Climate change reshapes the drivers of false spring risk across European trees

Catherine J. Chamberlain; Benjamin I. Cook; Ignacio Morales‐Castilla; E. M. Wolkovich

doi:10.1111/nph.16851

Gross Primary Production and False Spring: a spatio-temporal analysis

10.5194/egusphere-egu2020-17837 ◽

2020 ◽

Author(s):

Emma Izquierdo-Verdiguier ◽

Raúl Zurita-Milla ◽

Álvaro Moreno-Martinez ◽

Gustau Camps-Valls ◽

Anja Klisch ◽

...

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Primary Production ◽

Gross Primary Production ◽

Damage Index ◽

Temporal Analysis ◽

Environmental Stressors ◽

Impact Of Climate Change ◽

False Spring ◽

Spatial Temporal Analysis

Phenological information can be obtained from different sources of data. For instance, from remote sensing data or products and from models driven by weather variables. The former typically allows analyzing land surface phenology whereas the latter provide plant phenological information. Analyzing relationships between both sources of data allows us to understand the impact of climate change on vegetation over space and time. For example, the onset of spring is advanced or delayed by changes in the climate. These alterations affect plant productivity and animal migrations.Spring onset monitoring is supported by the Extended Spring Index (SI-x), which are a suite of regression-based models for key indicator plant species. These models (Schwartz et al. in 2013) are based on daily maximum and minimum temperature from the first day of the year (January 1st). The primary products of these models are the timing of first leaf and first bloom, but they also provide derivative products such as the timing of last freeze day and the risk of frost damage day (damage index) for each year. This information helps to understand if vegetation could have suffered from environmental stressors such as droughts or a late frost events. The effects of environmental stressors in vegetation could be captured by the false spring index, which relates the first leaf day and the last freeze day. Moreover, this information could be used to understand plant productivity as well as to evaluate the economic impact of climate change.Previous works studied the relationship between remote sensing and plant level products by means of spatial-temporal analysis between Gross Primary Production (GPP) and a spring onset index. However, they did not consider the possible impact of false spring effect in these relationships. Here, we present a spatial-temporal analysis between GPP and the damage index to better understand the effect of false springs (in annual gross photosynthesis data). The analysis is done for the period 2000 to 2015 over the contiguous US and at spatial resolution of 1 km. We used the MODIS annual sum of GPP and the damage and false spring indices derived from the SI-x models.

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Climate change reshapes the drivers of false spring risk across European trees

10.5194/egusphere-egu2020-5871 ◽

2020 ◽

Author(s):

Catherine Chamberlain ◽

Benjamin Cook ◽

Ignacio Morales-Castilla ◽

Elizabeth Wolkovich

Keyword(s):

Climate Change ◽

Boreal Forests ◽

Climatic Factors ◽

Alnus Glutinosa ◽

Residual Effects ◽

Spring Temperature ◽

Geographic Factors ◽

The North ◽

Increased Risk ◽

False Spring

Temperate and boreal forests are shaped by late spring freezing events after budburst, which are also known as false springs. Research has generated conflicting results on whether or not these events will change with climate change, potentially because---to date---no study has compared the myriad climatic and geographic factors that contribute to a plant's risk of a false spring. We assessed and compared the strength of the effects of mean spring temperature, distance from the coast, elevation and the North Atlantic Oscillation (NAO) using PEP725 leafout data for six temperate, decidious tree species across 11,648 sites in Central Europe and how these predictors shifted with climate change. Across species before recent warming, mean spring temperature and distance from the coast were the strongest predictors, with higher mean spring temperatures associated with decreased risk in false springs (&#8211;7.64% per 2&#176;C increase) and sites further from the coast experiencing an increased risk (5.32% per 150km from the coast). Elevation (2.23% per 200m increase in elevation) and NAO index (1.91% per 0.3 increase) also increased false spring risk.&#160;With climate change, elevation and distance from coast---i.e., the geographic factors---remain relatively stable, while climatic factors shifted in magnitude for mean spring temperature (down to -2.84% in risk per 2&#176;C), and in direction, with positive NAO phases leading to lower risk (-9.15% per 0.3). The residual effects of climate change---unexplained by the climatic and geographic factors already included in the model---magnified the species-level variation in risk, with risk increasing among early-leafout species (i.e., Aesculus hippocastanum, Alnus glutinosa and Betula pendula) but a decline or no change in risk among late-leafout species (i.e., Fagus sylvatica, Fraxinus excelsior and Quercus robur). Our results show that climate change has reshaped the major drivers of false spring risk and highlight how considering multiple factors can yield a better understanding of the complexities of climate change.

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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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