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Journal ArticleDOI

Focus on poleward shifts in species' distribution underestimates the fingerprint of climate change

TLDR
This paper analysed 60 years of past climate change on the Australian continent, assessing the velocity of changes in temperature and precipitation, as well as changes in climatic niche space for 464 Australian birds.
Abstract
Species are largely predicted to shift poleward as global temperatures increase, with this fingerprint of climate change being already observed across a range of taxonomic groups and, mostly temperate, geographic locations¹⁻⁵. However, the assumption of uni-directional distribution shifts does not account for complex interactions among temperature, precipitation and species-specific tolerances⁶, all of which shape the direction and magnitude of changes in a species' climatic niche. We analysed 60 years of past climate change on the Australian continent, assessing the velocity of changes in temperature and precipitation, as well as changes in climatic niche space for 464 Australian birds. We show large magnitude and rapid rates of change in Australian climate over the past 60 years resulting in high-velocity and multi-directional, including equatorial, shifts in suitable climatic space for birds (ranging from 0.1 to 7.6 km yr⁻¹, mean 1.27 km yr⁻¹). Overall, if measured only in terms of poleward distribution shifts, the fingerprint of climate change is underestimated by an average of 26% in temperate regions of the continent and by an average of 95% in tropical regions. We suggest that the velocity of movement required by Australian species to track their climatic niche may be much faster than previously thought and that the interaction between temperature and precipitation changes will result in multi-directional distribution shifts globally.

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Citations
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Journal ArticleDOI

How Should Beta-Diversity Inform Biodiversity Conservation?

TL;DR: How beta-diversity is impacted by human activities, including farming, selective logging, urbanization, species invasions, overhunting, and climate change is reviewed.
Journal ArticleDOI

Climate-related range shifts – a global multidimensional synthesis and new research directions

TL;DR: In this article, a review of the state of the art on geographical patterns of species range shifts under contemporary climate change for plants and animals across both terrestrial and marine ecosystems is presented.
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Multiple Dimensions of Climate Change and Their Implications for Biodiversity

TL;DR: This review critically assesses the variety of metrics commonly used to describe climate change in biodiversity-impact assessments covering local changes in climate averages and extremes, regional changes in the availability and position of climates, and the velocity of climate change.
References
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Journal ArticleDOI

Maximum entropy modeling of species geographic distributions

TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.
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A globally coherent fingerprint of climate change impacts across natural systems

TL;DR: A diagnostic fingerprint of temporal and spatial ‘sign-switching’ responses uniquely predicted by twentieth century climate trends is defined and generates ‘very high confidence’ (as laid down by the IPCC) that climate change is already affecting living systems.
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Ecological responses to recent climate change.

TL;DR: A review of the ecological impacts of recent climate change exposes a coherent pattern of ecological change across systems, from polar terrestrial to tropical marine environments.
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Ecological and Evolutionary Responses to Recent Climate Change

TL;DR: Range-restricted species, particularly polar and mountaintop species, show severe range contractions and have been the first groups in which entire species have gone extinct due to recent climate change.
Journal ArticleDOI

Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation

TL;DR: This paper presents a tuning method that uses presence-only data for parameter tuning, and introduces several concepts that improve the predictive accuracy and running time of Maxent and describes a new logistic output format that gives an estimate of probability of presence.
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