| 1. |
- Potapov, Anton M., et al.
(författare)
-
Global fine-resolution data on springtail abundance and community structure
- 2024
-
Ingår i: Scientific Data. - : Nature Publishing Group. - 2052-4463. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- Springtails (Collembola) inhabit soils from the Arctic to the Antarctic and comprise an estimated ~32% of all terrestrial arthropods on Earth. Here, we present a global, spatially-explicit database on springtail communities that includes 249,912 occurrences from 44,999 samples and 2,990 sites. These data are mainly raw sample-level records at the species level collected predominantly from private archives of the authors that were quality-controlled and taxonomically-standardised. Despite covering all continents, most of the sample-level data come from the European continent (82.5% of all samples) and represent four habitats: woodlands (57.4%), grasslands (14.0%), agrosystems (13.7%) and scrublands (9.0%). We included sampling by soil layers, and across seasons and years, representing temporal and spatial within-site variation in springtail communities. We also provided data use and sharing guidelines and R code to facilitate the use of the database by other researchers. This data paper describes a static version of the database at the publication date, but the database will be further expanded to include underrepresented regions and linked with trait data.
|
|
| 2. |
- Prager, Case M., et al.
(författare)
-
Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment : An example from the WaRM Network
- 2022
-
Ingår i: Ecology and Evolution. - : John Wiley & Sons. - 2045-7758. ; 12:10
-
Tidskriftsartikel (refereegranskat)abstract
- A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities.
|
|
| 3. |
- Alison, Jamie, et al.
(författare)
-
Deep learning to extract the meteorological by-catch of wildlife cameras
- 2024
-
Ingår i: Global Change Biology. - 1354-1013 .- 1365-2486. ; 30:1
-
Tidskriftsartikel (refereegranskat)abstract
- Microclimate—proximal climatic variation at scales of metres and minutes—can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors such as sunshine, hail and snow. Meanwhile, remote cameras have become a primary tool to monitor wild plants and animals, even at micro-scales, and deep learning tools rapidly convert images into ecological data. However, deep learning applications for wildlife imagery have focused exclusively on living subjects. Here, we identify an overlooked opportunity to extract latent, ecologically relevant meteorological information. We produce an annotated image dataset of micrometeorological conditions across 49 wildlife cameras in South Africa's Maloti-Drakensberg and the Swiss Alps. We train ensemble deep learning models to classify conditions as overcast, sunshine, hail or snow. We achieve 91.7% accuracy on test cameras not seen during training. Furthermore, we show how effective accuracy is raised to 96% by disregarding 14.1% of classifications where ensemble member models did not reach a consensus. For two-class weather classification (overcast vs. sunshine) in a novel location in Svalbard, Norway, we achieve 79.3% accuracy (93.9% consensus accuracy), outperforming a benchmark model from the computer vision literature (75.5% accuracy). Our model rapidly classifies sunshine, snow and hail in almost 2 million unlabelled images. Resulting micrometeorological data illustrated common seasonal patterns of summer hailstorms and autumn snowfalls across mountains in the northern and southern hemispheres. However, daily patterns of sunshine and shade diverged between sites, impacting daily temperature cycles. Crucially, we leverage micrometeorological data to demonstrate that (1) experimental warming using open-top chambers shortens early snow events in autumn, and (2) image-derived sunshine marginally outperforms sensor-derived temperature when predicting bumblebee foraging. These methods generate novel micrometeorological variables in synchrony with biological recordings, enabling new insights from an increasingly global network of wildlife cameras.
|
|
| 4. |
- Chen, Hui, et al.
(författare)
-
Lidar as a Potential Tool for Monitoring Migratory Insects : A Field Case Study in Sweden
- 2024
-
Ingår i: iScience. - 2589-0042. ; 27:5
-
Tidskriftsartikel (refereegranskat)abstract
- The seasonal migrations of insects involve a substantial displacement of biomass with significant ecological and economic consequences for regions of departure and arrival. Remote sensors have played a pivotal role in revealing the magnitude and general direction of bioflows above 150 m. Nevertheless, the take-off and descent activity of insects below this height is poorly understood. Our lidar observations elucidate the low-height dusk movements and detailed information of insects in southern Sweden from May to July, during the yearly northward migration period. Importantly, by filtering out moths from other insects based on optical information and wing beat frequency, we have introduced a promising new method to monitor the flight activities of nocturnal moths near the ground, many of which participate in migration through the area. Lidar thus holds the potential to enhance the scientific understanding of insect migratory behaviour and improve pest control strategies.
|
|
| 5. |
- Kropp, Heather, et al.
(författare)
-
Shallow soils are warmer under trees and tall shrubs across Arctic and Boreal ecosystems
- 2021
-
Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 16:1
-
Tidskriftsartikel (refereegranskat)abstract
- Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (>40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.
|
|
| 6. |
- Lindén, Elin, et al.
(författare)
-
Circum-Arctic distribution of chemical anti-herbivore compounds suggests biome-wide trade-off in defence strategies in Arctic shrubs
- 2022
-
Ingår i: Ecography. - : John Wiley & Sons. - 0906-7590 .- 1600-0587. ; :11
-
Tidskriftsartikel (refereegranskat)abstract
- Spatial variation in plant chemical defence towards herbivores can help us understand variation in herbivore top–down control of shrubs in the Arctic and possibly also shrub responses to global warming. Less defended, non-resinous shrubs could be more influenced by herbivores than more defended, resinous shrubs. However, sparse field measurements limit our current understanding of how much of the circum-Arctic variation in defence compounds is explained by taxa or defence functional groups (resinous/non-resinous). We measured circum-Arctic chemical defence and leaf digestibility in resinous (Betula glandulosa, B. nana ssp. exilis) and non-resinous (B. nana ssp. nana, B. pumila) shrub birches to see how they vary among and within taxa and functional groups. Using liquid chromatography–mass spectrometry (LC–MS) metabolomic analyses and in vitro leaf digestibility via incubation in cattle rumen fluid, we analysed defence composition and leaf digestibility in 128 samples from 44 tundra locations.We found biogeographical patterns in anti-herbivore defence where mean leaf triterpene concentrations and twig resin gland density were greater in resinous taxa and mean concentrations of condensing tannins were greater in non-resinous taxa. This indicates a biome-wide trade-off between triterpene- or tannin-dominated defences. However, we also found variations in chemical defence composition and resin gland density both within and among functional groups (resinous/non-resinous) and taxa, suggesting these categorisations only partly predict chemical herbivore defence. Complex tannins were the only defence compounds negatively related to in vitro digestibility, identifying this previously neglected tannin group as having a potential key role in birch anti-herbivore defence.We conclude that circum-Arctic variation in birch anti-herbivore defence can be partly derived from biogeographical distributions of birch taxa, although our detailed mapping of plant defence provides more information on this variation and can be used for better predictions of herbivore effects on Arctic vegetation.
|
|
| 7. |
- Prevéy, Janet S., et al.
(författare)
-
The tundra phenology database: more than two decades of tundra phenology responses to climate change
- 2022
-
Ingår i: Arctic Science. - : Canadian Science Publishing. - 2368-7460. ; 8:3, s. 1026-1039
-
Tidskriftsartikel (refereegranskat)abstract
- Observations of changes in phenology have provided some of the strongest signals of the effects of climate change on terrestrial ecosystems. The International Tundra Experiment (ITEX), initiated in the early 1990s, established a common protocol to measure plant phenology in tundra study areas across the globe. Today, this valuable collec-tion of phenology measurements depicts the responses of plants at the colder extremes of our planet to experimental and ambient changes in temperature over the past decades. The database contains 150 434 phenology observations of 278 plant species taken at 28 study areas for periods of 1–26 years. Here we describe the full data set to increase the visibility and use of these data in global analyses and to invite phenology data contributions from underrepresented tundra locations. Portions of this tundra phenology database have been used in three recent syntheses, some data sets are expanded, others are from entirely new study areas, and the entirety of these data are now available at the Polar Data Catalogue (https://doi.org/10.21963/13215).
|
|
| 8. |
- Rysgaard, Søren, et al.
(författare)
-
A mobile observatory powered by sun and wind for near real time measurements of atmospheric, glacial, terrestrial, limnic and coastal oceanic conditions in remote off-grid areas
- 2022
-
Ingår i: HardwareX. - : Elsevier BV. - 2468-0672. ; 12
-
Tidskriftsartikel (refereegranskat)abstract
- Climate change is rapidly altering the Arctic environment. Although long-term environmental observations have been made at a few locations in the Arctic, the incomplete coverage from ground stations is a main limitation to observations in these remote areas. Here we present a wind and sun powered multi-purpose mobile observatory (ARC-MO) that enables near real time measurements of air, ice, land, rivers, and marine parameters in remote off-grid areas. Two test units were constructed and placed in Northeast Greenland where they have collected data from cabled and wireless instruments deployed in the environment since late summer 2021. The two units can communicate locally via WiFi (units placed 25 km apart) and transmit near-real time data globally over satellite. Data are streamed live and accessible from (https://gios.org). The cost of one mobile observatory unit is c. 304.000€. These test units demonstrate the possibility for integrative and automated environmental data collection in remote coastal areas and could serve as models for a proposed global observatory system.
|
|
