How do climate change experiments alter plot‐scale climate?

To understand and forecast biological responses to climate change, scientists frequently use field experiments that alter temperature and precipitation. Climate manipulations can manifest in complex ways, however, challenging interpretations of biological responses. We reviewed publications to compile a database of daily plot‐scale climate data from 15 active‐warming experiments. We find that the common practices of analysing treatments as mean or categorical changes (e.g. warmed vs. unwarmed) masks important variation in treatment effects over space and time. Our synthesis showed that measured mean warming, in plots with the same target warming within a study, differed by up to 1.6 C (63% of target), on average, across six studies with blocked designs. Variation was high across sites and designs: for example, plots differed by 1.1 C (47% of target) on average, for infrared studies with feedback control (n = 3) vs. by 2.2 C (80% of target) on average for infrared with constant wattage designs (n = 2). Warming treatments produce non‐temperature effects as well, such as soil drying. The combination of these direct and indirect effects is complex and can have important biological consequences. With a case study of plant phenology across five experiments in our database, we show how accounting for drier soils with warming tripled the estimated sensitivity of budburst to temperature. We provide recommendations for future analyses, experimental design, and data sharing to improve our mechanistic understanding from climate change experiments, and thus their utility to accurately forecast species’ responses.     

Will climate change promote future invasions?

Biological invasion is increasingly recognized as one of the greatest threats to biodiversity. Using ensemble forecasts from species distribution models to project future suitable areas of the 100 of the world's worst invasive species defined by the International Union for the Conservation of Nature, we show that both climate and land use changes will likely cause drastic species range shifts. Looking at potential spatial aggregation of invasive species, we identify three future hotspots of invasion in Europe, northeastern North America, and Oceania. We also emphasize that some regions could lose a significant number of invasive alien species, creating opportunities for ecosystem restoration. From the list of 100, scenarios of potential range distributions show a consistent shrinking for invasive amphibians and birds, while for aquatic and terrestrial invertebrates distributions are projected to substantially increase in most cases. Given the harmful impacts these invasive species currently have on ecosystems, these species will likely dramatically influence the future of biodiversity.     

Detrending climate data prior to climate–growth analyses in dendroecology: A common best practice?

Tree growth varies closely with high–frequency climate variability. Since the 1930s detrending climate data prior to comparing them with tree growth data has been shown to better capture tree growth sensitivity to climate. However, in a context of increasingly pronounced trends in climate, this practice remains surprisingly rare in dendroecology. In a review of Dendrochronologia over the 2018–2021 period, we found that less than 20 % of dendroecological studies detrended climate data prior to climate-growth analyses. With an illustrative study, we want to remind the dendroecology community that such a procedure is still, if not more than ever, rational and relevant. We investigated the effects of detrending climate data on climate–growth relationships across North America over the 1951–2000 period. We used a network of 2536 tree individual ring-width series from the Canadian and Western US forest inventories. We compared correlations between tree growth and seasonal climate data (Tmin, Tmax, Prec) both raw and detrended. Detrending approaches included a linear regression, 30-yr and 100-yr cubic smoothing splines. Our results indicate that on average the detrending of climate data increased climate–growth correlations. In addition, we observed that strong trends in climate data translated to higher variability in inferred correlations based on raw vs. detrended climate data. We provide further evidence that our results hold true for the entire spectrum of dendroecological studies using either mean site chronologies and correlations coefficients, or individual tree time series within a mixed-effects model framework where regression coefficients are used more commonly. We show that even without a change in correlation, regression coefficients can change a lot and we tend to underestimate the true climate impact on growth in case of climate variables containing trends. This study demonstrates that treating climate and tree-ring time series “like-for-like” is a necessary procedure to reduce false negatives and positives in dendroecological studies. Concluding, we recommend using the same detrending for climate and tree growth data when tree-ring time series are detrended with splines or similar frequency-based filters.     

How does climate change cause extinction?

Anthropogenic climate change is predicted to be a major cause of species extinctions in the next 100 years. But what will actually cause these extinctions? For example, will it be limited physiological tolerance to high temperatures, changing biotic interactions or other factors? Here, we systematically review the proximate causes of climate-change related extinctions and their empirical support. We find 136 case studies of climatic impacts that are potentially relevant to this topic. However, only seven identified proximate causes of demonstrated local extinctions due to anthropogenic climate change. Among these seven studies, the proximate causes vary widely. Surprisingly, none show a straightforward relationship between local extinction and limited tolerances to high temperature. Instead, many studies implicate species interactions as an important proximate cause, especially decreases in food availability. We find very similar patterns in studies showing decreases in abundance associated with climate change, and in those studies showing impacts of climatic oscillations. Collectively, these results highlight our disturbingly limited knowledge of this crucial issue but also support the idea that changing species interactions are an important cause of documented population declines and extinctions related to climate change. Finally, we briefly outline general research strategies for identifying these proximate causes in future studies.     

Nitrogen–climate interactions in US agriculture

Agriculture in the United States (US) cycles large quantities of nitrogen (N) to produce food, fuel, and fiber and is a major source of excess reactive nitrogen (Nr) in the environment. Nitrogen lost from cropping systems and animal operations moves to waterways, groundwater, and the atmosphere. Changes in climate and climate variability may further affect the ability of agricultural systems to conserve N. The N that escapes affects climate directly through the emissions of nitrous oxide (N₂O), and indirectly through the loss of nitrate (NO₃ ^?), nitrogen oxides (NO _x ) and ammonia to downstream and downwind ecosystems that then emit some of the N received as N₂O and NO _x . Emissions of NO _x lead to the formation of tropospheric ozone, a greenhouse gas that can also harm crops directly. There are many opportunities to mitigate the impact of agricultural N on climate and the impact of climate on agricultural N. Some are available today; many need further research; and all await effective incentives to become adopted. Research needs can be grouped into four major categories: (1) an improved understanding of agricultural N cycle responses to changing climate; (2) a systems-level understanding of important crop and animal systems sufficient to identify key interactions and feedbacks; (3) the further development and testing of quantitative models capable of predicting N-climate interactions with confidence across a wide variety of crop-soil-climate combinations; and (4) socioecological research to better understand the incentives necessary to achieve meaningful deployment of realistic solutions.     

Does climate directly influence NPP globally?

The need for rigorous analyses of climate impacts has never been more crucial. Current textbooks state that climate directly influences ecosystem annual net primary productivity (NPP), emphasizing the urgent need to monitor the impacts of climate change. A recent paper challenged this consensus, arguing, based on an analysis of NPP for 1247 woody plant communities across global climate gradients, that temperature and precipitation have negligible direct effects on NPP and only perhaps have indirect effects by constraining total stand biomass (M_tot) and stand age (a). The authors of that study concluded that the length of the growing season (l_gs) might have a minor influence on NPP, an effect they considered not to be directly related to climate. In this article, we describe flaws that affected that study's conclusions and present novel analyses to disentangle the effects of stand variables and climate in determining NPP. We re‐analyzed the same database to partition the direct and indirect effects of climate on NPP, using three approaches: maximum‐likelihood model selection, independent‐effects analysis, and structural equation modeling. These new analyses showed that about half of the global variation in NPP could be explained by M_tot combined with climate variables and supported strong and direct influences of climate independently of M_tot, both for NPP and for net biomass change averaged across the known lifetime of the stands (ABC = average biomass change). We show that l_gs is an important climate variable, intrinsically correlated with, and contributing to mean annual temperature and precipitation (T_ann and P_ann), all important climatic drivers of NPP. Our analyses provide guidance for statistical and mechanistic analyses of climate drivers of ecosystem processes for predictive modeling and provide novel evidence supporting the strong, direct role of climate in determining vegetation productivity at the global scale.     

BVOCs: plant defense against climate warming?

Plants emit a substantial amount of biogenic volatile organic compounds (BVOCs) into the atmosphere. These BVOCs represent a large carbon loss and can be up to approximately 10% of that fixed by photosynthesis under stressful conditions and up to 100gCm(-2) per year in some tropical ecosystems. Among a variety of proven and unproven BVOC functions in plants and roles in atmospheric processes, recent data intriguingly link emission of these compounds to climate. Ongoing research demonstrates that BVOCs could protect plants against high temperatures. BVOC emissions are probably increasing with warming and with other factors associated to global change, including changes in land cover. These increases in BVOC emissions could contribute in a significant way (via negative and positive feedback) to the complex processes associated with global warming.     

Cooperative breeding: a question of climate?

In some species, including humans, parents receive help with offspring care. A new comparative study suggests that birds breed cooperatively when environmental conditions vary. Further empirical and theoretical work will be required to understand the evolutionary significance of this insight.     

Determining the climate impact of food for use in a climate tax—design of a consistent and transparent model

The International Journal of Life Cycle Assessment - The aim of this study was to determine transparent food carbon footprint values for use in a climate tax, using a consistent methodology across...     

Linking variability in climate to wetland habitat suitability: is it possible to forecast regional responses from simple climate measures?

Wetlands Ecology and Management - Temporary wetlands have value to both ecological and social systems. Interactions between local climate and the surrounding landscape result in patterns of...     

Missing chaos in global climate change data interpreting?

The main problem of ecological data modeling is their interpretation and its correct understanding. This problem cannot be solved solely by a big data collection. To sufficiently understand ecosystems we need to know how these processes behave and how they respond to internal and external factors. Similarly, we need to know the behavior of processes that are involved in the climate system and the biosphere of the earth. In order to characterize precisely the behavior of individual elements and ecosystems we need to use deterministic, stochastic and chaotic behavior. Unfortunately, the chaotic part of systems is typically completely ignored in almost all approaches. Ignoring of chaotical part leads to many biased outcomes. To overcome this gap we model chaotic system behavior by random iterated function system which provides a generic guideline for such data management. This also allows to replicate a complexity and chaos of ecosystem.     

PlantACT! – how to tackle the climate crisis

Greenhouse gas (GHG) emissions have created a global climate crisis which requires immediate interventions to mitigate the negative effects on all aspects of life on this planet. As current agriculture and land use contributes up to 25% of total GHG emissions, plant scientists take center stage in finding possible solutions for a transition to sustainable agriculture and land use. In this article, the PlantACT! (Plants for climate ACTion!) initiative of plant scientists lays out a road map of how and in which areas plant scientists can contribute to finding immediate, mid-term, and long-term solutions, and what changes are necessary to implement these solutions at the personal, institutional, and funding levels.     

El Niño,volcanism, and global climate

The June 1991 eruption of Mt. Pinatubo in the Philippines produced one of the greatest volcanic aerosols in the last hundred years. The estimated net decrease of radiation may have peaked at 10% in the tropics. What was the impact of the Pinatubo aerosol on regional and global climate? Besides the expected net cooling of the average global surface temperature, correlation studies indicate that other types of climate anomalies may also be expected. These include the appearance of an El Niño event, decreased Indian monsoon rainfall, fewer tropical storms in the north Atlantic Ocean in 1991–1993, and normal to above normal winter rainfall in California in 1991/92, all of which were observed. A proposed physical mechanism for the almost-simultaneous occurrence of this constellation of climate anomalies is presented. The results of correlation studies between low-latitude volcanic aerosols and the El Niño/Southern Oscillation are presented in some detail as one example. The correlation between Indian monsoon rainfall and tropical storms in the north Atlantic Ocean is also shown and is updated for the most recent 5 years.     

Plant adaptation to climate change—Where are we?

Climate change poses critical challenges for population persistence in natural communities, for agriculture and environmental sustainability, and for food security. In this review, we discuss recent progress in climatic adaptation in plants. We evaluate whether climate change exerts novel selection and disrupts local adaptation, whether gene flow can facilitate adaptive responses to climate change, and whether adaptive phenotypic plasticity could sustain populations in the short term. Furthermore, we discuss how climate change influences species interactions. Through a more in‐depth understanding of these eco‐evolutionary dynamics, we will increase our capacity to predict the adaptive potential of plants under climate change. In addition, we review studies that dissect the genetic basis of plant adaptation to climate change. Finally, we highlight key research gaps, ranging from validating gene function to elucidating molecular mechanisms, expanding research systems from model species to other natural species, testing the fitness consequences of alleles in natural environments, and designing multifactorial studies that more closely reflect the complex and interactive effects of multiple climate change factors. By leveraging interdisciplinary tools (e.g., cutting‐edge omics toolkits, novel ecological strategies, newly developed genome editing technology), researchers can more accurately predict the probability that species can persist through this rapid and intense period of environmental change, as well as cultivate crops to withstand climate change, and conserve biodiversity in natural systems.     

Can we produce carbon and climate neutral forest bioenergy?

Harvesting branches, stumps and unmercantable tops, in addition to stem wood, decreases the carbon input to the soil and consequently reduces the forest carbon stock. We examine the changes in the forest carbon cycle that would compensate for this carbon loss over a rotation period and lead to carbon neutral forest residue bioenergy systems. In addition, we analyse the potential climate impact of these carbon neutral systems. In a boreal forest, the carbon loss was compensated for with a 10% increase in tree growth or a postponing of final felling for 20 years from 90 to 110 years in one forest rotation period. However, these changes in carbon sequestration did not prevent soil carbon loss. To recover soil carbon stock, a 38% increase in tree growth or a 21% decrease in the decomposition rate of the remaining organic matter was needed. All the forest residue bioenergy scenarios studied had a warming impact on climate for at least 62 years. Nevertheless, the increases in the carbon sequestration from forest growth or reduction in the decomposition rate of the remaining organic matter resulted in a 50% smaller warming impact of forest bioenergy use or even a cooling climate impact in the long term. The study shows that carbon neutral forest residue bioenergy systems have warming climate impacts. Minimization of the forest carbon loss improves the climate impact of forest bioenergy.     

How are climate and marine biological outbreaks functionally linked?

Since the mid-1970s, large-scale episodic events such as disease epidemics, mass mortalities, harmful algal blooms and other population explosions have been occurring in marine environments at an historically unprecedented rate. The variety of organisms involved (host, pathogens and other opportunists) and the absolute number of episodes have also increased during this period. Are these changes coincidental? Between 1972 and 1976, a global climate regime shift took place, and it is manifest most clearly by a change in strength of the North Pacific and North Atlantic pressure systems. Consequences of this regime shift are: (1) prolonged drought conditions in the Sahel region of Africa; (2) increased dust supply to the global atmosphere, by a factor of approximately four; (3) increased easterly trade winds across the Atlantic; (4) increased eolian transport of dust to the Atlantic and Caribbean basins; and (5) increased deposition of iron-rich eolian dust to typically iron-poor marine regions. On the basis of well-documented climate and dust observations and the widely accepted increase in marine outbreak rates, this paper proposes that the increased iron supply has altered the micronutrient factors limiting growth of opportunistic organisms and virulence of pathogenic microbes, particularly in macronutrient-rich coastal systems.