Can interaction coefficients be determined from census data? Testing two estimation methods with Negev Desert rodents

Shenbrot, Georgy I.; Krasnov, Boris R.

doi:10.1034/j.1600-0706.2002.990105.x

Cited by 28 publications

(25 citation statements)

References 69 publications

(90 reference statements)

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“…This demonstrates the benefit of an ITA in assessing variation in the importance of variables among competing models rather than ecological inference based on a single ‘best model’. Shenbrot & Krasnov (2002) have shown that interspecific competition detected by the regression technique is most likely to be interference competition rather than exploitation competition. Further research is required to determine if interference – rather than exploitation – competition is the nature of the interaction between antilopine wallaroos and eastern grey kangaroos.…”

Section: Discussionmentioning

confidence: 99%

Separating the influences of environment and species interactions on patterns of distribution and abundance: competition between large herbivores

Ritchie

Martin

Johnson

et al. 2009

Journal of Animal Ecology

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Summary 1.Much recent research has focused on the use of species distribution models to explore the influence(s) of environment (predominantly climate) on species' distributions. A weakness of this approach is that it typically does not consider effects of biotic interactions, including competition, on species' distributions. 2.Here we identify and quantify the contribution of environmental factors relative to biotic factors (interspecific competition) to the distribution and abundance of three large, wide-ranging herbivores, the antilopine wallaroo ( Macropus antilopinus ), common wallaroo ( Macropus robustus ) and eastern grey kangaroo ( Macropus giganteus ), across an extensive zone of sympatry in tropical northern Australia. 3.To assess the importance of competition relative to habitat features, we constructed models of abundance for each species incorporating habitat only and habitat + the abundance of the other species, and compared their respective likelihoods using Akaike's information criterion. We further assessed the importance of variables predicting abundance across models for each species. 4. The best-supported models of antilopine wallaroo and eastern grey kangaroo abundance included both habitat and the abundance of the other species, providing evidence of interspecific competition. Contrastingly, models of common wallaroo abundance were largely influenced by climate and not the abundance of other species. The abundance of antilopine wallaroos was most influenced by water availability, eastern grey kangaroo abundance and the frequency of late season fires. The abundance of eastern grey kangaroos was most influenced by aspects of climate, antilopine wallaroo abundance and a measure of cattle abundance. 5. Our study demonstrates that where census and habitat data are available, it is possible to reveal species' interactions (and measure their relative strength and direction) between large, mobile and/ or widely-distributed species for which competition is difficult to demonstrate experimentally. This allows discrimination of the influences of environmental factors and species interactions on species' distributions, and should therefore improve the predictive power of species distribution models.

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Section: Discussionmentioning

confidence: 99%

Separating the influences of environment and species interactions on patterns of distribution and abundance: competition between large herbivores

Ritchie

Martin

Johnson

et al. 2009

Journal of Animal Ecology

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“…This is an interesting proposal which is supported by the results obtained and the rigorous approach used to avoid spurious correlations. The correlation between endemic and introduced species number is estimated only after considering the influence of significant environmental variables (Shenbrot & Krasnov, 2002). It may be possible that some neglected environmental variable may increase the explanatory capacity of the obtained models, so diminishing the significance of the number of endemic species in explaining the richness of introduced species.…”

Section: Discussionmentioning

confidence: 99%

“…Ultimately, as the residuals of the regression analysis using the selected explanatory variables can be considered as the variation in species richness not attributable to environmental or geographical factors, these residuals were regressed against one another as an estimate of the possible interaction between the two groups of species (Shenbrot & Krasnov, 2002). These residuals are also included as an explanatory variable in the final models (obtained with the environmental and geographical variables) in order to check if the richness variation in endemic species not attributable to environmental or geographical factors can influence the predictive capacity of the obtained model for introduced species, and vice versa.…”

Section: Methodsmentioning

confidence: 99%

Invasibility and species richness of island endemic arthropods: a general model of endemic vs. exotic species

Borges

Lobo

Azevedo

et al. 2005

Journal of Biogeography

116

137

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Aim This paper has two objectives. First, we examine how a variety of biotic, abiotic and anthropogenic factors influence the endemic and introduced arthropod richness on an oceanic island. Second, we look at the relationship between the endemic and introduced arthropod richness, to ask whether areas with high levels of endemic species richness deter invasions.Location The work was carried out on a young volcanic island, Terceira, in the Azores.Methods We used standard techniques to collect data on arthropod species richness. Environmental data were obtained from the CIELO climatic model and using GIS. The explanatory value of environmental variables on a small-scale gradient of endemic and exotic arthropod species richness was examined with generalized linear models (GLMs). In addition, the impact of both endemic and exotic species richness in the communities was assessed by entering them after the environmental variable(s) to see if they contributed significantly to the final model (the hierarchical method).Results Abiotic (climatic and geomorphological) variables gave a better explanation of the variation in endemic species richness, whereas anthropogenic variables explained most of the variation in introduced species richness. Furthermore, after accounting for all environmental variables, part of the unexplained variance in the endemic species richness is explained by the introduced species richness and vice-versa. That is, areas with high levels of endemic species richness had many introduced species. There is evidence of a somewhat inverse spatial distribution between a group of oceanic-type, forestdwelling, endemic, relict arthropods and a group of more generalist endemic arthropods that are able to survive in disturbed marginal sites particularly rich in non-indigenous species.Main conclusions Richness of endemic species is mainly driven by abiotic factors such as a climatic axis (oceanic-type localities with lower temperatures and summer precipitations) and a binary variable CALD (location of sites in caldeiras or ravines), whereas richness of introduced species depends on disturbance related factors. However, after factoring out these major influences, there is a correlation between endemic and introduced richness, suggesting thatindependent of the environmental and geographical factors that affect the distribution of endemic or introduced species -the richest endemic assemblages are more prone to invasion, due probably to a facilitation process. Inconclusive evidence suggests that non-indigenous species are limited to those sites under anthropogenic influence located mainly near forest edges, but the rate of expansion of those species to high-altitude, core pristine sites has still to be tested.

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“…Therefore, alternative methods have been devised to measure species interactions from census data (e.g. MacArthur and Levins 1967, Schoener 1974, Crowell and Pimm 1976, Fox and Luo 1996, Shenbrot and Krasnov 2002). Although some of these methods have been criticized (Rosenzweig et al 1985, Abramsky et al 1986), census data can nevertheless provide hints about the type of species interactions that might prevail in a community and, thus, can serve as a basis for further manipulative experiments and/or more sophisticated analysis.…”

mentioning

confidence: 99%

Abundance patterns and coexistence processes in communities of fleas parasitic on small mammals

Krasnov¹,

Mouillot²,

Shenbrot³

et al. 2005

Ecography

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R. 2005. Abundance patterns and coexistence processes in communities of fleas parasitic on small mammals. Á/ Ecography 28: 453 Á/464.The abundance of a given species in a community is likely to depend on both the total abundance and diversity of other species making up that community. A large number of co-occurring individuals or co-occurring species may decrease the abundance of any given species via diffuse competition; however, indirect interactions among many cooccurring species can have positive effects on a focal species. The existence of diffuse competition and facilitation remain difficult to demonstrate in natural communities.Here, we use data on communities of fleas ectoparasitic on small mammals from 27 distinct geographical regions to test whether the abundance of any given flea species in a community is affected by either the total abundance of all other co-occurring flea species, or the species richness and/or taxonomic diversity of the flea community. At all scales of analysis, i.e. whether we compared the same flea species on different host species, or different flea species, two consistent results emerged. First, the abundance of a given flea species correlates positively with the total abundance of all other cooccurring flea species in the community. Second, the abundance of any given flea species correlates negatively with either the species richness or taxonomic diversity of the flea community. The results do not support the existence of diffuse competition in these assemblages, because the more individuals of other flea species are present on a host population, the more individuals of the focal species are there as well. Instead, we propose explanations involving either apparent facilitation among flea species via suppression of host immune defenses, or niche filtering processes acting to restrict the taxonomic composition and abundance of flea assemblages.

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Can interaction coefficients be determined from census data? Testing two estimation methods with Negev Desert rodents

Cited by 28 publications

References 69 publications

Separating the influences of environment and species interactions on patterns of distribution and abundance: competition between large herbivores

Separating the influences of environment and species interactions on patterns of distribution and abundance: competition between large herbivores

Invasibility and species richness of island endemic arthropods: a general model of endemic vs. exotic species

Abundance patterns and coexistence processes in communities of fleas parasitic on small mammals

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