Adam J. Terando’s research while affiliated with North Carolina State University and other places

Decades of human activities and fire suppression have adversely affected longleaf pine (Pinus palustris) ecosystems, which are home to high levels of diversity and endemism. These iconic ecosystems also now face challenges from urbanization and climate change, which will alter conservation outcomes over the remainder of the 21st century. To explore how long‐term, large‐scale human influences could affect the spatial and functional persistence of extant longleaf pine ecosystems in the Florida Flatwoods Pyrome, we extracted a set of 2400 longleaf pine patches ≥40 ha in size from the Florida Longleaf Pine Ecosystem Geodatabase. Projections from the FUTURES urban growth model and the Florida 2070 project indicate that development will lead to losses of existing longleaf pine habitat, reductions in longleaf pine patch size, and patches that are predominantly located in close proximity to developed areas. Finer‐scale patterns of longleaf pine loss in three focal landscapes highlighted differences in land protection, ecological setting, and development pressure and the value of using of multiple urbanization iterations. The occurrence of suitable conditions to conduct prescribed fires, a crucial tool for maintaining, improving, and restoring longleaf pine ecosystems, is projected to decrease seasonally throughout the study area. As a result, the functional persistence of ecosystems is at risk due to climate changes that increase barriers to the safe and reliable application of intentional fire. The long‐term viability of this critical ecosystem will warrant the evaluation of adaptive strategies that explicitly account for the individual and compounding effects of urban development and changing fire management conditions when considering options for ecosystem protection, management, and restoration.

Temperature and precipitation have been identified as factors that potentially influence eastern wild turkey (Meleagris gallopavo silvestris) reproduction, but robust analyses testing the relationship between weather parameters and turkey nest success are lacking. Therefore, we assessed how weather influenced turkey daily nest survival using 8 years of data collected from 715 nests across the southeastern United States. We also conducted exploratory analyses investigating if weather conditions during or prior to nesting best predicted nest success. We then assessed the possible implications of climate change through 2041-2060 for future eastern wild turkey daily nest survival and nest success for variables determined significant in analyses. During incubation, positive anomalies of minimum daily temperature were associated with greater daily nest survival. Precipitation during nesting was not a good predictor of daily nest survival. Exploratory analyses unexpectedly indicated that weather conditions in January prior to incubation were more important to nest success than weather conditions during incubation. In January, negative anomalies of minimum temperature and greater average daily precipitation were associated with greater nest success. Projections of future nest success or daily nest survival based on these relationships with the predictive covariates, and informed by climate models, suggest that nest success may increase as January precipitation increases and that daily nest survival may increase as temperature during incubation increases. These positive associations could be offset by a negative association between nest success and the expected increases in January minimum average temperature. Additional research is needed to investigate causes of these relationships and assess the implications of climate change for eastern wild turkey poult survival.

Climate change may induce mismatches between wildlife reproductive phenology and temporal occurrence of resources necessary for reproductive success. Verifying and elucidating the causal mechanisms behind potential mismatches requires large-scale, longer-duration data. We used eastern wild turkey (Meleagris gallopavo silvestris) nesting data collected across the southeastern U.S. over eight years to investigate potential climatic drivers of variation in nest initiation dates. We investigated climactic relationships with two datasets, one inclusive of successful and unsuccessful nests (full dataset) and another of just successful nests (successfully hatched dataset), to determine whether successfully hatched nests responded differently to weather changes than all nests did. In the full dataset, each 10 cm increase in January precipitation was associated with nesting occurring 0.46-0.66 days earlier, and each 10 cm increase in precipitation during the 30 days preceding nesting was associated with nesting occurring 0.17-0.21 days later. In the successfully hatched dataset, a 10 cm increase in March precipitation was associated with nesting occurring 0.67-0.74 days earlier, and an increase of one unit of variation in February maximum temperature was associated with nesting occurring 0.02 days later. We combined the results of these modeled relationships with multiple climate scenarios to understand potential implications of future climate change on wild turkey nesting phenology; results indicated that mean nest initiation date is projected to change by <0.1 day by 2040-2060. Wild turkey nesting phenology did not track changes in spring green-up timing, which could result in phenological mismatch between the timing of nesting and the availability of resources critical for successful reproduction.

Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3.0) that can probabilistically predict urban growth while simulating human migration and other responses to flooding, essentially depicting the geography of impact and response. Accounting for human migration reduced total amounts of projected developed land exposed to flooding by 2050 by 5%–24%, depending on flood hazard zone (50%–0.2% annual probability). We simulated various “what-if” scenarios and found managed retreat to be the only intervention with predicted exposure below baseline conditions. In the business-as-usual scenario, existing and future development must be either protected or abandoned to cope with future flooding. Our open framework can be applied to different regions and advances local to regional-scale efforts to evaluate potential risks and tradeoffs.

Using climate model ensembles containing members that exhibit very high climate sensitivities to increasing CO2 concentrations can result in biased projections. Various methods have been proposed to ameliorate this ‘hot model’ problem, such as model emulators or model culling. Here, we utilize Bayesian Model Averaging as a framework to address this problem without resorting to outright rejection of models from the ensemble. Taking advantage of multiple lines of evidence used to construct the best estimate of the earth’s climate sensitivity, the Bayesian Model Averaging framework produces an unbiased posterior probability distribution of model weights. The updated multi-model ensemble projects end-of-century global mean surface temperature increases of 2 oC for a low emissions scenario (SSP1-2.6) and 5 oC for a high emissions scenario (SSP5-8.5). These estimates are lower than those produced using a simple multi-model mean for the CMIP6 ensemble. The results are also similar to results from a model culling approach, but retain some weight on low-probability models, allowing for consideration of the possibility that the true value could lie at the extremes of the assessed distribution. Our results showcase Bayesian Model Averaging as a path forward to project future climate change that is commensurate with the available scientific evidence.

Climate change impacts on tourism are well documented, with most studies focusing on challenges facing ski or beach tourism. While non-ski, mountain tourism accounts for almost one fifth of tourism worldwide, there is a dearth of research on tourists’ perceptions of climate change impacts and their effects on tourism demand in these areas. This study, conducted at the ecotourism destination of the Pueblos Mancomunados in the Sierra Norte Mountains of southern Mexico, helps to fill that gap by identifying important tourist decision factors and determining how tourists’ decisions to visit may change under different climatic conditions. Using on-site intercept survey research methodology involving 188 tourists, we found that some climate change scenarios affect tourists’ perceptions of the desirability of visiting nature-based tourism sites. Results indicate that community-based ecotourism businesses, such as the one that operates in the Pueblos Mancomunados, need to specifically plan for climate change impacts, as they may need to alter tourism offerings to sustain demand.