S.P. Worner

620 total citations
30 papers, 466 citations indexed

About

S.P. Worner is a scholar working on Insect Science, Plant Science and Ecology. According to data from OpenAlex, S.P. Worner has authored 30 papers receiving a total of 466 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Insect Science, 15 papers in Plant Science and 9 papers in Ecology. Recurrent topics in S.P. Worner's work include Insect-Plant Interactions and Control (9 papers), Forest Insect Ecology and Management (7 papers) and Species Distribution and Climate Change (5 papers). S.P. Worner is often cited by papers focused on Insect-Plant Interactions and Control (9 papers), Forest Insect Ecology and Management (7 papers) and Species Distribution and Climate Change (5 papers). S.P. Worner collaborates with scholars based in New Zealand, Australia and France. S.P. Worner's co-authors include S. D. Wratten, G. Fry, Michael Watts, Muriel Gevrey, D.A.J. Teulon, Erja Huusela-Veistola, Irene Vänninen, Stéphane Boyer, Marie-Caroline Lefort and R. J. Hale and has published in prestigious journals such as Agriculture Ecosystems & Environment, Journal of Biogeography and Ecological Modelling.

In The Last Decade

S.P. Worner

28 papers receiving 430 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
S.P. Worner New Zealand 13 236 178 153 131 96 30 466
Leonard B. Coop United States 13 187 0.8× 102 0.6× 156 1.0× 108 0.8× 49 0.5× 29 364
Suzanne T. E. Lommen Netherlands 12 368 1.6× 233 1.3× 238 1.6× 197 1.5× 108 1.1× 36 604
Sarah M. Swope United States 11 107 0.5× 142 0.8× 149 1.0× 151 1.2× 137 1.4× 16 450
L. E. Parkinson Australia 7 184 0.8× 154 0.9× 191 1.2× 105 0.8× 146 1.5× 11 429
Mamoru Matsuki Australia 15 273 1.2× 288 1.6× 183 1.2× 356 2.7× 173 1.8× 19 651
Triinu Remmel Estonia 11 191 0.8× 153 0.9× 209 1.4× 390 3.0× 163 1.7× 14 623
Xosé López‐Goldar United States 12 121 0.5× 145 0.8× 101 0.7× 121 0.9× 98 1.0× 17 319
Guofei Fang China 12 123 0.5× 314 1.8× 199 1.3× 56 0.4× 60 0.6× 30 465
Brus Isua Czechia 10 177 0.8× 197 1.1× 138 0.9× 331 2.5× 229 2.4× 17 556
Nicky Lustenhouwer United States 7 95 0.4× 82 0.5× 108 0.7× 96 0.7× 96 1.0× 12 271

Countries citing papers authored by S.P. Worner

Since Specialization
Citations

This map shows the geographic impact of S.P. Worner's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S.P. Worner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S.P. Worner more than expected).

Fields of papers citing papers by S.P. Worner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S.P. Worner. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S.P. Worner. The network helps show where S.P. Worner may publish in the future.

Co-authorship network of co-authors of S.P. Worner

This figure shows the co-authorship network connecting the top 25 collaborators of S.P. Worner. A scholar is included among the top collaborators of S.P. Worner based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with S.P. Worner. S.P. Worner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mansfield, Sarah, et al.. (2016). Growth rate survival and preference of porina (<i>Wiseana</i> spp) to selected grasses. Proceedings of the New Zealand Weed Control Conference. 69. 326–326.
2.
Worner, S.P., et al.. (2015). Responding positively to plant defences, a candidate key trait for invasion success in phytophagous insects. Unitec Research Bank (Unitec Institute of Technology). 3 indexed citations
3.
Jamieson, L.E., et al.. (2013). A review of methods for assessing and managing market access and biosecurity risks using systems approaches. Proceedings of the New Zealand Weed Control Conference. 66. 1–9. 10 indexed citations
4.
5.
Eyre, Dominic, Richard Baker, Sophie Brunel‐Muguet, et al.. (2012). Rating and mapping the suitability of the climate for pest risk analysis*. EPPO Bulletin. 42(1). 48–55. 21 indexed citations
6.
7.
Lefort, Marie-Caroline, Stéphane Boyer, S.P. Worner, & Karen Armstrong. (2011). Noninvasive molecular methods to identify live scarab larvae: an example of sympatric pest and nonpest species in New Zealand. Molecular Ecology Resources. 12(3). 389–395. 29 indexed citations
8.
Schliebs, Stefan, et al.. (2011). Determining factors that influence the dispersal of a pelagic species: A comparison between artificial neural networks and evolutionary algorithms. Ecological Modelling. 222(10). 1657–1665. 6 indexed citations
9.
Kriticos, Darren J., et al.. (2010). Evidence of active or passive downwind dispersal in mark–release–recapture of moths. Entomologia Experimentalis et Applicata. 134(2). 160–169. 12 indexed citations
10.
Chapman, R. B., et al.. (2008). Forecasting emergence and movement of overwintering hazelnut big bud mites from big buds. Experimental and Applied Acarology. 45(1-2). 39–51. 6 indexed citations
11.
Sullivan, Jon J., et al.. (2008). Can spatial variation in epiphyte diversity and community structure be predicted from sampling vascular epiphytes alone?. Journal of Biogeography. 35(12). 2274–2288. 21 indexed citations
12.
Worner, S.P., et al.. (2007). The application of artificial neural networks in plant protection*. EPPO Bulletin. 37(2). 277–282. 4 indexed citations
13.
Gevrey, Muriel & S.P. Worner. (2006). Prediction of Global Distribution of Insect Pest Species in Relation to Climate by Using an Ecological Informatics Method. Journal of Economic Entomology. 99(3). 979–986. 32 indexed citations
14.
Watts, Michael & S.P. Worner. (2006). Using MLP to Determine Abiotic Factors In uencing the Establishment of Insect Pest Species. The 2006 IEEE International Joint Conference on Neural Network Proceedings. 1840–1845. 3 indexed citations
15.
Worner, S.P., et al.. (2002). Improving prediction of aphid flights by temporal analysis of input data for an artificial neural network. Proceedings of the New Zealand Weed Control Conference. 55. 312–316. 9 indexed citations
16.
Worner, S.P., et al.. (2001). Can artificial Neural Network Systems be used for forecasting aphid flight patterns. Proceedings of the New Zealand Weed Control Conference. 54. 188–192. 5 indexed citations
17.
Wratten, S. D., et al.. (1995). Permeability of hedgerows to predatory carabid beetles. Agriculture Ecosystems & Environment. 52(2-3). 141–148. 93 indexed citations
18.
Julien, M., et al.. (1995). The potential geographical distribution of alligator weed (<i>Alternanthera philoxeroides</i>) and a biological control agent, <i>Agasicles hygrophila</i>, in New Zealand. Proceedings of the New Zealand Weed Control Conference. 48. 270–275. 9 indexed citations
19.
Penman, D. R., et al.. (1987). An evaluation of a phenological model (PETE) to assist insect pest control in apple orchards in Canterbury, New Zealand. New Zealand Journal of Crop and Horticultural Science. 15(3). 381–388. 7 indexed citations
20.
Worner, S.P. & D. R. Penman. (1983). Analysis of thermal summation models. Proceedings of the New Zealand Weed Control Conference. 36. 250–254. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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