A Food Web Approach to Evaluating the Effect of Insecticide Spraying on Insect Pest Population Dynamics in a Philippine Irrigated Rice Ecosystem

Cohen, Joel E.; Schoenly, K.L.; Heong, K. L.; Justo, H. D.; Arida, G. S.; Barrion, A. T.; Litsinger, J. A.

doi:10.2307/2404165

Cited by 99 publications

(53 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Tampering with the population of one species can cause surprising and dramatic changes in the populations of others (Cohen et al, 1994;Henneman and Memmott, 2001). Altering pressures to which ecosystems are exposed can drive them to alternative states (Beisner et al, 2003) or catastrophic failure (Sinclair and Byrom, 2006).…”

Section: Introductionmentioning

confidence: 99%

Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods

Faisal

Dondelinger

Husmeier

et al. 2010

Ecological Informatics

View full text Add to dashboard Cite

The complexity of ecosystems is staggering, with hundreds or thousands of species interacting in a number of ways from competition and predation to facilitation and mutualism. Understanding the networks that form the systems is of growing importance, e.g. to understand how species will respond to climate change, or to predict potential knock-on effects of a biological control agent. In recent years, a variety of summary statistics for characterising the global and local properties of such networks have been derived, which provide a measure for gauging the accuracy of a mathematical model for network formation processes. However, the critical underlying assumption is that the true network is known. This is not a straightforward task to accomplish, and typi- * Corresponding author. Tel: +44 (0) cally requires minute observations and detailed field work. More importantly, knowledge about species interactions is restricted to specific kinds of interactions. For instance, while the interactions between pollinators and their host plants are amenable to direct observation, other types of species interactions, like those mentioned above, are not, and might not even be clearly defined from the outset. To discover information about complex ecological systems efficiently, new tools for inferring the structure of networks from field data are needed. In the present study, we investigate the viability of various statistical and machine learning methods recently applied in molecular systems biology: graphical Gaussian models, L1-regularised regression with least absolute shrinkage and selection operator (LASSO), sparse Bayesian regression and Bayesian networks. We have assessed the performance of these methods on data simulated from food webs of known structure, where we combined a niche model with a stochastic population model in a 2-dimensional lattice.We assessed the network reconstruction accuracy in terms of the area under the receiver operator characteristics (ROC) curve, which was typically in the range between 0.75 and 0.9, corresponding to the recovery of about 60% of the true species interactions at a false prediction rate of 5%. We also applied the models to presence/absence data for 39 European warblers, and found that the inferred species interactions showed a weak yet significant correlation with phylogenetic similarity scores, which tended to weakly increase when including bio-climate covariates and allowing for spatial autocorrelation. Our findings demonstrate that relevant patterns in ecological networks can be identified from large-scale spatial data sets with machine learning methods, and that these methods have the potential to contribute novel important tools for gaining deeper insight into the structure and stability of ecosystems.

show abstract

Section: Introductionmentioning

confidence: 99%

Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods

Faisal

Dondelinger

Husmeier

et al. 2010

Ecological Informatics

View full text Add to dashboard Cite

show abstract

“…A sokvál-tozós módszerek, diverzitásmutatók és az ezeket alkalmazó szoftver csomagok elterjedése óta az összetételen alapuló mintázatelemzést rendkívül széles körben alkalmazzák nem csak az agrár-, de a természetes élőhelyek állategyütteseinek elemzésében is (GAUCH 1982, PODANI 1997, MAGURRAN 2004. Bár kiterjedt agrárzoológiai kutatások foglalkoztak a hasznos szervezetek szerepével a kártevők korlátozásában, táplálkozási hálózatokat, külö-nösen peszticidterhelésnek kitett mezőgazdasági területeken, ritkán vizsgáltak (COHEN et al 1994).…”

Section: Az 1950-es éVek Utánunclassified

Journey to the sources of community ecology − Gusztáv Szelényi’s agrozoocoenology and the Balogh–Szelényi debate

Markó¹

2015

Állattani Közlemények

View full text Add to dashboard Cite

"Egy működő elmélet alapvető próbája az, hogy milyen mértékben képes körültekintő és mélyreható kutatásokat ösztönözni." (HENRY C. COWLES) 2Összefoglalás. BALOGH JÁNOS és SZELÉNYI GUSZTÁV zoocönológiai vitája a hazai ökológia történeté-nek jelentős eseménye. A tanulmányban áttekintem a közösségi ökológia születését Magyarországon, főbb irányzatait az 1950-es években, és a BALOGH-SZELÉNYI-vitát. Bemutatom, hogy a vegetációku-tatás, a fitocönológia és az állategyüttesekkel foglalkozó közösségi ökológia 20. század első felében kialakult fontosabb modelljei hogyan vezettek BALOGH és SZELÉNYI zoocönológiai elképzeléseihez. BALOGH JÁNOS az észak-európai fitocönológiai iskola nyomdokain dolgozta ki koncepcióját, míg SZELÉNYI GUSZTÁV CHARLES ELTON modelljét fejlesztette tovább úgy, hogy a fajok trofikus specializációja alapján a táplálékhálón belül kisebb egységeket különített el. A tanulmány második felében sorra veszem, hogy milyen szemléleti keretek között értelmezhetők a közösségi ökológia korai koncepciói, és hogy BALOGH és SZELÉNYI elképzelései hogyan illeszthetők ezek közé a keretek közé. Vé-gül röviden kitérek arra, hogy BALOGH és SZELÉNYI állategyüttesek elemzésére és osztályozására tett kísérletei mennyire relevánsak a mai ökológia számára. Kulcsszavak: SZELÉNYI GUSZTÁV, BALOGH JÁNOS, zoocönológia, szünmorfológia, közösségi ökoló-gia története BevezetésKevés állatfajról tudunk annyit, mint a kártevőkről. A növényvédelmi állattannal foglalkozó átfogó munkák sokszor grandiózus terjedelemben tárgyalják a haszonnövényekhez kötődő fitofág fajok életmódját. Bár a kutatások jelentős része csupán néhány tucat kulcskártevő-fajra irányul, mégis populációbiológiájukról, egyedszámuk szabályozásáról tudományos folyóiratok lapjain sok ezer publikáció jelent meg. A "Google Tudós" kereső az "insect" és "pest management" vagy "plant protection" kifejezések együttes előfordulását -az átfedéseket kiszűrve -356 000 publikációban jelzi. Ha ezekhez hozzátesszük az

show abstract

“…Bignal and McCracken 1996;Pain and Pienkowski 1997;Ovenden et al 1998;Maeda 2001;Amano et al 2008). For instance, about 2000 species of plants and animals associated with rice paddy fields have been recorded in Japan (Hidaka 1998), 645 animal species were collected in the Philippines (Cohen et al 1994), and…”

Section: A Multi-scale Cause-effect Approachmentioning

confidence: 99%

“…Further, looking at landscape structure in a broader sense, landscape fragmentation has negative impacts on habitat suitability and biodiversity (Noss 1990;Di Giulio et al 2009). Changes in landscape structure were assessed based on the observations of fine-scale (<30 m) agricultural landscape transformation processes in northwest Taihu Lake Basin: Xiejia Village of Xueyan Township, Wujing County during 1930-1994(Ellis et al 2000 and a single field research site in Yixing County during 1989-2002). These studies stratified a village landscape into about 35-40 fine-scale landscape components with relatively homogeneous ecosystem processes (called ecotopes) by gathering data from aerial photography, field surveys, local knowledge, household surveys, interviewing elder villagers and historical sources.…”

Section: Assessing Pressures On Biodiversity At Landscape Leveltransfmentioning

confidence: 99%

Impacts of agricultural land-use changes on biodiversity in Taihu Lake Basin, China: a multi-scale cause–effect approach considering multiple land-use functions

Asai

Reidsma

Feng

2010

International Journal of Biodiversity Science, Ecosystem Servic

View full text Add to dashboard Cite

This paper aims to assess the impacts of agricultural land-use changes on biodiversity in Taihu Lake Basin, China, and to identify possible conservation strategies. We used the mean species abundance (MSA) approach, building on simple causeeffect relationships between environmental drivers and biodiversity impacts at the global level. Our assessment estimated that 21% of the original species in the undisturbed ecosystem were present in 2000. We also analysed and reviewed agricultural pressures at different spatial scales to enable the development of conservation strategies at regional and farm levels. This analysis showed, first, that intensive crop management is reflected by the amount of fertilisers applied. Policies and technologies aiming to reduce environmental impacts have been ineffective. Second, the abundance of semi-natural elements was found to be low and the fragmentation high. To link agricultural pressures to the MSA approach, we propose a multi-scale cause-effect approach, which can be linked to other land uses. This approach is useful to provide a quick scan of biodiversity status and identify conservation strategies. Training farmers to use site-specific nutrient management should be stimulated. Furthermore, acknowledging multiple land-use functions will help to develop biodiversity conservation strategies that are acceptable to farmers and policymakers.

show abstract

A Food Web Approach to Evaluating the Effect of Insecticide Spraying on Insect Pest Population Dynamics in a Philippine Irrigated Rice Ecosystem

Abstract: Population dynamics in a Philippine rice food web besides spraying (such as the introduction of genetically engineered cultivars), other biotic communities besides arthropods, and other crops besides rice.

Cited by 99 publications

References 28 publications

Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods

Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods

Journey to the sources of community ecology − Gusztáv Szelényi’s agrozoocoenology and the Balogh–Szelényi debate

Impacts of agricultural land-use changes on biodiversity in Taihu Lake Basin, China: a multi-scale cause–effect approach considering multiple land-use functions

Contact Info

Product

Resources

About