Incorporating abundance information and guiding variable selection for climate-based ensemble forecasting of species' distributional shifts

Climate change extinctions

Climate change is expected to cause irreversible changes to biodiversity, but predicting those risks remains uncertain. I synthesized 485 studies and more than 5 million projections to produce a quantitative global assessment of climate change extinctions. With increased certainty, this meta-analysis suggests that extinctions will accelerate rapidly if global temperatures exceed 1.5°C. The highest-emission scenario would threaten approximately one-third of species, globally. Amphibians; species from mountain, island, and freshwater ecosystems; and species inhabiting South America, Australia, and New Zealand face the greatest threats. In line with predictions, climate change has contributed to an increasing proportion of observed global extinctions since 1970. Besides limiting greenhouse gases, pinpointing which species to protect first will be critical for preserving biodiversity until anthropogenic climate change is halted and reversed.

Genetic variability and population structure of the Montezuma quail (Cyrtonyx montezumae) in the northern limit of its distribution

Restricted movement among populations decreases genetic variation, which may be the case for the Montezuma quail (Cyrtonyx montezumae), a small game bird that rarely flies long distances. In the northern limit of its distribution, it inhabits oak-juniper-pine savannas of Arizona, New Mexico, and Texas. Understanding genetic structure can provide information about the demographic history of populations that is also important for conservation and management. The objective of this study was to determine patterns of genetic variation in Montezuma quail populations using nine DNA microsatellite loci. We genotyped 119 individuals from four study populations: Arizona, Western New Mexico, Central New Mexico, and West Texas. Compared to other quail, heterozygosity was low (H ¯ 0 = 0.22 ± 0.04) and there were fewer alleles per locus (Ā = 2.41 ± 0.27). The global population genetic differentiation index RST = 0.045 suggests little genetic structure, even though a Bayesian allocation analysis suggested three genetic clusters (K = 3). This analysis also suggested admixture between clusters. Nevertheless, an isolation-by-distance analysis indicates a strong correlation (r = 0.937) and moderate evidence (P = 0.032) of non-independence between geographical and genetic distances. Climate change projections indicate an increase in aridity for this region, especially in temperate ecosystems where the species occurs. In this scenario, corridors between the populations may disappear, thus causing their complete isolation.

The broad scale impact of climate change on planning aerial wildlife surveys with drone-based thermal cameras

Helicopters used for aerial wildlife surveys are expensive, dangerous and time consuming. Drones and thermal infrared cameras can detect wildlife, though the ability to detect individuals is dependent on weather conditions. While we have a good understanding of local weather conditions, we do not have a broad-scale assessment of ambient temperature to plan drone wildlife surveys. Climate change will affect our ability to conduct thermal surveys in the future. Our objective was to determine optimal annual and daily time periods to conduct surveys. We present a case study in Texas, (United States of America [USA]) where we acquired and compared average monthly temperature data from 1990 to 2019, hourly temperature data from 2010 to 2019 and projected monthly temperature data from 2021 to 2040 to identify areas where surveys would detect a commonly studied ungulate (white-tailed deer [Odocoileus virginianus]) during sunny or cloudy conditions. Mean temperatures increased when comparing the 1990-2019 to 2010-2019 periods. Mean temperatures above the maximum ambient temperature in which white-tailed deer can be detected increased in 72, 10, 10, and 24 of the 254 Texas counties in June, July, August, and September, respectively. Future climate projections indicate that temperatures above the maximum ambient temperature in which white-tailed deer can be detected will increase in 32, 12, 15, and 47 counties in June, July, August, and September, respectively when comparing 2010-2019 with 2021-2040. This analysis can assist planning, and scheduling thermal drone wildlife surveys across the year and combined with daily data can be efficient to plan drone flights.

Potential Current and Future Distribution of the Long-Whiskered Owlet (Xenoglaux loweryi) in Amazonas and San Martin, NW Peru

Simple Summary

The long-whiskered owlet (Xenoglaux loweryi) is threatened by human activities and is currently listed as vulnerable by the IUCN. Here, we geo-referenced long-whiskered owlet records, identified key environmental variables affecting their distribution, and predicted their current and future distribution (2050 and 2070) in the Amazonas and San Martin areas of northwestern Peru. Under current conditions, areas with “high”, “moderate”, and “low” probability for the distribution of X. loweryi cover about 0.16% (140.85 km²), 0.46% (416.88 km²), and 1.16% (1048.79 km²) of the study area, respectively. Moreover, under future conditions, the “high”, “moderate”, and “low” probability areas showed profits and losses in terms of habitat suitability. Importantly, the natural protected areas in Amazonas and San Martin, both in current and in the future conditions, do not cover most of the pivotal habitats for X. loweryi. Furthermore, it was evident that the combination of climate change and anthropogenic activities will lead to further habitat loss for this species. Therefore, to effectively conserve this species over time, it is strongly recommended that areas with “high” (and even “moderate”) probability and the main ecosystems that this species inhabits be designated as priority areas for research and conservation (including in natural protected areas).

Abstract

The IUCN has listed the long-whiskered owlet (Xenoglaux loweryi) as vulnerable due to the presence of few geographic records, its restricted range, and anthropogenic threats. Its natural history and ecology are largely unknown, and its distribution is widely debated; therefore, there is an urgent need for the real-time conservation of X. loweryi. In this study, 66 geo-referenced records of X. loweryi, 18 environmental variables, and the maximum entropy model (MaxEnt) have been used to predict the current and future (2050 and 2070) potential distribution of X. loweryi in the Amazonas and San Martin regions of northwestern Peru. In fact, under current conditions, areas of “high”, “moderate”, and “low” potential habitat suitability cover 0.16% (140.85 km²), 0.46% (416.88 km²), and 1.16% (1048.79 km²) of the study area, respectively. Moreover, under future conditions, the “high”, “moderate”, and “low” probability areas present profits and losses in terms of habitat suitability. Based on the environmental variables, this species mostly inhabits areas with a forest fraction with presence of trees with an emergent tree canopy of ~10–30 metres and depends on Yunga montane forest habitats with high humidity but it is not dependent on bare cover area, crops, or grasslands. Nevertheless, most of the current and future distribution areas are not part of the protected natural areas of Amazonas and San Martin. Additionally, the combination of climate change and anthropogenic activities contribute to further losses of this species habitat. Therefore, from the management point of view, corrective and preventive actions will help to preserve this species over time.

Potential regional declines in species richness of tomato pollinators in North America under climate change

About 70% of the world's main crops depend on insect pollination. Climate change is already affecting the abundance and distribution of insects, which could cause geographical mismatches between crops and their pollinators. Crops that rely primarily on wild pollinators (e.g., crops that cannot be effectively pollinated by commercial colonies of honey bees) could be particularly in jeopardy. However, limited information on plant-pollinator associations and pollinator distributions complicate the assessment of climate change impacts on specific crops. To study the potential impacts of climate change on pollination of a specific crop in North America, we use the case of open-field tomato crops, which rely on buzz pollinators (species that use vibration to release pollen, such as bumble bees) to increase their production. We aimed to (1) assess potential changes in buzz pollinator distribution and richness, and (2) evaluate the overlap between areas with high densities of tomato crops and high potential decrease in richness. We used baseline (1961-1990) climate and future (2050s and 2080s) climatic projections in ecological niche models fitted with occurrences of wild bees, documented in the literature as pollinators of tomatoes, to estimate the baseline and future potential distribution of suitable climatic conditions of targeted species and to create maps of richness change across North America. We obtained reliable models for 15 species and found important potential decreases in the distribution of some pollinators (e.g., Lasioglossum pectorale and Augochlorella aurata). We observed geographical discrepancies in the projected change in species richness across North America, detecting important declines in the eastern United States (up to 11 species decrease for 2050s). After overlapping the maps of species richness change with a tomato crop map for the United States, we found spatial correspondence between richness declines and areas with high concentration of tomato crops. Disparities in the effects of climate change on the potential future distribution of different wild pollinators and geographical variation in richness highlight the importance of crop-specific studies. Our study also emphasizes the challenges of compiling and modeling crop-specific pollinator data and the need to improve our understanding of current distribution of pollinators and their community dynamics under climate change.

Collinearity in ecological niche modeling: Confusions and challenges

Ecological niche models are widely used in ecology and biogeography. Maxent is one of the most frequently used niche modeling tools, and many studies have aimed to optimize its performance. However, scholars have conflicting views on the treatment of predictor collinearity in Maxent modeling. Despite this lack of consensus, quantitative examinations of the effects of collinearity on Maxent modeling, especially in model transfer scenarios, are lacking. To address this knowledge gap, here we quantify the effects of collinearity under different scenarios of Maxent model training and projection. We separately examine the effects of predictor collinearity, collinearity shifts between training and testing data, and environmental novelty on model performance. We demonstrate that excluding highly correlated predictor variables does not significantly influence model performance. However, we find that collinearity shift and environmental novelty have significant negative effects on the performance of model transfer. We thus conclude that (a) Maxent is robust to predictor collinearity in model training; (b) the strategy of excluding highly correlated variables has little impact because Maxent accounts for redundant variables; and (c) collinearity shift and environmental novelty can negatively affect Maxent model transferability. We therefore recommend to quantify and report collinearity shift and environmental novelty to better infer model accuracy when models are spatially and/or temporally transferred.

Behavioral modifications lead to disparate demographic consequences in two sympatric species

Life-history theory suggests species that typically have a large number of offspring and high adult mortality may make decisions that benefit offspring survival in exchange for increased adult risks. Such behavioral adaptations are essential to understanding how demographic performance is linked to habitat selection during this important life-history stage. Though studies have illustrated negative fitness consequences to attendant adults or potential fitness benefits to associated offspring because of adaptive habitat selection during brood rearing, equivocal relationships could arise if both aspects of this reproductive trade-off are not assessed simultaneously. To better understand how adaptive habitat selection during brood rearing influences demographics, we studied the brood survival, attendant parental survival, and space use of two sympatric ground-nesting bird species, the northern bobwhite (hereafter: "bobwhite"; Colinus virgininanus) and scaled quail (Callipepla squamata). During the 2013-2014 breeding seasons, we estimated habitat suitability across two grains (2 m and 30 m) for both species and determined how adult space use of these areas influenced individual chick survival and parental risk. We found the proportion of a brood's home range containing highly suitable areas significantly increased bobwhite chick survival (β = 0.02, SE = 0.006). Additionally, adult weekly survival for bobwhite was greater for individuals not actively brooding offspring (0.9716, SE = 0.0054) as compared to brooding adults (0.8928, SE = 0.0006). Conversely, brood habitat suitability did not influence scaled quail chick survival during our study, nor did we detect a survival cost for adults that were actively brooding offspring. Our research illustrates the importance of understanding life-history strategies and how they might influence relationships between adaptive habitat selection and demographic parameters.