgia and South Carolina, US. Two groups of islands were sampled: islands that were logged prior to the filling of the reservoir and islands that were not logged. Each island was surveyed for the presence of all tree and shrub species, and its distance from the mainland was determined. In both groups of islands, the degree to which two islands are similar in their species composition was negatively and significantly correlated with distance to the mainland only on logged islands. The authors conclude that geographic isolation may affect species composition on islands, and that such an effect may occur even in the absence of a corresponding effect on species richness. 22 refs., 2 figs., 2 tabs.