1
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Schmid K, Keppeler FW, da Silva FRM, da Silva Santos JH, Franceschini S, Brodersen J, Russo T, Harvey E, Reis-Filho JA, Giarrizzo T. Use of long-term underwater camera surveillance to assess the effects of the largest Amazonian hydroelectric dam on fish communities. Sci Rep 2024; 14:22366. [PMID: 39333691 PMCID: PMC11436748 DOI: 10.1038/s41598-024-70636-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 08/20/2024] [Indexed: 09/29/2024] Open
Abstract
The increase in the construction of mega dams in tropical basins is considered a threat to freshwater fish diversity. Although difficult to detect in conventional monitoring programs, rheophilic species and those reliant on shallow habitats comprise a large proportion of fish diversity in tropical basins and are among the most sensitive species to hydropower impacts. We used Baited Remote Underwater Video (BRUV), an innovative, non-invasive sampling technique, to record the impacts caused by Belo Monte, the third largest hydropower project in the world, on fishes inhabiting fast waters in the Xingu River. BRUV were set in a river stretch of ~ 240 km for 7 years, 2 before and 5 after the Belo Monte operation. We explored the spatial and temporal variation in fish diversity (α, β, and γ) and abundance (MaxN) using generalized additive models. We also investigated the variation of environmental variables and tested how much information we gained by including them in the diversity and abundance models. Belo Monte altered the flow regime, water characteristics, and fishery yield in the Xingu, resulting in changes in the fish community structure. Temporally, we observed sharp declines in α diversity and abundance, far exceeding those from a previous study conducted with more conventional sampling methods (i.e., catch-based) in the region. γ-diversity was also significantly reduced, but we observed a non-expected increase in β diversity over time. The latter may be associated with a reduction in river connectivity and an increase in environmental heterogeneity among river sectors. Unexpected signs of recovery in diversity metrics were observed in the last years of monitoring, which may be associated with the maintenance of flow levels higher than those previously planned. These results showed that BRUV can be a useful and sensitive tool to monitor the impacts of dams and other enterprises on fish fauna from clear-water rivers. Moreover, this study enhances our comprehension of the temporal variations in freshwater fish diversity metrics and discusses the prevalent assumption that a linear continuum in fish-structure damage associated with dam impoundments may exhibit temporal non-linearity.
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Affiliation(s)
- Kurt Schmid
- Aquatic Ecology Group, Federal University of Pará (UFPA), Belém, PA, Brazil
- Department of Fish Ecology and Evolution, Swiss Federal Institute of Aquatic Science and Technology-Eawag, Kastanienbaum, Switzerland
- Thurgau Hunting and Fishing Administration, Frauenfeld, Switzerland
| | - Friedrich Wolfgang Keppeler
- Aquatic Ecology Group, Federal University of Pará (UFPA), Belém, PA, Brazil
- Núcleo de Ecologia Aquática e Pesca da Amazônia, Federal University of Pará, Belém, Brazil
- Civil Engineering Department, Federal University of Rio Grande do Norte, Campus Universitário Lagoa Nova, Natal, Brazil
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
| | | | | | - Simone Franceschini
- Hawai'i Institute of Marine Biology, University of Hawai'i at Mānoa, Honolulu, HI, USA
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
| | - Jakob Brodersen
- Department of Fish Ecology and Evolution, Swiss Federal Institute of Aquatic Science and Technology-Eawag, Kastanienbaum, Switzerland
| | - Tommaso Russo
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
| | - Euan Harvey
- Civil Engineering Department, Federal University of Rio Grande do Norte, Campus Universitário Lagoa Nova, Natal, Brazil
| | - José Amorim Reis-Filho
- Aquatic Ecology Group, Federal University of Pará (UFPA), Belém, PA, Brazil.
- Programa de Pós-Graduação em Ecologia: Teoria, Aplicação e Valores, Federal University of Bahia (UFBA), Salvador, BA, Brazil.
- Marine Sciences Laboratory-LABOMAR, Federal University of Ceará, Fortaleza, CE, Brazil.
- Department of Biology, University of Rome Tor Vergata, Rome, Italy.
| | - Tommaso Giarrizzo
- Aquatic Ecology Group, Federal University of Pará (UFPA), Belém, PA, Brazil
- Marine Sciences Laboratory-LABOMAR, Federal University of Ceará, Fortaleza, CE, Brazil
- Department of Biology, University of Rome Tor Vergata, Rome, Italy
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2
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Ahmed MS, Hanley BJ, Mitchell CI, Abbott RC, Hollingshead NA, Booth JG, Guinness J, Jennelle CS, Hodel FH, Gonzalez-Crespo C, Middaugh CR, Ballard JR, Clemons B, Killmaster CH, Harms TM, Caudell JN, Benavidez Westrich KM, McCallen E, Casey C, O'Brien LM, Trudeau JK, Stewart C, Carstensen M, McKinley WT, Hynes KP, Stevens AE, Miller LA, Cook M, Myers RT, Shaw J, Tonkovich MJ, Kelly JD, Grove DM, Storm DJ, Schuler KL. Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning. Sci Rep 2024; 14:14373. [PMID: 38909151 PMCID: PMC11193737 DOI: 10.1038/s41598-024-65002-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 06/15/2024] [Indexed: 06/24/2024] Open
Abstract
Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively impacts populations, erodes wildlife conservation, drains resource dollars, and challenges wildlife management agencies. Risk factors for CWD have been investigated at state scales, but a regional model to predict locations of new infections can guide increasingly efficient surveillance efforts. We predicted CWD incidence by county using CWD surveillance data depicting white-tailed deer (Odocoileus virginianus) in 16 eastern and midwestern US states. We predicted the binary outcome of CWD-status using four machine learning models, utilized five-fold cross-validation and grid search to pinpoint the best model, then compared model predictions against the subsequent year of surveillance data. Cross validation revealed that the Light Boosting Gradient model was the most reliable predictor given the regional data. The predictive model could be helpful for surveillance planning. Predictions of false positives emphasize areas that warrant targeted CWD surveillance because of similar conditions with counties known to harbor CWD. However, disagreements in positives and negatives between the CWD Prediction Web App predictions and the on-the-ground surveillance data one year later underscore the need for state wildlife agency professionals to use a layered modeling approach to ensure robust surveillance planning. The CWD Prediction Web App is at https://cwd-predict.streamlit.app/ .
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Affiliation(s)
- Md Sohel Ahmed
- Wildlife Health Lab, Cornell University, Ithaca, NY, USA.
- Texas A & M Transportation Institute, Austin, TX, USA.
| | | | - Corey I Mitchell
- Desert Centered Ecology, LLC, Tucson, AZ, USA
- U.S. Fish and Wildlife Service, Tucson, AZ, USA
| | | | | | - James G Booth
- Department of Statistics and Data Science, Cornell University, Ithaca, NY, USA
| | - Joe Guinness
- Department of Statistics and Data Science, Cornell University, Ithaca, NY, USA
| | - Christopher S Jennelle
- Minnesota Department of Natural Resources, Nongame Wildlife Program, Saint Paul, MN, USA
| | - Florian H Hodel
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Carlos Gonzalez-Crespo
- Center for Animal Disease Modelling and Surveillance, University of California, Davis, CA, USA
| | | | | | - Bambi Clemons
- Florida Fish and Wildlife Conservation Commission, Gainesville, FL, USA
| | | | | | - Joe N Caudell
- Indiana Department of Natural Resources, Bloomington, IN, USA
| | | | - Emily McCallen
- Indiana Department of Natural Resources, Bloomington, IN, USA
| | - Christine Casey
- Kentucky Department of Fish and Wildlife Resources, Frankfort, KY, USA
| | | | | | - Chad Stewart
- Michigan Department of Natural Resources, Grand Rapids, MI, USA
| | - Michelle Carstensen
- Minnesota Department of Natural Resources, Wildlife Health Program, Forest Lake, MN, USA
| | - William T McKinley
- Mississippi Department of Wildlife, Fisheries, and Parks, Jackson, MS, USA
| | - Kevin P Hynes
- New York State Department of Environmental Conservation, Delmar, NY, USA
| | - Ashley E Stevens
- New York State Department of Environmental Conservation, Delmar, NY, USA
| | - Landon A Miller
- New York State Department of Environmental Conservation, Delmar, NY, USA
| | - Merril Cook
- North Carolina Wildlife Resources Commission, Raleigh, NC, USA
| | - Ryan T Myers
- North Carolina Wildlife Resources Commission, Raleigh, NC, USA
| | - Jonathan Shaw
- North Carolina Wildlife Resources Commission, Raleigh, NC, USA
| | | | - James D Kelly
- Florida Fish and Wildlife Conservation Commission, Gainesville, FL, USA
| | | | - Daniel J Storm
- Wisconsin Department of Natural Resources, Madison, WI, USA
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3
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Szechyńska-Hebda M, Hebda M, Doğan-Sağlamtimur N, Lin WT. Let's Print an Ecology in 3D (and 4D). MATERIALS (BASEL, SWITZERLAND) 2024; 17:2194. [PMID: 38793260 PMCID: PMC11122764 DOI: 10.3390/ma17102194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 05/01/2024] [Accepted: 05/04/2024] [Indexed: 05/26/2024]
Abstract
The concept of ecology, historically rooted in the economy of nature, currently needs to evolve to encompass the intricate web of interactions among humans and various organisms in the environment, which are influenced by anthropogenic forces. In this review, the definition of ecology has been adapted to address the dynamic interplay of energy, resources, and information shaping both natural and artificial ecosystems. Previously, 3D (and 4D) printing technologies have been presented as potential tools within this ecological framework, promising a new economy for nature. However, despite the considerable scientific discourse surrounding both ecology and 3D printing, there remains a significant gap in research exploring the interplay between these directions. Therefore, a holistic review of incorporating ecological principles into 3D printing practices is presented, emphasizing environmental sustainability, resource efficiency, and innovation. Furthermore, the 'unecological' aspects of 3D printing, disadvantages related to legal aspects, intellectual property, and legislation, as well as societal impacts, are underlined. These presented ideas collectively suggest a roadmap for future research and practice. This review calls for a more comprehensive understanding of the multifaceted impacts of 3D printing and the development of responsible practices aligned with ecological goals.
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Affiliation(s)
| | - Marek Hebda
- Faculty of Materials Engineering and Physics, Cracow University of Technology, Warszawska 24, 31-155 Kraków, Poland;
| | | | - Wei-Ting Lin
- Department of Civil Engineering, National Ilan University, No. 1, Sec. 1, Shennong Rd., I-Lan 260, Taiwan;
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4
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Groffen J, Hoskin CJ. A portable Raspberry Pi-based camera set-up to record behaviours of frogs and other small animals under artificial or natural shelters in remote locations. Ecol Evol 2024; 14:e10877. [PMID: 38500857 PMCID: PMC10945077 DOI: 10.1002/ece3.10877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 12/29/2023] [Accepted: 01/09/2024] [Indexed: 03/20/2024] Open
Abstract
We describe a Raspberry Pi-based camera system that is portable, robust and weatherproof, with a close-up focus (2.5 cm). We show that this camera system can be used in remote locations with high rainfall and humidity. The camera has an Infrared LED light to film in dark places and can continuously record up to 21 days (504 h). We also describe how to make concrete artificial shelters to mount the camera in. One of the great strengths of this shelter/camera set-up is that the animals choose to take up residence and can then be filmed for extended periods with no disturbance. Furthermore, we give examples of how shelters and cameras could be used to film a range of behaviours in not only many small cryptic amphibian species but also other small vertebrates and invertebrates globally.
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Affiliation(s)
- Jordy Groffen
- College of Science and EngineeringJames Cook UniversityTownsvilleQueenslandAustralia
| | - Conrad J. Hoskin
- College of Science and EngineeringJames Cook UniversityTownsvilleQueenslandAustralia
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5
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Recopuerto-Medina LM, Gutierrez FCU, San Diego JAS, Alviar NAE, Santos JRM, Dagamac NHA. MaxEnt modeling of the potential risk of schistosomiasis in the Philippines using bioclimatic factors. Parasitol Int 2024; 98:102827. [PMID: 38030120 DOI: 10.1016/j.parint.2023.102827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Revised: 11/19/2023] [Accepted: 11/20/2023] [Indexed: 12/01/2023]
Abstract
Schistosomiasis is a parasitic infection caused by Schistosoma japonicum. It remains a principal local health issue in the Philippines, demonstrating endemicity in 28 provinces and afflicting thousands of Filipino individuals annually. Despite this, no clear distribution maps for the disease have been comprehensively reported. Therefore, species distribution modeling (SDM) employing the MaxEnt algorithm and GIS application techniques was utilized to denote the potential risk of schistosomiasis in the country. With a high AUC score of 0.846, the SDM yielded a favorable and reliable correlative map illustrating a predicted schistosomal temporal distribution concentrated primarily on the country's eastern portion with a more pronounced wet than dry season. The precipitation of the driest quarter was determined to be the most significant contributing factor among the bioclimatic variables evaluated. This suggests a possible increase in adaptations concerning the rainfall and thermal tolerances of the parasites' vectors. Moreover, socioeconomic status between Philippine regions revealed an inverse proportion with the number of schistosomiasis cases. This study also discussed the potential role of climate change on the range shifts and the potential risk of parasite infection in the Philippines.
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Affiliation(s)
- Loida M Recopuerto-Medina
- Department of Biological Sciences, College of Science, University of Santo Tomas, España, Manila 1008, Philippines
| | - Franchesca Chiny U Gutierrez
- Department of Biological Sciences, College of Science, University of Santo Tomas, España, Manila 1008, Philippines
| | - Jose Antonio S San Diego
- Department of Biological Sciences, College of Science, University of Santo Tomas, España, Manila 1008, Philippines
| | - Nickhole Andrei E Alviar
- Department of Biological Sciences, College of Science, University of Santo Tomas, España, Manila 1008, Philippines
| | - Joseff Rayven M Santos
- Department of Biological Sciences, College of Science, University of Santo Tomas, España, Manila 1008, Philippines
| | - Nikki Heherson A Dagamac
- Department of Biological Sciences, College of Science, University of Santo Tomas, España, Manila 1008, Philippines; Research Center for the Natural and Applied Sciences, University of Santo Tomas, España, Manila 1008, Philippines; The Graduate School, University of Santo Tomas, España, Manila 1008, Philippines.
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6
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McCarthy OS, Contractor K, Figueira WF, Gleason ACR, Viehman TS, Edwards CB, Sandin SA. Closing the gap between existing large-area imaging research and marine conservation needs. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024; 38:e14145. [PMID: 37403804 DOI: 10.1111/cobi.14145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 06/06/2023] [Accepted: 06/21/2023] [Indexed: 07/06/2023]
Abstract
Emerging technology has immense potential to increase the scale and efficiency of marine conservation. One such technology is large-area imaging (LAI), which relies on structure-from-motion photogrammetry to create composite products, including 3-dimensional (3-D) environmental models, that are larger in spatial extent than the individual images used to create them. Use of LAI has become widespread in certain fields of marine science, primarily to measure the 3D structure of benthic ecosystems and track change over time. However, the use of LAI in the field of marine conservation appears limited. We conducted a review of the coral reef literature on the use of LAI to identify research themes and regional trends in applications of this technology. We also surveyed 135 coral reef scientists and conservation practitioners to determine community familiarity with LAI, evaluate barriers practitioners face in using LAI, and identify applications of LAI believed to be most exciting or relevant to coral conservation. Adoption of LAI was limited primarily to researchers at institutions based in advanced economies and was applied infrequently to conservation, although conservation practitioners and survey respondents from emerging economies indicated they expect to use LAI in the future. Our results revealed disconnect between current LAI research topics and conservation priorities identified by practitioners, highlighting the need for more diverse, conservation-relevant research using LAI. We provide recommendations for how early adopters of LAI (typically Global North scientists from well-resourced institutions) can facilitate access to this conservation technology. These recommendations include developing training resources, creating partnerships for data storage and analysis, publishing standard operating procedures for LAI workflows, standardizing methods, developing tools for efficient data extraction from LAI products, and conducting conservation-relevant research using LAI.
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Affiliation(s)
- Orion S McCarthy
- Scripps Institution of Oceanography, Center for Marine Biodiversity and Conservation, University of California San Diego, La Jolla, California, USA
| | - Kanisha Contractor
- Scripps Institution of Oceanography, Center for Marine Biodiversity and Conservation, University of California San Diego, La Jolla, California, USA
| | - Will F Figueira
- School of Life and Environmental Sciences, University of Sydney, Sydney, New South Wales, Australia
| | | | - T Shay Viehman
- National Centers for Coastal Ocean Science, NOAA National Ocean Service, Beaufort, North Carolina, USA
| | - Clinton B Edwards
- Scripps Institution of Oceanography, Center for Marine Biodiversity and Conservation, University of California San Diego, La Jolla, California, USA
- Consolidated Safety Services Inc., under contract to NOAA National Centers for Coastal Ocean Science, Fairfax, Virginia, USA
| | - Stuart A Sandin
- Scripps Institution of Oceanography, Center for Marine Biodiversity and Conservation, University of California San Diego, La Jolla, California, USA
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7
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Potgieter LJ, Cadotte MW, Roets F, Richardson DM. Monitoring urban biological invasions using citizen science: the polyphagous shot hole borer ( Euwallacea fornicatus). JOURNAL OF PEST SCIENCE 2024; 97:2073-2085. [PMID: 39323576 PMCID: PMC11420376 DOI: 10.1007/s10340-024-01744-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 12/27/2023] [Accepted: 01/01/2024] [Indexed: 09/27/2024]
Abstract
Benefits provided by urban trees are increasingly threatened by non-native pests and pathogens. Monitoring of these invasions is critical for the effective management and conservation of urban tree populations. However, a shortage of professionally collected species occurrence data is a major impediment to assessments of biological invasions in urban areas. We applied data from iNaturalist to develop a protocol for monitoring urban biological invasions using the polyphagous shot hole borer (PSHB) invasion in two urban areas of South Africa. iNaturalist records for all known PSHB reproductive host species were used together with data on localities of sites for processing plant biomass to map priority monitoring areas for detecting new and expanding PSHB infestations. Priority monitoring areas were also identified using the distribution of Acer negundo, a highly susceptible host that serves as a sentinel species for the detection of PSHB infestations. iNaturalist data provided close to 9000 observations for hosts in which PSHB is known to reproduce in our study area (349 of which were A. negundo). High-priority areas for PSHB monitoring include those with the highest density of PSHB reproductive hosts found close to the 140 plant biomass sites identified. We also identified high-priority roads for visual and baited trap surveys, providing operational guidance for practitioners. The monitoring protocol developed in this study highlights the value of citizen or community science data in informing the management of urban biological invasions. It also advocates for the use of platforms such as iNaturalist as essential tools for conservation monitoring in urban landscapes. Supplementary Information The online version contains supplementary material available at 10.1007/s10340-024-01744-7.
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Affiliation(s)
- Luke J. Potgieter
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Stellenbosch, South Africa
- Department of Biological Sciences, University of Toronto-Scarborough, 1265 Military Trail, Toronto, ON M1C 1A4 Canada
| | - Marc W. Cadotte
- Department of Biological Sciences, University of Toronto-Scarborough, 1265 Military Trail, Toronto, ON M1C 1A4 Canada
| | - Francois Roets
- Department of Conservation Ecology and Entomology, Stellenbosch University, Stellenbosch, South Africa
| | - David M. Richardson
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Stellenbosch, South Africa
- Department of Invasion Ecology, Institute of Botany, Czech Academy of Sciences, Průhonice, Czech Republic
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8
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Gimeno M, Giménez J, Chiaradia A, Davis LS, Seddon PJ, Ropert-Coudert Y, Reisinger RR, Coll M, Ramírez F. Climate and human stressors on global penguin hotspots: Current assessments for future conservation. GLOBAL CHANGE BIOLOGY 2024; 30:e17143. [PMID: 38273518 DOI: 10.1111/gcb.17143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 12/14/2023] [Indexed: 01/27/2024]
Abstract
As charismatic and iconic species, penguins can act as "ambassadors" or flagship species to promote the conservation of marine habitats in the Southern Hemisphere. Unfortunately, there is a lack of reliable, comprehensive, and systematic analysis aimed at compiling spatially explicit assessments of the multiple impacts that the world's 18 species of penguin are facing. We provide such an assessment by combining the available penguin occurrence information from Global Biodiversity Information Facility (>800,000 occurrences) with three main stressors: climate-driven environmental changes at sea, industrial fisheries, and human disturbances on land. Our analyses provide a quantitative assessment of how these impacts are unevenly distributed spatially within species' distribution ranges. Consequently, contrasting pressures are expected among species, and populations within species. The areas coinciding with the greatest impacts for penguins are the coast of Perú, the Patagonian Shelf, the Benguela upwelling region, and the Australian and New Zealand coasts. When weighting these potential stressors with species-specific vulnerabilities, Humboldt (Spheniscus humboldti), African (Spheniscus demersus), and Chinstrap penguin (Pygoscelis antarcticus) emerge as the species under the most pressure. Our approach explicitly differentiates between climate and human stressors, since the more achievable management of local anthropogenic stressors (e.g., fisheries and land-based threats) may provide a suitable means for facilitating cumulative impacts on penguins, especially where they may remain resilient to global processes such as climate change. Moreover, our study highlights some poorly represented species such as the Northern Rockhopper (Eudyptes moseleyi), Snares (Eudyptes robustus), and Erect-crested penguin (Eudyptes sclateri) that need internationally coordinated efforts for data acquisition and data sharing to understand their spatial distribution properly.
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Affiliation(s)
- Míriam Gimeno
- Institut de Ciencies del Mar, Recursos Marins Renovables, Barcelona, Spain
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Spain
| | - Joan Giménez
- Institut de Ciencies del Mar, Recursos Marins Renovables, Barcelona, Spain
- Centro Oceanográfico de Málaga (COMA), Instituto Español de Oceanografía (IEO-CSIC), Fuengirola, Spain
| | - Andre Chiaradia
- Conservation Department, Phillip Island Nature Parks, Cowes, Victoria, Australia
| | | | | | | | - Ryan R Reisinger
- School of Ocean and Earth Science, University of Southampton, Southampton, UK
| | - Marta Coll
- Institut de Ciencies del Mar, Recursos Marins Renovables, Barcelona, Spain
- Ecopath International Initiative (EII), Barcelona, Spain
| | - Francisco Ramírez
- Institut de Ciencies del Mar, Recursos Marins Renovables, Barcelona, Spain
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9
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Zeuss D, Bald L, Gottwald J, Becker M, Bellafkir H, Bendix J, Bengel P, Beumer LT, Brandl R, Brändle M, Dahlke S, Farwig N, Freisleben B, Friess N, Heidrich L, Heuer S, Höchst J, Holzmann H, Lampe P, Leberecht M, Lindner K, Masello JF, Mielke Möglich J, Mühling M, Müller T, Noskov A, Opgenoorth L, Peter C, Quillfeldt P, Rösner S, Royauté R, Mestre-Runge C, Schabo D, Schneider D, Seeger B, Shayle E, Steinmetz R, Tafo P, Vogelbacher M, Wöllauer S, Younis S, Zobel J, Nauss T. Nature 4.0: A networked sensor system for integrated biodiversity monitoring. GLOBAL CHANGE BIOLOGY 2024; 30:e17056. [PMID: 38273542 DOI: 10.1111/gcb.17056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 10/13/2023] [Accepted: 10/26/2023] [Indexed: 01/27/2024]
Abstract
Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade-off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real-world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low-cost, and open-source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area-wide ecosystem mapping tasks, thereby providing an exemplary cost-efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystems and the provision of ecosystem services.
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Affiliation(s)
- Dirk Zeuss
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
| | - Lisa Bald
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
| | - Jannis Gottwald
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
| | - Marcel Becker
- Department of Biology, Conservation Ecology, Philipps-Universität Marburg, Marburg, Germany
| | - Hicham Bellafkir
- Department of Mathematics and Computer Science, Distributed Systems and Intelligent Computing, Philipps-Universität Marburg, Marburg, Germany
| | - Jörg Bendix
- Department of Geography, Climatology and Environmental Modelling, Philipps-Universität Marburg, Marburg, Germany
| | - Phillip Bengel
- Department of Geography, Didactics and Education, Philipps-Universität Marburg, Marburg, Germany
| | - Larissa T Beumer
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany
| | - Roland Brandl
- Department of Biology, Animal Ecology, Philipps-Universität Marburg, Marburg, Germany
| | - Martin Brändle
- Department of Biology, Animal Ecology, Philipps-Universität Marburg, Marburg, Germany
| | - Stephan Dahlke
- Department of Mathematics and Computer Science, Numerics, Philipps-Universität Marburg, Marburg, Germany
| | - Nina Farwig
- Department of Biology, Conservation Ecology, Philipps-Universität Marburg, Marburg, Germany
| | - Bernd Freisleben
- Department of Mathematics and Computer Science, Distributed Systems and Intelligent Computing, Philipps-Universität Marburg, Marburg, Germany
| | - Nicolas Friess
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
| | - Lea Heidrich
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
| | - Sven Heuer
- Department of Mathematics and Computer Science, Numerics, Philipps-Universität Marburg, Marburg, Germany
| | - Jonas Höchst
- Department of Mathematics and Computer Science, Distributed Systems and Intelligent Computing, Philipps-Universität Marburg, Marburg, Germany
| | - Hajo Holzmann
- Department of Mathematics and Computer Science, Stochastics, Philipps-Universität Marburg, Marburg, Germany
| | - Patrick Lampe
- Department of Mathematics and Computer Science, Distributed Systems and Intelligent Computing, Philipps-Universität Marburg, Marburg, Germany
| | - Martin Leberecht
- Department of Biology, Plant Ecology and Geobotany, Philipps-Universität Marburg, Marburg, Germany
| | - Kim Lindner
- Department of Biology, Conservation Ecology, Philipps-Universität Marburg, Marburg, Germany
| | - Juan F Masello
- Department of Animal Ecology & Systematics, Justus Liebig University Gießen, Gießen, Germany
| | - Jonas Mielke Möglich
- Department of Biology, Animal Ecology, Philipps-Universität Marburg, Marburg, Germany
| | - Markus Mühling
- Department of Mathematics and Computer Science, Distributed Systems and Intelligent Computing, Philipps-Universität Marburg, Marburg, Germany
| | - Thomas Müller
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany
- Department of Biological Sciences, Goethe University Frankfurt am Main, Frankfurt am Main, Germany
| | - Alexey Noskov
- Department of Geography, Climatology and Environmental Modelling, Philipps-Universität Marburg, Marburg, Germany
| | - Lars Opgenoorth
- Department of Biology, Plant Ecology and Geobotany, Philipps-Universität Marburg, Marburg, Germany
| | - Carina Peter
- Department of Geography, Didactics and Education, Philipps-Universität Marburg, Marburg, Germany
| | - Petra Quillfeldt
- Department of Animal Ecology & Systematics, Justus Liebig University Gießen, Gießen, Germany
| | - Sascha Rösner
- Department of Biology, Conservation Ecology, Philipps-Universität Marburg, Marburg, Germany
| | - Raphaël Royauté
- Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Frankfurt am Main, Germany
- Université Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, Palaiseau, France
| | - Christian Mestre-Runge
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
- Department of Biology, Plant Ecology and Geobotany, Philipps-Universität Marburg, Marburg, Germany
| | - Dana Schabo
- Department of Biology, Conservation Ecology, Philipps-Universität Marburg, Marburg, Germany
| | - Daniel Schneider
- Department of Mathematics and Computer Science, Distributed Systems and Intelligent Computing, Philipps-Universität Marburg, Marburg, Germany
| | - Bernhard Seeger
- Department of Mathematics and Computer Science, Database Systems, Philipps-Universität Marburg, Marburg, Germany
| | - Elliot Shayle
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
| | - Ralf Steinmetz
- Department of Electrical Engineering and Information Technology, Multimedia Communications Lab (KOM), Technical University of Darmstadt, Darmstadt, Germany
| | - Pavel Tafo
- Department of Mathematics and Computer Science, Stochastics, Philipps-Universität Marburg, Marburg, Germany
| | - Markus Vogelbacher
- Department of Mathematics and Computer Science, Distributed Systems and Intelligent Computing, Philipps-Universität Marburg, Marburg, Germany
| | - Stephan Wöllauer
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
| | - Sohaib Younis
- Department of Mathematics and Computer Science, Database Systems, Philipps-Universität Marburg, Marburg, Germany
| | - Julian Zobel
- Department of Electrical Engineering and Information Technology, Multimedia Communications Lab (KOM), Technical University of Darmstadt, Darmstadt, Germany
| | - Thomas Nauss
- Department of Geography, Environmental Informatics, Philipps-Universität Marburg, Marburg, Germany
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10
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Buchan C, Gilroy JJ, Catry I, Hewson CM, Atkinson PW, Franco AMA. Combining remote sensing and tracking data to quantify species' cumulative exposure to anthropogenic change. GLOBAL CHANGE BIOLOGY 2023; 29:6679-6692. [PMID: 37812027 PMCID: PMC10946810 DOI: 10.1111/gcb.16974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/19/2023] [Accepted: 09/25/2023] [Indexed: 10/10/2023]
Abstract
Identifying when and where organisms are exposed to anthropogenic change is crucial for diagnosing the drivers of biodiversity declines and implementing effective conservation measures. Accurately measuring individual-scale exposure to anthropogenic impacts across the annual cycle as they move across continents requires an approach that is both spatially and temporally explicit-now achievable through recent parallel advances in remote-sensing and individual tracking technologies. We combined 10 years of tracking data for a long-distance migrant, (common cuckoo, Cuculus canorus), with multi-dimensional remote-sensed spatial datasets encompassing thirteen relevant anthropogenic impacts (including infrastructure, hunting, habitat change, and climate change), to quantify mean hourly and total accumulated exposure of tracked individuals to anthropogenic change across each stage of the annual cycle. Although mean hourly exposure to anthropogenic change was greatest in the breeding stage, accumulated exposure to changes associated with direct mortality risks (e.g., built infrastructure) and with climate were greatest during the wintering stage, which comprised 63% of the annual cycle on average for tracked individuals. Exposure to anthropogenic change varied considerably within and between migratory flyways, but there were no clear between-flyway differences in overall exposure during migration stages. However, more easterly autumn migratory routes were significantly associated with lower subsequent exposure to anthropogenic impacts in the winter stage. Cumulative change exposure was not significantly associated with recent local-scale population trends in the breeding range, possibly because cuckoos from shared breeding areas may follow divergent migration routes and therefore encounter very different risk landscapes. Our study highlights the potential for the integration of tracking data and high-resolution remote sensing to generate valuable and detailed new insights into the impacts of environmental change on wild species.
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Affiliation(s)
- Claire Buchan
- School of Environmental SciencesUniversity of East AngliaNorwichUK
| | - James J. Gilroy
- School of Environmental SciencesUniversity of East AngliaNorwichUK
| | - Inês Catry
- School of Environmental SciencesUniversity of East AngliaNorwichUK
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório AssociadoUniversidade do PortoVairaoPortugal
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Instituto Superior de AgronomiaUniversidade de LisboaLisbonPortugal
- BIOPOLIS Program in GenomicsBiodiversity and Land Planning, CIBIOVairaoPortugal
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11
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Wang Z, Othman SN, Qiu Z, Lu Y, Prasad VK, Dong Y, Lu CH, Borzée A. An Isolated and Deeply Divergent Hynobius Species from Fujian, China. Animals (Basel) 2023; 13:ani13101661. [PMID: 37238092 DOI: 10.3390/ani13101661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/27/2023] [Accepted: 05/01/2023] [Indexed: 05/28/2023] Open
Abstract
It is important to describe lineages before they go extinct, as we can only protect what we know. This is especially important in the case of microendemic species likely to be relict populations, such as Hynobius salamanders in southern China. Here, we unexpectedly sampled Hynobius individuals in Fujian province, China, and then worked on determining their taxonomic status. We describe Hynobius bambusicolus sp. nov. based on molecular and morphological data. The lineage is deeply divergent and clusters with the other southern Chinese Hynobius species based on the concatenated mtDNA gene fragments (>1500 bp), being the sister group to H. amjiensis based on the COI gene fragment, despite their geographic distance. In terms of morphology, the species can be identified through discrete characters enabling identification in the field by eye, an unusual convenience in Hynobius species. In addition, we noted some interesting life history traits in the species, such as vocalization and cannibalism. The species is likely to be incredibly rare, over a massively restricted distribution, fitting the definition of Critically Endangered following several lines of criteria and categories of the IUCN Red List of Threatened Species.
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Affiliation(s)
- Zhenqi Wang
- The Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Siti N Othman
- Laboratory of Animal Behaviour and Conservation, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Zhixin Qiu
- The Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Yiqiu Lu
- The Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Vishal Kumar Prasad
- Laboratory of Animal Behaviour and Conservation, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Yuran Dong
- The Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Chang-Hu Lu
- The Co-Innovation Center for Sustainable Forestry in Southern China, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
| | - Amaël Borzée
- Laboratory of Animal Behaviour and Conservation, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
- Jiangsu Agricultural Biodiversity Cultivation and Utilization Research Center, Nanjing 210014, China
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12
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Besson M, Alison J, Bjerge K, Gorochowski TE, Høye TT, Jucker T, Mann HMR, Clements CF. Towards the fully automated monitoring of ecological communities. Ecol Lett 2022; 25:2753-2775. [PMID: 36264848 PMCID: PMC9828790 DOI: 10.1111/ele.14123] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 08/09/2022] [Accepted: 09/06/2022] [Indexed: 01/12/2023]
Abstract
High-resolution monitoring is fundamental to understand ecosystems dynamics in an era of global change and biodiversity declines. While real-time and automated monitoring of abiotic components has been possible for some time, monitoring biotic components-for example, individual behaviours and traits, and species abundance and distribution-is far more challenging. Recent technological advancements offer potential solutions to achieve this through: (i) increasingly affordable high-throughput recording hardware, which can collect rich multidimensional data, and (ii) increasingly accessible artificial intelligence approaches, which can extract ecological knowledge from large datasets. However, automating the monitoring of facets of ecological communities via such technologies has primarily been achieved at low spatiotemporal resolutions within limited steps of the monitoring workflow. Here, we review existing technologies for data recording and processing that enable automated monitoring of ecological communities. We then present novel frameworks that combine such technologies, forming fully automated pipelines to detect, track, classify and count multiple species, and record behavioural and morphological traits, at resolutions which have previously been impossible to achieve. Based on these rapidly developing technologies, we illustrate a solution to one of the greatest challenges in ecology: the ability to rapidly generate high-resolution, multidimensional and standardised data across complex ecologies.
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Affiliation(s)
- Marc Besson
- School of Biological SciencesUniversity of BristolBristolUK,Sorbonne Université CNRS UMR Biologie des Organismes Marins, BIOMBanyuls‐sur‐MerFrance
| | - Jamie Alison
- Department of EcoscienceAarhus UniversityAarhusDenmark,UK Centre for Ecology & HydrologyBangorUK
| | - Kim Bjerge
- Department of Electrical and Computer EngineeringAarhus UniversityAarhusDenmark
| | - Thomas E. Gorochowski
- School of Biological SciencesUniversity of BristolBristolUK,BrisEngBio, School of ChemistryUniversity of BristolCantock's CloseBristolBS8 1TSUK
| | - Toke T. Høye
- Department of EcoscienceAarhus UniversityAarhusDenmark,Arctic Research CentreAarhus UniversityAarhusDenmark
| | - Tommaso Jucker
- School of Biological SciencesUniversity of BristolBristolUK
| | - Hjalte M. R. Mann
- Department of EcoscienceAarhus UniversityAarhusDenmark,Arctic Research CentreAarhus UniversityAarhusDenmark
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13
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Flamm RO, Braunsberger K. Systems thinking to operationalize knowledge‐to‐action in fish and wildlife agencies. CONSERVATION SCIENCE AND PRACTICE 2022. [DOI: 10.1111/csp2.12774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Affiliation(s)
- Richard Owen Flamm
- Florida Fish & Wildlife Research Institute Florida Fish & Wildlife Conservation Commission Tallahassee Florida USA
| | - Karin Braunsberger
- Center for Entrepreneurship, Muma College of Business University of South Florida Tampa Florida USA
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14
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Lonsinger RC. Co-occurrence models fail to infer underlying patterns of avoidance and aggregation when closure is violated. Ecol Evol 2022; 12:e9104. [PMID: 35845361 PMCID: PMC9273567 DOI: 10.1002/ece3.9104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/15/2022] [Accepted: 06/22/2022] [Indexed: 11/29/2022] Open
Abstract
Advances in multi-species monitoring have prompted an increase in the use of multi-species occupancy analyses to assess patterns of co-occurrence among species, even when data were collected at scales likely violating the assumption that sites were closed to changes in the occupancy state for the target species. Violating the closure assumption may lead to erroneous conclusions related to patterns of co-occurrence among species. Occurrence for two hypothetical species was simulated under patterns of avoidance, aggregation, or independence, when the closure assumption was either met or not. Simulated populations were sampled at two levels (N = 250 or 100 sites) and two scales of temporal resolution for surveys. Sample data were analyzed with conditional two-species occupancy models, and performance was assessed based on the proportion of simulations recovering the true pattern of co-occurrence. Estimates of occupancy were unbiased when closure was met, but biased when closure violations occurred; bias increased when sample size was small and encounter histories were collapsed to a large-scale temporal resolution. When closure was met and patterns of avoidance and aggregation were simulated, conditional two-species models tended to correctly find support for non-independence, and estimated species interaction factors (SIF) aligned with predicted values. By contrast, when closure was violated, models tended to incorrectly infer a pattern of independence and power to detect simulated patterns of avoidance or aggregation that decreased with smaller sample size. Results suggest that when the closure assumption is violated, co-occurrence models often fail to detect underlying patterns of avoidance or aggregation, and incorrectly identify a pattern of independence among species, which could have negative consequences for our understanding of species interactions and conservation efforts. Thus, when closure is violated, inferred patterns of independence from multi-species occupancy should be interpreted cautiously, and evidence of avoidance or aggregation is likely a conservative estimate of true pattern or interaction.
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Affiliation(s)
- Robert C. Lonsinger
- U.S. Geological Survey, Oklahoma Cooperative Fish and Wildlife Research UnitOklahoma State UniversityStillwaterOklahomaUSA
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15
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Speaker T, O'Donnell S, Wittemyer G, Bruyere B, Loucks C, Dancer A, Carter M, Fegraus E, Palmer J, Warren E, Solomon J. A global community-sourced assessment of the state of conservation technology. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2022; 36:e13871. [PMID: 34904294 PMCID: PMC9303432 DOI: 10.1111/cobi.13871] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 10/13/2021] [Accepted: 10/15/2021] [Indexed: 06/14/2023]
Abstract
Conservation technology holds the potential to vastly increase conservationists' ability to understand and address critical environmental challenges, but systemic constraints appear to hamper its development and adoption. Understanding of these constraints and opportunities for advancement remains limited. We conducted a global online survey of 248 conservation technology users and developers to identify perceptions of existing tools' current performance and potential impact, user and developer constraints, and key opportunities for growth. We also conducted focus groups with 45 leading experts to triangulate findings. The technologies with the highest perceived potential were machine learning and computer vision, eDNA and genomics, and networked sensors. A total of 95%, 94%, and 92% respondents, respectively, rated them as very helpful or game changers. The most pressing challenges affecting the field as a whole were competition for limited funding, duplication of efforts, and inadequate capacity building. A total of 76%, 67%, and 55% respondents, respectively, identified these as primary concerns. The key opportunities for growth identified in focus groups were increasing collaboration and information sharing, improving the interoperability of tools, and enhancing capacity for data analyses at scale. Some constraints appeared to disproportionately affect marginalized groups. Respondents in countries with developing economies were more likely to report being constrained by upfront costs, maintenance costs, and development funding (p = 0.048, odds ratio [OR] = 2.78; p = 0.005, OR = 4.23; p = 0.024, OR = 4.26), and female respondents were more likely to report being constrained by development funding and perceived technical skills (p = 0.027, OR = 3.98; p = 0.048, OR = 2.33). To our knowledge, this is the first attempt to formally capture the perspectives and needs of the global conservation technology community, providing foundational data that can serve as a benchmark to measure progress. We see tremendous potential for this community to further the vision they define, in which collaboration trumps competition; solutions are open, accessible, and interoperable; and user-friendly processing tools empower the rapid translation of data into conservation action. Article impact statement: Addressing financing, coordination, and capacity-building constraints is critical to the development and adoption of conservation technology.
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Affiliation(s)
- Talia Speaker
- Human Dimensions of Natural ResourcesColorado State UniversityFort CollinsColoradoUSA
- World Wildlife FundWashingtonD.C.USA
| | | | - George Wittemyer
- Department of Fish, Wildlife, and Conservation BiologyColorado State UniversityFort CollinsColoradoUSA
| | - Brett Bruyere
- Human Dimensions of Natural ResourcesColorado State UniversityFort CollinsColoradoUSA
| | | | | | | | | | | | | | - Jennifer Solomon
- Human Dimensions of Natural ResourcesColorado State UniversityFort CollinsColoradoUSA
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16
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Toward a Unified TreeTalker Data Curation Process. FORESTS 2022. [DOI: 10.3390/f13060855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The Internet of Things (IoT) development is revolutionizing environmental monitoring and research in macroecology. This technology allows for the deployment of sizeable diffuse sensing networks capable of continuous monitoring. Because of this property, the data collected from IoT networks can provide a testbed for scientific hypotheses across large spatial and temporal scales. Nevertheless, data curation is a necessary step to make large and heterogeneous datasets exploitable for synthesis analyses. This process includes data retrieval, quality assurance, standardized formatting, storage, and documentation. TreeTalkers are an excellent example of IoT applied to ecology. These are smart devices for synchronously measuring trees’ physiological and environmental parameters. A set of devices can be organized in a mesh and permit data collection from a single tree to plot or transect scale. The deployment of such devices over large-scale networks needs a standardized approach for data curation. For this reason, we developed a unified processing workflow according to the user manual. In this paper, we first introduce the concept of a unified TreeTalker data curation process. The idea was formalized into an R-package, and it is freely available as open software. Secondly, we present the different functions available in “ttalkR”, and, lastly, we illustrate the application with a demonstration dataset. With such a unified processing approach, we propose a necessary data curation step to establish a new environmental cyberinfrastructure and allow for synthesis activities across environmental monitoring networks. Our data curation concept is the first step for supporting the TreeTalker data life cycle by improving accessibility and thus creating unprecedented opportunities for TreeTalker-based macroecological analyses.
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17
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Joo R, Picardi S, Boone ME, Clay TA, Patrick SC, Romero-Romero VS, Basille M. Recent trends in movement ecology of animals and human mobility. MOVEMENT ECOLOGY 2022; 10:26. [PMID: 35614458 PMCID: PMC9134608 DOI: 10.1186/s40462-022-00322-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 04/07/2022] [Indexed: 06/15/2023]
Abstract
Movement is fundamental to life, shaping population dynamics, biodiversity patterns, and ecosystem structure. In 2008, the movement ecology framework (MEF Nathan et al. in PNAS 105(49):19052-19059, 2008) introduced an integrative theory of organismal movement-linking internal state, motion capacity, and navigation capacity to external factors-which has been recognized as a milestone in the field. Since then, the study of movement experienced a technological boom, which provided massive quantities of tracking data of both animal and human movement globally and at ever finer spatio-temporal resolutions. In this work, we provide a quantitative assessment of the state of research within the MEF, focusing on animal movement, including humans and invertebrates, and excluding movement of plants and microorganisms. Using a text mining approach, we digitally scanned the contents of [Formula: see text] papers from 2009 to 2018 available online, identified tools and methods used, and assessed linkages between all components of the MEF. Over the past decade, the publication rate has increased considerably, along with major technological changes, such as an increased use of GPS devices and accelerometers and a majority of studies now using the R software environment for statistical computing. However, animal movement research still largely focuses on the effect of environmental factors on movement, with motion and navigation continuing to receive little attention. A search of topics based on words featured in abstracts revealed a clustering of papers among marine and terrestrial realms, as well as applications and methods across taxa. We discuss the potential for technological and methodological advances in the field to lead to more integrated and interdisciplinary research and an increased exploration of key movement processes such as navigation, as well as the evolutionary, physiological, and life-history consequences of movement.
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Affiliation(s)
- Rocío Joo
- Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, University of Florida, Fort Lauderdale, FL USA
- Global Fishing Watch, Washington DC, USA
| | - Simona Picardi
- Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, University of Florida, Fort Lauderdale, FL USA
- Jack H. Berryman Institute and Department of Wildland Resources, S.J. & Jessie E. Quinney College of Natural Resources, Utah State University, Logan, UT USA
| | - Matthew E. Boone
- Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, University of Florida, Fort Lauderdale, FL USA
| | - Thomas A. Clay
- School of Environmental Sciences, University of Liverpool, Liverpool, UK
- Institute of Marine Sciences, University of California Santa Cruz, Santa Cruz, CA USA
| | | | - Vilma S. Romero-Romero
- Systems Engineering, Faculty of Engineering and Architecture, University of Lima, Lima, Peru
| | - Mathieu Basille
- Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, University of Florida, Fort Lauderdale, FL USA
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18
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Oellermann M, Jolles JW, Ortiz D, Seabra R, Wenzel T, Wilson H, Tanner RL. Open Hardware in Science: The Benefits of Open Electronics. Integr Comp Biol 2022; 62:1061-1075. [PMID: 35595471 PMCID: PMC9617215 DOI: 10.1093/icb/icac043] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 04/30/2022] [Accepted: 05/13/2022] [Indexed: 11/30/2022] Open
Abstract
Openly shared low-cost electronic hardware applications, known as open electronics, have sparked a new open-source movement, with much untapped potential to advance scientific research. Initially designed to appeal to electronic hobbyists, open electronics have formed a global “maker” community and are increasingly used in science and industry. In this perspective article, we review the current costs and benefits of open electronics for use in scientific research ranging from the experimental to the theoretical sciences. We discuss how user-made electronic applications can help (I) individual researchers, by increasing the customization, efficiency, and scalability of experiments, while improving data quantity and quality; (II) scientific institutions, by improving access to customizable high-end technologies, sustainability, visibility, and interdisciplinary collaboration potential; and (III) the scientific community, by improving transparency and reproducibility, helping decouple research capacity from funding, increasing innovation, and improving collaboration potential among researchers and the public. We further discuss how current barriers like poor awareness, knowledge access, and time investments can be resolved by increased documentation and collaboration, and provide guidelines for academics to enter this emerging field. We highlight that open electronics are a promising and powerful tool to help scientific research to become more innovative and reproducible and offer a key practical solution to improve democratic access to science.
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Affiliation(s)
- Michael Oellermann
- Technical University of Munich, TUM School of Life Sciences, Aquatic Systems Biology Unit, Mühlenweg 22, D-85354 Freising, Germany.,University of Tasmania, Institute for Marine and Antarctic Studies, Fisheries and Aquaculture Centre, Private Bag 49, Hobart, TAS 7001, Australia
| | - Jolle W Jolles
- Centre for Research on Ecology and Forestry Applications (CREAF), Campus UAB, Edifici C. 08193 Bellaterra Barcelona, Spain
| | - Diego Ortiz
- INTA, Instituto Nacional de Tecnología Agropecuaria, Estación Experimental Manfredi, Ruta 9 Km 636, 5988, Manfredi, Córdoba, Argentina
| | - Rui Seabra
- CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, 4485-661, Vairão, Portugal
| | - Tobias Wenzel
- Pontificia Universidad Católica de Chile, Institute for Biological and Medical Engineering, Schools of Engineering (IIBM), Medicine and Biological Sciences, Santiago, Chile
| | - Hannah Wilson
- Utah State University, College of Science, Biology Department, 5305 Old Main Hill, Logan, UT, 84321, USA
| | - Richelle L Tanner
- Chapman University, Environmental Science and Policy Program, 1 University Drive, Orange, CA 92866, USA
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19
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Suraci JP, Smith JA, Chamaillé‐Jammes S, Gaynor KM, Jones M, Luttbeg B, Ritchie EG, Sheriff MJ, Sih A. Beyond spatial overlap: harnessing new technologies to resolve the complexities of predator–prey interactions. OIKOS 2022. [DOI: 10.1111/oik.09004] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
| | - Justine A. Smith
- Dept of Wildlife, Fish and Conservation Biology, Univ. of California Davis CA USA
| | - Simon Chamaillé‐Jammes
- CEFE, Univ. Montpellier, CNRS, EPHE, IRD Montpellier France
- Mammal Research Inst., Dept of Zoology&Entomology, Univ. of Pretoria Pretoria South Africa
| | - Kaitlyn M. Gaynor
- National Center for Ecological Analysis and Synthesis, Univ. of California Santa Barbara CA USA
| | - Menna Jones
- School of Natural Sciences, Univ. of Tasmania Tasmania Australia
| | - Barney Luttbeg
- Dept of Integrative Biology, Oklahoma State Univ. Stillwater OK USA
| | - Euan G. Ritchie
- School of Life and Environmental Sciences, Centre for Integrative Ecology, Deakin Univ. Burwood VIC Australia
| | | | - Andrew Sih
- Dept of Environmental Science and Policy, Univ. of California Davis CA USA
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20
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Hughes EJ, Mady RP, Bonter DN. Evaluating the accuracy and biological meaning of visits to RFID-enabled bird feeders using video. Ecol Evol 2021; 11:17132-17141. [PMID: 34938498 PMCID: PMC8668810 DOI: 10.1002/ece3.8352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/18/2021] [Accepted: 10/22/2021] [Indexed: 11/06/2022] Open
Abstract
Radio-frequency identification (RFID) technology has gained popularity in ornithological studies as a way to collect large quantities of data to answer specific biological questions, but few published studies report methodologies used for validating the accuracy of RFID data. Further, connections between the RFID data and the behaviors of interest in a study are not always clearly established. These methodological deficiencies may seriously impact a study's results and subsequent interpretation. We built RFID-equipped bird feeders and mounted them at three sites in Tompkins County, New York. We deployed passive integrated transponder tags on black-capped chickadees, tufted titmice, and white-breasted nuthatches and used a GoPro video camera to record the three tagged species at the feeders. We then reviewed the video to determine the accuracy of the RFID reader and understand the birds' behavior at the feeders. We found that our RFID system recorded only 34.2% of all visits by tagged birds (n = 237) and that RFID detection increased with the length of a visit. We also found that our three tagged species and two other species that visited the feeders, American goldfinch and hairy woodpecker, retrieved food in 79.5% of their visits. Chickadees, titmice, nuthatches, and woodpeckers spent, on average, 2.3 s at feeders to collect one seed per visit. In contrast, goldfinches spent an average of 9.0 s at feeders and consumed up to 30 seeds per visit. Our results demonstrate the importance of confirming detection accuracy and that video can be used to identify behavioral characteristics associated with an RFID reader's detections. This simple-yet time-intensive-method for assessing the accuracy and biological meaning of RFID data is useful for ornithological studies but can be used in research focusing on various taxa and study systems.
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Affiliation(s)
- Eric J. Hughes
- Department of Natural Resources & The EnvironmentCornell UniversityIthacaNew YorkUSA
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21
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Hereward HFR, Facey RJ, Sargent AJ, Roda S, Couldwell ML, Renshaw EL, Shaw KH, Devlin JJ, Long SE, Porter BJ, Henderson JM, Emmett CL, Astbury L, Maggs L, Rands SA, Thomas RJ. Raspberry Pi nest cameras: An affordable tool for remote behavioral and conservation monitoring of bird nests. Ecol Evol 2021; 11:14585-14597. [PMID: 34765127 PMCID: PMC8571635 DOI: 10.1002/ece3.8127] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 08/13/2021] [Accepted: 09/01/2021] [Indexed: 11/10/2022] Open
Abstract
Bespoke (custom-built) Raspberry Pi cameras are increasingly popular research tools in the fields of behavioral ecology and conservation, because of their comparative flexibility in programmable settings, ability to be paired with other sensors, and because they are typically cheaper than commercially built models.Here, we describe a novel, Raspberry Pi-based camera system that is fully portable and yet weatherproof-especially to humidity and salt spray. The camera was paired with a passive infrared sensor, to create a movement-triggered camera capable of recording videos over a 24-hr period. We describe an example deployment involving "retro-fitting" these cameras into artificial nest boxes on Praia Islet, Azores archipelago, Portugal, to monitor the behaviors and interspecific interactions of two sympatric species of storm-petrel (Monteiro's storm-petrel Hydrobates monteiroi and Madeiran storm-petrel Hydrobates castro) during their respective breeding seasons.Of the 138 deployments, 70% of all deployments were deemed to be "Successful" (Successful was defined as continuous footage being recorded for more than one hour without an interruption), which equated to 87% of the individual 30-s videos. The bespoke cameras proved to be easily portable between 54 different nests and reasonably weatherproof (~14% of deployments classed as "Partial" or "Failure" deployments were specifically due to the weather/humidity), and we make further trouble-shooting suggestions to mitigate additional weather-related failures.Here, we have shown that this system is fully portable and capable of coping with salt spray and humidity, and consequently, the camera-build methods and scripts could be applied easily to many different species that also utilize cavities, burrows, and artificial nests, and can potentially be adapted for other wildlife monitoring situations to provide novel insights into species-specific daily cycles of behaviors and interspecies interactions.
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Affiliation(s)
| | | | - Alyssa J. Sargent
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
- Department of BiologyUniversity of WashingtonSeattleWashingtonUSA
| | - Sara Roda
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
- A Rocha, CruzhinaAlvorPortugal
| | - Matthew L. Couldwell
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
- Gypseywood CottageYorkUK
| | | | - Katie H. Shaw
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
- University of CambridgeCambridgeUK
| | - Jack J. Devlin
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
- University of KentuckyLexingtonKentuckyUSA
| | - Sarah E. Long
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
| | - Ben J. Porter
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
- Tan y GarnRhiwUK
| | | | - Christa L. Emmett
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
- Department of Applied SciencesUniversity of the West of EnglandBristolUK
| | - Laura Astbury
- Cardiff School of BiosciencesCardiff UniversityCardiffUK
| | | | - Sean A. Rands
- School of Biological SciencesUniversity of BristolBristolUK
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22
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Maldonado‐Chaparro AA, Chaverri G. Why do animal groups matter for conservation and management? CONSERVATION SCIENCE AND PRACTICE 2021. [DOI: 10.1111/csp2.550] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Affiliation(s)
| | - Gloriana Chaverri
- Sede del Sur, Universidad de Costa Rica Golfito Costa Rica
- Smithsonian Tropical Research Institute Ancón Panama
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23
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Lahoz-Monfort JJ, Magrath MJL. A Comprehensive Overview of Technologies for Species and Habitat Monitoring and Conservation. Bioscience 2021; 71:1038-1062. [PMID: 34616236 PMCID: PMC8490933 DOI: 10.1093/biosci/biab073] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The range of technologies currently used in biodiversity conservation is staggering, with innovative uses often adopted from other disciplines and being trialed in the field. We provide the first comprehensive overview of the current (2020) landscape of conservation technology, encompassing technologies for monitoring wildlife and habitats, as well as for on-the-ground conservation management (e.g., fighting illegal activities). We cover both established technologies (routinely deployed in conservation, backed by substantial field experience and scientific literature) and novel technologies or technology applications (typically at trial stage, only recently used in conservation), providing examples of conservation applications for both types. We describe technologies that deploy sensors that are fixed or portable, attached to vehicles (terrestrial, aquatic, or airborne) or to animals (biologging), complemented with a section on wildlife tracking. The last two sections cover actuators and computing (including web platforms, algorithms, and artificial intelligence).
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Affiliation(s)
- José J Lahoz-Monfort
- School of Ecosystem and Forest Sciences, University of Melbourne, Melbourne, Victoria, Australia
| | - Michael J L Magrath
- Wildlife Conservation and Science, Zoos Victoria and with the School of BioSciences, University of Melbourne, Melbourne, Victoria, Australia
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24
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Maudet S, Andrieux G, Chevillon R, Diouris JF. Refined Node Energy Consumption Modeling in a LoRaWAN Network. SENSORS 2021; 21:s21196398. [PMID: 34640719 PMCID: PMC8512702 DOI: 10.3390/s21196398] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 09/17/2021] [Accepted: 09/22/2021] [Indexed: 11/16/2022]
Abstract
LPWAN technologies such as LoRa are widely used for the deployment of IoT applications, in particular for use cases requiring wide coverage and low energy consumption. To minimize the maintenance cost, which can become significant when the number of sensors deployed is large, it is essential to optimize the lifetime of nodes, which remains an important research topic. For this reason, it is necessary that it is based on a fine energy consumption model. Unfortunately, many existing consumption models do not take into account the specifications of the LoRaWAN protocol. In this paper, a refined energy consumption model based on in-situ measurements is provided for a LoRaWAN node. This improved model takes into account the number of nodes in the network, the collision probability that depends on the density of sensors, and the number of retransmissions. Results show the influence of the number of nodes in a LoRaWAN network on the energy consumption of a node and demonstrate that the number of sensors that can be integrated into a LoRaWAN network is limited due to the probability of collision.
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25
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McMahon MC, Ditmer MA, Forester JD. Comparing unmanned aerial systems with conventional methodology for surveying a wild white-tailed deer population. WILDLIFE RESEARCH 2021. [DOI: 10.1071/wr20204] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Abstract Context Ungulate populations are subject to fluctuations caused by extrinsic factors and require efficient and frequent surveying to monitor population sizes and demographics. Unmanned aerial systems (UAS) have become increasingly popular for ungulate research; however, little is understood about how this novel technology compares with conventional methodologies for surveying wild populations. Aims We examined the feasibility of using a fixed-wing UAS equipped with a thermal infrared sensor for estimating the population density of wild white-tailed deer (Odocoileus virginianus) at the Cedar Creek Ecosystem Science Reserve (CCESR), Minnesota, USA. We compared UAS density estimates with those derived from faecal pellet-group counts. Methods We conducted UAS thermal survey flights from March to April of 2018 and January to March of 2019. Faecal pellet-group counts were conducted from April to May in 2018 and 2019. We modelled deer counts and detection probabilities and used these results to calculate point estimates and bootstrapped prediction intervals for deer density from UAS and pellet-group count data. We compared results of each survey approach to evaluate the relative efficacy of these two methodologies. Key results Our best-fitting model of certain deer detections derived from our UAS-collected thermal imagery produced deer density estimates (WR20204_IE1.gif, 95% prediction interval = 4.32–17.84 deer km−2) that overlapped with the pellet-group count model when using our mean pellet deposition rate assumption (WR20204_IE2.gif, 95% prediction interval = 4.14–11.29 deer km−2). Estimates from our top UAS model using both certain and potential deer detections resulted in a mean density of 13.77 deer km−2 (95% prediction interval = 6.64–24.35 deer km−2), which was similar to our pellet-group count model that used a lower rate of pellet deposition (WR20204_IE3.gif, 95% prediction interval = 6.46–17.65 deer km−2). The mean point estimates from our top UAS model predicted a range of 136.68–273.81 deer, and abundance point estimates using our pellet-group data ranged from 112.79 to 239.67 deer throughout the CCESR. Conclusions Overall, UAS yielded results similar to pellet-group counts for estimating population densities of wild ungulates; however, UAS surveys were more efficient and could be conducted at multiple times throughout the winter. Implications We demonstrated how UAS could be applied for regularly monitoring changes in population density. We encourage researchers and managers to consider the merits of UAS and how they could be used to enhance the efficiency of wildlife surveys.
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26
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Williams BR, McAfee D, Connell SD. Repairing recruitment processes with sound technology to accelerate habitat restoration. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2021; 31:e02386. [PMID: 34128289 DOI: 10.1002/eap.2386] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 03/30/2021] [Accepted: 04/21/2021] [Indexed: 06/12/2023]
Abstract
Humanity's ambitions to revive ecosystems at large scales require solutions to move restoration efforts beyond the small scale. There are increasing calls for technological solutions to reduce costs and facilitate large-scale restoration through the use of emerging technologies using an adaptive process of research and development. We show how technological enrichment of marine soundscapes may provide a solution that repairs the recruitment process to accelerate the recovery of lost marine habitats. This solution would solve the problems of current practice that largely relies upon natural recruitment processes, which carries considerable risk where recruitment is variable or eroded. By combining the literature with laboratory experiments, we describe evidence for "highways of sound" that convey navigable information for dispersing life stages in search for adult habitat. We show that these navigational cues tend to be silenced as their habitat is lost, creating negative feedbacks that hinders restoration. We suggest that reprovisioning soundscapes using underwater technology offers the potential to reverse this feedback and entice target organisms to recruit in greater densities. Collective evidence indicates that the application of soundscape theory and technology may unlock the recruitment potential needed to trigger the recruitment of target organisms and the natural soundscapes they create at large scales.
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Affiliation(s)
- Brittany R Williams
- Southern Seas Ecology Laboratories, The Environment Institute, School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, 5005, Australia
| | - Dominic McAfee
- Southern Seas Ecology Laboratories, The Environment Institute, School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, 5005, Australia
| | - Sean D Connell
- Southern Seas Ecology Laboratories, The Environment Institute, School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, 5005, Australia
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27
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Jolles JW. Broad‐scale applications of the Raspberry Pi: A review and guide for biologists. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13652] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Jolle W. Jolles
- Zukunftskolleg University of Konstanz Konstanz Germany
- Department of Collective Behaviour Max Planck Institute of Animal Behaviour Konstanz Germany
- Centre for Research on Ecology and Forestry Applications (CREAF) Barcelona Spain
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28
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Ellis-Soto D, Ferraro KM, Rizzuto M, Briggs E, Monk JD, Schmitz OJ. A methodological roadmap to quantify animal-vectored spatial ecosystem subsidies. J Anim Ecol 2021; 90:1605-1622. [PMID: 34014558 DOI: 10.1111/1365-2656.13538] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 05/04/2021] [Indexed: 12/31/2022]
Abstract
Energy, nutrients and organisms move over landscapes, connecting ecosystems across space and time. Meta-ecosystem theory investigates the emerging properties of local ecosystems coupled spatially by these movements of organisms and matter, by explicitly tracking exchanges of multiple substances across ecosystem borders. To date, meta-ecosystem research has focused mostly on abiotic flows-neglecting biotic nutrient flows. However, recent work has indicated animals act as spatial nutrient vectors when they transport nutrients across landscapes in the form of excreta, egesta and their own bodies. Partly due to its high level of abstraction, there are few empirical tests of meta-ecosystem theory. Furthermore, while animals may be viewed as important mediators of ecosystem functions, better integration of tools is needed to develop predictive insights of their relative roles and impacts on diverse ecosystems. We present a methodological roadmap that explains how to do such integration by discussing how to combine insights from movement, foraging and ecosystem ecology to develop a coherent understanding of animal-vectored nutrient transport on meta-ecosystems processes. We discuss how the slate of newly developed technologies and methods-tracking devices, mechanistic movement models, diet reconstruction techniques and remote sensing-that when integrated have the potential to advance the quantification of animal-vectored nutrient flows and increase the predictive power of meta-ecosystem theory. We demonstrate that by integrating novel and established tools of animal ecology, ecosystem ecology and remote sensing, we can begin to identify and quantify animal-mediated nutrient translocation by large animals. We also provide conceptual examples that show how our proposed integration of methodologies can help investigate ecosystem impacts of large animal movement. We conclude by describing practical advancements to understanding cross-ecosystem contributions of animals on the move. Understanding the mechanisms by which animals shape ecosystem dynamics is important for ongoing conservation, rewilding and restoration initiatives around the world, and for developing more accurate models of ecosystem nutrient budgets. Our roadmap will enable ecologists to better qualify and quantify animal-mediated nutrient translocation for animals on the move.
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Affiliation(s)
- Diego Ellis-Soto
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.,Center for Biodiversity and Global Change, Yale University, New Haven, CT, USA
| | | | - Matteo Rizzuto
- Department of Biology, Memorial University of Newfoundland, St. John's, Canada
| | - Emily Briggs
- School of the Environment, Yale University, New Haven, CT, USA.,Department of Anthropology, Yale University, New Haven, CT, USA
| | - Julia D Monk
- School of the Environment, Yale University, New Haven, CT, USA
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29
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A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems. Nat Ecol Evol 2021; 5:219-230. [PMID: 33398104 DOI: 10.1038/s41559-020-01358-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Accepted: 10/22/2020] [Indexed: 12/31/2022]
Abstract
Technology is transforming societies worldwide. A major innovation is the emergence of robotics and autonomous systems (RAS), which have the potential to revolutionize cities for both people and nature. Nonetheless, the opportunities and challenges associated with RAS for urban ecosystems have yet to be considered systematically. Here, we report the findings of an online horizon scan involving 170 expert participants from 35 countries. We conclude that RAS are likely to transform land use, transport systems and human-nature interactions. The prioritized opportunities were primarily centred on the deployment of RAS for the monitoring and management of biodiversity and ecosystems. Fewer challenges were prioritized. Those that were emphasized concerns surrounding waste from unrecovered RAS, and the quality and interpretation of RAS-collected data. Although the future impacts of RAS for urban ecosystems are difficult to predict, examining potentially important developments early is essential if we are to avoid detrimental consequences but fully realize the benefits.
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30
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McClure EC, Sievers M, Brown CJ, Buelow CA, Ditria EM, Hayes MA, Pearson RM, Tulloch VJD, Unsworth RKF, Connolly RM. Artificial Intelligence Meets Citizen Science to Supercharge Ecological Monitoring. PATTERNS 2020; 1:100109. [PMID: 33205139 PMCID: PMC7660425 DOI: 10.1016/j.patter.2020.100109] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The development and uptake of citizen science and artificial intelligence (AI) techniques for ecological monitoring is increasing rapidly. Citizen science and AI allow scientists to create and process larger volumes of data than possible with conventional methods. However, managers of large ecological monitoring projects have little guidance on whether citizen science, AI, or both, best suit their resource capacity and objectives. To highlight the benefits of integrating the two techniques and guide future implementation by managers, we explore the opportunities, challenges, and complementarities of using citizen science and AI for ecological monitoring. We identify project attributes to consider when implementing these techniques and suggest that financial resources, engagement, participant training, technical expertise, and subject charisma and identification are important project considerations. Ultimately, we highlight that integration can supercharge outcomes for ecological monitoring, enhancing cost-efficiency, accuracy, and multi-sector engagement. Citizen science and artificial intelligence (AI) are often used in isolation for ecological monitoring, but their integration likely has emergent benefits for management and scientific inquiry. We explore the complementarity of citizen science and AI for ecological monitoring, highlighting key opportunities and challenges. We show that strategic integration of citizen science and AI can improve outcomes for conservation activities. For example, coupling the public engagement benefits of citizen science with the advanced analytical capabilities of AI can increase multi-stakeholder accord on issues of public and scientific interest. Furthermore, both techniques speed up data collection and processing compared with conventional scientific techniques, suggesting that their integration can fast-track monitoring and conservation actions. We present key project attributes that will assist project managers in prioritizing the resources needed to implement citizen science, AI, or preferably both.
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Affiliation(s)
- Eva C McClure
- Australian Rivers Institute - Coast and Estuaries, School of Environment and Science, Griffith University, Gold Coast, QLD 4222, Australia
| | - Michael Sievers
- Australian Rivers Institute - Coast and Estuaries, School of Environment and Science, Griffith University, Gold Coast, QLD 4222, Australia
| | - Christopher J Brown
- Australian Rivers Institute - Coast and Estuaries, School of Environment and Science, Griffith University, Nathan, QLD 4111, Australia
| | - Christina A Buelow
- Australian Rivers Institute - Coast and Estuaries, School of Environment and Science, Griffith University, Gold Coast, QLD 4222, Australia
| | - Ellen M Ditria
- Australian Rivers Institute - Coast and Estuaries, School of Environment and Science, Griffith University, Gold Coast, QLD 4222, Australia
| | - Matthew A Hayes
- Australian Rivers Institute - Coast and Estuaries, School of Environment and Science, Griffith University, Gold Coast, QLD 4222, Australia
| | - Ryan M Pearson
- Australian Rivers Institute - Coast and Estuaries, School of Environment and Science, Griffith University, Gold Coast, QLD 4222, Australia
| | - Vivitskaia J D Tulloch
- Department of Forest and Conservation Science, University of British Columbia, Vancouver, BC, Canada
| | - Richard K F Unsworth
- Seagrass Ecosystem Research Group, College of Science, Swansea University, Swansea SA2 8PP, UK
| | - Rod M Connolly
- Australian Rivers Institute - Coast and Estuaries, School of Environment and Science, Griffith University, Gold Coast, QLD 4222, Australia
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31
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Abstract
The last decade has transformed the field of artificial intelligence, with deep learning at the forefront of this development. With its ability to 'self-learn' discriminative patterns directly from data, deep learning is a promising computational approach for automating the classification of visual, spatial and acoustic information in the context of environmental conservation. Here, we first highlight the current and future applications of supervised deep learning in environmental conservation. Next, we describe a number of technical and implementation-related challenges that can potentially impede the real-world adoption of this technology in conservation programmes. Lastly, to mitigate these pitfalls, we discuss priorities for guiding future research and hope that these recommendations will help make this technology more accessible to environmental scientists and conservation practitioners.
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Affiliation(s)
- Aakash Lamba
- School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | - Phillip Cassey
- School of Biological Sciences, University of Adelaide, Adelaide, Australia
| | | | - Lian Pin Koh
- School of Biological Sciences, University of Adelaide, Adelaide, Australia; Betty and Gordon Moore Center for Science, Conservation International, Arlington, VA, USA.
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32
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Nuijten RJM, Gerrits T, Shamoun-Baranes J, Nolet BA. Less is more: On-board lossy compression of accelerometer data increases biologging capacity. J Anim Ecol 2020; 89:237-247. [PMID: 31828775 PMCID: PMC7004173 DOI: 10.1111/1365-2656.13164] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Accepted: 12/03/2019] [Indexed: 11/29/2022]
Abstract
GPS‐tracking devices have been used in combination with a wide range of additional sensors to study animal behaviour, physiology and interaction with their environment. Tri‐axial accelerometers allow researchers to remotely infer the behaviour of individuals, at all places and times. Collection of accelerometer data is relatively cheap in terms of energy usage, but the amount of raw data collected generally requires much storage space and is particularly demanding in terms of energy needed for data transmission. Here, we propose compressing the raw accelerometer (ACC) data into summary statistics within the tracking device (before transmission) to reduce data size, as a means to overcome limitations in storage and energy capacity. We explored this type of lossy data compression in the accelerometer data of tagged Bewick's swans Cygnus columbianus bewickii collected in spring 2017. Using software settings in which bouts of 2 s of both raw ACC data and summary statistics were collected in parallel but with different bout intervals to keep total data size comparable, we created the opportunity for a direct comparison of time budgets derived by the two data collection methods. We found that the data compression in our case yielded a six times reduction in data size per bout, and concurrent, similar decreases in storage and energy use of the device. We show that with the same accuracy of the behavioural classification, the freed memory and energy of the device can be used to increase the monitoring effort, resulting in a more detailed representation of the individuals’ time budget. Rare and/or short behaviours, such as daily roost flights, were picked up significantly more when collecting summary statistics instead of raw ACC data (but note differences in sampling rate). Such level of detail can be of essential importance, for instance to make a reliable estimate of the energy budgets of individuals. In conclusion, we argue that this type of lossy data compression can be a well‐considered choice in study situations where limitations in energy and storage space of the device pose a problem. Ultimately, these developments can allow for long‐term and nearly continuous remote monitoring of the behaviour of free‐ranging animals.
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Affiliation(s)
- Rascha J M Nuijten
- Department of Animal Ecology, Netherlands Institute of Ecology, Wageningen, The Netherlands
| | | | - Judy Shamoun-Baranes
- Department of Theoretical and Computational Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
| | - Bart A Nolet
- Department of Animal Ecology, Netherlands Institute of Ecology, Wageningen, The Netherlands.,Department of Theoretical and Computational Ecology, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
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33
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Proppe DS, Pandit MM, Bridge ES, Jasperse P, Holwerda C. Semi‐portable solar power to facilitate continuous operation of technology in the field. Methods Ecol Evol 2020. [DOI: 10.1111/2041-210x.13456] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Darren S. Proppe
- School of Natural Sciences St. Edward's University Austin TX USA
- Science Division Calvin University Grand Rapids MI USA
| | - Meelyn M. Pandit
- Department of Biology College of Arts and Sciences University of Oklahoma Norman OK USA
| | - Eli S. Bridge
- Oklahoma Biological Survey University of Oklahoma Norman OK USA
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34
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Sarira TV, Clarke K, Weinstein P, Koh LP, Lewis M. Rapid identification of shallow inundation for mosquito disease mitigation using drone-derived multispectral imagery. GEOSPATIAL HEALTH 2020; 15. [PMID: 32575964 DOI: 10.4081/gh.2020.851] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Accepted: 03/30/2020] [Indexed: 06/11/2023]
Abstract
Mosquito breeding habitat identification often relies on slow, labour-intensive and expensive ground surveys. With advances in remote sensing and autonomous flight technologies, we endeavoured to accelerate this detection by assessing the effectiveness of a drone multispectral imaging system to determine areas of shallow inundation in an intertidal saltmarsh in South Australia. Through laboratory experiments, we characterised Near-Infrared (NIR) reflectance responses to water depth and vegetation cover, and established a reflectance threshold for mapping water sufficiently deep for potential mosquito breeding. We then applied this threshold to field-acquired drone imagery and used simultaneous in-situ observations to assess its mapping accuracy. A NIR reflectance threshold of 0.2 combined with a vegetation mask derived from Normalised Difference Vegetation Index (NDVI) resulted in a mapping accuracy of 80.3% with a Cohen's Kappa of 0.5, with confusion between vegetation and shallow water depths (< 10 cm) appearing to be major causes of error. This high degree of mapping accuracy was achieved with affordable drone equipment, and commercially available sensors and Geographic Information Systems (GIS) software, demonstrating the efficiency of such an approach to identify shallow inundation likely to be suitable for mosquito breeding.
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Affiliation(s)
| | - Kenneth Clarke
- School of Biological Sciences, The University of Adelaide, Adelaide.
| | - Philip Weinstein
- School of Biological Sciences, The University of Adelaide, Adelaide.
| | - Lian Pin Koh
- School of Biological Sciences, The University of Adelaide, Adelaide, Australia; Department of Biological Sciences, National University of Singapore.
| | - Megan Lewis
- School of Biological Sciences, The University of Adelaide, Adelaide.
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35
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DeSantis DL, Mata-Silva V, Johnson JD, Wagler AE. Integrative Framework for Long-Term Activity Monitoring of Small and Secretive Animals: Validation With a Cryptic Pitviper. Front Ecol Evol 2020. [DOI: 10.3389/fevo.2020.00169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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36
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Beckman NG, Aslan CE, Rogers HS, Kogan O, Bronstein JL, Bullock JM, Hartig F, HilleRisLambers J, Zhou Y, Zurell D, Brodie JF, Bruna EM, Cantrell RS, Decker RR, Efiom E, Fricke EC, Gurski K, Hastings A, Johnson JS, Loiselle BA, Miriti MN, Neubert MG, Pejchar L, Poulsen JR, Pufal G, Razafindratsima OH, Sandor ME, Shea K, Schreiber S, Schupp EW, Snell RS, Strickland C, Zambrano J. Advancing an interdisciplinary framework to study seed dispersal ecology. AOB PLANTS 2020; 12:plz048. [PMID: 32346468 PMCID: PMC7179845 DOI: 10.1093/aobpla/plz048] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Accepted: 07/26/2019] [Indexed: 05/23/2023]
Abstract
Although dispersal is generally viewed as a crucial determinant for the fitness of any organism, our understanding of its role in the persistence and spread of plant populations remains incomplete. Generalizing and predicting dispersal processes are challenging due to context dependence of seed dispersal, environmental heterogeneity and interdependent processes occurring over multiple spatial and temporal scales. Current population models often use simple phenomenological descriptions of dispersal processes, limiting their ability to examine the role of population persistence and spread, especially under global change. To move seed dispersal ecology forward, we need to evaluate the impact of any single seed dispersal event within the full spatial and temporal context of a plant's life history and environmental variability that ultimately influences a population's ability to persist and spread. In this perspective, we provide guidance on integrating empirical and theoretical approaches that account for the context dependency of seed dispersal to improve our ability to generalize and predict the consequences of dispersal, and its anthropogenic alteration, across systems. We synthesize suitable theoretical frameworks for this work and discuss concepts, approaches and available data from diverse subdisciplines to help operationalize concepts, highlight recent breakthroughs across research areas and discuss ongoing challenges and open questions. We address knowledge gaps in the movement ecology of seeds and the integration of dispersal and demography that could benefit from such a synthesis. With an interdisciplinary perspective, we will be able to better understand how global change will impact seed dispersal processes, and potential cascading effects on plant population persistence, spread and biodiversity.
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Affiliation(s)
- Noelle G Beckman
- Department of Biology & Ecology Center, Utah State University, Logan, UT, USA
| | - Clare E Aslan
- Landscape Conservation Initiative, Northern Arizona University, Flagstaff, AZ, USA
| | - Haldre S Rogers
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA, USA
| | - Oleg Kogan
- Physics Department, California Polytechnic State University, San Luis Obispo, CA, USA
| | - Judith L Bronstein
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA
| | - James M Bullock
- Centre for Ecology and Hydrology, Benson Lane, Wallingford, UK
| | - Florian Hartig
- Theoretical Ecology, University of Regensburg, Regensburg, Germany
| | | | - Ying Zhou
- Department of Mathematics, Lafayette College, Easton, PA, USA
| | - Damaris Zurell
- Swiss Federal Research Institute WSL, Dept. Land Change Science, Birmensdorf, Switzerland
- Humboldt-University Berlin, Geography Dept., Berlin, Germany
| | - Jedediah F Brodie
- Division of Biological Sciences and Wildlife Biology Program, University of Montana, Missoula, MT, USA
| | - Emilio M Bruna
- Department of Wildlife Ecology & Conservation & Center for Latin American Studies, University of Florida, Gainesville, FL, USA
| | | | - Robin R Decker
- Department of Environmental Science and Policy, University of California, Davis, CA, USA
| | - Edu Efiom
- REDD+ Unit, Cross River State Forestry Commission, Calabar, Nigeria
- Biology Department, Lund University, Lund, Sweden
| | - Evan C Fricke
- National Socio-Environmental Synthesis Center, University of Maryland, Annapolis, MD, USA
| | - Katherine Gurski
- Department of Mathematics, Howard University, Washington, DC, USA
| | - Alan Hastings
- Department of Environmental Science and Policy, University of California, Davis, CA, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - Jeremy S Johnson
- School of Forestry, Northern Arizona University, Flagstaff, AZ, USA
| | - Bette A Loiselle
- Center for Latin American Studies and Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL, USA
| | - Maria N Miriti
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - Michael G Neubert
- Department of Biology, Woods Hole Oceanographic Institution, Woods Hole, MA, USA
| | - Liba Pejchar
- Department of Fish, Wildlife and Conservation Biology, Colorado State University, Fort Collins, CO, USA
| | - John R Poulsen
- Nicholas School of the Environment, Duke University, Durham, NC, USA
| | - Gesine Pufal
- Natur Conservation and Landscape Ecology, University of Freiburg Freiburg, Germany
| | | | - Manette E Sandor
- Landscape Conservation Initiative, Northern Arizona University, Flagstaff, AZ, USA
| | - Katriona Shea
- Department of Biology, The Pennsylvania State University, University Park, PA, USA
| | - Sebastian Schreiber
- Department of Evolution and Ecology and Center for Population Biology, University of California, Davis, CA, USA
| | - Eugene W Schupp
- Department of Wildland Resources & Ecology Center, Utah State University, Logan, UT, USA
| | - Rebecca S Snell
- Department of Environmental and Plant Biology, Ohio University, Athens, OH, USA
| | | | - Jenny Zambrano
- Department of Biology, University of Maryland, College Park, MD, USA
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McBride WJ, Courter JR. Using Raspberry Pi microcomputers to remotely monitor birds and collect environmental data. ECOL INFORM 2019. [DOI: 10.1016/j.ecoinf.2019.101016] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Moore HA, Dunlop JA, Valentine LE, Woinarski JCZ, Ritchie EG, Watson DM, Nimmo DG. Topographic ruggedness and rainfall mediate geographic range contraction of a threatened marsupial predator. DIVERS DISTRIB 2019. [DOI: 10.1111/ddi.12982] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Affiliation(s)
- Harry A. Moore
- School of Environmental Science, Institute for Land, Water and Society Charles Sturt University Albury NSW Australia
| | - Judy A. Dunlop
- Science and Conservation Division, Department of Biodiversity, Conservation and Attractions Kensington WA Australia
| | - Leonie E. Valentine
- School of Biological Sciences University of Western Australia, Crawley WA Australia
| | - John C. Z. Woinarski
- Threatened Species Recovery Hub National Environmental Science Program, Charles Darwin University Darwin NT Australia
| | - Euan G. Ritchie
- Centre for Integrative Ecology and School of Life and Environmental Sciences Deakin University Burwood VIC Australia
| | - David M. Watson
- School of Environmental Science, Institute for Land, Water and Society Charles Sturt University Albury NSW Australia
| | - Dale G. Nimmo
- School of Environmental Science, Institute for Land, Water and Society Charles Sturt University Albury NSW Australia
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Lahoz-Monfort JJ, Chadès I, Davies A, Fegraus E, Game E, Guillera-Arroita G, Harcourt R, Indraswari K, McGowan J, Oliver JL, Refisch J, Rhodes J, Roe P, Rogers A, Ward A, Watson DM, Watson JEM, Wintle BA, Joppa L. A Call for International Leadership and Coordination to Realize the Potential of Conservation Technology. Bioscience 2019. [DOI: 10.1093/biosci/biz090] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
AbstractAdvancing technology represents an unprecedented opportunity to enhance our capacity to conserve the Earth's biodiversity. However, this great potential is failing to materialize and rarely endures. We contend that unleashing the power of technology for conservation requires an internationally coordinated strategy that connects the conservation community and policy-makers with technologists. We argue an international conservation technology entity could (1) provide vision and leadership, (2) coordinate and deliver key services necessary to ensure translation from innovation to effective deployment and use of technology for on-the-ground conservation across the planet, and (3) help integrate innovation into biodiversity conservation policy from local to global scales, providing tools to monitor outcomes of conservation action and progress towards national and international biodiversity targets. This proposed entity could take the shape of an international alliance of conservation institutions or a formal intergovernmental institution. Active and targeted uptake of emerging technology can help society achieve biodiversity conservation goals.
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Affiliation(s)
- José J Lahoz-Monfort
- School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia
| | | | - Alasdair Davies
- Zoological Society of London, Regent's Park, London, NW1 4RY, United Kingdom
| | - Eric Fegraus
- 2011 Crystal Drive, Suite 600, Arlington, VA 22202 United Kingdom
| | - Edward Game
- The Nature Conservancy, South Brisbane, QLD 4101, Australia
| | | | - Robert Harcourt
- Department of Biological Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
| | - Karlina Indraswari
- School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, QLD, 4066, Australia
| | - Jennifer McGowan
- The Nature Conservancy, South Brisbane, QLD 4101, Australia
- Department of Biological Sciences, Macquarie University, North Ryde, NSW, 2109, Australia
- Centre of Excellence for Environmental Decisions, School of Biological Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Jessica L Oliver
- School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, QLD, 4066, Australia
| | - Johannes Refisch
- School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia
- Centre of Excellence for Environmental Decisions, School of Biological Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
- Great Apes Survival Partnership, UN Environment, P.O. Box 30552, 00100 Nairobi, Kenya
| | - Jonathan Rhodes
- School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Paul Roe
- School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane, QLD, 4066, Australia
| | - Alex Rogers
- Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | - Adrian Ward
- Wentworth Group of Concerned Scientists, 95 Pitt St, Sydney NSW 2000, Australia
| | - David M Watson
- Institute for Land, Water and Society, Charles Sturt University, Albury, NSW, Australia
| | - James E M Watson
- School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia
- School of Earth and Environmental Sciences, The University of Queensland, Brisbane, QLD 4072, Australia
- Wildlife Conservation Society, Global Conservation Program, Bronx NY 10460, United States
| | - Brendan A Wintle
- School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia
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Ditmer MA, Werden LK, Tanner JC, Vincent JB, Callahan P, Iaizzo PA, Laske TG, Garshelis DL. Bears habituate to the repeated exposure of a novel stimulus, unmanned aircraft systems. CONSERVATION PHYSIOLOGY 2019; 7:coy067. [PMID: 30680216 PMCID: PMC6331175 DOI: 10.1093/conphys/coy067] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2018] [Revised: 10/31/2018] [Accepted: 11/14/2018] [Indexed: 06/09/2023]
Abstract
Unmanned aircraft systems (UAS; i.e. 'drones') provide new opportunities for data collection in ecology, wildlife biology and conservation. Yet, several studies have documented behavioral or physiological responses to close-proximity UAS flights. We experimentally tested whether American black bears (Ursus americanus) habituate to repeated UAS exposure and whether tolerance levels persist during an extended period without UAS flights. Using implanted cardiac biologgers, we measured heart rate (HR) of five captive bears before and after the first of five flights each day. Spikes in HR, a measure of stress, diminished across the five flights within each day and over the course of 4 weeks of twice-weekly exposure. We halted flights for 118 days, and when we resumed, HR responses were similar to that at the end of the previous trials. Our findings highlight the capacity of a large mammal to become and remain habituated to a novel anthropogenic stimulus in a relatively short time (3-4 weeks). However, such habituation to mechanical noises may reduce their wariness of other human threats. Also, whereas cardiac effects diminished, frequent UAS disturbances may have other chronic physiological effects that were not measured. We caution that the rate of habituation may differ between wild and captive animals: while the captive bears displayed large initial spikes in HR change (albeit not as large as wild bears), these animals were accustomed to regular exposure to humans and mechanical noises that may have hastened habituation to the UAS.
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Affiliation(s)
- Mark A Ditmer
- Department of Fisheries, Wildlife & Conservation Biology, University of Minnesota, 135 Skok Hall, 2003 Upper Buford Circle St. Paul, MN, USA
| | - Leland K Werden
- Department of Plant and Microbial Biology, 140 Gortner Laboratory, 1479 Gortner Avenue, University of Minnesota, St. Paul, MN, USA
| | - Jessie C Tanner
- Department of Ecology, Evolution, and Behavior, 140 Gortner Laboratory, 1479 Gortner Avenue, University of Minnesota, St. Paul, MN, USA
| | | | - Peggy Callahan
- Wildlife Science Center, 22830 Sunrise Rd NE, Stacy, MN, USA
| | - Paul A Iaizzo
- Department of Surgery, University of Minnesota, B172 Mayo, MMC 195, 420 Delaware Street SE, Minneapolis, MN, USA
| | - Timothy G Laske
- Department of Surgery, University of Minnesota, B172 Mayo, MMC 195, 420 Delaware Street SE, Minneapolis, MN, USA
| | - David L Garshelis
- Department of Fisheries, Wildlife & Conservation Biology, University of Minnesota, 135 Skok Hall, 2003 Upper Buford Circle St. Paul, MN, USA
- Minnesota Department of Natural Resources, 1201 E Hwy 2, Grand Rapids, MN, USA
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Nimmo DG, Avitabile S, Banks SC, Bliege Bird R, Callister K, Clarke MF, Dickman CR, Doherty TS, Driscoll DA, Greenville AC, Haslem A, Kelly LT, Kenny SA, Lahoz‐Monfort JJ, Lee C, Leonard S, Moore H, Newsome TM, Parr CL, Ritchie EG, Schneider K, Turner JM, Watson S, Westbrooke M, Wouters M, White M, Bennett AF. Animal movements in fire‐prone landscapes. Biol Rev Camb Philos Soc 2018; 94:981-998. [DOI: 10.1111/brv.12486] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 11/08/2018] [Accepted: 11/14/2018] [Indexed: 01/14/2023]
Affiliation(s)
- Dale G. Nimmo
- School of Environmental Science Institute for Land, Water and Society, Charles Sturt University Albury New South Wales 2640 Australia
| | - Sarah Avitabile
- Department of Ecology, Environment and Evolution, School of Life Sciences La Trobe University Bundoora Victoria 3086 Australia
| | - Sam C. Banks
- Research Institute for the Environment and Livelihoods, College of Engineering, IT and the Environment, Charles Darwin University Casuarina Northern Territory 0810 Australia
| | - Rebecca Bliege Bird
- Department of Anthropology Pennsylvania State University University Park PA 16802 U.S.A
| | - Kate Callister
- Department of Ecology, Environment and Evolution, School of Life Sciences La Trobe University Bundoora Victoria 3086 Australia
| | - Michael F. Clarke
- Department of Ecology, Environment and Evolution, School of Life Sciences La Trobe University Bundoora Victoria 3086 Australia
- Research Centre for Future Landscapes, La Trobe University Bundoora Victoria 3086 Australia
| | - Chris R. Dickman
- School of Life and Environmental Sciences University of Sydney Sydney New South Wales 2006 Australia
| | - Tim S. Doherty
- School of Life and Environmental Sciences Centre for Integrative Ecology (Burwood campus), Deakin University Geelong Victoria 3220 Australia
| | - Don A. Driscoll
- School of Life and Environmental Sciences Centre for Integrative Ecology (Burwood campus), Deakin University Geelong Victoria 3220 Australia
| | - Aaron C. Greenville
- School of Life and Environmental Sciences University of Sydney Sydney New South Wales 2006 Australia
| | - Angie Haslem
- Department of Ecology, Environment and Evolution, School of Life Sciences La Trobe University Bundoora Victoria 3086 Australia
| | - Luke T. Kelly
- School of Ecosystem and Forest Sciences The University of Melbourne Parkville Victoria 3010 Australia
| | - Sally A. Kenny
- Victorian Department of Environment, Land Water & Planning Arthur Rylah Institute for Environmental Research 123 Brown St, Heidelberg Victoria 3081 Australia
| | - José J. Lahoz‐Monfort
- School of Ecosystem and Forest Sciences The University of Melbourne Parkville Victoria 3010 Australia
| | - Connie Lee
- School of Life and Environmental Sciences Centre for Integrative Ecology (Burwood campus), Deakin University Geelong Victoria 3220 Australia
| | - Steven Leonard
- Department of Ecology, Environment and Evolution, School of Life Sciences La Trobe University Bundoora Victoria 3086 Australia
| | - Harry Moore
- School of Environmental Science Institute for Land, Water and Society, Charles Sturt University Albury New South Wales 2640 Australia
| | - Thomas M. Newsome
- School of Life and Environmental Sciences University of Sydney Sydney New South Wales 2006 Australia
| | - Catherine L. Parr
- School of Environmental Sciences University of Liverpool Liverpool L69 3GP U.K
- Department of Zoology & Entomology University of Pretoria Pretoria 0002 South Africa
- School of Animal, Plant and Environmental Sciences University of the Witwatersrand Wits 2050 South Africa
| | - Euan G. Ritchie
- School of Life and Environmental Sciences University of Sydney Sydney New South Wales 2006 Australia
| | | | - James M. Turner
- School of Environmental Science Institute for Land, Water and Society, Charles Sturt University Albury New South Wales 2640 Australia
| | - Simon Watson
- Department of Ecology, Environment and Evolution, School of Life Sciences La Trobe University Bundoora Victoria 3086 Australia
| | - Martin Westbrooke
- School of Environmental Science Federation University Ballarat Victoria 3350 Australia
| | - Mike Wouters
- Fire & Flood Management, Department for Environment and Water Adelaide South Australia 5000 Australia
| | - Matthew White
- School of Ecosystem and Forest Sciences The University of Melbourne Parkville Victoria 3010 Australia
| | - Andrew F. Bennett
- Department of Ecology, Environment and Evolution, School of Life Sciences La Trobe University Bundoora Victoria 3086 Australia
- Research Centre for Future Landscapes, La Trobe University Bundoora Victoria 3086 Australia
- Victorian Department of Environment, Land Water & Planning Arthur Rylah Institute for Environmental Research 123 Brown St, Heidelberg Victoria 3081 Australia
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Behm JE, Waite BR, Hsieh ST, Helmus MR. Benefits and limitations of three-dimensional printing technology for ecological research. BMC Ecol 2018; 18:32. [PMID: 30200934 PMCID: PMC6131837 DOI: 10.1186/s12898-018-0190-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Accepted: 09/03/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Ecological research often involves sampling and manipulating non-model organisms that reside in heterogeneous environments. As such, ecologists often adapt techniques and ideas from industry and other scientific fields to design and build equipment, tools, and experimental contraptions custom-made for the ecological systems under study. Three-dimensional (3D) printing provides a way to rapidly produce identical and novel objects that could be used in ecological studies, yet ecologists have been slow to adopt this new technology. Here, we provide ecologists with an introduction to 3D printing. RESULTS First, we give an overview of the ecological research areas in which 3D printing is predicted to be the most impactful and review current studies that have already used 3D printed objects. We then outline a methodological workflow for integrating 3D printing into an ecological research program and give a detailed example of a successful implementation of our 3D printing workflow for 3D printed models of the brown anole, Anolis sagrei, for a field predation study. After testing two print media in the field, we show that the models printed from the less expensive and more sustainable material (blend of 70% plastic and 30% recycled wood fiber) were just as durable and had equal predator attack rates as the more expensive material (100% virgin plastic). CONCLUSIONS Overall, 3D printing can provide time and cost savings to ecologists, and with recent advances in less toxic, biodegradable, and recyclable print materials, ecologists can choose to minimize social and environmental impacts associated with 3D printing. The main hurdles for implementing 3D printing-availability of resources like printers, scanners, and software, as well as reaching proficiency in using 3D image software-may be easier to overcome at institutions with digital imaging centers run by knowledgeable staff. As with any new technology, the benefits of 3D printing are specific to a particular project, and ecologists must consider the investments of developing usable 3D materials for research versus other methods of generating those materials.
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Affiliation(s)
- Jocelyn E Behm
- Integrative Ecology Lab, Center for Biodiversity, Department of Biology, Temple University, Philadelphia, PA, USA. .,Department of Ecological Science-Animal Ecology, VU University Amsterdam, Amsterdam, The Netherlands.
| | - Brenna R Waite
- Integrative Ecology Lab, Center for Biodiversity, Department of Biology, Temple University, Philadelphia, PA, USA.,School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - S Tonia Hsieh
- Department of Biology, Temple University, Philadelphia, PA, USA
| | - Matthew R Helmus
- Integrative Ecology Lab, Center for Biodiversity, Department of Biology, Temple University, Philadelphia, PA, USA
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