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Predicted distribution for Iguana iguana in the Pacific ( a ), and the islands where they have been reported as established: Hawai‘i ( b ) and Fiji ( c ). The circle ( a ) represents the Ryukyu archipelago in Japan, and the arrow indicates the location of Ishigaki Island. Darker colors denote higher probabilities for the presence of the species.
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Green iguanas (Iguana iguana L.) have been introduced to many locations outside their native range due to both the pet trade and illegal in- troductions. This has led to the establishment of populations and subsequent spread outside the native range, with negative impacts documented in some places. The Pacific region is no exception, where green ig...
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... on the Pacific projection of our model, we observed that many islands of the Pacific show some degree of climatic suitabil- ity for green iguanas (Figure 5a) (see Table 1 for climatic suitability). For the Hawaiian Is- lands (Figure 5b have been reported (McKeown 1996, Kraus 2005, the model predicts high climatic suit- ability. ...
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... on the Pacific projection of our model, we observed that many islands of the Pacific show some degree of climatic suitabil- ity for green iguanas (Figure 5a) (see Table 1 for climatic suitability). For the Hawaiian Is- lands (Figure 5b have been reported (McKeown 1996, Kraus 2005, the model predicts high climatic suit- ability. The same is true for Kaua'i, Moloka'i, and the island of Hawai'i, especially ...
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... suitable areas on Maui are a few kilo- meters away from where a green iguana was recently captured (Kraus 2005). On the other hand, the model predicts high climatic suit- ability in virtually all islands of the Fijian ar- chipelago, including the ones where breeding populations and sightings have been reported (Figure 5c). In the case of Japan, the model predicts suitable habitat in the southwest coastal area of Kagoshima and virtually all the Ryukyu Islands, including Ishigaki Island, where green iguanas are established ( Figure 5a). ...
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... the other hand, the model predicts high climatic suit- ability in virtually all islands of the Fijian ar- chipelago, including the ones where breeding populations and sightings have been reported (Figure 5c). In the case of Japan, the model predicts suitable habitat in the southwest coastal area of Kagoshima and virtually all the Ryukyu Islands, including Ishigaki Island, where green iguanas are established ( Figure 5a). Moreover, the Ogasawara archipelago (also known as the Bonin Islands or Ogas- awara Guntö, Japan), where green iguanas were introduced through the pet trade (Shimizu 1995in Kraus 2009, and the Kazan Is- lands (south of Ogasawara) show high cli- matic suitability (>0.30 ...
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... et al. 2006). The Test AUC measures the model performance outside the model training points, for which the Test AUC provides a better indication of predictive ability of the model. Models with AUC values ≥ 0.90 are considered to have an excellent predictive performance; values < 0.90 are interpreted as having good (0.80 – 0.90) to poor ( < 0.70) predictive performance (Swets 1988, Manel et al. 2001, Franklin 2009). The average Training AUC of the GCB model was 0.90 (indicating how well the resulting predicted distribution matches the locations of the training data), and the average Test AUC value was 0.87 (indicating how well the resulting prediction of the geo- graphic distribution matches occurrence sites that were reserved for model testing) (Falcón et al. 2012). The GCB model demonstrated a high predictive ability for green iguanas in both the native and the invasive range in the Americas, and predicted the potential for spread in the Greater Caribbean Region (Fal- cón et al. 2012). To determine the potential distribution of green iguanas in the Pacific, we projected the GCB model into a set of Pacific layers ( longi- tudes 66 to − 139°, latitudes 47 to − 60°) using MaxEnt. The predicted distribution for green iguanas in the Pacific was visualized using DIVA-GIS after generating a binary map of presence/absence by using the average of the logistic threshold value that maximizes the sum of the training sensitivity and the speci- ficity (MTrS + S) as the cutoff point (0.30) (Falcón et al. 2012). The logistic output for- mat from MaxEnt provides values that range from 0 to 1, indicating the presence probabil- ity of the species in a given pixel (Phillips and Dudík 2008). The sensitivity is the propor- tion of correctly predicted presence observa- tions, and the specificity is the proportion of correctly predicted absences in terms of the fractional area predicted. The MTrS + S threshold criterion minimizes the mean of the error rate for positive and negative observa- tions (Manel et al. 2001, Freeman and Moisen 2008). When compared with other criteria, the Maximum Sensitivity plus Specificity threshold performs comparably or better than other threshold selection methods in provid- ing accurate presence predictions (Liu et al. 2005, Jiménez-Valverde and Lobo 2007, Freeman and Moisen 2008). Some areas of the Pacific layers used for the projection had environmental conditions that were not pres- ent in the calibration area ( layers used to train the model). To avoid incorrect predictions, we subtracted the layer with clamping pro- vided from the predicted distribution pro- duced by our model from the predicted dis- tribution (as recommended by S. J. Phillips). The clamping layer provides information about climatic values in a given pixel of the predictive layers that are outside the climatic conditions of the training data. Based on the Pacific projection of our model, we observed that many islands of the Pacific show some degree of climatic suitabil- ity for green iguanas (Figure 5 a ) (see Table 1 for climatic suitability). For the Hawaiian Is- lands (Figure 5 b ), the model predicts climatic suitability in areas where green iguanas have been captured, although it is not known whether recent captures were escaped illegal pet iguanas or established individuals. In O‘ahu and Maui, where feral populations have been reported (McKeown 1996, Kraus 2005), the model predicts high climatic suit- ability. The same is true for Kaua‘i, Moloka‘i, and the island of Hawai‘i, especially in coastal areas. For the island of Hawai‘i, the model predicts high climatic suitability, mainly along the coastline. Although a ring of climatically suitable areas is predicted around Mauna Loa, variables such as the minimum temperature during the coldest month may negatively af- fect the survival of green iguanas. Moreover, soil as well as biotic conditions in the area may not be suitable for reproduction. During our visit to the Hawaiian Islands, we observed suitable habitat and nesting areas for green iguanas in the predicted areas, with high climate suitability on Hawai‘i, O‘ahu, and Kaua‘i. O‘ahu has patches of exotic red man- grove ( Rhizophora mangle ), a species known to harbor high-density populations of iguanas in Florida and Puerto Rico. In the case of Maui, the model predicts suitability along the coasts on the east side, all over the west side of the island, and on the offshore islands as well. These suitable areas on Maui are a few kilo- meters away from where a green iguana was recently captured (Kraus 2005). On the other hand, the model predicts high climatic suit- ability in virtually all islands of the Fijian ar- chipelago, including the ones where breeding populations and sightings have been reported (Figure 5 c ). In the case of Japan, the model predicts suitable habitat in the southwest coastal area of Kagoshima and virtually all the Ryukyu Islands, including Ishigaki Island, where green iguanas are established (Figure 5 a ). Moreover, the Ogasawara archipelago (also known as the Bonin Islands or Ogas- awara Guntö, Japan), where green iguanas were introduced through the pet trade (Shi- mizu 1995 in Kraus 2009), and the Kazan Is- lands (south of Ogasawara) show high cli- matic suitability (>0.30 [not shown]). Also, all of the island of Tahiti (where a feral iguana was reported [see section on History]) appears to be climatically suitable. Moreover, tropical Australia shows high climatic suitability for green iguanas, especially in the coastal areas, including Townsville, Queensland, where a feral green iguana was reported (Csurhes 2011). Climatch (a climate-matching soft- ware [Australian Bureau of Rural Sciences 2009]) was used to predict suitable areas in Australia for green iguanas, and the results coincide with those of our model (see Csurhes 2011). Thus, according to the model, poten- tially suitable habitats are widespread in the Pacific. Green iguanas are found in habitats with a wide range of climatic conditions that vary from xeric dry tropical forests to mesic moun- tainous forests. In Florida, however, the northern expansion of the iguanas appears to be hindered by low winter temperatures, al- though it has been noted that many iguanas seek shelters in burrows and under buildings (Townsend et al. 2003). Using occurrence locations of green iguanas ( n = 187), we were able to extract climatic information about the location in which the reptiles were recorded (Falcón et al. 2012). Based on these data, the mean annual temperature for I. iguana loca- tions was 25.5°C (SD = 2.91; range: 18.2– 28.3°C). The mean maximum temperature during the warmest month throughout the range of green iguanas was 32.5°C (SD = 1.97; range: 23.3–37.3°C), whereas the mean mini- mum temperature during the coldest month was 18.5°C (SD = 2.78; range: 9.7– 23.7°C). As for precipitation, the mean annual precipi- tation value of the occurrence locations of green iguanas was 1,754.03 mm (SD = 882; range: 234 – 4,900 mm), the mean precipita- tion of the wettest month was 306 mm (SD = 139; range: 68–759 mm), and the mean precipitation of the driest month was 34 mm (SD = 37; range: 0 –190 mm). These reptiles are primarily arboreal, require trees and basking areas, and are typically found in riparian zones, around lakes and mangrove swamps, in dry forests, semiarid islands, and in relatively open areas where food resources are available (Swanson 1950, Moberly 1968, Mu ࡇ ller 1972, Distel and Veazey 1982, van Devender 1982, van Marken Lichtenbelt et al. 1993, Benítez-Malvido et al. 2003). In their invasive range, green iguanas are found in the same habitats, usually as- sociated with water in urbanized landscapes such as bays, parks, ditches, canals, and man- groves (Rivero 1998, Meshaka et al. 2004, Joglar 2005). They are also found on coastal cliffs in Martinique (Breuil 1997, Breuil 2002). In Puerto Rico, they occupy secondary forests domi nated by nonnative trees Albizia procera and Spathodea campanulata along the north and east coasts, as well as in some interior val- leys. In Florida, they disperse along water- ways (Meshaka et al. 2004), and the same seems to be true in Fiji (van Veen 2011), and Puerto Rico. When they are found near bodies of water, green iguanas are difficult to capture because they usually drop into the water when threatened or disturbed. When chased along the littoral zone, they can dive into the ocean and remain underwater for a considerable time (Rivero 1998, Joglar 2005, Harlow and Thomas 2010). Neonates and young iguanas tend to use low branches and are often found in groups of 10 –20 indi- viduals in a space of only several square meters (van Devender 1982, Burghardt and Rand 1985). Mature iguanas prefer trees with thick foliage and direct sun exposure, where they spend the day eating, and pass the night on perches located in the same area, whereas juveniles are more mobile (van Devender 1982). The home range of males is larger than that of females and juveniles, and can be up to 9,000 m 2 (Rand et al. 1989). Adult male iguanas hold territories where smaller males, juveniles, and females are tol- erated (Mu ࡇ ller 1972). Mature males establish territories primarily during the breeding sea- son to secure high and well-exposed areas where they perform their mating displays (Rodda 1992). In Hawai‘i, green iguanas primarily occupied forested valleys (McKeown 1996), but recent sightings in O‘ahu have been in or near resi- dential urban areas. In Fiji, all sightings of green iguanas have been within coastal areas, and the majority of observations occurred, in order of frequency, in mangrove forests, coastal headlands, and beach and littoral habi- tat (van Veen 2011). On Ishigaki Island, igua- nas are mainly found in windbreak forests along the coast (S. Tanigaki and S. Abe, pers. comm.). Iguanas have been reported from the Hawai- ian island of O‘ahu since the late 1950s or early 1960s, where breeding populations ...
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... range (Florida and Puerto Rico). Cli- matic variables considered were annual mean temperature (BIO1), isothermality (BIO3), temperature seasonality (BIO4), minimum temperature of the coldest month (BIO6), mean temperature of the warmest quarter (BIO10), annual precipitation (BIO12), pre- cipitation seasonality (BIO15), and precipita- tion of the warmest quarter (BIO18) as pre- dictive variables (for clarifications on the definitions, refer to .org/ bioclim). These temperature and pre- cipitation variables represent conditions that are biologically important to green iguanas and may limit their distribution (e.g., Mober- ly 1968, van Devender 1982, Bock and Rand 1989, van Marken Lichtenbelt et al. 1993, 1997). Once we had the occurrence records and the climatic variables for our GCB model, we assessed the potential distribution of green iguanas in the Greater Caribbean basin using the maximum entropy method for niche mod- eling (MaxEnt version 3.3.3e [Phillips et al. 2004, 2006]). MaxEnt uses machine learning methods with presence-only data in combina- tion with predictive variables to model the geographic distribution of a species (Phillips and Dudík 2008). Ten replicates of the model were run using bootstrapping, and 80% of the presence records were randomly selected for training, while 20% were reserved for testing in each run. Separate from the GCB model (Falcón et al. 2012), we ran the Pacific Region model with the “Auto features” on (i.e., the Threshold feature was used in this model). The performance of the model was evaluated using the AUC statistics (Area Under the ROC [Receiver Operating Characteristic] Curve), which yielded an average AUC value of 0.90. The AUC is a summary statistic that provides a measure of the performance of the model by comparing the predicted geo- graphical distribution of the species with the background data (Phillips et al. 2006). The Test AUC measures the model performance outside the model training points, for which the Test AUC provides a better indication of predictive ability of the model. Models with AUC values ≥ 0.90 are considered to have an excellent predictive performance; values < 0.90 are interpreted as having good (0.80 – 0.90) to poor ( < 0.70) predictive performance (Swets 1988, Manel et al. 2001, Franklin 2009). The average Training AUC of the GCB model was 0.90 (indicating how well the resulting predicted distribution matches the locations of the training data), and the average Test AUC value was 0.87 (indicating how well the resulting prediction of the geo- graphic distribution matches occurrence sites that were reserved for model testing) (Falcón et al. 2012). The GCB model demonstrated a high predictive ability for green iguanas in both the native and the invasive range in the Americas, and predicted the potential for spread in the Greater Caribbean Region (Fal- cón et al. 2012). To determine the potential distribution of green iguanas in the Pacific, we projected the GCB model into a set of Pacific layers ( longi- tudes 66 to − 139°, latitudes 47 to − 60°) using MaxEnt. The predicted distribution for green iguanas in the Pacific was visualized using DIVA-GIS after generating a binary map of presence/absence by using the average of the logistic threshold value that maximizes the sum of the training sensitivity and the speci- ficity (MTrS + S) as the cutoff point (0.30) (Falcón et al. 2012). The logistic output for- mat from MaxEnt provides values that range from 0 to 1, indicating the presence probabil- ity of the species in a given pixel (Phillips and Dudík 2008). The sensitivity is the propor- tion of correctly predicted presence observa- tions, and the specificity is the proportion of correctly predicted absences in terms of the fractional area predicted. The MTrS + S threshold criterion minimizes the mean of the error rate for positive and negative observa- tions (Manel et al. 2001, Freeman and Moisen 2008). When compared with other criteria, the Maximum Sensitivity plus Specificity threshold performs comparably or better than other threshold selection methods in provid- ing accurate presence predictions (Liu et al. 2005, Jiménez-Valverde and Lobo 2007, Freeman and Moisen 2008). Some areas of the Pacific layers used for the projection had environmental conditions that were not pres- ent in the calibration area ( layers used to train the model). To avoid incorrect predictions, we subtracted the layer with clamping pro- vided from the predicted distribution pro- duced by our model from the predicted dis- tribution (as recommended by S. J. Phillips). The clamping layer provides information about climatic values in a given pixel of the predictive layers that are outside the climatic conditions of the training data. Based on the Pacific projection of our model, we observed that many islands of the Pacific show some degree of climatic suitabil- ity for green iguanas (Figure 5 a ) (see Table 1 for climatic suitability). For the Hawaiian Is- lands (Figure 5 b ), the model predicts climatic suitability in areas where green iguanas have been captured, although it is not known whether recent captures were escaped illegal pet iguanas or established individuals. In O‘ahu and Maui, where feral populations have been reported (McKeown 1996, Kraus 2005), the model predicts high climatic suit- ability. The same is true for Kaua‘i, Moloka‘i, and the island of Hawai‘i, especially in coastal areas. For the island of Hawai‘i, the model predicts high climatic suitability, mainly along the coastline. Although a ring of climatically suitable areas is predicted around Mauna Loa, variables such as the minimum temperature during the coldest month may negatively af- fect the survival of green iguanas. Moreover, soil as well as biotic conditions in the area may not be suitable for reproduction. During our visit to the Hawaiian Islands, we observed suitable habitat and nesting areas for green iguanas in the predicted areas, with high climate suitability on Hawai‘i, O‘ahu, and Kaua‘i. O‘ahu has patches of exotic red man- grove ( Rhizophora mangle ), a species known to harbor high-density populations of iguanas in Florida and Puerto Rico. In the case of Maui, the model predicts suitability along the coasts on the east side, all over the west side of the island, and on the offshore islands as well. These suitable areas on Maui are a few kilo- meters away from where a green iguana was recently captured (Kraus 2005). On the other hand, the model predicts high climatic suit- ability in virtually all islands of the Fijian ar- chipelago, including the ones where breeding populations and sightings have been reported (Figure 5 c ). In the case of Japan, the model predicts suitable habitat in the southwest coastal area of Kagoshima and virtually all the Ryukyu Islands, including Ishigaki Island, where green iguanas are established (Figure 5 a ). Moreover, the Ogasawara archipelago (also known as the Bonin Islands or Ogas- awara Guntö, Japan), where green iguanas were introduced through the pet trade (Shi- mizu 1995 in Kraus 2009), and the Kazan Is- lands (south of Ogasawara) show high cli- matic suitability (>0.30 [not shown]). Also, all of the island of Tahiti (where a feral iguana was reported [see section on History]) appears to be climatically suitable. Moreover, tropical Australia shows high climatic suitability for green iguanas, especially in the coastal areas, including Townsville, Queensland, where a feral green iguana was reported (Csurhes 2011). Climatch (a climate-matching soft- ware [Australian Bureau of Rural Sciences 2009]) was used to predict suitable areas in Australia for green iguanas, and the results coincide with those of our model (see Csurhes 2011). Thus, according to the model, poten- tially suitable habitats are widespread in the Pacific. Green iguanas are found in habitats with a wide range of climatic conditions that vary from xeric dry tropical forests to mesic moun- tainous forests. In Florida, however, the northern expansion of the iguanas appears to be hindered by low winter temperatures, al- though it has been noted that many iguanas seek shelters in burrows and under buildings (Townsend et al. 2003). Using occurrence locations of green iguanas ( n = 187), we were able to extract climatic information about the location in which the reptiles were recorded (Falcón et al. 2012). Based on these data, the mean annual temperature for I. iguana loca- tions was 25.5°C (SD = 2.91; range: 18.2– 28.3°C). The mean maximum temperature during the warmest month throughout the range of green iguanas was 32.5°C (SD = 1.97; range: 23.3–37.3°C), whereas the mean mini- mum temperature during the coldest month was 18.5°C (SD = 2.78; range: 9.7– 23.7°C). As for precipitation, the mean annual precipi- tation value of the occurrence locations of green iguanas was 1,754.03 mm (SD = 882; range: 234 – 4,900 mm), the mean precipita- tion of the wettest month was 306 mm (SD = 139; range: 68–759 mm), and the mean precipitation of the driest month was 34 mm (SD = 37; range: 0 –190 mm). These reptiles are primarily arboreal, require trees and basking areas, and are typically found in riparian zones, around lakes and mangrove swamps, in dry forests, semiarid islands, and in relatively open areas where food resources are available (Swanson 1950, Moberly 1968, Mu ࡇ ller 1972, Distel and Veazey 1982, van Devender 1982, van Marken Lichtenbelt et al. 1993, Benítez-Malvido et al. 2003). In their invasive range, green iguanas are found in the same habitats, usually as- sociated with water in urbanized landscapes such as bays, parks, ditches, canals, and man- groves (Rivero 1998, Meshaka et al. 2004, Joglar 2005). They are also found on coastal cliffs in Martinique (Breuil 1997, Breuil 2002). In Puerto Rico, they occupy secondary forests domi nated by nonnative trees Albizia procera and Spathodea campanulata along the north and east coasts, as well as in some interior val- leys. In ...
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... the model included 166 records from the native range and 21 records from the invasive range (Florida and Puerto Rico). Cli- matic variables considered were annual mean temperature (BIO1), isothermality (BIO3), temperature seasonality (BIO4), minimum temperature of the coldest month (BIO6), mean temperature of the warmest quarter (BIO10), annual precipitation (BIO12), pre- cipitation seasonality (BIO15), and precipita- tion of the warmest quarter (BIO18) as pre- dictive variables (for clarifications on the definitions, refer to .org/ bioclim). These temperature and pre- cipitation variables represent conditions that are biologically important to green iguanas and may limit their distribution (e.g., Mober- ly 1968, van Devender 1982, Bock and Rand 1989, van Marken Lichtenbelt et al. 1993, 1997). Once we had the occurrence records and the climatic variables for our GCB model, we assessed the potential distribution of green iguanas in the Greater Caribbean basin using the maximum entropy method for niche mod- eling (MaxEnt version 3.3.3e [Phillips et al. 2004, 2006]). MaxEnt uses machine learning methods with presence-only data in combina- tion with predictive variables to model the geographic distribution of a species (Phillips and Dudík 2008). Ten replicates of the model were run using bootstrapping, and 80% of the presence records were randomly selected for training, while 20% were reserved for testing in each run. Separate from the GCB model (Falcón et al. 2012), we ran the Pacific Region model with the “Auto features” on (i.e., the Threshold feature was used in this model). The performance of the model was evaluated using the AUC statistics (Area Under the ROC [Receiver Operating Characteristic] Curve), which yielded an average AUC value of 0.90. The AUC is a summary statistic that provides a measure of the performance of the model by comparing the predicted geo- graphical distribution of the species with the background data (Phillips et al. 2006). The Test AUC measures the model performance outside the model training points, for which the Test AUC provides a better indication of predictive ability of the model. Models with AUC values ≥ 0.90 are considered to have an excellent predictive performance; values < 0.90 are interpreted as having good (0.80 – 0.90) to poor ( < 0.70) predictive performance (Swets 1988, Manel et al. 2001, Franklin 2009). The average Training AUC of the GCB model was 0.90 (indicating how well the resulting predicted distribution matches the locations of the training data), and the average Test AUC value was 0.87 (indicating how well the resulting prediction of the geo- graphic distribution matches occurrence sites that were reserved for model testing) (Falcón et al. 2012). The GCB model demonstrated a high predictive ability for green iguanas in both the native and the invasive range in the Americas, and predicted the potential for spread in the Greater Caribbean Region (Fal- cón et al. 2012). To determine the potential distribution of green iguanas in the Pacific, we projected the GCB model into a set of Pacific layers ( longi- tudes 66 to − 139°, latitudes 47 to − 60°) using MaxEnt. The predicted distribution for green iguanas in the Pacific was visualized using DIVA-GIS after generating a binary map of presence/absence by using the average of the logistic threshold value that maximizes the sum of the training sensitivity and the speci- ficity (MTrS + S) as the cutoff point (0.30) (Falcón et al. 2012). The logistic output for- mat from MaxEnt provides values that range from 0 to 1, indicating the presence probabil- ity of the species in a given pixel (Phillips and Dudík 2008). The sensitivity is the propor- tion of correctly predicted presence observa- tions, and the specificity is the proportion of correctly predicted absences in terms of the fractional area predicted. The MTrS + S threshold criterion minimizes the mean of the error rate for positive and negative observa- tions (Manel et al. 2001, Freeman and Moisen 2008). When compared with other criteria, the Maximum Sensitivity plus Specificity threshold performs comparably or better than other threshold selection methods in provid- ing accurate presence predictions (Liu et al. 2005, Jiménez-Valverde and Lobo 2007, Freeman and Moisen 2008). Some areas of the Pacific layers used for the projection had environmental conditions that were not pres- ent in the calibration area ( layers used to train the model). To avoid incorrect predictions, we subtracted the layer with clamping pro- vided from the predicted distribution pro- duced by our model from the predicted dis- tribution (as recommended by S. J. Phillips). The clamping layer provides information about climatic values in a given pixel of the predictive layers that are outside the climatic conditions of the training data. Based on the Pacific projection of our model, we observed that many islands of the Pacific show some degree of climatic suitabil- ity for green iguanas (Figure 5 a ) (see Table 1 for climatic suitability). For the Hawaiian Is- lands (Figure 5 b ), the model predicts climatic suitability in areas where green iguanas have been captured, although it is not known whether recent captures were escaped illegal pet iguanas or established individuals. In O‘ahu and Maui, where feral populations have been reported (McKeown 1996, Kraus 2005), the model predicts high climatic suit- ability. The same is true for Kaua‘i, Moloka‘i, and the island of Hawai‘i, especially in coastal areas. For the island of Hawai‘i, the model predicts high climatic suitability, mainly along the coastline. Although a ring of climatically suitable areas is predicted around Mauna Loa, variables such as the minimum temperature during the coldest month may negatively af- fect the survival of green iguanas. Moreover, soil as well as biotic conditions in the area may not be suitable for reproduction. During our visit to the Hawaiian Islands, we observed suitable habitat and nesting areas for green iguanas in the predicted areas, with high climate suitability on Hawai‘i, O‘ahu, and Kaua‘i. O‘ahu has patches of exotic red man- grove ( Rhizophora mangle ), a species known to harbor high-density populations of iguanas in Florida and Puerto Rico. In the case of Maui, the model predicts suitability along the coasts on the east side, all over the west side of the island, and on the offshore islands as well. These suitable areas on Maui are a few kilo- meters away from where a green iguana was recently captured (Kraus 2005). On the other hand, the model predicts high climatic suit- ability in virtually all islands of the Fijian ar- chipelago, including the ones where breeding populations and sightings have been reported (Figure 5 c ). In the case of Japan, the model predicts suitable habitat in the southwest coastal area of Kagoshima and virtually all the Ryukyu Islands, including Ishigaki Island, where green iguanas are established (Figure 5 a ). Moreover, the Ogasawara archipelago (also known as the Bonin Islands or Ogas- awara Guntö, Japan), where green iguanas were introduced through the pet trade (Shi- mizu 1995 in Kraus 2009), and the Kazan Is- lands (south of Ogasawara) show high cli- matic suitability (>0.30 [not shown]). Also, all of the island of Tahiti (where a feral iguana was reported [see section on History]) appears to be climatically suitable. Moreover, tropical Australia shows high climatic suitability for green iguanas, especially in the coastal areas, including Townsville, Queensland, where a feral green iguana was reported (Csurhes 2011). Climatch (a climate-matching soft- ware [Australian Bureau of Rural Sciences 2009]) was used to predict suitable areas in Australia for green iguanas, and the results coincide with those of our model (see Csurhes 2011). Thus, according to the model, poten- tially suitable habitats are widespread in the Pacific. Green iguanas are found in habitats with a wide range of climatic conditions that vary from xeric dry tropical forests to mesic moun- tainous forests. In Florida, however, the northern expansion of the iguanas appears to be hindered by low winter temperatures, al- though it has been noted that many iguanas seek shelters in burrows and under buildings (Townsend et al. 2003). Using occurrence locations of green iguanas ( n = 187), we were able to extract climatic information about the location in which the reptiles were recorded (Falcón et al. 2012). Based on these data, the mean annual temperature for I. iguana loca- tions was 25.5°C (SD = 2.91; range: 18.2– 28.3°C). The mean maximum temperature during the warmest month throughout the range of green iguanas was 32.5°C (SD = 1.97; range: 23.3–37.3°C), whereas the mean mini- mum temperature during the coldest month was 18.5°C (SD = 2.78; range: 9.7– 23.7°C). As for precipitation, the mean annual precipi- tation value of the occurrence locations of green iguanas was 1,754.03 mm (SD = 882; range: 234 – 4,900 mm), the mean precipita- tion of the wettest month was 306 mm (SD = 139; range: 68–759 mm), and the mean precipitation of the driest month was 34 mm (SD = 37; range: 0 –190 mm). These reptiles are primarily arboreal, require trees and basking areas, and are typically found in riparian zones, around lakes and mangrove swamps, in dry forests, semiarid islands, and in relatively open areas where food resources are available (Swanson 1950, Moberly 1968, Mu ࡇ ller 1972, Distel and Veazey 1982, van Devender 1982, van Marken Lichtenbelt et al. 1993, Benítez-Malvido et al. 2003). In their invasive range, green iguanas are found in the same habitats, usually as- sociated with water in urbanized landscapes such as bays, parks, ditches, canals, and man- groves (Rivero 1998, Meshaka et al. 2004, Joglar 2005). They are also found on coastal cliffs in Martinique (Breuil 1997, Breuil 2002). In Puerto Rico, they occupy secondary forests domi nated by nonnative trees Albizia procera and Spathodea campanulata ...
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... average AUC value of 0.90. The AUC is a summary statistic that provides a measure of the performance of the model by comparing the predicted geo- graphical distribution of the species with the background data (Phillips et al. 2006). The Test AUC measures the model performance outside the model training points, for which the Test AUC provides a better indication of predictive ability of the model. Models with AUC values ≥ 0.90 are considered to have an excellent predictive performance; values < 0.90 are interpreted as having good (0.80 – 0.90) to poor ( < 0.70) predictive performance (Swets 1988, Manel et al. 2001, Franklin 2009). The average Training AUC of the GCB model was 0.90 (indicating how well the resulting predicted distribution matches the locations of the training data), and the average Test AUC value was 0.87 (indicating how well the resulting prediction of the geo- graphic distribution matches occurrence sites that were reserved for model testing) (Falcón et al. 2012). The GCB model demonstrated a high predictive ability for green iguanas in both the native and the invasive range in the Americas, and predicted the potential for spread in the Greater Caribbean Region (Fal- cón et al. 2012). To determine the potential distribution of green iguanas in the Pacific, we projected the GCB model into a set of Pacific layers ( longi- tudes 66 to − 139°, latitudes 47 to − 60°) using MaxEnt. The predicted distribution for green iguanas in the Pacific was visualized using DIVA-GIS after generating a binary map of presence/absence by using the average of the logistic threshold value that maximizes the sum of the training sensitivity and the speci- ficity (MTrS + S) as the cutoff point (0.30) (Falcón et al. 2012). The logistic output for- mat from MaxEnt provides values that range from 0 to 1, indicating the presence probabil- ity of the species in a given pixel (Phillips and Dudík 2008). The sensitivity is the propor- tion of correctly predicted presence observa- tions, and the specificity is the proportion of correctly predicted absences in terms of the fractional area predicted. The MTrS + S threshold criterion minimizes the mean of the error rate for positive and negative observa- tions (Manel et al. 2001, Freeman and Moisen 2008). When compared with other criteria, the Maximum Sensitivity plus Specificity threshold performs comparably or better than other threshold selection methods in provid- ing accurate presence predictions (Liu et al. 2005, Jiménez-Valverde and Lobo 2007, Freeman and Moisen 2008). Some areas of the Pacific layers used for the projection had environmental conditions that were not pres- ent in the calibration area ( layers used to train the model). To avoid incorrect predictions, we subtracted the layer with clamping pro- vided from the predicted distribution pro- duced by our model from the predicted dis- tribution (as recommended by S. J. Phillips). The clamping layer provides information about climatic values in a given pixel of the predictive layers that are outside the climatic conditions of the training data. Based on the Pacific projection of our model, we observed that many islands of the Pacific show some degree of climatic suitabil- ity for green iguanas (Figure 5 a ) (see Table 1 for climatic suitability). For the Hawaiian Is- lands (Figure 5 b ), the model predicts climatic suitability in areas where green iguanas have been captured, although it is not known whether recent captures were escaped illegal pet iguanas or established individuals. In O‘ahu and Maui, where feral populations have been reported (McKeown 1996, Kraus 2005), the model predicts high climatic suit- ability. The same is true for Kaua‘i, Moloka‘i, and the island of Hawai‘i, especially in coastal areas. For the island of Hawai‘i, the model predicts high climatic suitability, mainly along the coastline. Although a ring of climatically suitable areas is predicted around Mauna Loa, variables such as the minimum temperature during the coldest month may negatively af- fect the survival of green iguanas. Moreover, soil as well as biotic conditions in the area may not be suitable for reproduction. During our visit to the Hawaiian Islands, we observed suitable habitat and nesting areas for green iguanas in the predicted areas, with high climate suitability on Hawai‘i, O‘ahu, and Kaua‘i. O‘ahu has patches of exotic red man- grove ( Rhizophora mangle ), a species known to harbor high-density populations of iguanas in Florida and Puerto Rico. In the case of Maui, the model predicts suitability along the coasts on the east side, all over the west side of the island, and on the offshore islands as well. These suitable areas on Maui are a few kilo- meters away from where a green iguana was recently captured (Kraus 2005). On the other hand, the model predicts high climatic suit- ability in virtually all islands of the Fijian ar- chipelago, including the ones where breeding populations and sightings have been reported (Figure 5 c ). In the case of Japan, the model predicts suitable habitat in the southwest coastal area of Kagoshima and virtually all the Ryukyu Islands, including Ishigaki Island, where green iguanas are established (Figure 5 a ). Moreover, the Ogasawara archipelago (also known as the Bonin Islands or Ogas- awara Guntö, Japan), where green iguanas were introduced through the pet trade (Shi- mizu 1995 in Kraus 2009), and the Kazan Is- lands (south of Ogasawara) show high cli- matic suitability (>0.30 [not shown]). Also, all of the island of Tahiti (where a feral iguana was reported [see section on History]) appears to be climatically suitable. Moreover, tropical Australia shows high climatic suitability for green iguanas, especially in the coastal areas, including Townsville, Queensland, where a feral green iguana was reported (Csurhes 2011). Climatch (a climate-matching soft- ware [Australian Bureau of Rural Sciences 2009]) was used to predict suitable areas in Australia for green iguanas, and the results coincide with those of our model (see Csurhes 2011). Thus, according to the model, poten- tially suitable habitats are widespread in the Pacific. Green iguanas are found in habitats with a wide range of climatic conditions that vary from xeric dry tropical forests to mesic moun- tainous forests. In Florida, however, the northern expansion of the iguanas appears to be hindered by low winter temperatures, al- though it has been noted that many iguanas seek shelters in burrows and under buildings (Townsend et al. 2003). Using occurrence locations of green iguanas ( n = 187), we were able to extract climatic information about the location in which the reptiles were recorded (Falcón et al. 2012). Based on these data, the mean annual temperature for I. iguana loca- tions was 25.5°C (SD = 2.91; range: 18.2– 28.3°C). The mean maximum temperature during the warmest month throughout the range of green iguanas was 32.5°C (SD = 1.97; range: 23.3–37.3°C), whereas the mean mini- mum temperature during the coldest month was 18.5°C (SD = 2.78; range: 9.7– 23.7°C). As for precipitation, the mean annual precipi- tation value of the occurrence locations of green iguanas was 1,754.03 mm (SD = 882; range: 234 – 4,900 mm), the mean precipita- tion of the wettest month was 306 mm (SD = 139; range: 68–759 mm), and the mean precipitation of the driest month was 34 mm (SD = 37; range: 0 –190 mm). These reptiles are primarily arboreal, require trees and basking areas, and are typically found in riparian zones, around lakes and mangrove swamps, in dry forests, semiarid islands, and in relatively open areas where food resources are available (Swanson 1950, Moberly 1968, Mu ࡇ ller 1972, Distel and Veazey 1982, van Devender 1982, van Marken Lichtenbelt et al. 1993, Benítez-Malvido et al. 2003). In their invasive range, green iguanas are found in the same habitats, usually as- sociated with water in urbanized landscapes such as bays, parks, ditches, canals, and man- groves (Rivero 1998, Meshaka et al. 2004, Joglar 2005). They are also found on coastal cliffs in Martinique (Breuil 1997, Breuil 2002). In Puerto Rico, they occupy secondary forests domi nated by nonnative trees Albizia procera and Spathodea campanulata along the north and east coasts, as well as in some interior val- leys. In Florida, they disperse along water- ways (Meshaka et al. 2004), and the same seems to be true in Fiji (van Veen 2011), and Puerto Rico. When they are found near bodies of water, green iguanas are difficult to capture because they usually drop into the water when threatened or disturbed. When chased along the littoral zone, they can dive into the ocean and remain underwater for a considerable time (Rivero 1998, Joglar 2005, Harlow and Thomas 2010). Neonates and young iguanas tend to use low branches and are often found in groups of 10 –20 indi- viduals in a space of only several square meters (van Devender 1982, Burghardt and Rand 1985). Mature iguanas prefer trees with thick foliage and direct sun exposure, where they spend the day eating, and pass the night on perches located in the same area, whereas juveniles are more mobile (van Devender 1982). The home range of males is larger than that of females and juveniles, and can be up to 9,000 m 2 (Rand et al. 1989). Adult male iguanas hold territories where smaller males, juveniles, and females are tol- erated (Mu ࡇ ller 1972). Mature males establish territories primarily during the breeding sea- son to secure high and well-exposed areas where they perform their mating displays (Rodda 1992). In Hawai‘i, green iguanas primarily occupied forested valleys (McKeown 1996), but recent sightings in O‘ahu have been in or near resi- dential urban areas. In Fiji, all sightings of green iguanas have been within coastal areas, and the majority of observations occurred, in order of frequency, in mangrove forests, coastal headlands, and beach and littoral habi- tat (van Veen 2011). On Ishigaki Island, igua- nas are ...
Citations
... In most cases, the use of animal predators has been used for addressing invasive fish Poole and Bajer 2019) or invertebrate pests (Garcia et al. 2020;Trdan et al. 2020;Lee et al. 2022). The establishment of an introduced species population is usually indicative of indigenous predators having limited impact on their numbers, or indigenous predators occurring at low population levels (Conti et al. 2021;Twinning et al. 2022); however, indigenous predators may provide enough predation pressure to prevent exotic species from successfully establishing by suppressing released or escaped individuals that would otherwise be founder individuals (Mori et al. 2020 (Meshaka et al. 2004b;Krysko et al. 2007), Hawaii (Powell 2005), Fiji (Falcón et al. 2013), Taiwan (Lee et al. 2019, and Japan (Mito and Uesugi 2004). These populations have become established mainly through captive iguanas being distributed widely through the exotic pet trade (Mitchell and Shane 2000;Stephen et al. 2011) and some subsequently escaping or being released (Meshaka et al. 2004a). ...
... Green Iguanas in captive collections have also been reported with bacterial skin infections, which may represent a risk to native reptiles (Hellebuyck et al. 2018). Introduced populations of Green Iguanas also have social and economic impacts, such as problems for gardeners and horticulturalists from iguanas consuming vegetation (Krysko et al. 2007;Falcón et al. 2013), their burrowing behavior causing soil erosion, bank destabilization, and damage to infrastructure (López-Torres et al. 2012), and iguanas representing runway strike hazards at airport sites (Engeman et al. 2005). Mitigating the risk of Green Iguanas establishing populations in Hong Kong would therefore have triplebottom line benefits. ...
Biological control is the management of non-native species through the use of their natural enemies. The Green Iguana (Iguana iguana), a large lizard of the Neotropics, has established populations in extralimital countries. There has been an increasing recent pattern of reports of free-living Green Iguanas in Hong Kong, which was the trigger of this desktop assessment of native Hong Kong fauna that may prey upon escaped or released iguanas. A literature review found documented predators of Green Iguanas from 12 vertebrate orders. There were two mammalian orders (Carnivora, Primates), eight avian orders (Cuculiformes, Pelecaniformes, Accipitriformes, Cathartiformes, Falconiformes, Strigiformes, Piciformes, Passeriformes), and two reptilian orders (Squamata, Crocodylia), which are all presently represented in Hong Kong with the exception of the orders Cathartiformes and Crocodylia. Based on knowledge of other taxa documented to prey upon lizards represented in Hong Kong, we suggested additional prospective predators of Green Iguanas from one further mammalian order (Artiodactyla) and one further avian order (Ciconiiformes). Since avian species generally have a greater representation in settled areas, along with stray domestic dogs and cats, we expect these species to be the potential predators most likely to take iguanas when they are first released or escaped.
... Su distribución es restringida por las bajas temperaturas, por lo que no se han establecido en el norte de Florida. Las iguanas verdes son comunes en entornos urbanos (14). Además de prosperar en áreas modificadas por humanos en Florida (por ejemplo, vecindarios suburbanos), también se encuentran en hábitats naturales como manglares y pinares (8). ...
... Se han observado a juveniles y adultos alimentándose de caracoles. Las iguanas verdes adultas ocasionalmente se alimentan de vertebrados pequeños, huevos de aves e incluso carroña (8,9,14,15). ...
... El ciclista requirió puntos en la cabeza y la iguana no sobrevivió el encuentro (23). También pueden causar accidentes vehiculares cuando cruzan repentinamente las carreteras (14). En lugares de Florida con altas densidades de iguanas, a menudo se encuentran muertas en la carretera después de ser atropelladas por automóviles (24). ...
Esta publicación resume el conocimiento general sobre la iguana verde (Iguana iguana) en Florida. Es parte de una serie de publicaciones similares sobre reptiles establecidos en el estado. La biología y los impactos de algunas de estas especies son bien conocidos, mientras que otros están poco estudiados. Esta serie fue producida por estudiantes universitarios en el curso Ecología de Anfibios y Reptiles Invasores, en el otoño de 2020 en la Universidad de Florida. La serie fue diseñada para orientar a los propietarios de viviendas y otros residentes y visitantes curiosos sobre la diversidad de la vida silvestre de Florida. Nuestro objetivo es crear conciencia sobre los numerosos reptiles invasores introducidos en el estado, así como motivar a las personas a tomar medidas para reducir su propagación en Florida.
... This species' native range extends from southern Brazil and Paraguay as far north as Mexico (Krysko et al. 2007). However, because of their popularity as pets, international trade in green iguanas has resulted in the establishment of non-native populations well outside this lizard's natural range (Falcon et al. 2013;Bock et al. 2016). As so, green iguanas have extended their range through over-water dispersal following hurricanes and human activities during post-hurricane relief efforts (Censky et al. 1998;van den Burg et al. 2020). ...
The genetic identity of the reptilian tick, Amblyomma helvolum, infesting wild green iguanas (Iguana iguana) in Taiwan, was examined. Genetic identity was determined by analyzing the 16S mitochondrial DNA gene sequences obtained from 11 Taiwan A. helvolum compared with other Amblyomma species, with two Dermacentor species and two Rhipicephalus species serving as outgroups. Phylogenetic analysis revealed that all the Taiwan specimens were genetically affiliated with a monophyletic group of A. helvolum and can be discriminated from other Amblyomma species. Our results provide the first genetic identification of adult A. helvolum ticks infesting wild iguanas in Taiwan. Further studies focused on the seasonal prevalence and vectorial capacity of A. helvolum for various tick-borne pathogens will help to clarify the epidemiological significance of this species and its impact on animal and human health in Taiwan.
... Iguana iguana is a large herbivorous, primarily arboreal lizard (adults can reach 50 cm in snout-vent length) with a diurnal activity cycle (Swanson, 1950;Rand et al., 1990;Fálcon et al., 2013;Bock, 2018). It is widely distributed from northern Mexico through Central America to northern South America, including many adjacent islands (Oliveira and Castro, 2017). ...
... para infectar reptiles y otros vertebrados. Falcón et al. (2013) indican que es muy poco probable que los individuos salvajes puedan transmitir enfermedades y parásitos al ser humano, pero sí pueden ser portadores de enfermedades y parásitos para otros reptiles con los que se encuentran en simpatría, lo que constituye una amenaza para las dos especies de iguanas nativas de la isla de Santo Domingo. Ambas especies se encuentran bajo alguna categoría de 'amenaza', Cyclura cornuta en categoría 'vulnerable' y C. ricordi 'en peligro', según la Lista Roja Nacional (MIMARENA, 2018). ...
El consumo de plástico se reporta cada vez con mayor frecuencia en reptiles acuáticos y terrestres. No siempre es fatal, pero indudablemente afecta la calidad de vida de los animales en formas que aún no son del todo claras. Durante jornadas de control de iguanas verdes (Iguana iguana) en la República Dominicana, se registraron dos individuos con fundas plásticas en el tracto gastrointestinal. La necropsia también reveló la presencia de nematodos aún no identificados. Este es el primer reporte, tanto de consumo de plásticos como de presencia de nematodos, en individuos de iguana verde de la isla de Santo Domingo.
... Numerous countries cite invasive green iguanas as a threat to agricultural production (Kern 2009;Van Veen 2011;López-Ortiz et al. 2012;Thomas et al. 2013), yet qualitative or quantitative analyses of the potential impact of green iguanas on agriculture are lacking. As the green iguana spreads (Falcón et al. 2012(Falcón et al. , 2013van den Burg et al. 2020) and increases its range, the need to understand its potential impact on agricultural food production becomes even more pressing. ...
Agricultural communities and crop production are negatively impacted by invasive species, with the effects of pathogenic fungi, parasitic insects and weedy plants being well studied. Mammals and birds are also recognized as impacting crops, but reptiles, such as non-native green iguanas (Iguana iguana), are typically not considered agricultural pests. Research on non-native green iguanas has largely focused on the lizard's interactions with native species with little attention given to its impact in the agricultural landscape. We conducted semi-structured interviews with farmers from 20 farms in Puerto Rico to explore the effect of the invasive green iguana on the production of crops and how farmers manage impacts, if any. A total of 34 of 55 crop species reported by farmers were negatively affected by the green iguana. We found that green iguanas were absent from 20% of farms, did not consume crops in 10% of the farms and caused negative impacts in 70% of the remaining farms. Negative impacts included crop loss and infrastructural damage, which had behavioral, emotional, and economic effects on farmers. Specific outcomes of these effects were revenue loss, refurbishing costs, changes in crop selection, management costs and emotional stress. Farmers considered management strategies as mitigation measures that needed to be constant to produce any positive effects on crop yield. They reported use of mesh fencing, hunting, and domestic animals as attempts to reduce negative effects of green iguanas on crop production. Recognition of this species as an agricultural pest is warranted in Puerto Rico and perhaps elsewhere in its introduced range. Agricultural extension agents should consider providing guidance on strategies to reduce negative impacts of green iguanas including cultivating less susceptible crops when possible.
... In captive collections, I. iguana has also been associated with bacterial skin infections, which raises biosecurity risks for native reptiles (Hellebuyck et al., 2018;Bautista-Trujillo et al., 2020). Socially and economically, the herbivorous diet of I. iguana can be problematic for gardeners and horticulturalists (Krysko et al., 2007;Falcón et al., 2013). Their burrowing behavior can cause soil erosion and bank destabilization, which can lead to damage to infrastructure (López-Torres et al., 2012). ...
... Our growing knowledge of threats posed by invasive I. iguana populations (e.g. Krysko et al., 2007;Falcón et al., 2013) highlights the urgent need to better understand the current status of these populations and implement control programs to address them. ...
This study investigated the frequency and distribution of reports of free-living green iguanas (Iguana iguana), a Neotropical lizard, in Hong Kong. We found 44 reports of I. iguana, of which 93% were removed from the wild. Thirty-nine reports were records kept by one non-government organization, one report from a government agency, and four reports from community members. Reports were sporadic between 2002 and 2011, but have occurred in every calendar year since 2012, predominately during March, July and October. Report locations were distributed broadly across 16 administrative districts, including heavily developed city areas, indicative of released or escaped pets being the source. Although there was evidence of two individuals living in one locality, we found no major concentrations of reports to indicate established populations. Nevertheless, these data should not be assumed benign since some established populations of I. iguana elsewhere have only become evident following prolonged periods of sporadic reports. It is therefore plausible that emerging reports in Hong Kong may represent a contemporary invasion presently under way. Public reporting of I. iguana plays an important role in preventative invasive species management. However, we also found cases where I. iguana reported as free-living were more likely the same captive I. iguana, highlighting potential errors with community science.
... The giant otter prefers fish ranging from 7-30 cm in length, although the the species has been seen catching prey up to 100 cm . For this reason, the attack to the iguana is not surprising; according to Falcón et al. (2013) the headbody length of an adult of iguana can reach up 50 cm and approximately 200 cm head to tail length; the tail represents almost two thirds of their body length. ...
The Giant otter (Pteronura brasiliensis) is a semi-aquatic mammal listed as Endangered (EN) at national and international levels. On 20 th April 2021, a P. brasiliensis was sighted and a video recorded the killing a Common green iguana (Iguana iguana). In this short note we report the first record of attack and consumption of iguana by giant otter and includ the Giant otter in the list of the occasional predators of these widespread lizards in a tributary of Tillavá River, tributary of the Vichada River, department of Meta, Colombia.
... While efforts continue to be constrained by limited funding (DoE, 2020), the only on-the-ground action was in early 2015, when the Fiji army dispatched more than 100 soldiers to affected islands and killed 40 iguanas (Radio New Zealand, 2015). This, of course, is insufficient to control an agile, quickly spreading invasive animal which, in the meantime, has reached Fiji's second largest island, Vanua Levu (Fiji Broadcasting Commission, 2017; see also Falcón et al., 2013). ...
... The green iguana is an invasive alien animal species with wellknown economic and ecological impacts. It is native to parts of Central and South America but has established feral populations on several islands (e.g., Puerto Rico and Hawaii) and parts of continental mainland United States (e.g., Florida), where its populations reach high densities (Falcón et al., 2013). The species poses considerable threats to native biodiversity and is displacing the critically endangered, congeneric Iguana delicatissima in some of the Lesser Antilles (van den Burg et al., 2018). ...
... The species poses considerable threats to native biodiversity and is displacing the critically endangered, congeneric Iguana delicatissima in some of the Lesser Antilles (van den Burg et al., 2018). As a predominantly herbivorous, but potentially opportunistically omnivorous, species, the iguana poses threats to the native flora and fauna (Falcón et al., 2013). In addition, the green iguana has been shown to eat important food and commercial plants (Falcón et al., 2013;CI-Pacific, 2013). ...
The South Pacific region is a hotspot of biodiversity but also has the world´s highest concentration of invasive alien plant species. Although the issue of biological invasions has been increasingly acknowledged by local governments and international agreements, invasive alien species are often not monitored properly. Knowledge of the potential impact of invasive alien species regularly does not result in on-the-ground action, adding to the growing extinction threat. This inaction persists despite international and national efforts for sustainable use and nature conservation of terrestrial biodiversity in the region's Small Island Developing States. We illustrate this problem with two relatively recent biological invaders in Fiji: the ivory cane palm (Pinanga coronata) and the green iguana (Iguana iguana). We use these examples to examine the potential consequences of continuing inaction, despite awareness in relevant government departments, for native forest biodiversity and human livelihoods. Through an examination of the institutional background, we discuss steps towards good governance and sustainable development of terrestrial biodiversity in the Small Island Developing States of the tropical South Pacific, where on-the-ground action to control, eradicate and prevent invasive alien species is desperately needed.
... We investigated verified observations of Green Iguanas from other mainland states in greater detail. By reviewing photographs uploaded by application users, we categorized an iguana as an adult if the jowl scale was visibly larger than the tympanum or a juvenile or hatchling if the jowl scale and tympanum were similar in size (Falcón et al. 2013); and subsequently examined the proportion of sightings of each age class. We did not attempt to distinguish adults and subadults due to the difficulty of differentiating them from photographs. ...
Presently, the only established populations of invasive Green Iguanas (Iguana iguana) on the mainland USA occur in Florida. We examined observation data from the online citizen-science application iNaturalist to determine the frequency of reports of free-living Green Iguanas in Florida and identify where iguanas have been reported in other parts of the mainland USA. Observations from Florida comprised 99.6% of the 5,929 verified Green Iguana observations from the mainland USA. The largest proportion were observations from 2016 to 2021, corresponding with an increasing number of application users contributing to the dataset during this period. The majority of Green Iguana observations from latitudes of 27–41°N in 11 other mainland states were from California. However, we noted no obvious concentrations of sightings to indicate the presence of established populations in any of those 11 states. The majority of observations from outside Florida were adults and were most frequently reported from suburbia and urban parks, suggesting that released or escaped pets were the likely source. More than one third of iguanas reported outside Florida were near water, which is worrisome because iguanas are known to use waterways to disperse. This study clearly demonstrates the value of public participation in assembling sighting records of non-native animals, and we encourage engagement campaigns that leverage reports from members of the public to achieve early detections of potentially invasive species.
