Brooke Bateman is a Senior Scientist, Climate and Director of Climate Watch at the National Audubon Society. She received her PhD in Zoology and Tropical Ecology at James Cook University in Australia and postdoctoral experience with the University of Wisconsin-Madison. Brooke’s research focuses on species distribution modeling, extreme weather, and climate change, and with a strong link to on-the-ground conservation and management actions, and since 2010 has led or contributed to 21 peer-reviewed publications. As the director of Climate Watch, Brooke works with Audubon volunteers to better understand how North American birds are being affected by climate change
The National Wildlife Refuge System (NWRS) provides one of the United States’ greatest protected ... more The National Wildlife Refuge System (NWRS) provides one of the United States’ greatest protected area networks for wildlife conservation. As climate changes beyond historical ranges of variability, refuge managers are confronted with assessing the utility of refuges, including how to best manage refuges both individually and as a system to help species cope with rapid change. Using published species distribution models, we projected species-specific changes in environmental suitability for 590 native North American bird species under a 2°C future warming scenario (~2050s under RCP8.5) at 525 refuges. For each species, we classified projected changes in suitability (i.e., improving, stable, or worsening suitability) and whether they crossed a model-derived persistence threshold at a refuge (i.e., potential colonization or potential extirpation). Overall, we found that a quarter of species (23% in summer, 26% in winter) could be different (i.e., turnover) across the refuge system desp...
Rapid and ongoing change creates novelty in ecosystems everywhere, both when comparing contempora... more Rapid and ongoing change creates novelty in ecosystems everywhere, both when comparing contemporary systems to their historical baselines, and predicted future systems to the present. However, the level of novelty varies greatly among places. Here we propose a formal and quantifiable definition of abiotic and biotic novelty in ecosystems, map abiotic novelty globally, and discuss the implications of novelty for the science of ecology and for biodiversity conservation. We define novelty as the degree of dissimilarity of a system, measured in one or more dimensions relative to a reference baseline, usually defined as either the present or a time window in the past. In this conceptualization, novelty varies in degree, it is multidimensional, can be measured, and requires a temporal and spatial reference. This definition moves beyond prior categorical definitions of novel ecosystems, and does not include human agency, self-perpetuation, or irreversibility as criteria. Our global assessm...
Contains Model output data for Short-term Climate Variability Models for species in the genera Ty... more Contains Model output data for Short-term Climate Variability Models for species in the genera Tyrannus, Tyto, Vermivora, Vireo, Xanthocephalus, and Zenaida
Cockatoo grass [Alloteropsis semialata (R.Br.) A. Hitchc.] is considered a keystone species in no... more Cockatoo grass [Alloteropsis semialata (R.Br.) A. Hitchc.] is considered a keystone species in northern Australian ecosystems as it provides a food resource for many species, including several endangered vertebrates. This study examined both local and regional environmental factors influencing cockatoo grass distribution and abundance in the Wet Tropics of north Queensland, Australia. Local distribution and abundance were investigated in the sclerophyll ecotone between open woodland and tall open forest, because little is known about cockatoo grass distribution within this habitat; also, the endangered northern bettong (Bettongia tropica) is restricted to this habitat and depends on cockatoo grass for its survival. Regional-scale modelling of distribution was undertaken to examine the climatic tolerances of cockatoo grass in Queensland. Density of cockatoo grass was negatively related to litter cover, soil moisture, and the presence of two dominant grass species, Themeda triandra [F...
Current applications of species distribution models (SDM) are typically static, in that they are ... more Current applications of species distribution models (SDM) are typically static, in that they are based on correlations between where a species has been observed (ignoring the date of the observation) and environmental features, such as long-term climate means, that are assumed to be constant for each site. Because of this SDMs do not account for temporal variation in the distribution of suitable habitat across the range of a species. Here, we demonstrate the temporal variability in the potential geographic distributions of an ...
Aim To measure the effects of including biotic interactions on climate-based species distribution... more Aim To measure the effects of including biotic interactions on climate-based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.
ABSTRACT AimSpecies distribution models (SDMs) generally use correlative relationships between th... more ABSTRACT AimSpecies distribution models (SDMs) generally use correlative relationships between the species location and the associated environment to project the species potential distribution under climate change. While projecting a future suitable climatic space is relatively simple using SDMs, predicting a species ability to occupy that space relies on understanding dispersal capacity; a lack of knowledge about species‐specific dispersal ability, varying geographical contexts and technical constraints of simple SDMs has limited the consideration of dispersal in most studies. We review the current treatment of dispersal in SDM studies addressing the effects of climate change and explore how incorporating ‘partial‐dispersal’ scenarios could lead to more realistic projections of species distributions into the future. LocationGlobal. Methods We consider the implications for projected distributions of incorporating full‐ and no‐dispersal scenarios in SDMs and identify a range of methods and their associated information needs for implementing partial‐dispersal scenarios. ResultsWhile simplistic and easy to implement, full‐ and no‐dispersal scenarios are only realistic in a few situations. Although implementing partial‐dispersal scenarios may require information that is lacking for many species, we argue that even relatively simple partial‐dispersal models, with fairly basic knowledge needs, improve projections of altered distributions under climate change. More complex models, using more sophisticated modelling approaches, have been tested in a few cases and provide robust projections. Main Conclusions While climate change SDM outputs have proved useful, we highlight that careful selection of dispersal scenarios, relevant to the particular questions being addressed, is necessary for appropriate interpretation of the model outputs when projecting into novel environments (e.g. future climates). A number of methods have been developed for incorporating partial‐dispersal scenarios in SDMs; however, the data and computation requirements currently limit their application to large numbers of species, highlighting the need for other techniques and generic user‐friendly modelling platforms.
The National Wildlife Refuge System (NWRS) provides one of the United States’ greatest protected ... more The National Wildlife Refuge System (NWRS) provides one of the United States’ greatest protected area networks for wildlife conservation. As climate changes beyond historical ranges of variability, refuge managers are confronted with assessing the utility of refuges, including how to best manage refuges both individually and as a system to help species cope with rapid change. Using published species distribution models, we projected species-specific changes in environmental suitability for 590 native North American bird species under a 2°C future warming scenario (~2050s under RCP8.5) at 525 refuges. For each species, we classified projected changes in suitability (i.e., improving, stable, or worsening suitability) and whether they crossed a model-derived persistence threshold at a refuge (i.e., potential colonization or potential extirpation). Overall, we found that a quarter of species (23% in summer, 26% in winter) could be different (i.e., turnover) across the refuge system desp...
Rapid and ongoing change creates novelty in ecosystems everywhere, both when comparing contempora... more Rapid and ongoing change creates novelty in ecosystems everywhere, both when comparing contemporary systems to their historical baselines, and predicted future systems to the present. However, the level of novelty varies greatly among places. Here we propose a formal and quantifiable definition of abiotic and biotic novelty in ecosystems, map abiotic novelty globally, and discuss the implications of novelty for the science of ecology and for biodiversity conservation. We define novelty as the degree of dissimilarity of a system, measured in one or more dimensions relative to a reference baseline, usually defined as either the present or a time window in the past. In this conceptualization, novelty varies in degree, it is multidimensional, can be measured, and requires a temporal and spatial reference. This definition moves beyond prior categorical definitions of novel ecosystems, and does not include human agency, self-perpetuation, or irreversibility as criteria. Our global assessm...
Contains Model output data for Short-term Climate Variability Models for species in the genera Ty... more Contains Model output data for Short-term Climate Variability Models for species in the genera Tyrannus, Tyto, Vermivora, Vireo, Xanthocephalus, and Zenaida
Cockatoo grass [Alloteropsis semialata (R.Br.) A. Hitchc.] is considered a keystone species in no... more Cockatoo grass [Alloteropsis semialata (R.Br.) A. Hitchc.] is considered a keystone species in northern Australian ecosystems as it provides a food resource for many species, including several endangered vertebrates. This study examined both local and regional environmental factors influencing cockatoo grass distribution and abundance in the Wet Tropics of north Queensland, Australia. Local distribution and abundance were investigated in the sclerophyll ecotone between open woodland and tall open forest, because little is known about cockatoo grass distribution within this habitat; also, the endangered northern bettong (Bettongia tropica) is restricted to this habitat and depends on cockatoo grass for its survival. Regional-scale modelling of distribution was undertaken to examine the climatic tolerances of cockatoo grass in Queensland. Density of cockatoo grass was negatively related to litter cover, soil moisture, and the presence of two dominant grass species, Themeda triandra [F...
Current applications of species distribution models (SDM) are typically static, in that they are ... more Current applications of species distribution models (SDM) are typically static, in that they are based on correlations between where a species has been observed (ignoring the date of the observation) and environmental features, such as long-term climate means, that are assumed to be constant for each site. Because of this SDMs do not account for temporal variation in the distribution of suitable habitat across the range of a species. Here, we demonstrate the temporal variability in the potential geographic distributions of an ...
Aim To measure the effects of including biotic interactions on climate-based species distribution... more Aim To measure the effects of including biotic interactions on climate-based species distribution models (SDMs) used to predict distribution shifts under climate change. We evaluated the performance of distribution models for an endangered marsupial, the northern bettong (Bettongia tropica), comparing models that used only climate variables with models that also took into account biotic interactions.
ABSTRACT AimSpecies distribution models (SDMs) generally use correlative relationships between th... more ABSTRACT AimSpecies distribution models (SDMs) generally use correlative relationships between the species location and the associated environment to project the species potential distribution under climate change. While projecting a future suitable climatic space is relatively simple using SDMs, predicting a species ability to occupy that space relies on understanding dispersal capacity; a lack of knowledge about species‐specific dispersal ability, varying geographical contexts and technical constraints of simple SDMs has limited the consideration of dispersal in most studies. We review the current treatment of dispersal in SDM studies addressing the effects of climate change and explore how incorporating ‘partial‐dispersal’ scenarios could lead to more realistic projections of species distributions into the future. LocationGlobal. Methods We consider the implications for projected distributions of incorporating full‐ and no‐dispersal scenarios in SDMs and identify a range of methods and their associated information needs for implementing partial‐dispersal scenarios. ResultsWhile simplistic and easy to implement, full‐ and no‐dispersal scenarios are only realistic in a few situations. Although implementing partial‐dispersal scenarios may require information that is lacking for many species, we argue that even relatively simple partial‐dispersal models, with fairly basic knowledge needs, improve projections of altered distributions under climate change. More complex models, using more sophisticated modelling approaches, have been tested in a few cases and provide robust projections. Main Conclusions While climate change SDM outputs have proved useful, we highlight that careful selection of dispersal scenarios, relevant to the particular questions being addressed, is necessary for appropriate interpretation of the model outputs when projecting into novel environments (e.g. future climates). A number of methods have been developed for incorporating partial‐dispersal scenarios in SDMs; however, the data and computation requirements currently limit their application to large numbers of species, highlighting the need for other techniques and generic user‐friendly modelling platforms.
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Papers by Brooke Bateman