Negative biotic interactions drive predictions of distributions for species from a grassland community

Understanding the factors that determine species' geographical distributions is important for addressing a wide range of biological questions, including where species will be able to maintain populations following environmental change. New methods for modelling species distributions include the effects of biotic interactions alongside more commonly used abiotic variables such as temperature and precipitation; however, it is not clear which types of interspecific relationship contribute to shaping species distributions and should therefore be prioritized in models. Even if some interactions are known to be influential at local spatial scales, there is no guarantee they will have similar impacts at macroecological scales. Here we apply a novel method based on information theory to determine which types of interspecific relationship drive species distributions. Our results show that negative biotic interactions such as competition have the greatest effect on model predictions for species from a California grassland community. This knowledge will help focus data collection and improve model predictions for identifying at-risk species. Furthermore, our methodological approach is applicable to any kind of species distribution model that can be specified with and without interspecific relationships.

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Environmental factors influencing fine-scale distribution of Antarctica’s only endemic insect

Oecologia ◽

10.1007/s00442-020-04714-9 ◽

2020 ◽

Vol 194 (4) ◽

pp. 529-539

Author(s):

Leslie J. Potts ◽

J. D. Gantz ◽

Yuta Kawarasaki ◽

Benjamin N. Philip ◽

David J. Gonthier ◽

...

Keyword(s):

Antarctic Peninsula ◽

Spatial Scales ◽

Abiotic Factors ◽

Ecological Factors ◽

Biotic Interactions ◽

Species Distributions ◽

Biotic Factors ◽

Belgica Antarctica ◽

Abiotic And Biotic Factors ◽

The Antarctic

AbstractSpecies distributions are dependent on interactions with abiotic and biotic factors in the environment. Abiotic factors like temperature, moisture, and soil nutrients, along with biotic interactions within and between species, can all have strong influences on spatial distributions of plants and animals. Terrestrial Antarctic habitats are relatively simple and thus good systems to study ecological factors that drive species distributions and abundance. However, these environments are also sensitive to perturbation, and thus understanding the ecological drivers of species distribution is critical for predicting responses to environmental change. The Antarctic midge, Belgica antarctica, is the only endemic insect on the continent and has a patchy distribution along the Antarctic Peninsula. While its life history and physiology are well studied, factors that underlie variation in population density within its range are unknown. Previous work on Antarctic microfauna indicates that distribution over broad scales is primarily regulated by soil moisture, nitrogen content, and the presence of suitable plant life, but whether these patterns are true over smaller spatial scales has not been investigated. Here we sampled midges across five islands on the Antarctic Peninsula and tested a series of hypotheses to determine the relative influences of abiotic and biotic factors on midge abundance. While historical literature suggests that Antarctic organisms are limited by the abiotic environment, our best-supported hypothesis indicated that abundance is predicted by a combination of abiotic and biotic conditions. Our results are consistent with a growing body of literature that biotic interactions are more important in Antarctic ecosystems than historically appreciated.

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Predicting habitat suitability for rare plants at local spatial scales using a species distribution model

Ecological Applications ◽

10.1890/09-1190.1 ◽

2011 ◽

Vol 21 (1) ◽

pp. 33-47 ◽

Cited By ~ 73

Author(s):

Melanie Gogol-Prokurat

Keyword(s):

Species Distribution ◽

Habitat Suitability ◽

Species Distribution Model ◽

Spatial Scales ◽

Rare Plants ◽

Distribution Model

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Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model

Ecology ◽

10.1002/ecy.2190 ◽

2018 ◽

Vol 99 (5) ◽

pp. 1018-1023 ◽

Cited By ~ 4

Author(s):

Nina K. Lany ◽

Phoebe L. Zarnetske ◽

Erin M. Schliep ◽

Robert N. Schaeffer ◽

Colin M. Orians ◽

...

Keyword(s):

Species Distribution ◽

Species Distribution Model ◽

Biotic Interactions ◽

Distribution Model ◽

Niche Differences

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Matching expert range maps with species distribution model predictions

Conservation Biology ◽

10.1111/cobi.13492 ◽

2020 ◽

Vol 34 (5) ◽

pp. 1292-1304 ◽

Cited By ~ 1

Author(s):

Kumar Mainali ◽

Trevor Hefley ◽

Leslie Ries ◽

William F. Fagan

Keyword(s):

Species Distribution ◽

Species Distribution Model ◽

Distribution Model ◽

Model Predictions

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Confronting species distribution model predictions with species functional traits

Ecology and Evolution ◽

10.1002/ece3.1898 ◽

2016 ◽

Vol 6 (4) ◽

pp. 873-879 ◽

Cited By ~ 15

Author(s):

Marion E. Wittmann ◽

Matthew A. Barnes ◽

Christopher L. Jerde ◽

Lisa A. Jones ◽

David M. Lodge

Keyword(s):

Functional Traits ◽

Species Distribution ◽

Species Distribution Model ◽

Distribution Model ◽

Model Predictions

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Trawl survey data and species distribution model predictions for presence, absence and abundance

Biological and Chemical Oceanography Data Management Office ◽

10.1575/1912/bco-dmo.753142.1 ◽

2019 ◽

Author(s):

Malin Pinsky ◽

Rebecca Selden

Keyword(s):

Survey Data ◽

Species Distribution ◽

Species Distribution Model ◽

Distribution Model ◽

Trawl Survey ◽

Model Predictions

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Predicted distribution of a rare and understudied forest carnivore: Humboldt martens (Martes caurina humboldtensis)

10.1101/2021.02.05.429381 ◽

2021 ◽

Author(s):

Katie Moriarty ◽

Joel Thompson ◽

Matthew Delheimer ◽

Brent Barry ◽

Mark Linnell ◽

...

Keyword(s):

North American ◽

Species Distribution Model ◽

Spatial Scales ◽

Abiotic Factors ◽

Mammalian Species ◽

Distribution Model ◽

Shrub Cover ◽

Limited Information ◽

Distribution Models ◽

Management Actions

AbstractBackgroundA suite of mammalian species have experienced range contractions following European settlement and post-settlement development of the North American continent. For example, while North American martens (American marten, Martes americana; Pacific marten, M. caurina) generally have a broad range across northern latitudes, local populations have experienced substantial reductions in distribution and some extant populations are small and geographically isolated. The Humboldt marten (M. c. humboldtensis), a subspecies of Pacific marten that occurs in coastal Oregon and northern California, was recently designated as federally threatened in part due to its reduced distribution. To inform strategic conservation actions, we assessed Humboldt marten occurrence by compiling all known records from their range.MethodsWe compiled Humboldt marten locations since their rediscover to present (1,692 marten locations, 1996-2020). We spatially-thinned locations to 500-m to assess correlations with variables across contemporary Humboldt marten distribution (n=384). Using maximum entropy modeling (Maxent), we created distribution models with variables optimized for spatial scale; pre-selected scales were associated with marten ecology (50 to 1170 m radius). Marten locations were most correlated with abiotic factors (e.g., precipitation), which are unalterable and therefore uninformative within the context of restoration or management actions. Thus, we created variables to focus on hypothesized marten habitat relationships, including understory conditions such as predicted suitability of shrub species.ResultsHumboldt marten locations were positively associated with increased shrub cover (salal (Gautheria shallon), mast producing trees), increased pine (Pinus sp) overstory cover and precipitation at home-range spatial scales, areas with low and high amounts of canopy cover and slope, and cooler August temperatures. Unlike other recent literature on the species, we found little evidence that Humboldt marten locations were associated with old growth structural indices, perhaps because of a potential mismatch in the association between this index and shrub cover. As with any species distribution model, there were gaps in predicted distribution where Humboldt martens have been located during more recent surveys, for instance the southeastern portion of Oregon’s coast range. Conservation efforts and our assessment of potential risks to Humboldt marten populations would benefit from additional information on range extent, population sizes, and fine-scale habitat use. Like many rare and lesser-known species, this case study provides an example of how limited information can provide differing interpretations, emphasizing the need for study-level replication in ecology.

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Do priority effects outweigh environmental filtering in a guild of dominant freshwater macroinvertebrates?

10.1101/216267 ◽

2017 ◽

Author(s):

Chelsea J. Little ◽

Florian Altermatt

Keyword(s):

Species Distribution Model ◽

Environmental Filtering ◽

Biotic Interactions ◽

Priority Effects ◽

Distribution Model ◽

Amphipod Species ◽

Macroinvertebrate Communities ◽

Field Evidence ◽

Equal Importance ◽

Environmental Requirements

AbstractAbiotic conditions have long been considered essential in structuring freshwater macroinvertebrate communities. Ecological drift, dispersal, and biotic interactions also structure communities, and although these mechanisms are more difficult to detect, they may be of equal importance in natural communities. Here, we conducted repeated surveys of locally-dominant amphipod species across ten naturally replicated stream catchments. We then used a hierarchical joint species distribution model to assess the influence of different drivers on species co-occurrences. The species had unique environmental requirements, but a distinct spatial structure in their distributions was unrelated to habitat. Species co-occurred much less frequently than predicted by their niches, which was surprising because laboratory and field evidence suggests they are capable of coexisting in equal densities. We suggest that niche preemption may limit their distribution and that a blocking effect determines which species colonizes and dominates a given stream catchment, thus resolving a long-standing conundrum in freshwater ecology.

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Modelling the spatial–temporal distributions and associated determining factors of a keystone pelagic fish

ICES Journal of Marine Science ◽

10.1093/icesjms/fsaa148 ◽

2020 ◽

Author(s):

Samantha Andrews ◽

Shawn J Leroux ◽

Marie-Josée Fortin

Keyword(s):

Species Distribution Model ◽

Spatial Dynamics ◽

Species Distributions ◽

Predictive Modelling ◽

Distribution Model ◽

Ecological Processes ◽

Pelagic Species ◽

The North ◽

The North Atlantic Oscillation ◽

Over Time

Abstract Mobile pelagic species habitat is structured around dynamic oceanographic and ecological processes that operate and interact horizontally and vertically throughout the water column and change over time. Due to their extensive movements, pelagic species distributions are often poorly understood. We use the Maxent species distribution model to assess how changes in the relative importance of modelled oceanographic (e.g. temperature) and climatic variables (e.g. the North Atlantic Oscillation) over 17 years affect the monthly average horizontal and vertical distribution of a keystone pelagic forage species, Atlantic Canadian capelin (Mallotus villosus). We show that the range and distribution of capelin occurrence probabilities vary across horizontal and vertical axes over time, with binary presence/absence predictions indicating capelin occupy between 0.72% (April) and 3.45% (November) of the total modelled space. Furthermore, our analysis reveals that the importance of modelled oceanographic variables, such as temperature, varies between months (44% permutation importance in August to 2% in May). By capturing the spatial dynamics of capelin over horizontal, vertical, and temporal axes, our analysis builds on work that improves our understanding and predictive modelling ability of pelagic species distributions under current and future conditions for proactive ecosystem-based management.

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