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Jarnevich C, Engelstad P, LaRoe J, Hays B, Hogan T, Jirak J, Pearse I, Prevéy J, Sieracki J, Simpson A, Wenick J, Young N, Sofaer HR. Invaders at the doorstep: Using species distribution modeling to enhance invasive plant watch lists. ECOL INFORM 2023. [DOI: 10.1016/j.ecoinf.2023.101997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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Takaya K, Sasaki Y, Ise T. Automatic detection of alien plant species in action camera images using the chopped picture method and the potential of citizen science. BREEDING SCIENCE 2022; 72:96-106. [PMID: 36045894 PMCID: PMC8987844 DOI: 10.1270/jsbbs.21062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 12/20/2021] [Indexed: 06/15/2023]
Abstract
Monitoring and detection of invasive alien plant species are necessary for effective management and control measures. Although efforts have been made to detect alien trees using satellite images, the detection of alien herbaceous species has been difficult. In this study, we examined the possibility of detecting non-native plants using deep learning on images captured by two action cameras. We created a model for each camera using the chopped picture method. The models were able to detect the alien plant Solidago altissima (tall goldenrod) and obtained an average accuracy of 89%. This study proved that it is possible to automatically detect exotic plants using inexpensive action cameras through deep learning. This advancement suggests that, in the future, citizen science may be useful for conducting distribution surveys of alien plants in a wide area at a low cost.
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Affiliation(s)
- Kosuke Takaya
- Graduate School of Agriculture, Kyoto University, Kitashirakawaoiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan
| | - Yu Sasaki
- Center for the Promotion of Interdisciplinary Education and Research, Kyoto University, Kitashirakawaoiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan
| | - Takeshi Ise
- Field Science Education and Research Center, Kyoto University, Kitashirakawaoiwake-cho, Sakyo-ku, Kyoto 606-8502, Japan
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Bindewald A, Brundu G, Schueler S, Starfinger U, Bauhus J, Lapin K. Site-specific risk assessment enables trade-off analysis of non-native tree species in European forests. Ecol Evol 2021; 11:18089-18110. [PMID: 35003660 PMCID: PMC8717284 DOI: 10.1002/ece3.8407] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 10/27/2021] [Accepted: 11/12/2021] [Indexed: 12/23/2022] Open
Abstract
Non-native tree species (NNT) are used in European forestry for many purposes including their growth performance, valuable timber, and resistance to drought and pest or pathogen damage. Yet, cultivating NNT may pose risks to biodiversity, ecosystem functioning, and the provisioning of ecosystem services, and several NNT have been classified as invasive in Europe. Typically, such classifications are based on risk assessments, which do not adequately consider site-specific variations in impacts of the NNT or the extent of affected areas. Here, we present a new methodological framework that facilitates both mitigating risks associated with NNT and taking advantage of their ecosystem services. The framework is based on a stratified assessment of risks posed by NNT which distinguishes between different sites and considers effectiveness of available management strategies to control negative effects. The method can be applied to NNT that already occur in a given area or those NNT that may establish in future. The framework consists of eight steps and is partly based on existing knowledge. If adequate site-specific knowledge on NNT does not yet exist, new evidence on the risks should be obtained, for example, by collecting and analyzing monitoring data or modeling the potential distribution of NNT. However, limitations remain in the application of this method, and we propose several policy and management recommendations which are required to improve the responsible use of NNT.
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Affiliation(s)
- Anja Bindewald
- Department of Forest ConservationForest Research Institute of Baden‐Württemberg (FVA)FreiburgGermany
- Chair of SilvicultureUniversity of FreiburgFreiburgGermany
| | - Giuseppe Brundu
- Department of Agricultural SciencesUniversity of SassariSassariItaly
| | | | - Uwe Starfinger
- Julius Kühn‐Institut (JKI)Federal Research Centre for Cultivated PlantsBraunschweigGermany
| | - Jürgen Bauhus
- Chair of SilvicultureUniversity of FreiburgFreiburgGermany
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Assessment of the Spatial Invasion Risk of Intentionally Introduced Alien Plant Species (IIAPS) under Environmental Change in South Korea. BIOLOGY 2021; 10:biology10111169. [PMID: 34827162 PMCID: PMC8614709 DOI: 10.3390/biology10111169] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 11/03/2021] [Accepted: 11/09/2021] [Indexed: 12/21/2022]
Abstract
Predicting the regions at risk of invasion from IIAPS is an integral horizon-scanning activity that plays a crucial role in preventing, controlling, and eradicating invasive species. Here, we quantify the spatial distribution area and invasion risk of IIAPS using a species distribution model under different levels of environmental change in South Korea. From the model predictions, the current average spatial extent of the 10 IIAPS is 33,948 km2, and the individual spatial extents are estimated to change by -7% to 150% by 2050 and by -9% to 156% by 2070. The spatial invasion risk assessment shows that, currently, moderate-to-high invasion risk is limited to coastal areas and densely populated metropolitan cities (e.g., Seoul, Busan, and Gwangju), but that the area with this level of risk is expected to spread toward the central and northern regions of the country in the future, covering 86.21% of the total area of the country by 2070. These results demonstrate that the risk of invasion by IIAPS is estimated to enlarge across the whole country under future environmental changes. The modeling system provided in this study may contribute to the initial control and strategic management of IIAPS to maintain the dynamic ecosystems of South Korea.
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Hong SH, Lee YH, Lee G, Lee DH, Adhikari P. Predicting Impacts of Climate Change on Northward Range Expansion of Invasive Weeds in South Korea. PLANTS (BASEL, SWITZERLAND) 2021; 10:plants10081604. [PMID: 34451649 PMCID: PMC8401637 DOI: 10.3390/plants10081604] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/27/2021] [Accepted: 08/01/2021] [Indexed: 05/04/2023]
Abstract
Predicting the distribution of invasive weeds under climate change is important for the early identification of areas that are susceptible to invasion and for the adoption of the best preventive measures. Here, we predicted the habitat suitability of 16 invasive weeds in response to climate change and land cover changes in South Korea using a maximum entropy modeling approach. Based on the predictions of the model, climate change is likely to increase habitat suitability. Currently, the area of moderately suitable and highly suitable habitats is estimated to be 8877.46 km2, and 990.29 km2, respectively, and these areas are expected to increase up to 496.52% by 2050 and 1439.65% by 2070 under the representative concentration pathways 4.5 scenario across the country. Although habitat suitability was estimated to be highest in the southern regions (<36° latitude), the central and northern regions are also predicted to have substantial increases in suitable habitat areas. Our study revealed that climate change would exacerbate the threat of northward weed invasions by shifting the climatic barriers of invasive weeds from the southern region. Thus, it is essential to initiate control and management strategies in the southern region to prevent further invasions into new areas.
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Affiliation(s)
- Sun Hee Hong
- School of Plant Science and Landscape Architecture, Hankyong National University, Anseong-si 17579, Gyeonggi-do, Korea;
| | - Yong Ho Lee
- Institute of Ecological Phytochemistry, Hankyong National University, Anseong-si 17579, Gyeonggi-do, Korea; (Y.H.L.); (G.L.)
- OJeong Resilience Institute, Korea University, Seongbuk-gu, Seoul 02841, Korea
| | - Gaeun Lee
- Institute of Ecological Phytochemistry, Hankyong National University, Anseong-si 17579, Gyeonggi-do, Korea; (Y.H.L.); (G.L.)
| | - Do-Hun Lee
- National Institute of Ecology, Seocheon-gun 33657, Chungcheongnam-do, Korea;
| | - Pradeep Adhikari
- Institute of Ecological Phytochemistry, Hankyong National University, Anseong-si 17579, Gyeonggi-do, Korea; (Y.H.L.); (G.L.)
- Correspondence: ; Tel.: +82-31-670-5087
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Rojas‐Sandoval J, Ackerman JD, Tremblay RL. Island biogeography of native and alien plant species: Contrasting drivers of diversity across the Lesser Antilles. DIVERS DISTRIB 2020. [DOI: 10.1111/ddi.13139] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Affiliation(s)
- Julissa Rojas‐Sandoval
- Institute of the Environment University of Connecticut Storrs CT USA
- Department of Botany National Museum of Natural History Smithsonian Institution Washington DC USA
| | | | - Raymond L. Tremblay
- Department of Biology University of Puerto Rico San Juan PR USA
- Analítica Fundación Caguas PR USA
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Modeling the Potential Global Distribution of Phenacoccus madeirensis Green under Various Climate Change Scenarios. FORESTS 2019. [DOI: 10.3390/f10090773] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The Madeira mealybug, Phenacoccus madeirensis Green, is a serious invasive pest that does significant damage to more than 120 genera of host plants from 51 families in more than 81 countries. However, the potential distribution range of this pest is unclear, which could hamper control and eradication efforts. In the current study, MaxEnt models were developed to forecast the current and future distribution of the Madeira mealybug around the world. Moreover, the future potential distribution of this invasive species was projected for the 2050s and 2070s under three different climate change scenarios (HADGEM2-AO, GFDL-CM3, and MIROC5) and two representative concentration pathways (RCP-2.6 and RCP-8.5). The final model indicates that the Madeira mealybug has a highly suitable range for the continents of Asia, Europe, and Africa, as well as South America and North America, where this species has already been recorded. Potential expansions or reductions in distribution were also simulated under different future climatic conditions. Our study also suggested that the mean temperature of the driest quarter (Bio9) was the most important factor and explained 46.9% of the distribution model. The distribution model from the current and future predictions can enhance the strategic planning of agricultural and forestry organization by identifying regions that will need to develop integrated pest management programs to manage Madeira mealybug, especially for some highly suitable areas, such as South Asia and Europe. Moreover, the results of this research will help governments to optimize investment in the control and management of the Madeira mealybug by identifying regions that are or will become suitable for infestations.
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Zettlemoyer MA, McKenna DD, Lau JA. Species characteristics affect local extinctions. AMERICAN JOURNAL OF BOTANY 2019; 106:547-559. [PMID: 30958894 DOI: 10.1002/ajb2.1266] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Accepted: 02/04/2019] [Indexed: 06/09/2023]
Abstract
PREMISE OF THE STUDY Human activities threaten thousands of species with extinction. However, it remains difficult to predict extinction risk for many vulnerable species. Species traits, species characteristics such as rarity or habitat use, and phylogenetic patterns are associated with responses to anthropogenic environmental change and may help predict likelihood of extinction. METHODS We used historical botanical data from Kalamazoo County, Michigan, USA, to examine whether species traits (growth form, life history, nitrogen-fixation, photosynthetic pathway), species characteristics (community association, species origin, range edge, habitat specialization, rarity), or phylogenetic relatedness explain local species loss at the county level. KEY RESULTS Across Kalamazoo County, prairie species, species at the edge of their native range, regionally rare species, and habitat specialists were most likely to become locally extinct. Prairie species experienced the highest local extinction rates of any habitat type, and among prairie species, regionally rare and specialist species were most vulnerable to loss. We found no evidence for a phylogenetic pattern in plant extinctions. CONCLUSIONS Our study illustrates the value of historical datasets for understanding and potentially predicting biodiversity loss. Not surprisingly, rare, specialist species occupying threatened habitats are most at risk of local extinction. As a result, identifying mechanisms to conserve or restore rare or declining species and preventing further habitat destruction may be the most effective strategies for reducing future extinction.
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Affiliation(s)
- Meredith A Zettlemoyer
- Department of Plant Biology, Michigan State University, East Lansing, Michigan, 48824-6406, USA
- Kellogg Biological Station, Michigan State University, Hickory Corners, Michigan, 49060-9505, USA
| | - Duane D McKenna
- Department of Biological Sciences, University of Memphis, Memphis, Tennessee, 38152-3560, USA
| | - Jennifer A Lau
- Department of Plant Biology, Michigan State University, East Lansing, Michigan, 48824-6406, USA
- Kellogg Biological Station, Michigan State University, Hickory Corners, Michigan, 49060-9505, USA
- Department of Biology, Indiana University-Bloomington, Bloomington, Indiana, 47405-7005, USA
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Capinha C, Essl F, Seebens H, Pereira HM, Kühn I. Models of alien species richness show moderate predictive accuracy and poor transferability. NEOBIOTA 2018. [DOI: 10.3897/neobiota.38.23518] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Robust predictions of alien species richness are useful to assess global biodiversity change. Nevertheless, the capacity to predict spatial patterns of alien species richness remains largely unassessed. Using 22 data sets of alien species richness from diverse taxonomic groups and covering various parts of the world, we evaluated whether different statistical models were able to provide useful predictions of absolute and relative alien species richness, as a function of explanatory variables representing geographical, environmental and socio-economic factors. Five state-of-the-art count data modelling techniques were used and compared: Poisson and negative binomial generalised linear models (GLMs), multivariate adaptive regression splines (MARS), random forests (RF) and boosted regression trees (BRT). We found that predictions of absolute alien species richness had a low to moderate accuracy in the region where the models were developed and a consistently poor accuracy in new regions. Predictions of relative richness performed in a superior manner in both geographical settings, but still were not good. Flexible tree ensembles-type techniques (RF and BRT) were shown to be significantly better in modelling alien species richness than parametric linear models (such as GLM), despite the latter being more commonly applied for this purpose. Importantly, the poor spatial transferability of models also warrants caution in assuming the generality of the relationships they identify, e.g. by applying projections under future scenario conditions. Ultimately, our results strongly suggest that predictability of spatial variation in richness of alien species richness is limited. The somewhat more robust ability to rank regions according to the number of aliens they have (i.e. relative richness), suggests that models of aliens species richness may be useful for prioritising and comparing regions, but not for predicting exact species numbers.
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Magarey R, Newton L, Hong SC, Takeuchi Y, Christie D, Jarnevich CS, Kohl L, Damus M, Higgins SI, Millar L, Castro K, West A, Hastings J, Cook G, Kartesz J, Koop AL. Comparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States. Biol Invasions 2017. [DOI: 10.1007/s10530-017-1567-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Padalia H, Bahuguna U. Spatial modelling of congruence of native biodiversity and potential hotspots of forest invasive species (FIS) in central Indian landscape. J Nat Conserv 2017. [DOI: 10.1016/j.jnc.2017.02.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Crall AW, Jarnevich CS, Young NE, Panke BJ, Renz M, Stohlgren TJ. Citizen science contributes to our knowledge of invasive plant species distributions. Biol Invasions 2015. [DOI: 10.1007/s10530-015-0885-4] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Byers JE, McDowell WG, Dodd SR, Haynie RS, Pintor LM, Wilde SB. Climate and pH predict the potential range of the invasive apple snail (Pomacea insularum) in the southeastern United States. PLoS One 2013; 8:e56812. [PMID: 23451090 PMCID: PMC3579942 DOI: 10.1371/journal.pone.0056812] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2012] [Accepted: 01/14/2013] [Indexed: 11/19/2022] Open
Abstract
Predicting the potential range of invasive species is essential for risk assessment, monitoring, and management, and it can also inform us about a species' overall potential invasiveness. However, modeling the distribution of invasive species that have not reached their equilibrium distribution can be problematic for many predictive approaches. We apply the modeling approach of maximum entropy (MaxEnt) that is effective with incomplete, presence-only datasets to predict the distribution of the invasive island apple snail, Pomacea insularum. This freshwater snail is native to South America and has been spreading in the USA over the last decade from its initial introductions in Texas and Florida. It has now been documented throughout eight southeastern states. The snail's extensive consumption of aquatic vegetation and ability to accumulate and transmit algal toxins through the food web heighten concerns about its spread. Our model shows that under current climate conditions the snail should remain mostly confined to the coastal plain of the southeastern USA where it is limited by minimum temperature in the coldest month and precipitation in the warmest quarter. Furthermore, low pH waters (pH <5.5) are detrimental to the snail's survival and persistence. Of particular note are low-pH blackwater swamps, especially Okefenokee Swamp in southern Georgia (with a pH below 4 in many areas), which are predicted to preclude the snail's establishment even though many of these areas are well matched climatically. Our results elucidate the factors that affect the regional distribution of P. insularum, while simultaneously presenting a spatial basis for the prediction of its future spread. Furthermore, the model for this species exemplifies that combining climatic and habitat variables is a powerful way to model distributions of invasive species.
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Affiliation(s)
- James E Byers
- Odum School of Ecology, University of Georgia, Athens, Georgia, United States of America.
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Crall AW, Jarnevich CS, Panke B, Young N, Renz M, Morisette J. Using habitat suitability models to target invasive plant species surveys. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2013; 23:60-72. [PMID: 23495636 DOI: 10.1890/12-0465.1] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P < 0.01), and targeted sampling did detect more species than nontargeted sampling with less sampling effort (chi2 = 47.42, P < 0.01). From these findings, we conclude that habitat suitability models can be highly useful tools for guiding invasive species monitoring, and we support the use of an iterative sampling design for guiding such efforts.
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Affiliation(s)
- Alycia W Crall
- Department of Agronomy, University of Wisconsin, 1575 Linden Drive, Madison, Wisconsin 53706, USA.
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Challenges of predicting the potential distribution of a slow-spreading invader: a habitat suitability map for an invasive riparian tree. Biol Invasions 2010. [DOI: 10.1007/s10530-010-9798-4] [Citation(s) in RCA: 61] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Crall AW, Newman GJ, Jarnevich CS, Stohlgren TJ, Waller DM, Graham J. Improving and integrating data on invasive species collected by citizen scientists. Biol Invasions 2010. [DOI: 10.1007/s10530-010-9740-9] [Citation(s) in RCA: 151] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Denslow JS, Space JC, Thomas PA. Invasive Exotic Plants in the Tropical Pacific Islands: Patterns of Diversity. Biotropica 2009. [DOI: 10.1111/j.1744-7429.2008.00469.x] [Citation(s) in RCA: 65] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Pysek P, Richardson DM, Pergl J, Jarosík V, Sixtová Z, Weber E. Geographical and taxonomic biases in invasion ecology. Trends Ecol Evol 2008; 23:237-44. [PMID: 18367291 DOI: 10.1016/j.tree.2008.02.002] [Citation(s) in RCA: 490] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2008] [Revised: 02/11/2008] [Accepted: 02/12/2008] [Indexed: 11/30/2022]
Affiliation(s)
- Petr Pysek
- Institute of Botany, Academy of Sciences of the Czech Republic, Průhonice, Czech Republic.
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Rodríguez JP, Brotons L, Bustamante J, Seoane J. The application of predictive modelling of species distribution to biodiversity conservation. DIVERS DISTRIB 2007. [DOI: 10.1111/j.1472-4642.2007.00356.x] [Citation(s) in RCA: 259] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Flather CH, Stohlgren TJ, Jarnevich C, Barnett D, Kartesz J. PLANT SPECIES INVASIONS ALONG THE LATITUDINAL GRADIENT IN THE UNITED STATES: REPLY. Ecology 2006. [DOI: 10.1890/0012-9658(2006)87[3213:psiatl]2.0.co;2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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