Advances in Monitoring and Modelling Climate at Ecologically Relevant Scales

Bramer, Isobel; Anderson, Barbara J.; Bennie, Jonathan; Bladon, Andrew J.; Frenne, Pieter De; Hemming, Deborah; Hill, Ross A.; Kearney, Michael R.; Körner, Christian; Korstjens, Amanda H.; Lenoir, Jonathan; Maclean, Ilya M. D.; Marsh, Christopher; Morecroft, Michael D.; Ohlemüller, Ralf; Slater, Helen; Suggitt, Andrew J.; Zellweger, Florian; Gillingham, Phillipa K.

doi:10.1016/bs.aecr.2017.12.005

Cited by 218 publications

(287 citation statements)

References 178 publications

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“…Miniature data-loggers can provide high-resolution measurements of surface, soil and air temperatures, with the major advantage that conditions can be measured where they are expected to be ecologically most relevant to living organisms (Rae et al 2006, Ashcroft et al 2008, Bramer et al 2018. Small sensors can even be attached to the organisms themselves to obtain temperature information at the level of the study object (Potter et al 2013).…”

Section: In-situ Measurementsmentioning

confidence: 99%

“…However, a drawback of microclimate data from in-situ loggers lies in the short temporal extent (Table 1). The use of such loggers over large geographic extents is also still limited by the cost (Lenoir et al 2013), despite the increasing availability of small, relatively cheap and robust temperature sensors (Bramer et al 2018). To improve the accuracy of SDMs, the high spatial and temporal accuracy of these in-situ measurements will need to be combined with long-term records, either by maintaining loggers in the field over periods of several years or by coupling these loggers with historical data from the long-established networks of national weather stations.…”

Section: In-situ Measurementsmentioning

confidence: 99%

“…The most common strategy is to work with a set of bioclimatic variables at 30 arc-second resolution (ca 1 km at the equator) or coarser (Hijmans et al 2005, Warren et al 2008, Sears et al 2011, Slavich et al 2014, Gonzalez-Moreno et al 2015 which usually represent freeair conditions averaged over 30 yr or more. in mountains, forests or cities) (Bramer et al 2018). Differences between macro-and microclimate are expected to be particularly pronounced where habitat includes a vertical dimension with significant variation along it, originating from either biotic, abiotic or human-made features (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…In cities, the urban heat island (UHI) effect results in higher air and surface temperatures than in rural surroundings, especially at night (Grimm et al 2008). In general, temperature variation occurs at multiple scales, from the smallest boundary layer of air to the landscape level (Pincebourde et al 2016, Bramer et al 2018. The UHI effect results from the interaction between the vertical use of space (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Another use of microclimatic data lies in the assessment of stepping stones, referring to areas with favourable microclimates that facilitate species' range shifts, e.g. free-air conditions) and the apparent microclimatic conditions that living organisms experience has only recently been acknowledged in SDMs (Dobrowski 2011, Pradervand et al 2014, Slavich et al 2014), yet considerable progress in tackling this problem has been made and has produced improvements in SDM predictions (Ashcroft et al 2008, Dobrowski 2011, Pradervand et al 2014, Slavich et al 2014, Meineri and Hylander 2017, Bramer et al 2018). Such stepping stones can exist in mountain environments (Lembrechts et al 2018), yet the urban matrix can also act as such for the poleward expansion of both heat-loving native and non-native species (Menke et al 2011). This mismatch between how we traditionally use climate (cf.…”

Section: Introductionmentioning

confidence: 99%

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Incorporating microclimate into species distribution models

2018

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Ecography E4 awardSpecies distribution models (SDMs) have rapidly evolved into one of the most widely used tools to answer a broad range of ecological questions, from the effects of climate change to challenges for species management. Current SDMs and their predictions under anthropogenic climate change are, however, often based on free-air or synoptic temperature conditions with a coarse resolution, and thus fail to capture apparent temperature (cf. microclimate) experienced by living organisms within their habitats. Yet microclimate operates as soon as a habitat can be characterized by a vertical component (e.g. forests, mountains, or cities) or by horizontal variation in surface cover. The mismatch between how we usually express climate (cf. coarse-grained free-air conditions) and the apparent microclimatic conditions that living organisms experience has only recently been acknowledged in SDMs, yet several studies have already made considerable progress in tackling this problem from different angles. In this review, we summarize the currently available methods to obtain meaningful microclimatic data for use in distribution modelling. We discuss the issue of extent and resolution, and propose an integrated framework using a selection of appropriatelyplaced sensors in combination with both the detailed measurements of the habitat 3D structure, for example derived from digital elevation models or airborne laser scanning, and the long-term records of free-air conditions from weather stations. As such, we can obtain microclimatic data with a relevant spatiotemporal resolution and extent to dynamically model current and future species distributions.

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Section: In-situ Measurementsmentioning

confidence: 99%

Section: In-situ Measurementsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Incorporating microclimate into species distribution models

2018

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Arduinos in the wild: A novel, low‐cost sensor network for high‐resolution microclimate monitoring in remote ecosystems

Mühlbauer,

Zavattoni,

Virtanen

et al. 2023

Ecol Sol and Evidence

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The importance of microclimate conditions is becoming increasingly recognised in ecological research, especially as they can differ widely from macro‐ and mesoclimate. Effective measurement of microclimate variability in heterogeneous field conditions requires measurements from a large number of sensors, ideally sampling across both small and large scales, which necessitates the development of cost‐effective sensor networks. Here, we develop an environmental microcontroller (EMU) sensor network for measuring soil moisture and temperature with high spatiotemporal coverage. The system can easily be implemented in larger or smaller setups, though our study consisted of 40 plots distributed across 4 sites in northern Lapland. Using 40 EMUs, each equipped with 10 soil temperature and 10 soil moisture sensors, we collected roughly 3.5 million unique soil temperature and moisture records over the course of about 2 months. We then compared these measurements to those from commercial temperature sensors (iButtons) and TDR soil moisture probes. We show that our sensor network is able to successfully characterise microclimate variation at the site, plot and within‐plot scales with high accuracy and good reliability. Moreover, even including development costs, the total price per EMU unit was less than €100, yielding a much cheaper and higher resolution system than is currently available from commercial producers. For both temperature and soil moisture, we found a strong relationship between the sensor network measurement and those obtained from commercial systems. Roughly 10% of the overall spatial variation in temperature and moisture occurred within plots—that is. over the scale of 25–50 cm. Our results show that accurate measurements of microclimate soil temperature and soil moisture can be obtained using low‐cost sensor networks. We also show that microclimate variability at small scales can make up a considerable fraction of total environmental variability. To this end, we discuss some of the difficulties encountered during the development process and suggest possible improvements for further studies. While the sensor network described here can be applied without any modifications for quantifying topsoil conditions, we note that with minor changes to our code and hardware, the system can be customised for other kinds of measurements.

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Community turnover by composition and climatic affinity across scales in an alpine system

Smithers

Oldfather

Koontz

et al. 2019

American J of Botany

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Premise Examining community turnover across climate gradients at multiple scales is vital to understanding biogeographic response to climate change. This approach is especially important for alpine plants in which the relative roles of topographic complexity and nonclimatic or stochastic factors vary across spatial scales. Methods We examined the structure of alpine plant communities across elevation gradients in the White Mountains, California. Using community climatic niche means (CCNMs) and measures of community dissimilarity, we explored the relation between community composition and elevation gradients at three scales: the mountain range, individual peaks, and within elevation contours. Results At the mountain range scale, community turnover and CCNMs showed strongly significant relations with elevation, with an increase in the abundance of cooler and wetter‐adapted species at higher elevations. At the scale of single peaks, we found weak and inconsistent relations between CCNMs and elevation, but variation in community composition explained by elevation increased. Within the elevation contours, the range of CCNMs was weakly positively correlated with turnover in species identity, likely driven by microclimate and other site‐specific factors. Conclusions Our results suggest that there is strong environmental sorting of alpine plant communities at broad scales, but microclimatic and site‐specific, nonclimatic factors together shape community turnover at finer scales. In the context of climate change, our results imply that community–climate relations are scale‐dependent, and predictions of local alpine plant range shifts are limited by a lack of topoclimatic and habitat information.

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Advances in Monitoring and Modelling Climate at Ecologically Relevant Scales

Cited by 218 publications

References 178 publications

Incorporating microclimate into species distribution models

Incorporating microclimate into species distribution models

Arduinos in the wild: A novel, low‐cost sensor network for high‐resolution microclimate monitoring in remote ecosystems

Community turnover by composition and climatic affinity across scales in an alpine system

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