Configuration of the thermal landscape determines thermoregulatory performance of ectotherms

Although most organisms thermoregulate behaviorally, biologists still cannot easily predict whether mobile animals will thermoregulate in natural environments. Current models fail because they ignore how the spatial distribution of thermal resources constrains thermoregulatory performance over space and time. To overcome this limitation, we modeled the spatially explicit movements of animals constrained by access to thermal resources. Our models predict that ectotherms thermoregulate more accurately when thermal resources are dispersed throughout space than when these resources are clumped. This prediction was supported by thermoregulatory behaviors of lizards in outdoor arenas with known distributions of environmental temperatures. Further, simulations showed how the spatial structure of the landscape qualitatively affects responses of animals to climate. Biologists will need spatially explicit models to predict impacts of climate change on local scales.

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Climate, ticks and disease

10.1079/9781789249637.0000 ◽

2021 ◽

Keyword(s):

Climate Change ◽

Spatial Distribution ◽

Disease Ecology ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Expert Opinions ◽

The World ◽

Host Pathogen ◽

The Future ◽

Impacts Of Climate Change

Abstract This book is a collection of 77 expert opinions arranged in three sections. Section 1 on "Climate" sets the scene, including predictions of future climate change, how climate change affects ecosystems, and how to model projections of the spatial distribution of ticks and tick-borne infections under different climate change scenarios. Section 2 on "Ticks" focuses on ticks (although tick-borne pathogens creep in) and whether or not changes in climate affect the tick biosphere, from physiology to ecology. Section 3 on "Disease" focuses on the tick-host-pathogen biosphere, ranging from the triangle of tick-host-pathogen molecular interactions to disease ecology in various regions and ecosystems of the world. Each of these three sections ends with a synopsis that aims to give a brief overview of all the expert opinions within the section. The book concludes with Section 4 (Final Synopsis and Future Predictions). This synopsis attempts to summarize evidence provided by the experts of tangible impacts of climate change on ticks and tick-borne infections. In constructing their expert opinions, contributors give their views on what the future might hold. The final synopsis provides a snapshot of their expert thoughts on the future.

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Local extinction risk of three species of lizard from Patagonia as a result of global warming

Canadian Journal of Zoology ◽

10.1139/cjz-2015-0024 ◽

2016 ◽

Vol 94 (1) ◽

pp. 49-59 ◽

Cited By ~ 32

Author(s):

E.L. Kubisch ◽

V. Corbalán ◽

N.R. Ibargüengoytía ◽

B. Sinervo

Keyword(s):

Climate Change ◽

Extinction Risk ◽

Physiological Model ◽

Single Equation ◽

Reproductive Period ◽

Local Extinction ◽

Physiological Constraints ◽

Local Warming ◽

Environmental Temperatures ◽

Impacts Of Climate Change

Recently, Sinervo et al. (2010, Science, 328: 894–899) reported declines of lizard biodiversity due to local warming trends and altered thermal niches. Herein, we applied the Sinervo et al. (2010) physiological model to predict the local extinction risk of three species of lizard from Patagonia. Whereas the previous model used a single equation (for the extinctions of Blue Spiny Lizard (Sceloporus serrifer Cope, 1866) in the Yucatan Peninsula) relating environmental temperatures (Te) to hours of restriction (i.e., the period when lizards are forced into retreat sites because environmental temperatures are too high), we measured habitat-specific equations for the Te values of each species. We analyzed the vulnerability of Darwin’s Ground Gecko (Homonota darwinii Boulenger, 1885), Bariloche Lizard (Liolaemus pictus (Duméril and Bibron, 1837)), and Mountain Slope Lizard (Liolaemus elongatus Koslowsky, 1896) to climate change considering thermal physiological constraints on activity during the reproductive period. While Sinervo et al. (2010) predicted that the Phyllodactylidae family will not suffer from impacts of climate change, our physiological model predicted that 20% of the H. darwinii populations could become extinct by 2080. The physiological model also predicted that 15% of L. pictus populations and 26.5% of L. elongatus populations could become extinct by 2080. The most vulnerable populations are those located near the northern and eastern boundaries of their distributions.

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Agroforestry systems can mitigate the impacts of climate change on coffee production: A spatially explicit assessment in Brazil

Agriculture Ecosystems & Environment ◽

10.1016/j.agee.2020.106858 ◽

2020 ◽

Vol 294 ◽

pp. 106858 ◽

Cited By ~ 7

Author(s):

L.C. Gomes ◽

F.J.J.A. Bianchi ◽

I.M. Cardoso ◽

R.B.A. Fernandes ◽

E.I. Fernandes Filho ◽

...

Keyword(s):

Climate Change ◽

Agroforestry Systems ◽

Spatially Explicit ◽

Coffee Production ◽

Impacts Of Climate Change

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A Study of the Impacts of Climate Change Scenarios on the Plant Hardiness Zones of Albania

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0108.1 ◽

2017 ◽

Vol 56 (3) ◽

pp. 615-631 ◽

Cited By ~ 1

Author(s):

Zydi Teqja ◽

Albert Kopali ◽

Zamir Libohova ◽

Phillip R. Owens

Keyword(s):

Climate Change ◽

Spatial Distribution ◽

New Species ◽

Cold Season ◽

Climate Change Scenarios ◽

Climate Scenarios ◽

Climate Change Effects ◽

Temperature Trends ◽

Plant Hardiness ◽

Impacts Of Climate Change

AbstractMaps of plant hardiness zones are useful tools for determining the extreme limits for the survival of plants. Exploration of projected climate change effects on hardiness zones can help identify areas most affected by climate change. Such studies are important in areas with high risks related to climate change, such as the Mediterranean Sea region. The objectives of this study were to (i) map plant hardiness zones for Albania and (ii) assess the projected effects of climate scenarios on the distribution of hardiness zones. Hardiness zones were affected by IPCC AR5 climate scenarios. The most extreme hardiness zone (6a) disappeared while a new, warmer zone (10b) appeared, reflecting rising temperature trends during the cold season. The shifts in spatial distribution of hardiness zones may represent opportunities for introducing new species to Albanian agriculture and forestry; however, the introduction of new species would require further studies on the variability of plant hardiness zones at local scales.

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Contribution of spatially explicit models to climate change adaptation and mitigation plans for a priority forest habitat

Mitigation and Adaptation Strategies for Global Change ◽

10.1007/s11027-017-9738-z ◽

2017 ◽

Vol 23 (3) ◽

pp. 371-386 ◽

Cited By ~ 9

Author(s):

Ricardo A. Correia ◽

Miguel N. Bugalho ◽

Aldina M. A. Franco ◽

Jorge M. Palmeirim

Keyword(s):

Climate Change ◽

Climate Change Adaptation ◽

Spatially Explicit ◽

Forest Habitat ◽

Spatially Explicit Models ◽

A Priority ◽

Adaptation And Mitigation

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Periodic synchronization of dengue epidemics in Thailand: the roles played by temperature and immunity

10.1101/2021.03.01.433325 ◽

2021 ◽

Author(s):

Bernardo García-Carreras ◽

Bingyi Yang ◽

Mary K Grabowski ◽

Lawrence W Sheppard ◽

Angkana T Huang ◽

...

Keyword(s):

Climate Change ◽

Spatial Distribution ◽

Seasonal Variation ◽

Temporal Dynamics ◽

Large Impact ◽

Haemorrhagic Fever ◽

Disease Patterns ◽

Spatio Temporal ◽

Dengue Epidemics ◽

Impacts Of Climate Change

The spatial distribution of dengue and its vectors (spp. Aedes) may be the widest it has ever been, and projections suggest that climate change may allow the expansion to continue. However, the largest impacts of climate change on dengue might be in regions where the pathogen is already endemic. In these areas, the waxing and waning of immunity has a large impact on temporal dynamics of cases of dengue haemorrhagic fever. Here, we use 51 years of data across 72 provinces and characterise spatio-temporal patterns of dengue in Thailand, where dengue has caused almost 1.5 million cases over the last thirty years, and examine the roles played by temperature and dynamics of immunity in giving rise to those patterns. We find that timescales of multiannual oscillations in dengue vary in space and time and uncover an interesting spatial phenomenon: Thailand has experienced multiple, periodic synchronization events. We show that patterns in synchrony of dengue are consistent with those observed in temperature. Applying a temperature-driven dengue model, we explore how dynamics of immunity interact with temperature to produce the observed multiannual dynamics and patterns in synchrony. While multiannual oscillations are readily produced by immunity in absence of multiannual timescales in temperature, synchrony in temperature can synchronise dengue dynamics in different locations. However, at higher mean temperatures and lower seasonal variation, immune dynamics become more predominant, and dengue dynamics become more insensitive to multiannual fluctuations in temperature. These findings can help underpin predictions of disease patterns as global temperatures rise.

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Spatial modeling of Bering Sea walleye pollock with integrated age-structured assessment models in a changing environment

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2013-0020 ◽

2013 ◽

Vol 70 (9) ◽

pp. 1402-1416 ◽

Cited By ~ 24

Author(s):

Peter-John F. Hulson ◽

Terrance J. Quinn ◽

Dana H. Hanselman ◽

James N. Ianelli

Keyword(s):

Climate Change ◽

Bering Sea ◽

Walleye Pollock ◽

Spatially Explicit ◽

Parameter Estimates ◽

Effective Sample Size ◽

Climate Change Effects ◽

Spatially Explicit Models ◽

Distribution Shifts ◽

Age Structured

Climate change may affect the spatial distribution of fish populations in ways that would affect the accuracy of spatially aggregated age-structured assessment models. To evaluate such scenarios, spatially aggregated models were compared with spatially explicit models using simulations. These scenarios were based on hypothetical climate-driven distribution shifts and reductions in mean recruitment of walleye pollock (Gadus chalcogrammus) in the eastern Bering Sea. Results indicate that biomass estimates were reasonably accurate for both types of estimation models and precision improved with the inclusion of tagging data. Bias in some aggregated model scenarios could be attributed to unaccounted-for process errors in annual fishing mortality rates and was reduced when estimating effective sample size or time-varying selectivity. Spatially explicit models that allow estimation of variability in movement and ontogenetic parameters (specified as a random walk process) were shown to be feasible, whereas models that misspecified ontogenetic movement and climate change effects resulted in biased biomass and movement parameter estimates. These results illustrate that more complex models may characterize processes better but may be less robust for management advice.

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