Wells, C.N.; Tonkyn, D. Changes in the Geographic Distribution of the Diana Fritillary (Speyeria diana: Nymphalidae) under Forecasted Predictions of Climate Change. Insects2018, 9, 94.
Wells, C.N.; Tonkyn, D. Changes in the Geographic Distribution of the Diana Fritillary (Speyeria diana: Nymphalidae) under Forecasted Predictions of Climate Change. Insects 2018, 9, 94.
Wells, C.N.; Tonkyn, D. Changes in the Geographic Distribution of the Diana Fritillary (Speyeria diana: Nymphalidae) under Forecasted Predictions of Climate Change. Insects2018, 9, 94.
Wells, C.N.; Tonkyn, D. Changes in the Geographic Distribution of the Diana Fritillary (Speyeria diana: Nymphalidae) under Forecasted Predictions of Climate Change. Insects 2018, 9, 94.
Abstract
Climate change is predicted to alter the geographic distribution of a wide variety of taxa, including butterfly species. Research has focused primarily on high latitude species in North America, with no known studies examining responses of taxa in the southeastern US. The Diana fritillary (Speyeria diana) has experienced a recent range retraction in that region, disappearing from lowland sites and now persisting in two, phylogenetically disjunct mountainous regions. These findings are consistent with the predicted effects of a warming climate on numerous taxa, including other butterfly species in North America and Europe. We used ecological niche modeling to predict future changes to the distribution of S. diana under several climate models. To evaluate how climate change might influence the geographic distribution of this butterfly, we developed ecological niche models using Maxent. We used two global circulation models, CCSM and MIROC, under low and high emissions scenarios to predict the future distribution of S. diana. Models were evaluated using the Receiver Operating Characteristics Area Under Curve test and the True Skill Statistics (mean AUC = 0.91± 0.0028 SE, TSS = 0.87 ± 0.0032 SE for RCP = 4.5, and mean AUC = 0.87± 0.0031SE, TSS = 0.84 ± 0.0032 SE for RCP = 8.5), which both indicate that the models we produced were significantly better than random (0.5). The four modeled climate scenarios resulted in an average loss of 91% of suitable habitat for S. diana by 2050. Populations in the Southern Appalachian Mountains were predicted to suffer the most severe fragmentation and reduction in suitable habitat, threatening an important source of genetic diversity for the species. The geographic and genetic isolation of populations in the west suggest that those populations are equally as vulnerable to decline in the future, warranting ongoing conservation of those populations as well. Our results suggest that the Diana fritillary is under threat of decline by 2050 across its entire distribution from climate change, and is likely to be negatively affected by other human-induced factors as well.
Keywords
Speyeria diana, butterfly, conservation, fragmentation, global warming, Maxent, WorldClim
Subject
Biology and Life Sciences, Ecology, Evolution, Behavior and Systematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
(Click to see Publons profile: )
The commenter has declared there is no conflict of interests.
Comment:
This publication is a valuable contribution to the understanding of the effects of climate change on this taxonomic group. After reading the document, I suggest that several sections of the document could be modified. In the section on occurrence data, I consider that the authors do not specify in detail how the data were obtained, as well as their special purification. In relation to the environmental data, I consider that they should justify why only climatic data are used and also cite articles where reference is made to the variables that could influence the distribution of this species. Finally, regarding the modeling algorithm. Why maxent? Aren't there other algorithms? If you use maxent why not innovate and use packages like kuenm that help to create several candidate models and be evaluated with different evaluation metrics.
Commenter:
The commenter has declared there is no conflict of interests.