New Tool Uses Satellite Data to Combat Olive Fruit Fly

At a recent con­fer­ence held at the European Space Agency in Frascati, Italy, researchers show­cased a tool that can help com­bat and pre­vent olive fruit fly infes­ta­tions in the face of cli­mate change.

The project stems from inte­grat­ing the bio­log­i­cal cycles of the olive tree and the olive fruit fly with rel­e­vant satel­lite data.

“We should con­sider this project as a new con­tri­bu­tion to ongo­ing pest con­trol efforts,” Luigi Ponti, a researcher at the Italian National Agency for New Technologies, Energy and Sustainable Economic Development, told Olive Oil Times.

You can’t con­duct ten years of field tri­als across all of Puglia. But this model lets you do that vir­tu­ally within min­utes.- Luigi Ponti, researcher, ENEA

A cru­cial source of data for the project comes from satel­lite obser­va­tions made using mod­er­ate-res­o­lu­tion imag­ing spec­tro­ra­diome­ter (MODIS) sen­sors installed aboard two NASA satel­lites, Terra and Aqua.

Over the past two decades, these sen­sors have mea­sured sev­eral sur­face vari­ables, such as veg­e­ta­tion indices, while also pro­vid­ing highly reli­able land sur­face tem­per­a­ture data.

“They mea­sured sur­face tem­per­a­ture from space with daily tem­po­ral res­o­lu­tion, also cap­tur­ing approx­i­mate daily max­i­mum and min­i­mum tem­per­a­tures thanks to their over­pass times,” Ponti said. 

See Also:Decoding the Olive Fly’s Symbiotic Secret

Previous research by Markus Neteler, founder of Mundialis, a German part­ner com­pany in the project, devised a method to extract tem­per­a­ture data from the satel­lite obser­va­tions.

Additionally, a method­ol­ogy based on sta­tis­tics and spa­tial infor­ma­tion was devel­oped to fill in the gaps caused by cloud cover, since MODIS sen­sors can­not see through clouds.

The research pre­sented by Ponti and his col­leagues aimed to link this broad dataset to a MODIS-derived veg­e­ta­tion index known as the Normalized Difference Vegetation Index (NDVI).

MODIS NDVI mea­sures the amount of green veg­e­ta­tion on Earth’s sur­face, pro­vid­ing infor­ma­tion about land cover through­out the year. That infor­ma­tion can be used to enhance tem­per­a­ture data derived from MODIS satel­lites.

The effec­tive­ness of this approach builds on ear­lier research by a team of Israeli sci­en­tists who devel­oped a method to cal­i­brate MODIS-derived land sur­face tem­per­a­tures using NDVI data.

“They installed ther­mome­ters inside olive tree canopies and found that the tem­per­a­ture derived from MODIS satel­lites, once cor­rected using MODIS NDVI, esti­mated canopy tem­per­a­ture bet­ter than the near­est weather sta­tion,” Ponti said.

Thanks to these data, it is pos­si­ble to esti­mate the tem­per­a­ture expe­ri­enced by both the plant and the olive fruit fly.

“If we want real agri­cul­tural impact, we need to observe what hap­pens day by day, because that’s how plants and inter­act­ing organ­isms oper­ate,” Ponti noted.

The need for highly pre­cise infor­ma­tion about agroe­cosys­tems led to the devel­op­ment of the phys­i­o­log­i­cally based demo­graphic model of the olive agroe­cosys­tem in col­lab­o­ra­tion with the non-profit sci­en­tific con­sor­tium CASAS Global.

The mod­el’s out­put is a detailed and real­is­tic bio­log­i­cal rep­re­sen­ta­tion of the life cycles of the olive tree and the olive fruit fly, includ­ing their inter­ac­tions.

This type of mod­el­ing, which com­bines a top-down approach (using satel­lite data) with a bot­tom-up approach (bio­log­i­cal mech­a­nisms), over­comes the lim­i­ta­tions of both and pro­vides a pow­er­ful tool for strate­gic analy­sis in agri­cul­tural man­age­ment.

The com­bi­na­tion of satel­lite obser­va­tions, bio­log­i­cal mod­el­ing and open-source geo­graphic infor­ma­tion tools allows researchers to visu­al­ize and ana­lyze dynam­ics with unprece­dented tem­po­ral (daily) and spa­tial (250-meter) res­o­lu­tion.

“For the plant, [the model] sim­u­lates leaf pop­u­la­tions, branch pop­u­la­tions and root pop­u­la­tions. With the same base model, it sim­u­lates birth, growth, aging and death of plant organs or insect stages,” Ponti said.

“So we use the same model to describe both insects and plants in our olive – olive fruit fly sys­tem,” he added.

For the plant, the pri­mary resource is the energy in solar radi­a­tion, along with nutri­ents and water from the soil. For the fly, the resource is the plant it feeds on: how many olives it can find to lay eggs. Its vital rates (growth, repro­duc­tion) depend on olive avail­abil­ity.

“This gives the mod­els a degree of bio­log­i­cal real­ism, because they’re con­strained by the real-world resource con­straints that organ­isms face,” Ponti said.

“If the fly doesn’t find olives, it goes into repro­duc­tive qui­es­cence, just like in nature. So, it’s not a tool to ​‘pre­dict’ an infes­ta­tion exactly, but it can tell you that under cer­tain con­di­tions, the envi­ron­ment is suit­able for one,” he explained.

“You can’t say ​‘the fly will arrive tomor­row,’ but you can say ​‘this area cur­rently has con­di­tions that would sup­port fly devel­op­ment,’” Ponti added.

Just like weather fore­casts, bio­log­i­cal fore­casts are chal­leng­ing. Weather fore­cast­ing itself is con­sid­ered unre­li­able beyond a short period of about three days.

“Still, we use weather data as input for our bio­log­i­cal mod­els, so uncer­tainty com­pounds,” Ponti said. ​“What our mod­els add is strate­gic infor­ma­tion.” 

Forecasting can indi­cate when to act, but it can­not tell you why some­thing is hap­pen­ing or how to pre­pare more effec­tively in a chang­ing cli­mate.

“That requires under­stand­ing mech­a­nisms and dynam­ics in the field,” Ponti said. ​“That’s the point: if the olive fly is a key pest, how can we man­age it bet­ter eco­nom­i­cally and oper­a­tionally, espe­cially under cli­mate change, where the assump­tions about cli­mate are obso­lete and the con­se­quent man­age­ment rules may no longer apply?” 

See Also:Researchers Develop Algorithm to Predict Harvest Potential from Climate Data

“We showed this clearly in our work in Andalusia,” he added. ​“For instance, in some areas, there are not enough chill­ing hours to induce flow­er­ing in olives any­more. In warmer areas, the fly pop­u­la­tion stays below thresh­old due to high tem­per­a­tures that approach or exceed the fly’s ther­mal tol­er­ance.” 

Using more pre­cise cli­mate and veg­e­ta­tive infor­ma­tion can help pol­i­cy­mak­ers reshape pest con­trol strate­gies.

Region-spe­cific inter­ven­tions and poli­cies, such as those in Andalusia, where inte­grated con­trol orga­ni­za­tions mon­i­tor and pre­scribe treat­ments, rely on ana­lyz­ing past data.

“For exam­ple, mon­i­tor­ing might tra­di­tion­ally start in May, but if win­ters are warmer, it may be more use­ful to start ear­lier,” Ponti said.

The olive fruit fly has rapid pop­u­la­tion growth, is closely syn­chro­nized with the olive tree’s life­cy­cle, and can repro­duce year-round as soon as olive fruit and cli­mate are suit­able. This makes it a sig­nif­i­cant pest of olive crops world­wide.

“If not mon­i­tored and con­trolled early, it gets out of hand quickly,” Ponti said. ​“So the best approach may be to mon­i­tor even dur­ing the ​‘quiet’ sea­son, late win­ter or early spring. With future cli­mate trends, being proac­tive will be cru­cial.”

As the weather becomes increas­ingly unpre­dictable and extreme events become more com­mon, to the point where they are no longer excep­tional, agri­cul­tural insti­tu­tions find it increas­ingly chal­leng­ing to plan effec­tive pro­tec­tion ser­vices.

“This mod­el­ing tool gives you a real­is­tic view of what’s hap­pen­ing in the field, some­thing you could never get through field obser­va­tions at this scale, for this dura­tion,” Ponti said.

“In Puglia, we sim­u­lated 20 years of olive and fly dynam­ics on a daily timescale at 250-meter res­o­lu­tion for hun­dreds of thou­sands of loca­tions, thanks to cloud com­put­ing pro­vided by the Italian part­ner Recube,” he added.

“Getting the same kind of data from field obser­va­tions would sim­ply be impos­si­ble. This kind of sys­tem gives you that field-level insight essen­tially for free,” Ponti con­tin­ued.

Since cli­mate affects plants and insects dif­fer­ently, their inter­ac­tions and bal­ance shift.

“That’s impor­tant to know. You could sim­u­late dif­fer­ent man­age­ment sce­nar­ios, such as ear­lier inter­ven­tion, and eval­u­ate how ben­e­fi­cial it is,” Ponti said.

“You can’t con­duct ten years of field tri­als across all of Puglia. But this model lets you do that vir­tu­ally within min­utes,” he added. ​“So, while it’s not meant for short-term fore­cast­ing, because that would require per­fectly detailed real-time bio­log­i­cal and cli­mate data, it’s great for describ­ing and plan­ning strate­gi­cally.”

The NASA Aqua and Terra satel­lites are on track to be decom­mis­sioned. As a result, researchers are already work­ing on using other satel­lites, such as those launched by Eumetsat and the European Space Agency, that carry sim­i­lar sen­sors.

The new gen­er­a­tion of the agency’s Sentinel satel­lites has high spa­tial res­o­lu­tion and can observe sur­face tem­per­a­tures.

“But they cur­rently don’t have daily tem­po­ral res­o­lu­tion, although there are plans to reach daily res­o­lu­tion in future Sentinel mis­sions,” Ponti said.

“That means they can’t pro­vide daily max­i­mum and min­i­mum tem­per­a­tures, which are cru­cial for cir­ca­dian rhythms, the nat­ural cycles that reg­u­late life on Earth,” he explained.

Satellite-derived and other cli­mate data, com­bined with phys­i­o­log­i­cally based demo­graphic model intel­li­gence, may prove cru­cial in the years ahead, not just for olive groves, but for many crops that researchers have already stud­ied.

The project was car­ried out within the frame­work of the TEBAKA project and is based on the ICT infra­struc­ture devel­oped by the Med-Gold project, both of which are funded by the European Union.

For this data to inform strat­egy, pub­lic insti­tu­tions and regional orga­ni­za­tions must take action.

“What’s miss­ing are the research and project resources to sup­port the required cloud com­put­ing while main­tain­ing and extend­ing the time series of the dataset we used, which cov­ers about 20 years, from 2003 to 2023. That’s a long and valu­able period,” Ponti said.

“Climate change is not some­thing that will hap­pen at the end of the cen­tury. It is some­thing that is hap­pen­ing right now,” he con­cluded. ​“Statistical analy­ses of what hap­pened in the past in a given area are a great tool, but they are no longer enough, because cli­mate is chang­ing rapidly.”