Submitted by editor on 30 June 2020. Get the paper!
By Jamie M. Kass, Verónica Juárez-Jaimes, José Juan Flores-Martínez, Víctor Sánchez-Cordero
Range estimates provide crucial and foundational information for conservation assessment and help to delimit areas for prioritization. Even for relatively well-known species of conservation concern, portions of their ranges may be poorly understood due to a historical lack of data. This is particularly problematic for wide-ranging, migratory species as they often traverse areas with low sampling effort. Migratory populations are influenced by large-scale events that frequently exceed the scales of ecosystems and national borders, so associated conservation efforts depend on connectivity through migratory corridors that can be data-poor (Martin et al. 2007). A lack of suitable habitat in such corridors can deplete essential food resources and reduce opportunities for shelter. For many species, such habitats are defined by select plant communities, and availability of food resources is frequently dictated by phenology. Species distribution models (SDMs) are widely used to make range estimates, but they are typically fit with abiotic predictor variables such as climate or topography. Biotic predictor variables can add important information to predict such migration corridors, but how best to integrate them into SDMs is an open question, and how to include phenological information for such variables has rarely been considered. We addressed both of these issues to estimate the poorly-known migratory range of the imperiled monarch butterfly (Danaus plexippus L. 1758) as it travels from the southern USA to central Mexico over a three-month period.
This photo is from El Rosario, Michoacán, Mexico and shows monarch butterflies perched (Danaus plexippus) on an oyamel fir tree (Abies religiosa). Monarchs rely on oyamel firs and other particular tree species for suitable microclimates while they migrate through Mexico from the southern USA and overwinter in Michoacán.
The distribution of the eastern North American monarch butterfly has been well studied in its northern and southern extremes, but its migratory routes, which are fundamental for the conservation of this wide-ranging population, are still being investigated. This population and its cross-continental migration face multiple threats of both natural and anthropogenic origin. Recently, Wilcox et al. (2019) provided an updated summary of these threats and associated each with particular regions of the monarch’s geographical distribution: climate change and deforestation are mainly associated with overwintering sites, while pesticide use is a key issue in the breeding range. It is notable that, to date, there is an absence of discussion concerning the migratory route connecting the northern breeding range in the U.S. to the southern overwintering range in central Mexico. For example, although habitat loss and its effects on the monarch have been extensively studied in both the breeding and overwintering ranges, conditions along the migratory route are rarely addressed. This discrepancy is due in a large part to a historical lack of available data for this region and is now being remedied by a major monarch butterfly sampling collection effort by the Mexican National Commission of Protected Natural Areas (CONANP).
Monarch butterfly larvae are obligate to species of milkweed (Asclepias spp.), but the adults are generalists that use them as an important nectar source. We built species distribution models (SDMs) using climatic variables for all the milkweed species found in the monarch’s migration range from southern Texas to central Mexico, as well as for a selection of montane tree species that monarchs use for sheltering. As we hypothesized that the richness of either of these groups of plants would be positively associated with monarch suitability, we made richness estimates from the plant SDMs and included them as biotic predictors alongside climatic ones in our monarch models. As adult monarchs only feed on flowering milkweeds, we compiled a phenology database for these milkweeds based on herbarium specimens and used this information to choose which species to include in richness estimates per month (Fig. 1). We then compared models built with different variable sets per month to determine whether the biotic variables would prove useful or not to estimate the monarch’s range.
Using information criteria, we found that the optimal monthly models included both abiotic and biotic variables. These models produced range estimates that best matched our biogeographical expectations for the monarch in the Mexican migration corridor, but that had marginal environmental responses that for some months did not align with our ecological expectations. Although tree richness was always positively related to monarch suitability, milkweed richness had a negative relationship for two months, regardless of accounting for phenology. We discussed possible explanations for this in the paper, but here we mention some techniques that should be generally useful for addressing this issue with biotic predictor variables. First, correcting the estimated ranges of interacting species using expert range maps as references will likely result in more realistic associations with the focal species. Second, selecting just those interacting species with known high abundance within the focal species’ range will also make richness estimates more conservative. When abundance data is lacking, using proxies such as biogeographical regions, soil information, or elevation could aid in the selection process. Third, biotic predictor variables may be correlated in unexpected ways with each other or with abiotic variables, and perhaps building a series of models with and without the biotic predictor in question would lead to new insights. In some cases, removing a correlated variable might change the direction of a biotic variable’s response.
Although more work is needed, the range estimates we produced for the monarch’s Mexican migration are among the best we currently have. Using these range estimates, not only can more focused actions be considered in existing natural protected areas in Mexico, but other candidate sites can be proposed through strategies such as systematic planning for conservation (Margules and Sarkar 2007). For example, Suárez-Mota et al. (2018) and Monroy-Gamboa et al. (2019) recently used the prioritization software ConsNet (Ciarleglio et al. 2009) to determine optimal sites for conservation of plants and terrestrial vertebrates, respectively, in the State of Oaxaca, Mexico using range estimates from SDMs. If based on our SDM predictions for monarchs made with biotic variables, such analyses could identify sites for conservation that are both biologically suitable for migrating monarchs and socioeconomically more feasible to implement (Margules and Sarkar 2011). Recently, Castañeda et al. (2019) also modeled this migration route with CONANP data using climatic and topographic variables with the addition of edaphic variables, which can be informative for plant growth. This study also demonstrates the utility in using biotic variables or their proxies to model migratory corridors. As methods improve and a consensus among predictions emerges, we plan to use these new range estimates for conservation planning in the Mexican migration corridor, likely focusing on the Trans-Mexican Volcanic Belt region that includes the overwintering range. The modeling of migratory species’ ranges is certainly more complicated than that of species with static distributions, but biogeographic studies that incorporate biotic information have great promise to better inform conservation implementation of migratory species such as the monarch butterfly.
Castañeda, S., Botello, F., Sánchez-Cordero, V., Sarkar, S. (2019). Spatio-Temporal Distribution of Monarch Butterflies Along Their Migratory Route. Frontiers in Ecology & Evolution, 7: 400.
Ciarleglio, M., Wesley Barnes, J. and Sarkar, S. (2009). ConsNet: new software for the selection of conservation area networks with spatial and multi‐criteria analyses. Ecography, 32: 205 – 209. doi:10.1111/j.1600-0587.2008.05721.x
Margules, C., Sarkar, S. (2007). Systematic Conservation Planning. Ecology, Biodiversity and Conservation. Cambridge University Press, Cambridge, UK.
Monroy-Gamboa, A. G., Briones-Salas, M. Á., Sarkar, S., & Sánchez-Cordero, V. (2019). Terrestrial vertebrates as surrogates for selecting conservation areas in a biodiversity hotspot in Mexico. Conservation Science and Practice, 1: e12. doi: 10.1111/csp2.12
Suárez-Mota, M. E., Villaseñor, J. L. & Ramírez-Aguirre, M. B. (2018) Sitios prioritarios para la conservación de la riqueza florística y el endemismo de la Sierra Norte de Oaxaca, México (English: Priority sites for the conservation of floristic richness and endemism of the Sierra Norte de Oaxaca, Mexico). Acta Botanica Mexicana, 124. doi: 10.21829/abm124.2018.1296