Climate-change versus landslide origin of fill terraces in a rapidly eroding bedrock landscape: San Gabriel River, California

Dirk Scherler; Michael P. Lamb; Edward J. Rhodes; Jean-Philippe Avouac

doi:10.1130/b31356.1

Climate-change versus landslide origin of fill terraces in a rapidly eroding bedrock landscape: San Gabriel River, California

Geological Society of America Bulletin ◽

10.1130/b31356.1 ◽

2016 ◽

Vol 128 (7-8) ◽

pp. 1228-1248 ◽

Cited By ~ 12

Author(s):

Dirk Scherler ◽

Michael P. Lamb ◽

Edward J. Rhodes ◽

Jean-Philippe Avouac

Keyword(s):

Climate Change ◽

San Gabriel River

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Averting robo-bees: why free-flying robotic bees are a bad idea

Emerging Topics in Life Sciences ◽

10.1042/etls20190063 ◽

2019 ◽

Vol 3 (6) ◽

pp. 723-729

Author(s):

Roslyn Gleadow ◽

Jim Hanan ◽

Alan Dorin

Keyword(s):

Climate Change ◽

Computer Simulation ◽

Food Security ◽

European Countries ◽

Plant Interactions ◽

Plant Insect Interactions ◽

Native Habitat ◽

Insect Pollinators ◽

Insect Interactions

Food security and the sustainability of native ecosystems depends on plant-insect interactions in countless ways. Recently reported rapid and immense declines in insect numbers due to climate change, the use of pesticides and herbicides, the introduction of agricultural monocultures, and the destruction of insect native habitat, are all potential contributors to this grave situation. Some researchers are working towards a future where natural insect pollinators might be replaced with free-flying robotic bees, an ecologically problematic proposal. We argue instead that creating environments that are friendly to bees and exploring the use of other species for pollination and bio-control, particularly in non-European countries, are more ecologically sound approaches. The computer simulation of insect-plant interactions is a far more measured application of technology that may assist in managing, or averting, ‘Insect Armageddon' from both practical and ethical viewpoints.

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Modelling ecosystem adaptation and dangerous rates of global warming

Emerging Topics in Life Sciences ◽

10.1042/etls20180113 ◽

2019 ◽

Vol 3 (2) ◽

pp. 221-231 ◽

Cited By ~ 4

Author(s):

Rebecca Millington ◽

Peter M. Cox ◽

Jonathan R. Moore ◽

Gabriel Yvon-Durocher

Keyword(s):

Climate Change ◽

Global Warming ◽

Diffusion Rate ◽

Individual Species ◽

Genetic Evolution ◽

Rates Of Change ◽

Rapid Climate Change ◽

Warming Climate ◽

Intraspecies Competition ◽

High Trait

Abstract We are in a period of relatively rapid climate change. This poses challenges for individual species and threatens the ecosystem services that humanity relies upon. Temperature is a key stressor. In a warming climate, individual organisms may be able to shift their thermal optima through phenotypic plasticity. However, such plasticity is unlikely to be sufficient over the coming centuries. Resilience to warming will also depend on how fast the distribution of traits that define a species can adapt through other methods, in particular through redistribution of the abundance of variants within the population and through genetic evolution. In this paper, we use a simple theoretical ‘trait diffusion’ model to explore how the resilience of a given species to climate change depends on the initial trait diversity (biodiversity), the trait diffusion rate (mutation rate), and the lifetime of the organism. We estimate theoretical dangerous rates of continuous global warming that would exceed the ability of a species to adapt through trait diffusion, and therefore lead to a collapse in the overall productivity of the species. As the rate of adaptation through intraspecies competition and genetic evolution decreases with species lifetime, we find critical rates of change that also depend fundamentally on lifetime. Dangerous rates of warming vary from 1°C per lifetime (at low trait diffusion rate) to 8°C per lifetime (at high trait diffusion rate). We conclude that rapid climate change is liable to favour short-lived organisms (e.g. microbes) rather than longer-lived organisms (e.g. trees).

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