Philippa Kaur

Doubleday, Z. A. et al. Global proliferation of cephalopods. Curr. Biol. 26, R406–R407 (2016).CAS 
PubMed 
Article 

Google Scholar 
Jereb, P. et al. Cephalopod biology and fisheries in Europe: II. Species Accounts. ICES Cooperative Research Report No vol. 325 (2015).ICES. ICES WGCEPH REPORT 2015 Interim Report of the Working Group on Cephalopod Fisheries and Life History (WGCEPH). 8–11 (2019).Quetglas, A. et al. Long-term spatiotemporal dynamics of cephalopod assemblages in the Mediterranean sea. Sci. Mar. 83, 33–42 (2019).Article 

Google Scholar 
Martins, H. R. Biological studies of the exploited stock of Loligo forbesi (Mollusca: Cephalopoda) in the Azores. J. Mar. Biol. Assoc. United Kingdom 62, 799–808 (1982).Article 

Google Scholar 
Guerra, A. & Rocha, F. The life history of Loligo vulgaris and Loligo forbesi (Cephalopoda: Loliginidae) in Galician waters (NW Spain). Fish. Res. 21, 43–69 (1994).Article 

Google Scholar 
Pierce, G. J. & Boyle, P. R. Empirical modelling of interannual trends in abundance of squid (Loligo forbesi) in Scottish waters. Fish. Res. 59, 305–326 (2003).Article 

Google Scholar 
Lishchenko, F. et al. A review of recent studies on the life history and ecology of European cephalopods with emphasis on species with the greatest commercial fishery and culture potential. Fish. Res. 236, 105847 (2021).Article 

Google Scholar 
Laptikhovsky, V. et al. Identification of benthic egg masses and spawning grounds in commercial squid in the English Channel and Celtic Sea: Loligo vulgaris vs L. forbesii. Fish. Res. 241, 106004 (2021).Article 

Google Scholar 
Souza, H. V. et al. Analysis of the mitochondrial COI gene and its informative potential for evolutionary inferences in the families Coreidae and Pentatomidae (Heteroptera). Genet. Mol. Res. 15, 1–14 (2016).CAS 

Google Scholar 
Brierley, A. S. et al. Genetic variation in the neritic squid Loligo forbesi (Myopsida: Loliginidae) in the northeast Atlantic Ocean. Mar. Biol. 122, 79–86 (1995).Article 

Google Scholar 
Shaw, P. W. et al. Subtle population structuring within a highly vagile marine invertebrate, the veined squid Loligo forbesi, demonstrated with microsatellite DNA markers. Mol. Ecol. 8, 407–417 (1999).CAS 
Article 

Google Scholar 
Ellegren, H. Microsatellites: Simple sequences with complex evolution. Nat. Rev. Genet. 5, 435–445 (2004).CAS 
PubMed 
Article 

Google Scholar 
Begg, G. A. & Waldman, J. R. An holistic approach to fish stock identification. Fish. Res. 43, 35–44 (1999).Article 

Google Scholar 
Shaw, P. W. Polymorphic microsatellite markers in a cephalopod: The veined squid Loligo forbesi. Mol. Ecol. 6, 297–298 (1997).CAS 
Article 

Google Scholar 
Emery, A. M. et al. New microsatellite markers for assessment of paternity in the squid Loligo forbesi (Mollusca: Cephalopoda). Mol. Ecol. 9, 110–112 (2000).CAS 
PubMed 
Article 

Google Scholar 
Butler, J. M. Advanced Topics in Forensic DNA Typing: Interpretation (Elsevier Academic Press, 2015).
Google Scholar 
Park, S. D. E. Trypanotolerance in West African Cattle and the Population Genetics Effects of Selection. Trinity Coll. (2001).Nei, M. Molecular Evolutionary Genetics (Columbia University Press, 1987).
Google Scholar 
Hedrick, P. W. Genetics of Populations (Science Books International, 1983).
Google Scholar 
Weir, B. S. & Cockerham, C. C. Estimating F statistics for Population Structure. Evolution 38, 1358–1370 (1984).CAS 
PubMed 

Google Scholar 
Raymond, M. & Rousset, F. GENEPOP (version 1.2): Population genetics software for exact tests and ecumenicism. J. Hered. 86, 248–249 (1995).Article 

Google Scholar 
Rousset, F. GENEPOP’007: A complete re-implementation of the GENEPOP software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106 (2008).PubMed 
Article 

Google Scholar 
Kalinowski, S. T. HP-RARE 1.0: A computer program for performing rarefaction on measures of allelic richness. Mol. Ecol. Notes 5, 187–189 (2005).CAS 
Article 

Google Scholar 
Excoffier, L. et al. Arlequin (version 3.0): An integrated software package for population genetics data analysis. Evol. Bioinforma. 1, 117693430500100 (2005).Article 

Google Scholar 
Pritchard, J. K. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gilbert, K. J. et al. Recommendations for utilizing and reporting population genetic analyses: The reproducibility of genetic clustering using the program structure. Mol. Ecol. 21, 4925–4930 (2012).PubMed 
Article 

Google Scholar 
Porras-Hurtado, L. et al. An overview of STRUCTURE: Applications, parameter settings, and supporting software. Front. Genet. 4, 1–13 (2013).CAS 
Article 

Google Scholar 
Evanno, G. et al. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14, 2611–2620 (2005).CAS 
PubMed 
Article 

Google Scholar 
Kopelman, N. M. et al. Clumpak: A program for identifying clustering modes and packaging population structure inferences across K. Mol. Ecol. Resour. 15, 1179–1191 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Folmer, O. et al. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 3, 294–299 (1994).CAS 
PubMed 

Google Scholar 
Hall, T. A. BioEdit: A user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp. Ser. 41, 95–98 (1999).CAS 

Google Scholar 
Anderson, F. E. Phylogeny and historical biogeography of the loliginid squids (Mollusca: Cephalopoda) based on mitochondrial DNA sequence data. Mol. Phylogenet. Evol. 15, 191–214 (2000).CAS 
PubMed 
Article 

Google Scholar 
Gebhardt, K. & Knebelsberger, T. Identification of cephalopod species from the North and Baltic Seas using morphology, COI and 18S rDNA sequences. Helgol. Mar. Res. 69, 259–271 (2015).ADS 
Article 

Google Scholar 
Lobo, J. et al. Enhanced primers for amplification of DNA barcodes from a broad range of marine metazoans. BMC Ecol. 13, 1–8 (2013).Article 
CAS 

Google Scholar 
de Luna Sales, J. B. et al. New molecular phylogeny of the squids of the family Loliginidae with emphasis on the genus Doryteuthis Naef ,1912: Mitochondrial and nuclear sequences indicate the presence of cryptic species in the southern Atlantic Ocean. Mol. Phylogenet. Evol. 68, 293–299 (2013).Article 

Google Scholar 
Tatulli, G. et al. A rapid colorimetric assay for on-site authentication of cephalopod species. Biosensors 10, 3–10 (2020).Article 
CAS 

Google Scholar 
Velasco, A. et al. A new rapid method for the authentication of common octopus (Octopus vulgaris) in seafood products using recombinase polymerase amplification (rpa) and lateral flow assay (lfa). Foods 10, 1825 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Luz, A. & Keskin, E. Building Reference Library for Marine Fish Species of Azores Archipelago and Bio-monitoring via DNA Metabarcoding. https://www.ncbi.nlm.nih.gov/nuccore/MT491734 (2020).BoldSystems. https://boldsystems.org/index.php/Public_RecordView?processid=AZB030-20 (2018). (Accessed 2 May 2022).Tamura, K. et al. MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol. Biol. Evol. 30, 2725–2729 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ronquist, F. & Huelsenbeck, J. P. MrBayes 3: Bayesian phylogenetic inference under mixed models. Bioinformatics 19, 1572–1574 (2003).CAS 
PubMed 
Article 

Google Scholar 
Rambaut, A. et al. Posterior summarization in Bayesian phylogenetics using Tracer 1.7. Syst. Biol. 67, 901–904 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bandelt, H.-J. et al. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 16, 37–48 (2009).Article 

Google Scholar 
Librado, P. & Rozas, J. DnaSP v5: A software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25, 1451–1452 (2009).CAS 
PubMed 
Article 

Google Scholar 
Schlitzer, R. Ocean Data View. (2013).Shaw, P. W. & Boyle, P. R. Multiple paternity within the brood of single females of Loligo forbesi (Cephalopoda: Loliginidae), demonstrated with microsatellite DNA markers. Mar. Ecol. Prog. Ser. 160, 279–282 (1997).ADS 
Article 

Google Scholar 
Emery, A. M. et al. Assignment of paternity groups without access to parental genotypes: Multiple mating and developmental plasticity in squid. Mol. Ecol. 10, 1265–1278 (2001).CAS 
PubMed 
Article 

Google Scholar 
Catarino, D. et al. The role of the Strait of Gibraltar in shaping the genetic structure of the Mediterranean Grenadier, Coryphaenoides mediterraneus, between the Atlantic and Mediterranean Sea. PLoS ONE 12, 1–24 (2017).
Google Scholar 
Gonzalez, E. G. & Zardoya, R. Relative role of life-history traits and historical factors in shaping genetic population structure of sardines (Sardina pilchardus). BMC Evol. Biol. 7, 1–12 (2007).Article 
CAS 

Google Scholar 
Reichow, D. & Smith, M. J. Microsatellites reveal high levels of gene flow among populations of the California squid Loligo opalescens. Mol. Ecol. 10, 1101–1109 (2001).CAS 
PubMed 
Article 

Google Scholar 
Shaw, P. W. et al. DNA markers indicate that distinct spawning cohorts and aggregations of Patagonian squid, Loligo gahi, do not represent genetically discrete subpopulations. Mar. Biol. 144, 961–970 (2004).CAS 
Article 

Google Scholar 
Göpel, A. Populationsgenetik und Phylogeographie des Nordischen Kalmars Loligo forbesii Steenstrup, 1856 in Europäischen Gewässern. Masterthesis, Univ. Rostock in German, 76pp (2020).Oesterwind, D. et al. Biology and meso-scale distribution patterns of North Sea cephalopods. Fish. Res. 106, 141–150 (2010).Article 

Google Scholar 
Sauer, W. H. H. et al. Tag recapture studies of the chokka squid Loligo vulgaris reynaudii d’Orbigny, 1845 on inshore spawning grounds on the south-east coast of South Africa. Fish. Res. 45, 283–289 (2000).ADS 
Article 

Google Scholar 
Knowlton, N. & Weigt, L. A. New dates and new rates for divergence across the Isthmus of Panama. Proc. R. Soc. B Biol. Sci. 265, 2257–2263 (1998).Article 

Google Scholar 
Pérez-Losada, M. et al. Testing hypotheses of population structuring in the Northeast Atlantic Ocean and Mediterranean Sea using the common cuttlefish Sepia officinalis. Mol. Ecol. 16, 2667–2679 (2007).PubMed 
Article 

Google Scholar 
O’Dor, R. K. Can understanding squid life-history strategies and recruitment improve management?. South African J. Mar. Sci. 7615, 193–206 (1998).Article 

Google Scholar 
Izquierdo, A. et al. Modelling in the Strait of Gibraltar: From operational oceanography to scale interactions. Fundam. i Prikl. Gidrofiz. 9, 15–24 (2016).
Google Scholar 
Clarke, M. & Hart, M. Treatise Online no. 102: Part M, Chapter 11: Statoliths and coleoid evolution. Treatise Online (2018).Hsü, K. J. et al. Late Miocene desiccation of the mediterranean. Nature 242, 240–244 (1973).ADS 
Article 

Google Scholar 
Garcia-Castellanos, D. et al. Catastrophic flood of the Mediterranean after the Messinian salinity crisis. Nature 462, 778–781 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Thunell, R. C. et al. Atlantic-mediterranean water exchange during the late neocene. Paleoceanography 2(6), 661 (1987).ADS 
Article 

Google Scholar 
Green, C. P. et al. Combining statolith element composition and fourier shape data allows discrimination of spatial and temporal stock structure of arrow squid (Nototodarus gouldi). Can. J. Fish. Aquat. Sci. 72, 1609–1618 (2015).Article 

Google Scholar  More

Sampling sitesLongitudinal observation campaigns for I. ricinus nymph activity were carried out at 11 sampling sites in forest areas from seven different tick observatories across France. Tick observatories are located at the following French municipal areas, where the coordinates of the centre of each municipal area and the climatic types29 are also provided as: (1) La Tour de Salvagny (45° 48′ 50.6″ N 4° 42′ 53.2″ E; Mixed climates); (2) Saint-Genès-Champanelle (45° 43′ 23.8″ N 3°01′ 08.0″ E; Mountain climate); (3) Etiolles (48° 37′ 59.9″ N 2° 28′ 00.1″ E; Degraded oceanic climate); (4) Carquefou (47° 17′ 58.5″ N 1° 29′ 26.0″ W; Oceanic climate); (5) Gardouch (43°23′ 25.7″ N 1° 41′ 02.1″ E; South-West Basin climate); (6) Velaine-en-Haye (48° 42′ 13.4″ N 6° 01′ 16.1″ E; Semi-continental climate); (7) Les Bordes (47° 48′ 47.3″ N 2° 24′ 01.3″ E; Degraded-oceanic climate) (Fig. 1). The observation campaigns were carried out from April/June 2014 to May/June 2021 in most observatories, except for Les Bordes, which began in April 2018.Figure 1The map was created using QGIS version 3.8, Zanzibar (https://www.qgis.org). The climatic region types were previously classified by Joly et al.29.The distribution of tick observatories according to the climatic region types of continental France: (1) Etiolles (degraded oceanic); (2) Velaine-en-Haye (semi-continental); (3) Les Bordes (degraded oceanic); (4) Carquefou (oceanic); (5) La Tour de Salvagny (mixed); (6) Saint-Genès-Champanelle (mountain); (7) Gardouch (south-west basin). Phenological patterns observed at each observatory were also indicated.Full size imageEach tick observatory corresponds to one sampling site except La Tour de Salvagny, Gardouch, and Les Bordes (Table S1). In La Tour de Salvagny, we had to withdraw the observations at the original site (La Tour de Salvagny A) in September 2016 because the site became no longer accessible. In April 2017, we continued our observations at a nearby site, approximately 2 km apart (La Tour de Salvagny B). In Gardouch, the activity of questing nymphs was observed both inside and outside the enclosed area of an experimental station on roe deer (Capreolus capreolus), referred to as Gardouch Inside and Gardouch Outside, respectively. The estimated population density of roe deer in Gardouch Inside (50 individuals per 100 ha) was higher than Gardouch Outside (less than 20 individuals per 100 ha) (H. Verheiden, personal communication, 15th October 2021). Furthermore, three sampling sites in Les Bordes, approximately 1.2 km apart, were referred to as Les Bordes A, B, and C, respectively. Additional sampling sites of these observatories were considered and reported as distinct sampling sites in further analyses, resulting in a total to 11 sampling sites from 7 observatories. Furthermore, due to their geographical proximity, meteorological/climatic factors of different sampling sites from the same observatories were considered identical in subsequent statistical analyses, whereas land cover and topography factors could be varied.Field observation campaigns were planned and carried out by local investigators who had been trained on the sampling protocol. The locations of forests, sampling sites, and passages were chosen where their biotopes are known to be suitable for I. ricinus tick populations around each observatory at the time the field observation campaigns started30. The observations were never carried out during the daytime when the weather was highly unfavourable to questing ticks, e.g., heavy rain, snow, or snow cover.Sampling protocol for questing Ixodes ricinus nymphsActivity of questing I. ricinus nymphs was observed by a cloth-dragging sampling technique31. Within a 1-km radius, a 1 m × 1 m white cloth was dragged over 10 observation units of 10 m short-grass vegetative forest floors, called transects. For each transect, a repeated removal sampling design was used27. The cloth-dragging sampling process was successively repeated three times per sampling. All nymphs found on white cloth in each campaign were removed and collected in a vial for subsequent morphological identification32 by the same acarologists at the corresponding laboratories. As a result, the questing nymph activity of each sampling site was monitored as a total number of confirmed I. ricinus nymphs collected from three repeated sampling on 10 transects, equivalent to a surface area of 100 m2. This measure was considered as an indicator for tick abundance on the day of sampling. The same transects were repeatedly sampled throughout the study period at approximately 1-month intervals.Environmental dataWe tested 28 environmental variables to explain the observed I. ricinus nymph activity (Table 1). These variables could be categorized as: (1) Daytime duration and meteorological variables (time-dependent, 9 variables); (2) Land cover, topography, and bioclimatic variables (time-independent, 19 variables).Table 1 Environmental variables (meteorological, land cover, topography, and bioclimatic variables) used to explain I. ricinus nymph counts per 100 m2 in regression analysis.Full size tableDaytime duration and meteorological variablesDaytime duration ((daytime)) from January 2013 to June 2021 at each sampling site was obtained from the corresponding latitude using geosphere package33. Hourly meteorological data (2-m temperature and relative humidity) were recorded locally at each forest. Subsequently, daily mean, minimum, and maximum values of temperature (({T}_{M}), ({T}_{N}), and ({T}_{X}); in °C) and relative humidity (({U}_{M}), ({U}_{N}), and ({U}_{X}); in %) were derived from these hourly records. The meteorological seasons of the temperate area in northern hemisphere are defined as: (1) Spring, 1st March to 31st May; (2) Summer, 1st June to 31st August; (3) Autumn, 1st September to 30th November; (4) Winter, 1st December to 28th or 29th February.Missing values found on these local daily-level variables were imputed by the random forest algorithm in mice package34. External daily meteorological data, i.e., daily average temperature and relative humidity, derived from neighbouring weather stations (Météo-France or INRAE), as well as month and year information, were used as auxiliary variables (Table S2). As a result, the imputation process creates a total of 500 iterated values for each variable. The median values of 500 imputations were used to replace the missing values.The imputed daily meteorological data were subsequently used to calculate the averaged values in different lagged time intervals for further analysis, called interval-average variables15. The interval-average variables were generated to reduce the uncertainty that might arise during the imputation process and to capture the cumulative effects of the meteorological variables, which were mean temperature ({T}_{M}) and minimum relative humidity ({U}_{N}). The interval-average variables were defined as the average values of a meteorological variable (Min) {({T}_{M}), ({U}_{N})} during a period between ({t}_{1}) to ({t}_{2}) month(s) before the sampling, denoted as ({M}^{{t}_{1}:{t}_{2}}), where 1 month consists of 28 days. As temperature conditions affect several ecological processes of tick populations, particularly developmental and questing rates3, the mean temperature ({T}_{M}) was selected for further analysis to reflect the overall temperature effects. While the minimum relative humidity ({U}_{N}) was chosen for the following reasons: (1) the survival of I. ricinus is highly sensitive to desiccation conditions6,7,8. As a result, when compared to mean or maximum relative humidity, minimum relative humidity is a relatively strong indicator of the effects of desiccation stress; (2) the variation of minimum relative humidity among all sites was higher than that of the mean and maximum relative humidity. This high variation allowed us to better describe meteorological characteristics of each sampling site.Here, we hypothesized that interval-average meteorological conditions influence the dynamics of observed nymph activity at different time lags in different manners. Short-term lags may have an impact on immediate responses, such as the probability of questing. At the same time, long-term lags may influence the dynamics of nymph abundance, which is associated with development and survival rates. Therefore, we explored the impact of each meteorological variable at following time lags on the observed nymphs activity in subsequent regression analysis: (1) 1-month moving average condition, ({M}^{0:1}); (2) previous 3-to-6-month moving average condition, ({M}^{3:6}); (3) 6-month moving average condition, ({M}^{0:6}); (4) 12-month moving average condition, ({M}^{0:12}). For instance, ({T}_{M}^{0:1}) denotes 1-month moving average temperature, representing an average of temperature between 0 and 1 months (0–28 days) before the day of sampling.In addition to the interval-average variables, monthly and seasonal average values of mean temperature and minimum relative humidity during the observation period were also calculated to describe the characteristics of meteorological conditions of each sampling site.Land cover, topography, and bioclimatic variablesWe obtained land cover, topography, and bioclimatic data from a 1-km radius buffer area around the center of each sampling site to capture habitat characteristics across all 10 transects. All the variables were handled and obtained by using QGIS version 3.8.035. The digital elevation model (DEM) data derived from the Shuttle Radar Topography Mission (SRTM) database36 was used to describe the topographic features of sampling sites, which included the mean (({mean}_{elv})) and standard deviation (({sd}_{elv})) of the elevation (in m above sea level), the proportion of flat area (({p}_{flat}); defined by the slope ≤ 2.5%37), the proportion of area facing north (({p}_{north})), east (({p}_{east})), west (({p}_{west})), and south (({p}_{south})), and the catchment area ((catchment)) as a proxy variable for moisture. Bioclimatic variables for each site (historical average conditions during 1970–2000) were derived from the WorldClim database38, including the annual mean temperature (({BIO1}_{Temp}); in °C), the mean diurnal range (({BIO2}_{Diur}); in °C), the maximum temperature of the warmest month (({BIO5}_{maxTemp}); in °C), and the annual precipitation (({BIO12}_{Prec}); in mm). The land cover features of each sampling site were described using the CORINE Land Cover (CLC) 201839, while the characteristics of forests were explained by the BD forêt version 2 data40. The forest fragmentation was characterized by the percentage of forest-covering area (({p}_{Forest})), the forest edge density (({ED}_{Forest}); in m/km2), and the number of forest patches (({n}_{Forest})). While the diversities of the land cover types (level-1 and level-2 CLC) and the forest types were calculated by using the Shannon’s diversity index41 ((H)) as (H=sum_{i=1}^{S}{p}_{i}mathrm{ln}{p}_{i}), where (S) is the total number of land cover/forest types and ({p}_{i}) is the proportion of land cover/forest type (i) within the 1-km radius buffer area. The Shannon’s diversity index for level-1 CLC, level-2 CLC, and forest types were denoted as ({H}_{CLC1}), ({H}_{CLC2}), and ({H}_{Forest}), respectively. Finally, the soil pH data (({pH}_{soil})) was retrieved from the European Soil Data Centre (ESDC) database42.Statistical analysisAll the statistical analyses were carried out using the programming language R version 3.6.043. The variations of questing nymph population of each site were described by using (1) baseline annual nymph counts (spatial variation); (2) phenological patterns (seasonal variation). A baseline annual nymph count of site (i) (({{N}_{base}}_{i})) was defined as a summation of monthly median nymph counts ({varvec{tilde{N}}}_{i}={{tilde{N }}_{i,t}}) across all 12 months (tin left{mathrm{1,2},dots ,12right}) and expressed as: ({{N}_{base}}_{i}=sum_{t=1}^{12}{tilde{N }}_{i,t}). Subsequently, the monthly median nymph counts of each site ({varvec{tilde{N}}}_{i}) were transformed into normalized monthly median nymph counts ({varvec{tilde{N}}}_{i}^{*}={{tilde{N }}_{i,t}^{*}}) following Eq. (1) to have a range value of 0 to 1, which allows us to compare phenological patterns among all sites that have different annual baseline nymph counts.$${tilde{N }}_{i,t}^{*}=frac{{tilde{N }}_{i,t}}{mathrm{max}({stackrel{sim }{{varvec{N}}}}_{i})}$$
(1)
The term (mathrm{max}({stackrel{sim }{{varvec{N}}}}_{i})) denoted the maximum monthly median nymph counts. The normalized median nymph count ({tilde{N }}_{i,t}^{*}) of 1 indicates the maximum nymph activity (peak), while the value ({tilde{N }}_{i,t}^{*}) of 0 designates the absence of nymph activity. Afterwards, the phenological patterns were descriptively classified using the following criteria: (1) the season which the peaks of activity arrive; (2) evidence of reduced activity during winter (November–January); (3) the number of activity waves in a year, whether the pattern is unimodal or bimodal. After assigning phenological patterns to each site, the overall trends of different patterns were derived from medians of the normalized monthly median nymph count ({tilde{N }}_{i,t}^{*}) from all sites that belonged to each pattern. Furthermore, the directional changes in the maximum nymph counts were tested using a Spearman’s rank correlation coefficient, a p-value More

Growth in harvests of crops meant for exports, processing and industrial use, together with their higher yields and faster yield gains, stands out globally; at a more granular level, this was driven by specific global regions that are getting increasingly specialized in harvesting crops for these usages.Changes in global-level harvested areasAt the global scale, we find that crops harvested for direct food utilization have the highest area and have been relatively stable over the study period (Fig. 1a). However, as the total harvested hectares have increased globally (Supplementary Table 1), this has translated into decreasing fractions of crops harvested for direct food utilization, from ~51% in the 1960s (average over 1964 to 1968) to ~37% in the 2010s (average over 2009 to 2013), with a similar reduction in feed crop harvests (Table 1). Conversely, there has been a substantial increase in crops for processing, exports and industrial use (Fig. 1a, Table 1 and Supplementary Table 1). The increase in industrial crop harvests occurred after year 2000. Around the same time, harvested hectares for exported crops ramped up and by the 2010s had surpassed those of crops harvested for feed use (Fig. 1a). Crops harvested for seed usage and losses are relatively minor, and we will not discuss them further. If the global trends observed in the past 20 years continue (Fig. 1a), by 2030, crops harvested for exports, processing and industrial use will account for ~ 23%, 17% and 8% of overall harvested hectares, whereas those for food will decrease to ~29% (Table 1).Fig. 1: Sector-based global crop-utilization trends.a–d, Observed total harvested ha (a), average yield in kcal ha−1 per year (b), average yield in protein ha−1 per year (c) and average yield in fat ha−1 per year (d) in the seven sectors of food, feed, processing, export, other uses (non-food/industrial), seed and losses from 1964 to 2013, annually, and projections to 2030 based on the past 20 years. The shading shows the 90% confidence interval for the significant linear model projections.Full size imageTable 1 Sector-based global crop-utilization changesFull size tableChanges in global-level crop yieldsWe find that crops harvested for direct food usage generally have had lower yields than all other sectors at the global scale over the time period of the study (Fig. 1b–d). This is not a new phenomenon, as crops harvested for direct food utilization have always had lower yields relative to other sectors (Supplementary Table 1). What has changed, however, is the ramping up (steeper positive slopes) of industrial, export and processing crop yields (Fig. 1b–d and Table 1). At these rates, caloric yields of industrial-use crops could increase by 28% from the 2010s to 2030 compared with 24% and 21% yield increases of crops harvested for directly consumed food and for feed use (Fig. 1b). Given that caloric yields of industrial-use crops are already substantially higher than food and feed crops (2× and 1.4×, respectively, in the 2010s), the faster caloric yield increases for industrial-use crops will widen this gap (2.1× and 1.5×, respectively). Yield measurements in other units of protein and fat show similar results (Table 1, Fig. 1c,d and Supplementary Table 1).Changes in the spatial patterns of harvested areas and productionWithin country-level information on harvested areas and productivity based on utilization categories is required for developing more locally effective agricultural policies. Over the course of the study time period 1964 to 2013 (Fig. 2a,b and Supplementary Video 1), we find changes in all continents when spatially analysed at the grid-cell level, except for most parts of Africa. Even in Africa, there are locations with fractional reductions in food crop harvests over the study period, such as parts of Angola, Ghana, Nigeria and South Africa. Within these and other countries, the exact location, magnitude and direction of the change varies from one region to the next (that is, compare Fig. 2a with Fig. 2b).Fig. 2: Sector-based spatial changes in crop harvests.a,b, The fraction of a grid cell in one of seven categories—food, feed, processing, export, other (non-food/industrial use), seed and losses—in each period, 1964–1968 (a) and 2009–2013 (b).Full size imageCrops harvested for direct food utilization have been prevalent in Asia, though much has changed since the 1960s (Fig. 2a,b and Supplementary Video 1). In China, there appears to be an imaginary belt, north and west of which harvests of crops used as directly consumed food decreased between the 1960s (Fig. 2a) and 2010s (Fig. 2b), while those for other uses increased. This belt appears to roughly extend from the northern half of Jiangsu (a province on the Yellow Sea in the east), curving westwards and southwards through northern Anhui, southern Henan, central Hubei and the northern tip of Hunan, and then turning sharply south and splitting Guangdong (a province on the South China Sea) through the middle. The sector gaining from the 10–20% fractional food harvest reduction varies. The increase in crops for feed, processing and industrial usage increases as one moves northward, especially north of Jiangsu and Anhui (Fig. 2a,b and Supplementary Video 1).Similarly, in India, there is a north–south zone encompassing eastern Haryana in the north, moving southwards through eastern Rajasthan, western Madhya Pradesh to eastern Maharashtra in the south, where there was a drastic reduction in crops harvested for direct food utilization over the study period (Fig. 2 and Supplementary Video 1); crops harvested for processing primarily increased. Changes in South and Southeast Asia over the study period are primarily away from once-dominant harvests of directly consumed food crops to feed crops, followed by processing crops, export crops and industrial-use crops, as in Myanmar and Thailand. In Malaysia, the growth was in export and industrial-usage crops, whereas in Indonesia, it was export crops and smaller increases in industrial-utilization crops. Central Asian states, especially Kazakhstan and some parts of Russia, witnessed a large reduction in crops harvested for direct food use over the study period, replaced by the crops destined for exports between the two periods (Fig. 2 and Supplementary Video 1).In Australia in the 1960s, food crops were harvested everywhere, accounting for ~10% of the total, which declined to ~5% by the 2010s. This was accompanied by small reductions in crops harvested for feed and export and balanced mainly by increases in crops for processing and industrial utilization (Fig. 2 and Supplementary Video 1).In Europe in the 1960s, crops were dominantly harvested for food and feed, but by the 2010s, this changed to include crops harvested for processing (Fig. 2 and Supplementary Video 1). In France, major reductions in feed crops have been balanced by growth in processing, export and industrial-use crops. In Spain, the primary change is from crops harvested for direct food to those of feed. In Germany, crops harvested for export have replaced those for direct food utilization.Latin America used to dominantly harvest food crops (as in Mexico) or food and feed crops (as in Brazil and Argentina) (Fig. 2 and Supplementary Video 1). Midwestern Brazil used to harvest only food crops, and feed and processing crop harvests were restricted to the Atlantic states (the 1960s; Fig. 2a), but by the 2010s (Fig. 2b), harvests of food crops had become a negligible fraction in Midwestern Brazil (as in Mato Grosso), and crops harvested for processing and exports are dominant now. In the Atlantic states of Brazil, one of the major changes is the increased proportion of harvests for industrial crops. In Argentina, over the study period, the proportion of crops harvested for food and feed has decreased, and this utilization has been mainly replaced by crops harvested for processing; crops harvested for exports changed, but the direction of change was spatially heterogeneous across Argentina (Fig. 2 and Supplementary Video 1). In Mexico, the primary change is the reduction in the fraction of crops harvested for direct food consumption and the increased harvests of crops for feed.Crops harvested for food and feed are also on the decline proportionally in North America. The United States has experienced a change from the dominance of food and feed crops in the 1960s to processing and industrial-usage crops in the 2010s. Detailed changes in the United States and Canada vary from one location to the next (Fig. 2), though the major change is the lower fraction of crops harvested for direct food consumption.Results are similar when viewed through the lens of calories, protein and fat with local-level differences as yields vary based on the measurement units (Supplementary Fig. 1). Further dramatic changes can be expected if observed linear trends from 1994 to 2013 at each grid cell continued until 2030 (Supplementary Fig. 2).Calories harvested in 2030 and achieving UN SDG 2We compare the extra food calories that will potentially be harvested in 2030 (Fig. 3a and Supplementary Data 2) to those required for both the projected extra population and feeding the projected undernourished population in each country (Fig. 3b and Supplementary Data 2). As an extreme case, we also compared whether total calories (all seven utilization sectors) would be sufficient (Fig. 3c and Supplementary Data 2). Altogether, we evaluated 156 countries, of which 86 had reported undernourished populations (Supplementary Data 2). On the basis of the minimum dietary energy requirement (MDER), we find that countries with reported undernourished populations will have a shortfall of ~675.4 trillion kcal per year to nourish the increased population and the expected undernourished from their extra harvested food calories. However, compared with the more realistic average dietary energy requirement (ADER), this shortfall will be ~993.9 trillion kcal per year (or ~70% from requirements) in 2030 (15 additional scenarios of undernourished populations in 2030 (provided in Supplementary Data 3) show global calorie shortfalls may similarly range from ~587.2 trillion kcal per year to ~1,269.3 trillion kcal per year based on the MDER level of nutrition requirement, and ~880.7 trillion kcal per year to ~1,755.6 trillion kcal per year based on the more realistic ADER level of nutrition requirement in 2030).Fig. 3: Meeting UN SDG goal 2 in 2030.a, Same as Fig. 2 but for the projected kcal ha−1 per year in 2030 per utilization sector and then mapping the fraction of total kcal ha−1 per year projected as harvested. b, Shortfall or gap from kcal per year harvested in 2030 as crops for direct food use and those to plug the gap from population growth and/or undernourished population. Computed based on the 2018 to 2020 ADER number for the country. c, Same as b but the kcal per year harvested used for computation is the total across all the seven sectors and shortfall is from whether the total calories harvested were used for direct food consumption (little to no processing).Full size imageCountries reporting undernourishment can, however, meet their requirement of extra calories in 2030 for both population change and those for the undernourished if calories from other utilization sectors are diverted and consumed directly as food calories (Fig. 3c and Supplementary Data 2 and 3). Though at the global scale, it appears that countries with high levels of undernourishment in 2030 can divert just a portion of their total harvested calories and meet some of the requirements of UN’s SDG 2 (ref. 4). In reality, many of the individual countries concentrated in sub-Saharan Africa have limited scope of diversion of calories from other sectors such as feed, processing or exports as crops for direct food use, as they already harvest most crops for direct food consumption (Fig. 2 and Supplementary Figs. 1 and 2). As such, many countries in this region may see deepening reliance on food imports. Note that the UN’s second SDG goal is broader in scope, including efforts to end malnutrition and increase agricultural productivity, among other goals4. Reconfiguration planning19 can use our spatially detailed information (Figs. 2 and 3, Supplementary Figs. 1 and 2 and Supplementary Data 2 and 3) in conjunction with policies that incentivize increased food crop harvests globally and ensure their equitable distribution to undernourished regions when local production is not sufficient20,21. This will require supply chain management22,23 and detailed analysis of optimization scenarios24 with our maps and tables as an important step linking specific production regions with the initial use of that production. More

Carvalho, A. M. & Barata, A. M. The consumption of wild edible plants. In Wild plants, mushrooms and nuts: functional food properties and applications (eds Isabel, C. F. R. et al.) (John Wiley & Sons, New York City, 2017).
Google Scholar 
Diazgranados, M. et al. World checklist of useful plant species. Royal Botanic Gardens, Kew. (Richmond, UK, 2020).
Google Scholar 
Ulian, T. et al. Unlocking plant resources to support food security and promote sustainable agriculture. Plants People Planet 12(5), 421–445 (2020).Article 

Google Scholar 
Shaheen, S., Ahmad, M., Haroon, N. Edible wild plants: a solution to overcome food insecurity. In: Edible Wild Plants: An alternative approach to food security (eds Shaheen, S., et al.) 41–57. Springer, Cham. https://doi.org/10.1007/978-3-319-63037-3_2 (2017).Chapter 

Google Scholar 
Food and Agriculture Organization. World programme for the census of agriculture 2020, Vol. 1. FAO, (Rome, Italy, 2015).
Google Scholar 
Wolff, F. Legal factors driving agrobiodiversity loss. Environ. Law Netw. Int. 1, 1–11 (2004).
Google Scholar 
Padulosi, S., Heywood, V., Hunter, D. & Jarvis, A. Underutilized species and climate change: current status and outlook. In Crop Adaptation to Climate Change (eds Shyam, S. Y. et al.) 507–517 (Blackwell Publishers, 2011).Chapter 

Google Scholar 
Kalamandeen, M., Gloor, E. & Mitchard, E. Pervasive raise of small-scale deforestation in Amazonia. Sci. Rep. 8(1600), 1–10 (2018).CAS 

Google Scholar 
Kor, L., Homewood, K., Dawson, T. P. & Diazgranados, M. Sustainability of wild plant use in the Andean community of South America. Ambio 50, 1681–1697 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Nogueira, S. & Nogueira-Filho, S. Wildlife farming: an alternative to unsustainable hunting and deforestation in neotropical forests?. Biodivers. Consrv. 20, 1385–1397 (2011).Article 

Google Scholar 
Pilgrim, S. E., Cullen, L. C., Smith, D. J. & Pretty, J. Ecological knowledge is lost in wealthier communities and countries. Environ. Sci. Technol. 42(4), 1004–1009 (2008).CAS 
PubMed 
Article 

Google Scholar 
Sánchez-Cuervo, A. M. & Mitchell-Aide, T. Consequences of the armed conflict forced human displacement, and land abandonment on forest cover change in Colombia: a multi-scaled analysis. Ecosystems 16, 1052–1070 (2013).Article 

Google Scholar 
Rodriguez-Eraso, N., Armenteras-Pascual, D. & Retana-Alumbreros, J. Land use and land cover change in the Colombian Andes: dynamics and future scenarios. J. Land Use Sci. 8(2), 154–174 (2013).Article 

Google Scholar 
Food and Agriculture Organization. in The State of the World’s biodiversity for food and agriculture. FAO Commission on Genetic Resources for Food and Agriculture Assessments (eds Bélanger, J., Pilling, D.). (FAO, Rome, Italy, 2019).Borelli, T. et al. Local solutions for sustainable food systems: the contribution of orphan crops and wild edible species. Agronomy 10(2), 231–256 (2020).CAS 
Article 

Google Scholar 
Padulosi, S., Thompson, J. & Rudebjer, P. Fighting poverty, hunger and malnutrition with neglected and underutilized species (NUS): needs, challenges and the way forward (Bioversity International, 2013).
Google Scholar 
Hunter, D. et al. The potential of neglected and underutilized species for improving diets and nutrition. Planta 250, 709–729 (2019).CAS 
PubMed 
Article 

Google Scholar 
Brehmy, J. M., Maxted, N., Martin-Louçao, M. A. & Frod-Lloyd, B. V. New approaches for establishing conservation priorities for socio-economically important plant species. Biodivers. Conserv. 19(9), 2715–2740 (2010).Article 

Google Scholar 
N’Danikou, S., Achigan-Dako, E. G. & Wong, J. L. G. Eliciting local values of wild edible plants in Southern Benin to identify priority species for conservation. Econ. Bot. 65, 381–395 (2011).Article 

Google Scholar 
Dulloo, M. E. et al. Conserving agricultural biodiversity for use in sustainable food systems. (2017).de Oliveira Beltrame, D. M. et al. Brazilian underutilised species to promote dietary diversity, local food procurement, and biodiversity conservation: a food composition gap analysis. Lancet Planet. Health. 2, S22. (2018).Article 

Google Scholar 
Raven, P. H. et al. The distribution of biodiversity richness in the tropics. Sci. Adv. 6(37), 1–5 (2020).Article 

Google Scholar 
Renjifo, L. M., Amaya-Villareal, A. M. & Butchart, S. H. M. Tracking extinction risk trends and patterns in a mega-diverse country: a red list index for birds in Colombia. PLoSONE 15(1), 1–19 (2020).Article 

Google Scholar 
Clerici, N., Salazar, C., Pardo-Díaz, C., Jiggins, C. D. & Linares, M. Peace in Colombia is a critical moment for neotropical connectivity and conservation: save the northern Andes-Amazon biodiversity bridge. Conserv. Lett. 12, 1–7 (2019).Article 

Google Scholar 
Hurtado-Bermudez, L. J., Vélez-Torres, I. & Méndez, F. No land for food: prevalence of food insecurity in ethnic communities enclosed by sugarcane monocrop in Colombia. Int. J. Public Health 65, 1087–1096 (2020).PubMed 
Article 

Google Scholar 
Boron, V., Payan, E., McMillan, D. & Tzanopulos, J. Achieving sustainable development in rural areas in Colombia: future scenarios for biodiversity conservation under land use change. Land Use Policy 59, 27–37 (2016).Article 

Google Scholar 
Grau, H. R. & Aide, M. Globalization and land-use transitions in Latin America. Ecol. Soc. 13(2), 1–16 (2008).Article 

Google Scholar 
Rivas Abadía, X., Pazos, S. C., Castillo, S. K. & Pachón, H. Indigenous foods of the indigenous and Afro-descendant communities of Colombia (International Center for Tropical Agriculture (CIAT), Cali, 2010) ((In Spanish, English summary)).
Google Scholar 
López Diago, D. & García, N. Wild edible fruits of Colombia: diversity and use prospects. Biota Colomb. 22(2), 16–55 (2021).Article 

Google Scholar 
Pieroni, A., Pawera, L. & Shah, G. M. Gastronomic ethnobiology. In Introduction to Ethnobiology (eds Albuquerque, U. P. & Alves, R. N.) 53–62 (Springer, 2016).Chapter 

Google Scholar 
Castañeda, R. R. Frutas silvestres de Colombia. Instituto Colombiano de Cultura Hispánica. (1991).Medina, C. I., Martínez, E. & López, C. A. Phenological scale for the mortiño or agraz (Vaccinium meridionale Swartz) in the high Colombian Andean area. Revista Facultad Nacional de Agronomía Medellín 72(3), 8897–8908 (2019).Article 

Google Scholar 
Asprilla-Perea, J. & Díaz-Puente, J. M. Traditional use of wild edible food in rural territories within tropical forest zones: a case study from the northwestern Colombia. New Trends Issues Proc. Humanit. Soc. Sci. 5(1), 162–181 (2018).
Google Scholar 
López Estupiñán, L. Potatoes and land in Boyacá: ethnobotanical and ethnohistorical research of one of the main products of Colombian food. Boletín de Antropología Universidad de Antioquia 30(50), 170–190 (2015) ((In Spanish)).
Google Scholar 
Marín Santamaría, C.M. Potential for food use for human consumption of wild fruits in Encenillo Biological Reserve, Guasca, Cundinamarca. Thesis in Biological Sciences. Pontificia Universidad Javeriana. Bogotá, Colombia. (2010) (In Spanish).Molina Samacá, J. R. Ancestral Food Plant Heritage: Construction of the Baseline in the Province of Sumapaz. Master thesis in Agricultural Sciences. University of Cundinamarca, Colombia (2019) (In Spanish).Pasquini, M. W., Sánchez-Ospina, C. & Mendoza, J. S. Traditional food plant knowledge and use in three afro-descendant communities in the Colombian Caribbean Coast: Part II drivers of change. Econ. Bot. 72(3), 295–310 (2018).Article 

Google Scholar 
Villa Villegas, M. Análisis del conocimiento asociado al uso de la flora alimenticia y medicinal en la comunidad de San Francisco, Acandí (Chocó. Pontificia Universidad Javeriana, 2020).
Google Scholar 
Cook, E. M. F. Economic botany data collection standard (Royal Botanic Gardens, Kew, Richmond, 1995).
Google Scholar 
Diazgranados, M. & Kor, L. Notes on the biogeographic distribution of the useful plants of Colombia. In: Catalogue of useful plants of Colombia (eds Negrão, R. et al.) 147–161. Royal Botanic Gardens, Kew. Kew Publishing, London (in press).Diazgranados, M. et al. Annotated checklist of useful plants of Colombia. In: Catalogue of useful plants of Colombia (eds Negrão, R. et al.) 165–473. Royal Botanic Gardens, Kew. Kew Publishing, London (in press).R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. Available at: https://www.R-project.org/. (2021)POWO. Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew. Retrieved on 14 April, 2021, from: http://www.plantsoftheworldonline.org/ (2021).Missouri Botanical Gardens. Tropicos.org. Retrieved on 10 April 2021, https://tropicos.org (2021)Wickham, H. The split-apply-combine strategy for data analysis. J. Stat. Softw. 40(1), 1–29 (2011).Article 

Google Scholar 
Wickham, H., Francois, R. Dplyr: A Grammar of Data Manipulation. R Package Version 0.4.3 (2021).GBIF Sectretaria. GBIF backbone taxonomy. Retrieved on 22 April 2021, from: https://www.gbif.org/ (2021)Food and Agriculture Organization. The second report on the State of The World’s plant genetic resources for food and agriculture. (FAO, Rome, Italy, 2015).Bystriakova, N. et al. Colombia’s bioregions as a source of useful plants. PLoS One 16(8), 1–19 (2021).Article 

Google Scholar 
Olson, D. M. et al. Terrestrial ecoregions of the world: A new map of life on earth a new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. BioScience 51(11), 933–938 (2001).Article 

Google Scholar 
Chamberlain, S., Oldoni, D., Barve, V., Desmet, P., Geffert, L., Mcglinn, D., Ram, K. Rgbif: interface to the global “Biodiversity” information facility API. R Package Version 3.6.0. (2021)Ondo, I. et al. ShinyCCleaner: an interactive app for cleaning species occurrence records. Unpublished (2021).Bivand, R., Keitt, T., Rowlingson, B., Pebesma, E., Summer, M., Hijmans, R., Baston, D., Rouault, E., et al. Rgdal: bindings for the “Geospatial” data abstraction library. R Package Version 1.5-23. Retrieved from: https://cran.r-project.org/web/packages/rgdal/index.html (2021)Hijmans, R. J., van Etten, J. Raster: geographic analysis and modeling with raster data. R package version 2.0-12. Available at: http://CRAN.R-project.org/package=raster (2012)Bivand, R.S., Pebesma, E., Gomez-Rubio, V. Applied spatial data analysis with R, Second edition. Springer, NY. Available at: https://asdar-book.org/ (2013)Brown, J. L., Bennett, J. & French, C. M. SDMtoolbox: the next generation python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. PeerJ 5, e4095 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
DANE. Indigenous population of Colombia. In: Results of the national population and housing census 2018 (eds DANE). (Bogotá, Colombia, 2019) (In Spanish).Minority Rights Home Minorities and indigenous peoples in Colombia. Retrieved on 20 October, 2021, from: Colombia – World Directory of Minorities & Indigenous Peoples (minorityrights.org) (2021).Maffi, L. & Woodley, E. Biocultural diversity conservation: a global sourcebook 304 (Routledge, 2012).Book 

Google Scholar 
van Zonnevelda, M. et al. Human diets drive range expansion of megafauna-dispersed fruit species. PNAS 115(13), 3326–3331 (2018).Article 

Google Scholar 
Diazgranados, M., Mendoza, J. E., Peñuela, M., Ramírez, W. Comida, identidad, paisaje… ¿articulación o antagonismo? Universitas Humanistica pp. 119–127. ISSN-0120-4807 (1997).Rojas, T.M., Cortés, C., Pizano, M.N., Ulian, T., Diazgranados, M. Evaluación del estado de los desarrollos bioeconómicos colombianos en plantas y hongos. Royal Botanic Gardens, Kew and Instituto de Investigaciones en Recursos Biológicos Alexander von Humboldt (2020).Departamento Administrativo de la Función Pública. Decree 690 of 2021, Article 10. Bogotá, Colombia (2021).Ahoyo, C. C. et al. A quantitative ethnobotanical approach toward biodiversity conservation of useful woody species in Wari-Maro forest reserve (Benin, West Africa). Environ. Dev. Sustain. https://doi.org/10.1007/s10668-017-9990-0 (2017).Article 

Google Scholar 
Suwardi, A. B., Navia, Z. I., Harmawan, T. & Syamsuardi, E. Ethnobotany and conservation of indigenous edible fruit plants in South Aceh, Indonesia. Biodiversitas 12(5), 1850–1860 (2020).
Google Scholar 
Pei, S., Alan, H. & Wang, Y. Vital roles for ethnobotany in conservation and sustainable development. Plant Divers. 42(6), 399 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Bernal, M. H. Y. & Correa, Q. J. E. Erythrina edulis. In Promising plant species from countries of the Convenio Andrés Bello Vol. 8 (eds Bernal, M. H. Y. & Correa, Q. J. E.) 231–278 (Editora Guadalupe Ltda, Bogotá, 1992) ((In Spanish)).
Google Scholar 
Bernal, M.H.Y., Correa, Q.J.E. Food plants of Colombia. in Promising plant species from the Andrés Bello Convention countries (andean countries). First edition. (eds Bernal M.H.Y., Correa, Q.J.E.) Editora Guadalupe Ltda. Bogotá, D.C., Colombia. Volume I, p. 547; Volume II, 462; Volume III, 485; Volume IV, 489; Volume V, 569; Volume VI, 507; Volume VII, p. 684; Volume VIII, p. 547; Volume IX, p. 482; Volume X, 549; Volume XI, p. 516 and Volume XII, p. 621 (1989–1998) (In Spanish).Bernal, M.H.Y., Farfán, M.M. Guide for the cultivation and use of the “chachafruto” or “balú” (Erythrina edulis Triana ex Micheli). Bogotá: Editoria Guadalupe Ltda. 50 p. (1996) (In Spanish).Bernal, M.H.Y., Jiménez, L.C. The “Creole bean” Canavalia ensiformis (Linnaeus) De Candolle (Fabaceae-Faboideae). Bogotá: Editoria Guadalupe Ltda. 533 p. (1990) (In Spanish).Jiménez, B.L.C., Bernal, M.H.Y. The “inchi” Caryodendron orinocense Karsten (Euphorbiaceae). Bogotá: Editora Guadalupe Ltda. p. 429 (1992) (In Spanish).Melgarejo, L.M., Hernández, M.S., Barrera, J.A., Carrillo, M. Offers and potential of a germplasm bank of the genus Theobroma for the enrichment of Amazonian systems. Instituto de Investigaciones Científicas Sinchi. Universidad Nacional de Colombia. Bogotá, Colombia. p. 225 (2006) (In Spanish).Bernal, R., Galeano, G., Rodríguez, A., Sarmiento, H., Gutiérrez, M. Nombres Comunes de las Plantas de Colombia. Retrieved 15 June, 2021, from: http://www.biovirtual.unal.edu.co/nombrescomunes/ (2017)Food Plants International. Retrieved on 14 March 2021 at Articles & Books – Food Plants International (2021).Lorenzi, H., Bacher, L., Lacerda, M. & Sartori, S. Brazilian fruits and cultivated exotics (Instituto Plantarum De Estudos Da Flora LTDA, Nova Odessa, 2000).
Google Scholar 
Martín, F.W., Campbell, C.W., Ruberté, R.M. Perennial Edible Fruits of the Tropics: An Inventory. U.S. Department of Agriculture, Agricultural Research Service. (1987)Marrugo, S. L. Como Pepa’e Guama: Lo que no sabías acerca de la vida de los guamos (Royal Botanic Gardens Kew, Richmond, 2019).
Google Scholar 
Leon, J. Central American and West Indian Species of Inga (Leguminosae). Ann. Mo. Bot. Gard. 53(3), 265–359 (1966).Article 

Google Scholar 
Blombery, A. & Rodd, T. Palms of the world (Angus and Robertson, 1992).
Google Scholar 
Wickens, G. E. Edible nuts: non-wood forest products, handbook 5 (FAO, 1995).
Google Scholar 
Chízmar, C. Plantas comestibles de Centroamérica. Santo Domingo de Heredia, Costa Rica: Editorial INBio. p. 358 (2009)Rodríguez, L. M. G. Growth and fruit production study of Bactris guineesis (güiscoyol) in Agroforestry Systems as development potential in the Chorotega Region (Universidad Técnica Nacional Investigación y transferencia, 2019).
Google Scholar 
Bax, V. & Francesconi, W. Conservation gaps and priorities in the Tropical Andes biodiversity hotspot: Implications for the expansion of protected areas. J. Environ. Manage. 232, 387–396 (2019).PubMed 
Article 

Google Scholar 
Noh, J. K. et al. Warning about conservation status of forest ecosystems in tropical Andes: National assessment based on IUCN criteria. PLoS One 15(8), e0237877 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Brooks, M. T. et al. Habitat loss and extinction in the hotspots of biodiversity. Biodivers. Conserv. 16(4), 909–923 (2002).
Google Scholar 
Ocampo, J. Diversidad y distribución de las Passifloraceae en el departamento del Huila en Colombia. Acta biologica Colombiana 18(3), 511–516 (2013).
Google Scholar 
Durán-Izquierdo, M. & Olivero-Verbel, J. Vulnerability assessment of Sierra Nevada de Santa Marta Colombia World’s most irreplaceable nature reserve. Glob. Ecol. Conserv. 28, e01592 (2021).Article 

Google Scholar 
Cabrera Gaviria, L.D., Gil Pereira, L.F. Comparative analysis of the loss of natural coverage in the protected areas Nukak and Puinawai and their effects on the ecosystems present in the period between the years 2000–2020. Thesis in Environmental and Sanitary Engineering. Universidad de La Salle, Bogotá. Available at: https://ciencia.lasalle.edu.co/ing_ambiental_sanitaria/1943 (2021) (In Spanish).Castillo, H. M. N. A story of the indigenous struggle against mining: the creation of the Yaigojé-Apaporis National Natural Park in the Colombian Amazon (Universidade Federal De Minas Gerais, 2018) ((In Portuguese)).
Google Scholar 
Walsh, J. & Sanchez, G. The spreading of illicit crops in Colombia (Instituto de Estudios para el Desarrollo y la Paz, Bogotá, 2008).
Google Scholar 
MAPS, OPS, ICBF. Encuesta Nacional de la Situacion Nutricional-ENSIN. Retrieved on 12 October, 2-21, from: http://www.ensin.gov.co/Documents/Documento-metodologico-ENSIN-2015.pdf (2015)Correa-García, E., Vélez-Correa, J., Zapata-Caldas, E., Vélez-Torres, I. & Figueroa-Casas, A. Territorial transformations produced by the sugarcane agroindustry in the ethnic communities of López Adentro and El Tiple, Colombia. Land Use Policy 76, 847–860 (2018).Article 

Google Scholar 
Hurtado, D. & Vélez-Torres, I. Toxic dispossession: on the social impacts of the aerial use of glyphosate by the sugarcane agroindustry in Colombia. Crit. Criminol. 28, 557–576 (2020).Article 

Google Scholar 
Vélez-Torres, I., Varela-Corredor, D., Rátiva-Gaona, S., Salcedo-Fidalgo, A. Agroindustry and extractivism in the Alto Cauca: impact on the livelihood systems of Afro-descendent Farmers and Resistance (1950–2011). CS, 12: 157–188. (2013) (In Spanish, English summary).Fernández Lucero, M. Protocol for the use of Guáimaro (Brosimum alicastrum Sw.) seeds in Montes de María and Serranía del Perijá, Colombian Caribbean. Bogotá: Instituto de Investigación de Recursos Biológicos Alexander von Humboldt (2021) (In Spanish).Santillán-Fernández, A. et al. Brosimum alicastrum Swartz as an alternative for the productive reconversion of agrosilvopastoral areas in Campeche. Revista Mexicana de Ciencias Forestales 11(61), 51–69 (2020).Article 

Google Scholar 
Subiria-Cueto, R. et al. Brosimum alicastrum Sw. (Ramón): an alternative to improve the nutritional properties and functional potential of the wheat flour tortilla. Foods 8(12), 613 (2019).CAS 
PubMed Central 
Article 

Google Scholar 
Quiñones-Hoyos, C., Rengifo-Fernández, A., Bernal-Galeano, S., Peña, R., Fernández, M., Tatiana Rojas, M., Diazgranados, M. A look at useful plants and fungi in three biodiverse areas of Colombia. Royal Botanic Gardens, Kew and Instituto de Investigaciones en Recursos Biológicos Alexander von Humboldt. Bogotá, Colombia (2021) (In Spanish)Royal Botanic Gardens, Kew. Discovering the Guáimaro trails: promote a market for native species. Retrieved on 18 February 2022 from https://storymaps.arcgis.com/stories/f540b764fc6c47db886b38515560852f (2022)Gottesch, B. et al. Extinction risk of Mesoamerican crop wild relatives. Plants People Planet 3, 775–795 (2021).Article 

Google Scholar 
French, B. Food plants international database of edible plants of the world, a free resource for all. Acta Hort. 1241, 1–6 (2019).
Google Scholar 
Meyers, N., Mittermeier, R., Mittermeier, C. G. & Kent, J. Biodiversity hotspot for conservation priority. Nature 403(6772), 853–858 (2000).Article 

Google Scholar  More

Siński, E. & Welc-Falęciak, R. Risk of Infections Transmitted by Ticks in Forest Ecosystems of Poland. (Zarządzanie Ochroną Przyrody w Lasach 6, 2012).Kantar Public. Zwierzęta w polskich domach, 2017. http://www.tnsglobal.pl/archiwumraportow/files/2017/05/K.021_Zwierzeta_domowe_O04a-17.pdf.Maia, C. et al. Bacterial and protozoal agents of feline vector-borne diseases in domestic and stray cats from southern Portugal. Parasit. Vectors. 7, 115. https://doi.org/10.1186/1756-3305-7-115 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Maia, C. et al. Bacterial and protozoal agents of canine vector-borne diseases in the blood of domestic and stray dogs from southern Portugal. Parasit. Vectors. 23(8), 138. https://doi.org/10.1186/s13071-015-0759-8 (2015).Article 

Google Scholar 
Baturo, I.M. Parki narodowe i krajobrazowe, rezerwaty przyrody. (Departament Turystyki, Sportu, Promocji Urzędu Marszłkowskiego Województwa Małopolskiego, 2010).Dulias, R. & Hibszer, A. Województwo śląskie—przyroda, gospodarka, dziedzictwo kulturowe (Wydawnictwo Kubajak, 2004).
Google Scholar 
Siuda, K. Kleszcze Polski Acari Ixodida). Część II. Systematyka i Rozmieszczenie (Polskie Towarzystwo Parazytologiczne, 1993).
Google Scholar 
Nowak-Chmura, M. Fauna kleszczy (Ixodida) Europy Środkowej (Wydawnictwo Naukowe Uniwersytetu Pedagogicznego, 2013).
Google Scholar 
Rijpkema, S., Golubić, D., Molkenboer, M., Verbeek-De Kruif, N. & Schellekens, J. Identification of four genomic groups of Borrelia burgdorferi sensu lato in Ixodes ricinus ticks collected in a Lyme borreliosis endemic region of northern Croatia. Exp. Appl. Acarol. 20, 23–30 (1996).CAS 
Article 

Google Scholar 
Wójcik-Fatla, A., Szymańska, J., Wdowiak, L., Buczek, A. & Dutkiewicz, J. Coincidence of three pathogens (Borrelia burgdorferi sensu lato, Anaplasma phagocytophilum and Babesia microti) in Ixodes ricinus ticks in the Lublin makroregion. Ann. Agric. Environ. Med. 16(1), 151–158 (2009).PubMed 

Google Scholar 
Massung, R. F. et al. Nested PCR assay for detection of granulocytic ehrlichiae. J. Clin. Microbiol. 36(4), 1090–1095 (1998).CAS 
Article 

Google Scholar 
Persing, D. H. et al. Detection of Babesia microti by polymerase chain reaction. J. Clin. Microbiol. 30, 2097–2103 (1992).CAS 
Article 

Google Scholar 
Sroka, J., Szymańska, J. & Wójcik-Fatla, A. The occurence of Toxoplasma gondii and Borrelia burgdorferi sensu lato in Ixodes ricinus ticks from east Poland with the use of PCR. Ann. Agric. Environ. Med. 16(2), 313–319 (2009).PubMed 

Google Scholar 
Siuda, K., Nowak, M., Gierczak, M., Wierzbowska, I. & Faber, M. Kleszcze (Acari: Ixodida) pasożytujące na psach i kotach domowych w Polsce. Wiad. Parazytol. 53, 155 (2007).
Google Scholar 
Zajkowska, P. Ticks (Acari:Ixodida) attacking domestic dogs in the Malopolska voivodeship, Poland. In Arthropods: In the contemporary world (eds Buczek, A. & Błaszak, C. Z.) 87–99 (Koliber, 2015).Chapter 

Google Scholar 
Szymański, S. Przypadek masowego rozwoju kleszcza Rhipicephalus sanguineus (Latreile, 1806) w warszawskim mieszkaniu. Wiad. Parazytol. 25, 453–458 (1979).PubMed 

Google Scholar 
Król, N., Obiegala, A., Pfeffer, M., Lonc, E. & Kiewra, D. Detection of selected pathogens in ticks collected from cats and dogs in the Wrocław Agglomeration South-West Poland. Parasit. Vectors. 9(1), 351. https://doi.org/10.1186/s13071-016-1632-0 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Kocoń, A., Nowak-Chmura, M., Kłyś, M. & Siuda, K. Ticks (Acari: Ixodida) attacking domestic cats (Felis catus L.) in southern Poland. In Arthropods in Urban and Suburban Environments (eds Buczek, A. & Błaszak, C.) 51–61 (Koliber, 2017).
Google Scholar 
Roczeń-Karczmarz, M. et al. Comparison of the occurrence of tick-borne diseases in ticks collected from vegetation and animals in the same area. Med. Weter. 74(8), 484–488. https://doi.org/10.21521/mw.6107 (2018).Article 

Google Scholar 
Cuber, P., Asman, M., Solarz, K., Szilman, E. & Szilman, P. Pierwsze stwierdzenia obecności wybranych patogenów chorób transmisyjnych w kleszczach Ixodes ricinus (Acari: Ixididae) zebranych w okolicach zbiorników wodnych w Rogoźniku (województwo śląskie) in Stawonogi. Ekologiczne i patologiczne aspekty układu pasożyt – żywiciel (eds. Buczek, C. & Błaszak, Cz.). 155-164 (Akapit, Lublin, 2010).Asman, M. et al. The risk of exposure to Anaplasma phagocytophilum, Borrelia burgdorferi sensu lato, Babesia sp. and co-infections in Ixodes ricinus ticks on the territory of Niepołomice Forest (southern Poland). Ann. Parasitol. 59(1), 13–19 (2013).PubMed 

Google Scholar 
Pawełczyk, O. et al. The PCR detection of Anaplasma phagocytophilum, Babesia microti and Borrelia burgdorferi sensu lato in ticks and fleas collected from pets in the Będzin district area (Upper Silesia, Poland) – the preliminary studies in Stawonogi: zagrożenie zdrowia człowieka i zwierząt (eds. Buczek, C. & Błaszak, Cz.). 111–119 (Koliber, Lublin, 2014).Strzelczyk, J. K. et al. Prevalence of Borrelia burgdorferi sensu lato in Ixodes ricinus ticks collected from southern Poland. Acta Parasitol. 60(4), 666–674. https://doi.org/10.1515/ap-2015-0095 (2015).CAS 
Article 
PubMed 

Google Scholar 
Zygner, W. & Wędrychowicz, H. Occurrence of hard ticks in dogs from Warsaw area. Ann. Agric. Environ. Med. 13(2), 355–359 (2006).PubMed 

Google Scholar 
Kilar, P. Ticks attacking domestic dogs in the area of the Rymanów district, Subcarpathian province Poland. Wiad. Parazytol. 57(3), 189–1991 (2011).PubMed 

Google Scholar 
Claerebout, E. et al. Ticks and associated pathogens collected from dogs and cats in Belgium. Parasit. Vectors. 6, 183. https://doi.org/10.1186/1756-3305-6-183 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Schreiber, C. et al. Pathogens in ticks collected from dogs in Berlin/Brandenburg, Germany. Parasit. Vectors. 7, 535. https://doi.org/10.1186/s13071-014-0535-1 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Eichenberger, R. M., Deplazes, P. & Mathis, A. Ticks on dogs and cats: A pet owner-based survey in a rural town in northeastern Switzerland. Ticks Tick-borne Dis. 6, 267–271. https://doi.org/10.1016/j.ttbdis.2015.01.007 (2015).Article 
PubMed 

Google Scholar 
Michalski, M. M. Skład gatunkowy kleszczy psów (Acari: Ixodida) z terenu aglomeracji miejskiej w cyklu wieloletnim. Med. Weter. 73(11), 698–701 (2017).
Google Scholar 
Geurden, T. et al. Detection of tick-borne pathogens in ticks from dogs and cats in different European countries. Ticks. Tick. Borne. Dis. 9(6), 1431–1436. https://doi.org/10.1016/j.ttbdis.2018.06.013 (2018).Article 
PubMed 

Google Scholar 
Namina, A. et al. Tick-borne pathogens in ticks collected from dogs, Latvia, 2011–2016. BMC Vet. Res. 15, 398. https://doi.org/10.1186/s12917-019-2149-5 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Bhide, M., Travnicek, M., Curlik, J. & Stefancikova, A. The importance of dogs in eco-epidemiology of Lyme borreliosis: a review. Vet. Med. Czech 49(4), 135–142 (2004).Article 

Google Scholar 
Burgess, E. C. Experimentally induced infection of cats with Borrelia burgdorferi. Am. J. Vet. Res. 53, 1507–1511 (1992).CAS 
PubMed 

Google Scholar 
Skotarczak, B. & Wodecka, B. Identification of Borrelia burgdorferi genospecies inducing Lyme disease in dogs from western Poland. Acta Vet. Hung. 53(1), 13–21 (2005).Article 

Google Scholar 
Skotarczak, B. et al. Prevalence of DNA and antibodies to Borrelia burgdorferi sensu lato in dogs suspected of borreliosis. Ann. Agric. Environm. Med. 12(2), 199–205 (2005).CAS 

Google Scholar 
Adaszek, Ł, Winiarczyk, S., Kutrzeba, J., Puchalski, A. & Dębiak, P. Przypadki boreliozy u psow na Lubelszczyźnie. Życie Wet. 83, 311–313 (2008).
Google Scholar 
Hovius, K. E. Borreliosis. In Arthropod-borne Infectious Diseases of the Dog and Cat (eds Shaw, S. E. & Day, M. J.) 100–109 (Manson Publishing, 2005).Chapter 

Google Scholar 
Zygner, W., Jaros, S. & Wędrychowicz, H. Prevalence of Babesia canis, Borrelia afzelii, and Anaplasma phagocytophilum infection in hard ticks removed from dogs in Warsaw (central Poland). Vet. Parasitol. 153, 139–142. https://doi.org/10.1016/j.vetpar.2008.01.036 (2008).Article 
PubMed 

Google Scholar 
Welc-Falęciak, R., Rodo, A., Siński, E. & Bajer, A. Babesia canis and other tick-borne infections in dogs in Central Poland. Vet. Parasitol. 166(3–4), 191–198. https://doi.org/10.1016/j.vetpar.2009.09.038 (2009).Article 
PubMed 

Google Scholar 
Michalski, M. M., Kubiak, K., Szczotko, M., Chajęcka, M. & Dmitryjuk, M. Molecular Detection of Borrelia burgdorferi Sensu Lato and Anaplasma phagocytophilum in Ticks Collected from Dogs in Urban Areas of North-Eastern Poland. Pathogens. 9(6), 455. https://doi.org/10.3390/pathogens9060455 (2020).CAS 
Article 
PubMed Central 

Google Scholar 
Nijhof, A. M. et al. Ticks and associated pathogens collected from domestic animals in the Netherlands. Vector. Borne. Zoonot. Dis. 7, 585–595. https://doi.org/10.1089/vbz.2007.0130 (2007).Article 

Google Scholar 
Adaszek, Ł, Martinez, A. C. & Winiarczyk, S. The factors affecting the distribution of babesiosis in dogs in Poland. Vet. Parasitol. 181, 160–165. https://doi.org/10.1016/j.vetpar.2011.03.059 (2011).Article 
PubMed 

Google Scholar 
Adaszek, Ł, Łukaszewska, J., Winiarczyk, S. & Kunkel, M. Pierwszy przypadek babeszjozy u kota w Polsce. Życie Wet. 83(8), 668–670 (2008).
Google Scholar 
Kocoń, A. et al. Molecular detection of tick-borne pathogens in ticks collected from pets in selected mountainous areas of Tatra County (Tatra Mountains, Poland). Sci. Rep. 10, 15865. https://doi.org/10.1038/s41598-020-72981-w (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Asman, M. et al. Detection of protozoans Babesia microti and Toxoplasma gondii and their co-existence in ticks (Acari: Ixodida) collected in Tarnogórski district (Upper Silesia, Poland). Ann. Agric. Environ. Med. 22(1), 80–83. https://doi.org/10.5604/12321966.1141373 (2015).Article 
PubMed 

Google Scholar 
Stensvold, C. R. et al. Babesia spp. and other pathogens in ticks recovered from domestic dogs in Denmark. Parasit. Vectors. 8(8), 262. https://doi.org/10.1186/s13071-015-0843-0 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Abdullah, S., Helps, C., Tasker, S., Newbury, H. & Wall, R. Prevalence and distribution of Borrelia and Babesia species in ticks feeding on dogs in the UK. Med. Vet. Entomol. 32(1), 14–22. https://doi.org/10.1111/mve.12257 (2018).CAS 
Article 
PubMed 

Google Scholar 
Bjoersdorff, A., Svendenius, L., Owens, J. H. & Massung, R. F. Feline granulocytic ehrlichiosis– a report of a new clinical entity and characterisation of the infectious agent. J. Small. Anim. Pract. 40(1), 20–24. https://doi.org/10.1111/j.1748-5827.1999.tb03249 (1999).CAS 
Article 
PubMed 

Google Scholar 
Lappin, M. R. et al. Molecular and serologic evidence of Anaplasma phagocytophilum infection in cats in North America. J. Am. Vet. Med. Assoc. 225(6), 893–896. https://doi.org/10.2460/javma.2004.225.893 (2004).Article 
PubMed 

Google Scholar 
Shaw, S. E. et al. Molecular evidence of tick-transmitted infections in dogs and cats in the United Kingdom. Vet. Rec. 157(21), 645–648. https://doi.org/10.1136/vr.157.21.645 (2005).CAS 
Article 
PubMed 

Google Scholar 
Tarello, W. Microscopic and clinical evidence for Anaplasma (Ehrlichia) phagocytophilum infection in Italian cats. Vet. Rec. 156(24), 772–774. https://doi.org/10.1136/vr.156.24.772 (2005).CAS 
Article 
PubMed 

Google Scholar 
Schaarschmidt-Kiener, D., Graf, F., von Loewenich, F. D. & Muller, W. Anaplasma phagocytophilum infection in a cat in Switzerland. Schweiz. Arch. Tierheilkd. 151(7), 336–341. https://doi.org/10.1024/0036-7281.151.7.336 (2009).CAS 
Article 
PubMed 

Google Scholar 
Heikkila, H. M., Bondarenko, A., Mihalkov, A., Pfister, K. & Spillmann, T. Anaplasma phagocytophilum infection in a domestic cat in Finland. Acta. Vet. Scand. 52(1), 62. https://doi.org/10.1186/1751-0147-52-62 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Hamel, D., Bondarenko, A., Silaghi, C., Nolte, I. & Pfister, K. Seroprevalence and bacteremia of Anaplasma phagocytophilum in cats from Bavaria and Lower Saxony (Germany). Berl. Munch. Tierarztl. Wochenschr. 125(3–4), 163–167 (2012).PubMed 

Google Scholar 
Morgenthal, D. et al. Prevalence of haemotropic Mycoplasma spp., Bartonella spp. and Anaplasma phagocytophilum in cats in Berlin/Brandenburg (Northeast Germany). Berl. Munch Tierarztl. Wochenschr. 125(9–10), 418–427 (2012).PubMed 

Google Scholar 
Adaszek, Ł, Winiarczyk, S. & Łukaszewska, J. A first case of ehrlichiosis in a horse in Poland. Dtsch. Tierarztl. Wchschr. 116(9), 330–334 (2009).
Google Scholar 
Adaszek, Ł, Policht, K., Gorna, M., Kutrzuba, J. & Winiarczyk, S. Pierwszy w Polsce przypadek anaplazmozy (erlichiozy) granulocytarnej u kota. Życie Wet. 86, 132–135 (2011).
Google Scholar 
Adaszek, Ł, Kotowicz, W., Klimiuk, P., Gorna, M. & Winiarczyk, S. Ostry przebieg anaplazmozy granulocytarnej u psa—przypadek własny. Wet. w Praktyce 9, 59–62 (2011).
Google Scholar 
Adaszek, Ł et al. Three clinical cases of Anaplasma phagocytophilum infection in cats in Poland. J. Feline Med. Surg. 15, 333–337. https://doi.org/10.1177/1098612X12466552 (2013).Article 
PubMed 

Google Scholar 
Pusterla, N. et al. Seroprevalence of Ehrlichia canis and of canine granulocytic ehrlichia infection in dogs in Switzerland. J. Clin. Microbiol. 36, 3460–3462. https://doi.org/10.1128/JCM.36.12.3460-3462.1998 (1998).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Egenvall, A. et al. Detection of granulocytic Ehrlichia species DNA by PCR in persistently infected dogs. Vet. Rec. 146(7), 186–190. https://doi.org/10.1136/vr.146.7.186 (2000).CAS 
Article 
PubMed 

Google Scholar 
Shaw, S. E. et al. Review of exotic infectious dise-ases in small animals entering the United Kingdom from abroad diagnosed by PCR. Vet. Rec. 152(6), 176–177. https://doi.org/10.1136/vr.152.6.176 (2003).CAS 
Article 
PubMed 

Google Scholar 
Skotarczak, B., Adamska, M. & Supron, M. Blood DNA analysis for Ehrlichia (Anaplasma) phagocytophila and Babesia spp in dogs from Northern Poland. Acta Vet. Brno. 73, 347–351. https://doi.org/10.1136/vr.152.6.176 (2004).Article 

Google Scholar 
Adaszek, Ł. Wybrane Aspekty Epidemiologii Babeszjozy, Boreliozy i Erlichiozy Psów (Praca doktorska, 2007).
Google Scholar 
Kybicová, K. et al. Detection of Anaplasma phagocytophilum and Borrelia burgdorferi sensu lato in dogs in the Czech Republic. Vec. Born Zoon Dis. 9(6), 655–661. https://doi.org/10.1089/vbz.2008.0127 (2009).Article 

Google Scholar  More

Our results show that the effects of the forest disturbance drivers on biodiversity are likely to be different from those simply expected from the baseline proportions of the forest disturbance drivers if we take into account the threatened species’ distributions. The amount of forest habitat is a primary factor for species diversity of many taxa, including mammals, amphibians, reptiles, birds, insects, and plants18. Indeed, our results revealed that threatened forest species have been exposed to a disproportional decrease in their habitat amount globally (i.e., lower proportions of forest with no or minor loss in all regions when species ranges were considered). Although this finding may be intuitive as population size and/or species range are part of the criteria in the IUCN assessment19, the detected pattern supports the validity of our approach of combining a forest disturbance map and species ranges for evaluating the impact of forest disturbances on threatened species. Moreover, we found that the dominant drivers differ among regions: the proportion of forestry, for example, increased in northern regions such as North America and Europe, whereas that of shifting agriculture increased in tropical regions when threatened species’ distributions were considered. These facts indicate although several influential international schemes for conservation have been implemented for regulating forestry20,21, different mechanisms aiming to directly tackle the over land use for local agriculture may increase their importance when we consider conservation in tropical regions. Our findings suggest that the social and economic drivers underlying the forest disturbance that impacts biodiversity differ among regions or nations, and it is important to establish specific conservation strategies in order to be effective.Based on the findings, we further emphasize that the combinations of multiple interacting drivers are likely to vary among regions. For example, the frequency and extent of stand-replacing natural disturbances such as wildfires have clearly been magnified by climate change, particularly in the Northern Hemisphere (e.g.,22). After such natural disturbances, societal demand for timber and/or pest reduction compels forest managers to ‘salvage’ timber by logging before it deteriorates, a common practice even in locations otherwise exempt from conventional green-tree harvesting, such as national parks or wilderness areas23. Thus, salvage logging clearly mediates the interaction between disturbances by forestry and wildfires and is likely to further affect biodiversity under climate change. Especially in regions where infrastructure (e.g., irrigation systems) has not been well developed, unpredictable changes in precipitation due to climate change was reported to increase forest disturbance by unregulated increases of agricultural land use24. Such regions largely overlapped with regions where shifting agriculture was identified as a dominant disturbance driver for threatened species in this study. Moreover, species themselves shift their ranges in response to climate change25, which would also shift major disturbance drivers and influential interactions of drivers to which the species are exposed, given the region-specific driver patterns. These examples clearly suggest the necessity to understand both the region-specific interrelations among multiple drivers and species’ responses for better prediction of land-use change and thus its effects on biodiversity.Shifting agriculture was the most dominant driver in all tropical regions corresponding to the recent estimates suggesting that the cover of regenerating secondary forest is increasing worldwide26. We demonstrated that this tendency is more drastic especially within the range of threatened species. The effect of shifting agriculture per unit area might be more limited than that of commodity-driven deforestation, which permanently alters forests into other land uses, since habitat structure might recover as the forest vegetation regenerates to a secondary state following the abandonment of the small clearings. However, ample evidence shows that many types of agricultural activities significantly degrade the conservation value of primary forest, especially in the tropics27, which often recovers very slowly if ever28 with the loss of irreplaceable conservation values. Therefore, given the wide areas of dominance of shifting agriculture across all tropical regions, its effect is likely to be pervasive. Consistently, our results show that species extinction risk (i.e., IUCN Red List status) is positively related to the proportional coverage of shifting agriculture (Fig. 2). In addition, as expected, a larger current proportion of shifting agriculture within a species range worsens the change rate in IUCN Red List status of the species (Fig. 4b). Furthermore, the effect is anticipated to be magnified for forest specialists because they are exposed to larger proportions of shifting agriculture than are forest generalist (Fig. 2), and they are also reported to recover more slowly than do forest habitat generalists27,28.A guideline for forest restoration suggested that appropriately sized landscapes should contain ≥40% forest cover (higher percentages are likely needed in the tropics), with about 10% in a very large forest patch and the remaining 30% in many evenly dispersed smaller patches and semi-natural wooded elements (e.g., vegetation corridors)29. Importantly, the guideline also suggests that the patches should be embedded in a high-quality matrix. Although younger secondary forest cannot be a substitute for pristine forest until 50 years or more after a disturbance, it can help to improve the quality of matrix in agricultural landscapes30. Indeed, we show that the negative impacts of shifting agriculture and forestry on IUCN status change have improved over time (Fig. 4b, c), presumably corresponding to the forest regenerating and recovery process. In contrast, the pattern of commodity-driven deforestation, a land use accompanied with permanent forest loss, showed a prolonged negative impact on IUCN status change (Fig. 4a). Notably, whether regenerating forests can move towards a highly diverse and structurally complex state or towards a state of low to intermediate levels of biodiversity and structural complexity depends on the amount of remaining intact mature forest in the landscape29. Therefore, a promising direction for future research would be to develop our analysis further to include spatiotemporal relationships among mature forest remnants, secondary forests, disturbance drivers, and threatened species populations.For conserving the core patches of mature forests, the establishment of protected areas (PAs) is one of the most effective legal measures that has been widely used to regulate land use for biodiversity31. On the other hand, for improving matrix quality, balancing conservation and use of the ecosystem would be critically important; shifting agriculture, for example, causes forest degradation, but it also contributes to food supply chains sourced from smallholder farmers and to food security of local communities8. In fact, establishing mechanisms for managing biodiversity-friendly landscapes has been intensively discussed recently, given the large potential influence of these landscapes on conservation32. These mechanisms include setting an international target on OECMs15. Our finding of a disproportional decrease in forest proportions with minor or no loss within species ranges supports the urgency of the discussion. At the same time, our results highlight an opportunity because large portions of the disturbed forests for threatened species are dominated by shifting agriculture at the global scale, especially in the tropics. As suggested above, if manged properly, such landscapes can still retain or improve functions as essential habitats and/or matrix for a variety of forest-dwelling species. Our analytical method provides a tool set to identify and prioritize areas where such attempts are urgently needed.Global demands for natural resources and ecosystem services drive land use in forests33 and thus affect biodiversity. Therefore, connecting the supply chains to the five major drivers of forest disturbance and their spatial overlaps with biodiversity is essential to inform how we should regulate and design material flows from forest ecosystems to keep them sustainable by minimizing the effects on biodiversity. Existing studies examining the impacts of resource consumption on biodiversity through supply chains of various sectors have often been assessed at the country scale (e.g.,12), partly because the availability of statistics needed to estimate material flows in supply chains is usually limited at finer (i.e., subnational) scales (but see34). We believe that our study provides the first basis for filling the resolution gap between trade statistics and local biodiversity effects by identifying patterns of the local co-occurrence of biodiversity and the forest disturbance drivers that can be directly linked to resource production at the national scale. Note, however, that downscaling a remotely sensed global data set into finer scales inevitably propagates errors and biases which include both those in the original maps and those in the processed data produced by analyses. Thus, preparation of more high-resolution data sets is essential, especially for disturbance drivers and threatened species’ distributions in our case, to keep the errors and biases at a reasonable level at focal spatial scales.The effectiveness of area-based conservation measures to regulate land use for conservation including PAs and OECMs also depends strongly on social and ecosystem conditions. For example, a few studies show that the effectiveness of PAs in halting or slowing forest disturbances depends on PA characteristics such as size and history, as well as on the management entities such as subnational governments or indigenous peoples35,36,37. Moreover, there has been no attempt to elucidate whether PAs and OECMs are effective at regulating supply chains as a supply-side measure by balancing resource production, ecosystem services for local communities, and biodiversity conservation; to tackle this issue, it will be necessary to conduct extensive analyses integrating spatial and temporal patterns of biodiversity, forest loss, its drivers, and material flows in global food supply chains. Though it is challenging and beyond the scope of this paper, solving this issue is urgent and raises a promising opportunity for future research. More

Cockroach strainsAll cockroaches were maintained on rodent diet (Purina 5001, PMI Nutrition International, St. Louis, MO) and distilled water at 27 °C, ~40% RH, and a 12:12 h L:D cycle. The WT colony (Orlando Normal) was collected in Florida in 1947 and has served as a standard insecticide-susceptible strain. The GA colony (T-164) was collected in 1989, also in Florida, and shown to be aversive to glucose; continued artificial selection with glucose-containing toxic bait fixed the homozygous GA trait in this population (approximately 150 generations as of 2020).Generating recombinant lines and life history dataTo homogenize the genetic backgrounds of the WT and GA strains, two recombinant colonies were initiated in 2013 by crossing 10 pairs of WT♂ × GA♀ and 10 pairs of GA♂ × WT♀ (Fig. 3a). At the F8 generation (free bulk mating without selection), 400 cockroaches were tested in two-choice feeding assays (see below) that assessed their initial response to tastants, as described in previous studies11,26. The cockroaches were separated into glucose-accepting and glucose-rejecting groups by the rapid Acceptance-Rejection assay (described in Feeding Bioassays). These colonies were bred for three more generations, and 200 cockroaches from each group were assayed in the F11 generation and backcrossed to obtain homozygous glucose-accepting (aa) and glucose-averse (AA) lines. Similar results were obtained in both directions of the cross, confirming previous findings of no sex linkage of the GA trait27. These two lines were defined as WT_aa (homozygotes, glucose-accepting) and GA_AA (homozygotes, glucose-averse). To obtain heterozygous GA cockroaches, GA_Aa, a single intercross group was generated from crosses of 10 pairs of WT_aa♂ × GA_AA♀ and 10 pairs of GA_AA♂ × WT_aa♀.The GA trait follows Mendelian inheritance. Therefore, we used backcrosses, guided by two-choice feeding assays and feeding responses in Acceptance-rejection assays, to determine the homozygosity of WT and GA cockroaches. The cross of WT♂ × WT♀ produced homozygous F1 cockroaches showing maximal glucose-acceptance. The cross of GA♂ × GA♀ produced homozygous F1 cockroaches showing maximal glucose-aversion. The cross of WT × GA produced F1 heterozygotes with intermediate glucose-aversion. When the F1 heterozygotes were backcrossed with WT cockroaches, they produced F2 cockroaches with a 1:1 ratio of WT and GA phenotypes.The two-choice feeding assay assessed whether cockroaches accepted or rejected glucose (binary: yes-no). Insects were held for 24 h without water, or starved without food and water. Either 10 adults or 2 day-old first instar siblings (30–40) were placed in a Petri dish (either 90 mm or 60 mm diameter × 15 mm height). Each Petri dish contained two agar discs: one disc contained 1% agar and 1 mmol l−1 red food dye (Allura Red AC), and the second disc contained 1% agar, 0.5 mmol l−1 blue food dye (Erioglaucine disodium salt) and either 1000 mmol l−1 or 3000 mmol l−1 glucose. The assay duration was 2 h during the dark phase of the insects’ L:D cycle. After each assay, the color of the abdomen of each cockroach was visually inspected under a microscope to infer the genotype.We assessed whether the recombinant colonies had different traits from the parental WT and GA lines. We paired single newly eclosed females (day 0) with single 10–12 days-old males of the same line in a Petri dish (90 mm diameter, 15 mm height) with fresh distilled water in a 1.5 ml microcentrifuge tube and a pellet of rodent food, and monitored when they mated. When females formed egg cases, each gravid female was placed individually in a container (95 × 95 × 80 mm) with food and water until the eggs hatched. After removing the female, her offspring were monitored until adult emergence. We recorded the time to egg hatch, first appearance of each nymphal stage, first appearance of adults and the end of adult emergence. The first instar nymphs and adults in each cohort were counted to obtain measures of survivorship. Although there were significant differences in some of these parameters across all four strains, we found no significant differences between the two recombinant lines, except mating success, which was significantly lower in GA_AA♀ than WT_aa♀ (Supplementary Table 11).Mating bioassaysAll mating sequences were recorded using an infra-red-sensitive camera (Polestar II EQ610, Everfocus Electronics, New Taipei City, Taiwan) coupled to a data acquisition board and analyzed by searchable and frame-by-frame capable software (NV3000, AverMedia Information) at 27 °C, ~40% RH and a 12:12 h L:D cycle. For behavioral analysis, tested pairs were classified into two groups: mated (successful courtship) and not-mated (failed courtship). Four distinct behavioral events (Fig. 1c, Contact, Wing raising, Nuptial feeding, and Copulation) were analyzed using seven behavioral parameters as shown in Supplementary Table 2.We extracted behavioral data from successful courtship sequences, defined as courtship that led to Copulation. For failed courtship sequences, we extracted the behavioral data from the first courtship of both mated and not-mated groups, because most pairs in both groups failed to copulate in their first encounter, and there were no significant differences in behavioral parameters between the two groups.To assay female choice, we conducted two-choice mating assays (Fig. 1a). A single focal WT♀ or GA♀ and two males, one WT and one GA, were placed in a Petri dish (90 mm diameter, 15 mm height) with fresh distilled water in a 1.5 ml microcentrifuge tube and a pellet of rodent food (n = 25 WT♀ and 27 GA♀). To assay male choice, a single focal WT♂ or GA♂ was given a choice of two females, one WT♀ and one GA♀ (n = 27 WT♂ and 18 GA♂). Experiments were started using 0 day-old sexually unreceptive females and 10–12 days-old sexually mature males. Newly emerged (0 day-old) females were used to avoid the disruption of introducing a sexually mature female into the bioassay. B. germanica females become sexually receptive at 5–7 days of age, so the mating behavior of the focal insect was video-recorded for several days until they mated. Fertility of mated females was evaluated by the number of offspring produced. We assessed the gustatory phenotype of nymphs (either WT-type or GA-type) to determine which of the two adult cockroaches mated with the focal insect. Each gravid female was maintained individually in a container (95 × 95 × 80 mm) with food and water until the eggs hatched. Two day-old first instar nymphs were starved for one day without water and food, and then they were tested in Two-choice feeding assays using 1000 mmol l−1 glucose-containing agar with 0.5 mmol l−1 blue food dye vs. plain sugar-free agar with 1 mmol l−1 red food dye. If all the nymphs chose the glucose-containing agar, their parents were considered WT♂ and WT♀. When all the nymphs showed glucose-aversion, they were raised to the adult stage. Newly emerged adults were backcrossed with WT cockroaches, and their offspring were tested in the Two-choice assay. When the parents were both GA, 100% of the offspring exhibited glucose-aversion. When the parents were WT and GA, the offspring showed a 1:1 ratio of glucose-accepting and glucose-aversive behavior. Mate choice, mating success ratio and the number of offspring were analyzed statistically.We conducted no-choice mating assay using the WT and GA strains (Fig. 1b, d). A female and a male were placed in a Petri dish with fresh water and a piece of rodent food and video-recorded for 24 h. The females were 5–7 days-old and males were 10–12 days-old. Four treatment pairs were tested: WT♂ × WT♀ (n = 20, 18 and 14 pairs for 5, 6 and 7 day-old females, respectively); GA♂ × GA♀ (n = 23, 22 and 35 pairs); GA♂ × WT♀ (n = 21, 14 and 17 pairs); and WT♂ × GA♀ (n = 33, 19 and 15 pairs).To confirm that gustatory stimuli guide nuptial feeding, we artificially augmented the male nuptial secretion and assessed whether the duration of nuptial feeding and mating success of GA♀ were affected (Fig. 2c). Before starting the mating assay with 5 day-old GA♀, 10–12 days-old WT♂ were separated into three groups: A control group did not receive any augmentation; A water control group received distilled water with 1 mmol l−1 blue dye (+Blue); A fructose group received 3000 mmol l−1 fructose solution with blue dye (+Blue+Fru). Approximately 50 nl of the test solution was placed into the tergal gland reservoirs using a glass microcapillary. No-choice mating assays were carried out for 24 h. n = 20–25 pairs for each treatment.We evaluated the association of short nuptial feeding (Fig. 1c) and the GA trait we conducted no-choice mating assays using females from the recombinant lines (Fig. 3c). Before starting each mating assay with 4 day-old females from the WT, GA and recombinant lines (WT_aa, GA_AA and GA_Aa), the EC50 for glucose was obtained by the instantaneous Acceptance-Rejection assay using 0, 10, 30, 100, 300, 1000 and 3000 mmol l−1 glucose (WT♀ and WT_aa♀, non-starved; GA♀, GA_AA♀ and GA_Aa♀, 1-day starved). After the Acceptance-Rejection assay, GA_Aa♀ were separated into two groups according to their sensitivity for rejecting glucose; the GA_Aa_high sensitivity group rejected glucose at 100 and 300 mmol l−1, whereas the GA_Aa_low sensitivity group rejected glucose at 1000 and 3000 mmol l−1. We paired these females with 10–12 days-old WT♂ (n = 15 WT_aa♀, n = 20 GA_AA♀, n = 20 GA_Aa_high♀ and n = 17 GA_Aa_low♀).Feeding bioassayWe conducted two feeding assays: Acceptance-Rejection assay and Consumption assay. The Acceptance-Rejection assay assessed the instantaneous initial responses (binary: yes-no) of cockroaches to tastants, as previously described7,22,27. Briefly, acceptance means that the cockroach started drinking. Rejection means that the cockroach never initiated drinking. The percentage of positive responders was defined as the Number of insects accepting tastants/Total number of insects tested. The effective concentration (EC50) for each tastant was obtained from dose-response curves using this assay. The Consumption assay was previously described27. Briefly, we quantified the amount of test solution females ingested after they started drinking. Females were observed until they stopped drinking, and we considered this a single feeding bout.We used the Acceptance-Rejection assay and Consumption assay, respectively, to assess the sensitivity of 5 day-old WT♀ and GA♀ for accepting and consuming the WT♂ nuptial secretion (Fig. 2a, b). The secretion was diluted with HPLC-grade water to 0.001, 0.01, 0.03, 0.1, 0.3 and 1 male-equivalents/µl (n = 20 non-starved females each). The amount of nuptial secretion consumed was tested at 0.1 male-equivalents/µl in the Consumption assay (n = 10 each).The Acceptance-Rejection assay was used to calculate the effective concentration (EC50) of glucose for females in the WT, GA and recombinant lines (Fig. 3a, b). A glucose concentration series of 0.1, 1, 10, 100 and 1000 mmol l−1 was tested with one-day starved 4-day old females (n = 65 GA_Aa♀, n = 50 GA_AA♀ and n = 50 GA♀) and non-starved females (n = 50 WT_aa♀ and n = 16 WT♀).The effects of female saliva on feeding responses of 5 day-old WT♀ and GA♀ were tested using the Acceptance-Rejection assay (Fig. 4a). Freshly collected saliva of WT♀ and GA♀ was immediately used in experiments. Assays were prepared as follows: 3 µl of 200 mmol l−1 maltose or maltotriose were mixed with 3 µl of either HPLC-grade water or saliva of WT♀ or GA♀. The final concentration of each sugar was 100 mmol l−1 in a total volume of 6 µl. This concentration represented approximately the acceptance EC70 for WT♀ and GA♀27. Nuptial secretion (1 µl representing 10 male-equivalents) was mixed with 1 µl of either HPLC-grade water or saliva from WT♀ or GA♀, and 8 µl of HPLC-grade water was added to the mix. The final concentration of the nuptial secretion was 1 male-equivalent/µl in a total volume of 10 µl. This concentration also represented approximately the acceptance EC70 for WT♀ and GA♀ (Fig. 2a). The mix of saliva and either sugar or nuptial secretion was incubated for 300 s at 25 °C. Additionally, we tested the effect of only saliva in the Acceptance-Rejection assay. Either 1-day starved or non-starved females were tested with water only and then a 1:1 mixture of saliva and water. Saliva alone did not affect acceptance or rejection of stimuli. n = 20–33 females from each strain.To evaluate whether salivary enzymes are involved in the hydrolysis of oligosaccharides, the contribution of salivary glucosidases was tested using the glucosidase inhibitor acarbose in the Acceptance-Rejection assay (Fig. 4b), as previously described27. We first confirmed that the range of 0–125 mmol l−1 acarbose in HPLC-grade water did not disrupt the acceptance and rejection of tastants. Test solutions were prepared as follows: 2 µl of either HPLC-grade water or saliva of GA♀ was mixed with 1 µl of either 250 µmol l−1 of acarbose or HPLC-grade water, then the mixture was added to 1 µl of 400 mmol l−1 of either maltose or maltotriose solution. The total volume was 4 µl, with the final concentration of sugar being 100 mmol l−1. For assays with nuptial secretion, 1 µl of either HPLC-grade water or saliva from 5 day-old GA♀ was mixed with 0.5 µl of either 250 µmol l−1 of acarbose or HPLC-grade water. This mixture was added to 0.5 µl of 10 male-equivalents of nuptial secretion (i.e., 20 male-equivalents/µl). HPLC-grade water was added for a total volume of 10 µl and a final concentration of 1 male-equivalent/µl. The mix of saliva and either sugars or nuptial secretion was incubated for 5 min at 25 °C. All test solutions contained blue food dye. Test subjects were 5 day-old GA♀ and 20–25 females were tested in each assay.Nuptial secretion and saliva collectionsThe nuptial secretion of WT♂ was collected by the following method: Five 10–12 days-old males were placed in a container (95 × 95 × 80 mm) with 5 day-old GA♀. After the males displayed wing-raising courtship behavior toward the females, individual males were immediately decapitated and the nuptial secretion in their tergal gland reservoirs was drawn into a calibrated borosilicate glass capillary (76 × 1.5 mm) under the microscope. The nuptial secretions from 30 males were pooled in a capillary and stored at −20 °C until use. Saliva from 5 day-old WT♀ and GA♀ was collected by the following method: individual females were briefly anesthetized with carbon dioxide under the microscope and the side of the thorax was gently squeezed. A droplet of saliva that accumulated on the mouthparts was then collected into a microcapillary (10 µl, Kimble Glass). Fresh saliva was immediately used in experiments.GC-MS procedures for analysis of sugarsStandards of D-( + )-glucose (Sigma-Aldrich), D-( + )-maltose (Fisher Scientific) and maltotriose (Sigma-Aldrich) were diluted in HPLC-grade water (Fisher Scientific) at 10, 50, 100, 500 and 1000 ng/µl to generate calibration curves. Samples were vortexed for 20 s and a 10 μl aliquot of each sample was transferred to a Pyrex reaction vial containing a 10 μl solution of 5 ng/μl sorbitol (≥98%) in HPLC-grade water as internal standard and dried under a gentle flow of N2 for 20 min.Samples containing degradation products from nuptial secretions were prepared by adding 15 μl of HPLC-water to each sample in a 1.5 ml Eppendorf tube, vortexed for 30 s and centrifuged at 8000 rpm (5223 RCF) for 5 min to separate lipids from the water layer. The water phase was transferred to a reaction vial using a glass capillary. This procedure was repeated with the remaining lipid layer and the water layers were combined in the same reaction vial containing 10 μl of a solution of 5 ng/μl sorbitol and dried under N2 for 20 min.For derivatization of sugars and samples, each reaction vial received 12 μl of anhydrous pyridine under a constant N2 flow, then vortexed and incubated at 90 °C for 5 min. Three μl of N-methyl-N-(trimethylsilyl)trifluoroacetamide (MSTFA; Sigma-Aldrich) was added to each reaction vial and centrifuged at 1000 rpm (118 RCF) for 2 min. Vials were incubated in a heat block at 90 °C for 1.5 hr and vortexed every 10 min for the first 30 min of incubation.The total volume of sample was ~10 μl, and 1 μl was injected into the GC-MS (6890 GC coupled to a 5975 MS, Agilent Technologies, Palo Alto, CA). The inlet was operated in splitless mode (17.5 psi) at 290 °C. The GC was equipped with a DB-5 column (30 m, 0.25 mm, 0.25 μm, Agilent), and helium was used as the carrier gas at an average velocity of 50 cm/s. The oven temperature program started at 80 °C for 1 min, increased at 10 °C/min to 180 °C, then increased at 5 °C/min to 300 °C, and held for 10 min. The transfer line was set at 250 °C for 24 min, ramped at 5 °C/min to 300 °C and held until the end of program. The ion source operated at 70 eV and 230 °C, while the MS quadrupole was maintained at 200 °C. The MSD was operated in scan mode, starting after 9 min (solvent delay time) with a mass range of 33–650 AMU.For GC-MS data analysis, the sorbitol peak area was obtained from the extracted ion chromatograms with m/z = 205, the sorbitol base peak. The area of peaks of glucose, maltose and maltotriose were obtained from the extracted ion chromatograms using m/z = 204, the base peak of the three sugars. The most abundant peaks of each sugar were selected for quantification36, and these peaks did not coelute with other peaks. Then, the peak areas of the three sugars were divided by the area of the respective sorbitol peak in each sample to normalize the data and to correct technical variability during sample processing. This procedure was performed to obtain the calibration curves and quantification of sugars in our experiments.The results of sugar analysis using GC-MS are reported in Supplementary Figs. 1–4.Analysis of nuptial secretionsWe focused the GC-MS analysis on glucose, maltose and maltotriose in WT♂ nuptial secretion (Fig. 4c). To quantify the time-course of saliva-catalyzed hydrolysis of WT♂ nuptial secretion to glucose, 1 µl of GA♀ saliva was mixed with 1 µl of 10 male-equivalents/µl. We incubated the mixtures for 0, 5, 10 and 300 s at 25 °C, and added 4 µl of methanol to stop the enzyme activity (n = 5 each treatment). Each sample contained the nuptial secretions of 5 males to obtain enough detectable amount of sugars. For the statistical analysis, the amounts of sugars were divided by 5 to obtain the amount of sugars in 1 male (1 male-equivalent). These amounts were also used for generating Fig. 4c and Supplementary Table 9. In calculations of the concentration of the three sugars (mmol l−1), the mass and volume of the nuptial secretion were measured using 70–130 male-equivalents of undiluted secretion of each strain (n = 3). The mass and volume of the nuptial secretion/male, including both lipid and aqueous layers, were approximately 30–50 µg and 40–50 nl. Because it was difficult to separate the lipid layer from the water layer at this small scale, we roughly estimated that the tergal reservoirs of the four cockroach lines had 30 nl of aqueous layer that contained sugars.To quantify the time-course of saliva-catalyzed hydrolysis of maltose and maltotriose to glucose, 1 µl of GA♀ saliva was mixed with 1 µl of 200 mmol l−1 of either maltose or maltotriose (Fig. 4d, e). Incubation time points were 0, 5, 10 and 300 s at 25 °C and methanol was used to stop the enzyme activity. Controls without saliva were also prepared using HPLC-grade water instead of saliva and 300 s incubations. n = 5 for each treatment.PhotomicroscopyThe photographs of the tergal glands and mouthparts (Fig. 5) were obtained using an Olympus Digital camera attached to an Olympus CX41 microscope (Olympus America, Center Valley, PA).Statistics and reproducibilityThe sample size and number of replicates for each experiment are noted in the respective section describing the experimental details. In summary, the samples sizes were: Mating bioassays, n = 18–80; Feeding assays, n = 16–65; Sugar analysis, n = 5; Life history parameters, n  > 14. All statistical analyses were conducted in R Statistical Software (v4.1.0; R Core Team 2021) and JMP Pro 15.2 software (SAS Institute Inc., Carey, NC). For bioassay data and sugar analysis data, we calculated the means and standard errors, and we used the Chi-square test with Holm’s method for post hoc comparisons, t-test, and ANOVA followed by Tukey’s HSD test (all α = 0.05), as noted in each section describing the experimental details, results, and in Supplementary Tables 1–11.Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

Godfray, H. C. J. et al. Science 327, 812–818 (2010).ADS 
CAS 
Article 

Google Scholar 
Pimm, S. L. et al. Science 344, 1246752 (2014).CAS 
Article 

Google Scholar 
Chung, M. G. & Liu, J. Nat. Food https://doi.org/10.1038/s43016-022-00499-7 (2022).Myers, N., Mittermeier, R. A., Mittermeier, C. G., Da Fonseca, G. A. & Kent, J. Nature 403, 853–858 (2000).ADS 
CAS 
Article 

Google Scholar 
A complex prairie ecosystem. National Park Service https://www.nps.gov/tapr/learn/nature/a-complex-prairie-ecosystem.htm (2022)Davalos, L. M. et al. Environ. Sci. Technol. 45, 1219–1227 (2011).ADS 
CAS 
Article 

Google Scholar 
Vijay, V., Pimm, S. L., Jenkins, C. N. & Smith, S. J. PLoS ONE 11, e0159668 (2016).Article 

Google Scholar 
Liu, J. et al. Ecol. Soc. 18, 26 (2013).CAS 
Article 

Google Scholar 
Liu, J. Consumption patterns and biodiversity. The Royal Society https://go.nature.com/3M19vup (2020).Xu, Z. et al. Nat. Sustain. 3, 964–971 (2020).Article 

Google Scholar 
Dou, Y., da Silva, R. F. B., Yang, H. & Liu, J. J. Geogr. Sci. 28, 1715–1732 (2018).Article 

Google Scholar  More