species population UAV OBIS data
Marine megafauna populations are challenging to assess, thanks to their cryptic nature and patchy availability to many forms of remote sensing. The Duke University Marine Robotics and Remote Sensing lab (MaRRS) strives to advance marine wildlife assessment methodology by fusing unoccupied aerial vehicles (UAV), advanced sensor packages and computer vision algorithms. This combination promises to improve the efficiency, economy and safety for surveys that are often tedious and dangerous for those that conduct them in remote parts of the world.
In the spring of 2015, the MaRRS lab conducted surveys over two grey seal breeding colonies in Nova Scotia using a small fixed-wing UAV called an “ebee”, taking pictures of the colonies with standard RGB and thermal cameras mounted in the belly of the aircraft. In the thermal images, seal pups and adults showed up as hot “blips” on a frigid background of ice and frozen earth, presenting an ideal opportunity to compare how humans and automated machine learning approaches detect and count animals in remotely-sensed data. The MaRRS lab computer vision algorithm proved extremely accurate, yielding total seal counts only 2% different than manual counts by humans, even tackling a long-time hurdle in automated detection by consistently discriminating seals within closely packed “piles”.
The above case study is widely applicable to species that seasonally aggregate on land, particularly pinnipeds and colonial seabirds. UAVs, by their very nature, are capable of rapid deployment and can take advantage of temporal windows where weather is good and animals are visible on land. The MaRRS computer vision algorithm operates in the common program ArcMap (ESRI), and is designed for quick modification to apply to other pinnipeds and even entirely different genera. This type of flexible and easily-modifiable model design is critical for practical applications in wildlife management. Algorithm development is time consuming and if time must be taken to extensively retrain a model for each new dataset, many advantages in efficiency are lost over traditional, manual-counting methods.
As UAVs proliferate and more data is collected, analysis becomes a bottleneck for getting relevant information to resource managers and decision makers. Combining UAVs with computer vision is a way to stay ahead of the curve and ensure that big data is an advantage and not a stumbling-block for wildlife management.
In total, 3,355 grey seals were counted in this case study led by Alexander Seymour and his team at the Duke University Marine Laboratory, North Carolina, USA and Fisheries and Oceans Canada. The locations of the identified grey seals are available through the OBIS web site titled “Atlantic grey seal breeding colonies in Hay and Saddle Islands, Nova Scotia” at http://iobis.org/explore/#/dataset/4534. The more detailed information, georeferenced RGB pictures and thermal images are available through the OBIS-SEAMAP web site at http://seamap.env.duke.edu/dataset/1462.
Reference: Seymour, A., Dale, J., Hammill, M., Halpin, P and Johnston, D. 2017. Automated detection and enumeration of marine wildlife using unmanned aircraft systems (UAS) and thermal imagery. Scientific Reports. 7: 45127. https://www.nature.com/articles/srep45127.
species distribution modelling predictor selection OBIS data
Climatological conditions are currently changing at an unprecedented rate and anthropogenic activities displace species out of their native area across the globe. Both processes have the potential to alter biological communities and reduce ecosystem services. Knowing under which environmental conditions species may maintain or establish viable populations therefore is more critical than ever. Species distributions are increasingly modelled for conservation and ecological purposes. A better understanding of mechanisms shap- ing species distributions allows for more accurate predictions of future distributions of species in a rapidly changing world.
Thanks to the availability of an increasing number of online distribution records (e.g., OBIS, GBIF), pre-processed environmental data layers (e.g., WorldClim, Climond, Bio-ORACLE, MARSPEC) and modelling algorithms accessible through various statistical packages, SDM has become a widely applied technique in ecology and conservation biology.
Altough the importance for SDM of selecting biologically relevant predictors, and its impact on model uncertainty and transferability has been highlighted by several studies, to date no comprehensive study on the relevance of the predictors of marine species distributions across taxa has been performed.
In this study, Bosch et al. (2017) created the Marine SPEcies with Environmental Data (MarineSPEED) dataset and used it to: (1) identify the most relevant predictors of marine species distributions and (2) identify which parts of the SDM process impact the relevance of predictors the most.
For MarineSPEED, we selected well-studied and identifiable species from all major marine taxonomic groups. Distribution records were compiled from public sources (e.g., OBIS, GBIF, Reef Life Survey) and linked to environmental data from Bio-ORACLE and MARSPEC. Using this dataset, predictor relevance was analysed under different variations of modelling algorithms, numbers of predictor variables, cross-validation strategies, sampling bias mitigation methods, evaluation methods and ranking methods. SDMs for all combinations of predictors from eight correlation groups were fitted and ranked, from which the top five predictors were selected as the most relevant.
We collected two million distribution records from 514 species across 18 phyla. Mean sea surface temperature and calcite are, respectively, the most relevant and irrelevant predictors. A less clear pattern was derived from the other predictors. The biggest differences in predictor relevance were induced by varying the number of predictors, the modelling algorithm and the sample selection bias correction. The distribution data and associated environmental data are made available through the R package marinespeed and at http://marinespeed.org.
- Bosch S., Tyberghein L., Deneudt K., Hernandez F., & De Clerck O. (2018) In search of relevant predictors for marine species distribution modelling using the MarineSPEED benchmark dataset. Diversity and Distributions, 24. http://dx.doi.org/10.1111/ddi.12668
Biogeography OBIS data
The mesopelagic, or “twilight” zone (open ocean waters between 200 – 1000 m depth), is the world’s second-largest cumulative ecosystem, trailing only the bathypelagic zone (waters > 1000 m depth). In this zone there is not enough sunlight to support photosynthesis (i.e., less than 1% of surface irradiance), but enough light that animals can detect the difference between night and day. The importance of deep-pelagic ecosystems in global ecosystem functioning, such as carbon cycling, is widely acknowledged, but poorly understood. To date less than 1% of this habitat has been sampled, hampering statistical approaches to map its inhabitants on a global scale. A recent paper provides a synthesis of what is known about the distribution of life in the Twilight Zone. Experts integrated available biological data with physical oceanographic spatial modelling to present a biogeographic classification of this massive ecosystem. Thirty-three global ecoregions were identified, of which 20 were truly oceanic, while 13 were ‘distant neritic.’ Each ecoregion harbors a characteristic combination of organisms, with ‘boundaries’ between ecoregions being more like gradients than sharp discontinuities. Each ecoregion is driven by a complex of driving factors, but some of the most important are phytoplankton production in the overlying waters, the presence or absence of oxygen minimum strata, upwelling, and water column stratification. Much work needs to be done to produce a truly dynamic mesopelagic biogeography – huge sections of the World Ocean are still unsampled, and seasonal sampling is rare in all but a few locations. As resource extraction from the deep increases, so too does the need for baseline information to assess human impacts. The proposed mesopelagic classification addresses a standing data gap in global ocean management and conservation efforts.
- Sutton, T.T., M.R. Clark, D.C. Dunn, P.N. Halpin, A.D. Rogers, J. Guinotte, S.J. Bograd, M.V. Angel, J.A.A. Perez, K. Wishner, R.L. Haedrich, D.J. Lindsay, J.C. Drazen, A. Vereshchaka, U. Piatkowski, T. Morato, K. Błachowiak-Samołyk, B.H. Robison, K.M. Gjerde, A. Pierrot-Bults, P. Bernal, G. Reygondeau. and M. Heino (2017) A global biogeographic classification of the mesopelagic zone. Deep Sea Research I 126: 85-102. https://doi.org/10.1016/j.dsr.2017.05.006
species diversity Biological evolution OBIS data
The question of why some groups of animals and plants flourish while others do not has puzzled biologists for centuries. One way to address the question is to look for special features or abilities shared by the successful groups. We know that smaller organisms like insects or bacteria are more diverse than larger organisms (birds, mammals), and that the warmer habitats of the tropics generate more animal and plant diversity than temperate areas.
The ability to eat new foods also helps explain the incredible number of species among the herbivorous insects. Just like insects on land, many crustaceans – the 70,000 species of crabs, lobsters and their relatives – eat plants and seaweeds in the kelp forests and coral reefs in the sea, and in streams and lakes around the world. Some crabs even climb mangrove trees to feed on leaves, and others eat seedlings from the rainforest floor.
Poore et al. (2017) showed that the ability to eat seaweeds and plants promotes diversity among crustaceans, just as it does among herbivorous insects. To do this, they examined the evolutionary tree of crustaceans and found animals eating plants in at least 31 different lineages. Then, to test whether plant-feeding promotes diversity, they compared the number of species in each plant-feeding group with their nearest relatives. These sister comparisons showed that the herbivores had, on average, 21 times more species than their nearest relatives - crustaceans eating live animals, microbes or decaying organic material. The geographic distributions of plant-feeding and sister taxa were analysed to examine whether shifts to plant feeding have facilitated increases in range size and to test the likelihood of contrasts in richness being confounded by possible regional differences in richness (latitude, biogeographic regions). The records from OBIS for each clade were analysed to estimate range size, latitudinal range and the occurrence in the biogeographic realms of Spalding et al. (2007). These analyses detected that plant-feeding clades did, on average, have larger range sizes, and that the increases in their richness could not be explained by disproportionate sampling in the tropics or in certain biogeographic regions.
- Poore, AGB, ST Ahyong, JK Lowry and EE Sotka. 2017. Plant feeding is associated with high species richness in the Crustacea. Proceedings of the National Academy of Sciences, USA. 114: 8829–8834. http://dx.doi.org/10.1073/pnas.1706399114
- Spalding MD et al. (2007) Marine ecoregions of the world: A bioregionalization of coastal and shelf areas. Bioscience 57: 573–583.
species distributions OBIS data
Early explorers classified the land into “biogeographic” realms based on their distinctive fauna and flora. On land the contrast was obvious – kiwi in New Zealand and kangaroos in Australia, for example – but the ocean realm was different. Experts doubted whether distinct biogeographic boundaries existed in the oceans, partly because for species like whales, birds, and large fish, the whole ocean is their habitat. Before OBIS existed it was too difficult and expensive to collate the tens of thousands of species distribution records from many thousands of publications, specimen collections’, and unpublished sources to test this. Now, using cluster analysis of species distributions in OBIS, 30 distinct realms have been identified, of which two are largely freshwater (Baltic and Black Seas).Two-thirds of all realms were coastal, because the coastal environment is less stable and more variable. Because the offshore and deep-sea areas offer similar environmental conditions over much larger areas the species there have larger geographic ranges; thus offshore realms are larger than coastal. The most widespread species in the ocean were the smallest and largest; the microscopic plankton that drift until they find suitable conditions for growth, and the whales, birds, turtles, and large fish “megafauna” that travel across the oceans. In addition to improved understanding of ocean biogeography, these new maps will have practical use for conservation planning (each realm should have a network of Marine Reserves), and reporting on ocean trends (by definition each realm is unique and so needs separate surveillance).
- Costello, M.J.; Tsai, P.; Wong, P.S.; Cheung, A.K.L.; Basher, Z.; Chaudhary, C. (2017). Marine biogeographic realms and species endemicity. Nature Comm. 8(1): 1057. https://hdl.handle.net/10.1038/s41467-017-01121-2
species distribution OBIS data
Costello & Chaudhary (2017) used data from OBIS to show that marine species richness is higher in the coastal tropics and decreases with depth. The paper reviews what factors have led to species diversification, and how this knowledge informs conservation priorities.
Two representations of species richness were compared to sea surface temperature and productivity. To minimise sampling effort bias, Estimated Species richness (ES50) was calculated as the number of species in 50 random samples from each 5 degree latitude-longitude cell derived from a dataset of 65,000 species distributions from OBIS in 2009 and equal area hexagons from 51,670 species from OBIS in 2015.
Four measures of species richness calculated from the above hexagons, and sea temperature, were plotted with depth. Species richness, calculated for 32,328 species with known depth of occurrence, for 50,000 km2 hexagrids in the depth range 0 – 500 m (interval of 100) and 500 – 9,000 m (interval of 500).
For environmental data see http://gmed.auckland.ac.nz/.
Details in: Costello MJ, Chaudhary C. 2017. Marine biodiversity, biogeography, deep-sea gradients, and conservation. Current Biology 27, R511–R527. http://dx.doi.org/10.1016/j.cub.2017.04.060
species distribution OBIS data
A global analysis of the biogeography of species richness in razor clams (Solenidae) found the number of species was highest in the northern hemisphere, and dipped at the equator with a smaller peak in the southern hemisphere (Saeedi et al. 2016). Thus Chaudhary et al. (2016) reviewed previous studies and found that almost all latitudinal gradients in marine species richness peaked in the northern hemisphere, with a smaller southern hemisphere peak, and dip at the equator. This contradicted the prevailing paradigm that biodiversity peaks at the equator. A response to this paper suggested that the pattern could be affected by sampling bias (Fernandez and Marques 2016). Thus Chaudhary et al. (2017) used data from OBIS to show that indeed sampling bias influenced the gradient. However, this effect was reduced when using gamma (total species in a latitudinal band) over alpha (average species in latitude-longitude cells in a latitudinal band). Furthermore, when adjusted for sampling effort using ES50 index, the pattern was still bimodal with a dip at the equator, but the peaks in richness were equal in both hemispheres. The authors suggest that this may be because temperature is the main cause of the gradient and is getting too hot at the equator for some species.
These analyses would not have been possible without the integration of data across all taxa and geographic locations by OBIS (the full list of resources used is available in supplement info).
- Saeedi, H, Dennis TE, Costello MJ. 2016. Bimodal latitudinal species richness and high endemicity in razor clams (Mollusca). Journal of Biogeography, online. DOI: http://dx.doi.org/10.1111/jbi.12903
- Chaudhary C., Saeedi H., Costello MJ. 2016. Bimodality of latitudinal gradients in marine species richness. Trends in Ecology and Evolution, 31 (9), 670-676. DOI: http://dx.doi.org/10.1016/j.tree.2016.06.001
- Fernandez, M.O. and Marques, A.C. 2016. Diversity of diversities: a response to Chaudhary, Saeedi, and Costello. Trends Ecol. Evol. Published online November 26 2016. http://dx.doi.org/10.1016/j.tree.2016.10.013
- Chaudhary C., Saeedi H., Costello MJ. 2017. Marine Species Richness Is Bimodal with Latitude: A Reply to Fernandez and Marques. Trends in Ecology and Evolution, 31 DOI: http://dx.doi.org/10.1016/j.tree.2017.02.007
Some like it warm? Warm-dwelling species have increased in response to climate change in western/central Europe
Climate Change species abundance OBIS data
The effect of climate change on population abundances are less studied than those on species ranges. This is partly because population abundance data are harder to obtain. Nonetheless, abundance is an interesting variable to study. A species may change in abundance before there are changes in its range; therefore, we may detect climate change impacts on abundance that are not apparent if we just look at range edges. The aim of our study was to study the impacts of climate change on long-term abundance trends, using a broad range of species from all environmental realms. We included time-series data from 22 different communities since the 1980s, including 6 marine datasets collected from the North Sea (phytoplankton, benthic invertebrates and fish). Our test was based on the prediction that warm-adapted species should increase (or decrease less) than cold-adapted ones within each community under climate change. We used the population data to estimate species’ population trends and compiled distribution data (e.g., from GBIF and OBIS) to estimate species’ temperature preferences. We found a mixture of population trends in almost all datasets: many species have decreased, but many species have also increased. On average, temperature preference was positively related to population trends. Although some of the cold-adapted terrestrial species had decreased, more commonly warm-adapted terrestrial species had increased. We found weaker relationships in the marine and freshwater datasets although warm-dwelling marine fish have increased. Attributing changes in species’ abundance to particular drivers is tricky because populations are exposed to many drivers at the same time. By relating population trends to species characteristics (temperature preferences), we show how it is possible to detect the particular effects of climate change on species’ abundances, and how this is useful for comparative analysis of climate change impacts across environmental realms.
Full reference: Diana E. Bowler, Christian Hof, Peter Haase, Ingrid Kröncke, Oliver Schweiger, Rita Adrian, Léon Baert, Hans-Günther Bauer, Theo Blick, Rob W. Brooker, Wouter Dekoninck, Sami Domisch, Reiner Eckmann, Frederik Hendrickx, Thomas Hickler, Stefan Klotz, Alexandra Kraberg, Ingolf Kühn, Silvia Matesanz, Angelika Meschede, Hermann Neumann, Robert O’Hara, David J. Russell, Anne F. Sell, Moritz Sonnewald, Stefan Stoll, Andrea Sundermann, Oliver Tackenberg, Michael Türkay, Fernando Valladares, Kok van Herk, Roel van Klink, Rikjan Vermeulen, Karin Voigtländer, Rüdiger Wagner, Erik Welk, Martin Wiemers, Karen H. Wiltshire & Katrin Böhning-Gaese. 2017. Cross-realm assessment of climate change impacts on species’ abundance trends. Nature Ecology & Evolution 1: 0067 (doi:10.1038/s41559-016-0067)
species distributions OBIS data
Species abundance distributions (SADs) depict the relative abundance of the species present in a community and describe one of the most fundamental patterns of species diversity. In our recent study, we analysed over 100 datasets covering different taxa and habitats, and showed that c. 15% of the SADs were multimodal with strong support, indicating that multimodality is a more common pattern than currently appreciated. We also showed that this pattern is more prevalent for communities encompassing broader spatial scales or greater taxonomic diversity, suggesting that multimodality increases with ecological heterogeneity. Our results emphasize the need for macroecological theories to include multimodality in the range of SADs they predict. Furthermore, differences in SAD shape across different scales provide important insights into the current endeavour of biodiversity scaling. OBIS was an invaluable source of high quality data, including metadata, from where we retrieved 25 datasets that met our selection criteria. Being able to access the data in a centralized repository was instrumental in terms of gathering appropriate data in a timely manner.
Prevalence of multimodal species abundance distributions is linked to spatial and taxonomic breadth. Laura Henriques Antão, Sean R. Connolly, Anne E. Magurran, Amadeu Soares & Maria Dornelas. Global Ecology and Biogeography, 2016. DOI: 10.1111/geb.12532
species composition biodiversity change
The extent to which biodiversity change in local assemblages contributes to global biodiversity loss is poorly understood. 100 time series from biomes across Earth were analysed to see how diversity within assemblages is changing through time. They quantified patterns of temporal alpha diversity, measured as change in local diversity, and temporal beta diversity, measured as change in community composition. Contrary to their expectations, they did not detect systematic loss of a diversity. However, community composition changed systematically through time, in excess of predictions from null models. Heterogeneous rates of environmental change, species range shifts associated with climate change, and biotic homogenization may explain the different patterns of temporal alpha and beta diversity. Monitoring and understanding change in species composition should be a conservation priority.
This study, which appeared in Science, used 80 time series datasets from OBIS.
Dornelas, M.; Gotelli, N.J.; McGill, B.; Shimadzu, H.; Moyes, F.; Sievers, C.; Magurran, A.E. (2014). Assemblage time series reveal biodiversity change but not systematic loss. Science (Wash.) 344: 296-299. DOI 10.1126/science.1248484
ophiuroids deep sea
The deep ocean is the largest and least-explored ecosystem on Earth, and a uniquely energy-poor environment. The distribution, drivers and origins of deep-sea biodiversity remain unknown at global scales. Here we analyse a database of more than 165,000 distribution records of Ophiuroidea (brittle stars), a dominant component of sea-floor fauna, and find patterns of biodiversity unlike known terrestrial or coastal marine realms. Both patterns and environmental predictors of deep-sea (2,000–6,500m) species richness fundamentally differ from those found in coastal (0–20m), continental shelf (20–200m), and upper-slope (200–2,000m) waters. Continental shelf to upper-slope richness consistently peaks in tropical Indo-west Pacific and Caribbean (0–30°) latitudes, and is well explained by variations in water temperature. In contrast, deep-sea species show maximum richness at higher latitudes (30–50°), concentrated in areas of high carbon export flux and regions close to continental margins. We reconcile this structuring of oceanic biodiversity using a species–energy framework, with kinetic energy predicting shallow-water richness, while chemical energy (export productivity) and proximity to slope habitats drive deep-sea diversity. Our findings provide a global baseline for conservation efforts across the sea floor, and demonstrate that deep-sea ecosystems show a biodiversity pattern consistent with ecological theory, despite being different from other planetary-scale habitats.
ocean acidification pteropods
Pteropods, also called sea butterflies, are tiny snails living in the water column that play a critical role in various ecosystems as prey for a variety of predators. There is a great concern about the potential impact of global change – and particularly ocean acidification – on these organisms as they exhibit an external shell, which is sensitive to changes in ocean chemistry. To represent the impact of both ocean acidification and global warming on pteropods, risk indicators have been calculated for three widely spread taxa that are dominant in high latitudes (Limacina helicina), temperate (Limacina retroversa), and warm waters (Creseis spp.). To create the indicators, experimental and observational data on pteropods’ response to global change were coupled with models describing chemical (aragonite saturation state) and physical (temperature) conditions of the ocean at present, in 2030 and 2050, under the “business as usual” carbon dioxide (CO2) emission scenario (RCP 8.5) and the “two degree stabilization” CO2 emission scenario (RCP 4.5). The present results confirm that global change is a very serious threat for high latitude pteropods: by 2050 under the CO2 emissions scenario RCP 8.5, they likely will not be able to thrive in most of the Arctic Ocean and some regions of the Southern Ocean.
OBIS SEAMAP cetaceans
Cetaceans are protected worldwide but vulnerable to incidental harm from an expanding array of human activities at sea. Managing potential hazards to these highly-mobile populations increasingly requires a detailed understanding of their seasonal distributions and habitats. Pursuant to the urgent need for this knowledge for the U.S. Atlantic and Gulf of Mexico, we integrated 23 years of aerial and shipboard cetacean surveys, linked them to environmental covariates obtained from remote sensing and ocean models, and built habitat-based density models for 26 species and 3 multi-species guilds using distance sampling methodology.