Geology Reports⌕ Search

USGS · 70253907

Environmental variation structures reproduction and recruitment in long-lived mega-herbivores: Galapagos giant tortoises

Abstract

Migratory, long-lived animals are an important focus for life-history theory because they manifest extreme trade-offs in life-history traits: delayed maturity, low fecundity, variable recruitment rates, long generation times, and vital rates that respond to variation across environments. Galapagos tortoises are an iconic example: they are long-lived, migrate seasonally, face multiple anthropogenic threats, and have cryptic early life-history stages for which vital rates are unknown. From 2012 to 2021, we studied the reproductive ecology of two species of Galapagos tortoises ( Chelonoidis porteri and C. donfaustoi ) along elevation gradients that coincided with substantial changes in climate and vegetation productivity. Specifically, we (1) measured the body and reproductive condition of 166 adult females, (2) tracked the movements of 33 adult females using global positioning system telemetry, and monitored their body condition seasonally, (3) recorded nest temperatures, clutch characteristics, and egg survival from 107 nests, and (4) used radiotelemetry to monitor growth, survival, and movements of 104 hatchlings. We also monitored temperature and rainfall from field sites, and remotely sensed primary productivity along the elevation gradient. Our study showed that environmental variability, mediated by elevation, influenced vital rates of giant tortoises, specifically egg production by adult females and juvenile recruitment. Adult females were either elevational migrants or year-round lowland residents. Migrants had higher body condition than residents, and body condition was positively correlated with the probability of being gravid. Nests occurred in the hottest, driest parts of the tortoise's range, between 6 and 165 m elevation. Clutch size increased with elevation, whereas egg survival decreased. Hatchling survival and growth were highest at intermediate elevations. Hatchlings dispersed rapidly to 100–750 m from their nests before becoming sedentary (ranging over <0.2 ha). Predicted future climates may impact the relationships between elevation and vital rates of Galapagos tortoises and other species living across elevation gradients. Resilience will be maximized by ensuring the connectivity of foraging and reproductive areas within the current and possible future elevational ranges of these species.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: -0.7783452498541266° to -0.5968399941543368° latitude; -90.56105950601605° to -90.1639880007019° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Stephen Blake, Fredy Cabrera, Sebastian Cruz, Diego Ellis-Soto, Charles B. Yackulic, Guillaume Bastille-Rousseau, Martin Wikelski, Franz Kuemmeth, James P. Gibbs, Sharon L. Deem. 2024-02-13. Environmental variation structures reproduction and recruitment in long-lived mega-herbivores: Galapagos giant tortoises. https://doi.org/10.1002/ecm.1599

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Probabilistic forecasting of coastal wetland elevation and soil carbon response to sea-level rise

Tidal wetlands build soil as a dynamic response to inundation, resulting in carbon sequestration and resilience to sea-level rise. Process models can be used to make site-specific forecasts, anticipate future changes, and plan management responses. But to be actionable, forecasts from these models need to be accompanied by descriptions of their confidence. In this study, we demonstrate the application of ecological forecasting principles to the unique case of tidal wetland vulnerability and carbon storage, given accelerating and uncertain sea-level rise. We present a case study using the Cohort Marsh Equilibrium Model at the Global Change Research Wetland in Maryland, USA. We used meta-analyses to quantify lab- and sample-level measurement uncertainties for common soil measurements and to develop Bayesian model priors. Reanalysis of previous literature supported predictive relationships between belowground turnover and mean annual temperature, as well as between soil erodibility and suspended sediment concentration that could be transferable to other locations. The model forecasted a likely conversion of low-elevation marsh to open water by the 2060s, accompanied by a decrease in marsh carbon storage capacity. Forecasted uncertainty in elevation was dominated by structural uncertainty in the model, while carbon accumulation rates were more influenced by parameter uncertainty. After 2050, and increasingly as the forecast approached 2100, uncertainty in sea-level rise projections contributed to uncertainty in both forecasts. Forecasts were most sensitive to processes related to organic matter preservation, plant productivity (maximum aboveground biomass and belowground turnover), and organic soil packing density. The soil formed was an organic-rich peat (>70% organic matter according to the data), and model predictions were insensitive to parameters associated with mineral sedimentation. We identify additional field data collection, such as on decomposition trajectories and plant productivity, and data-model coupling of near-term elevation records as the most impactful strategies for reducing uncertainties in future forecasting efforts. Future work can build on this forecasting framework in other locations, using it for adaptive management, identifying appropriate interventions to mitigate wetland loss, and projecting future carbon removal capacity in response to accelerated sea-level rise.

Maryland↗

Missing data in ecology: Syntheses, clarifications, and considerations

In ecology and related sciences, missing data are common and occur in a variety of different contexts. When missing data are not handled properly, subsequent statistical estimates tend to be biased, inefficient, and lack proper confidence interval coverage. Missing data are often grouped into three categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). We review each category and compare their benefits and drawbacks. We review several approaches to handling missing data including complete case analysis, imputation, inverse probability weighting, and data augmentation. We clarify what types of variables should accompany imputation methods and how those variables are influenced by the analysis methods. Additionally, we discuss missing data that lack a formal basis for measurement and hence are fundamentally different from MCAR, MAR, and MNAR missing data. Throughout, we introduce concepts and numeric examples using both simulated data and data from the United States Environmental Protection Agency's 2016 National Wetland Condition Assessment. We conclude by providing five considerations for ecologists and other scientists handling missing data.

Ecological Monographs↗

Mammalian predator co‐occurrence affected by prey and habitat more than competitor presence at multiple time scales

The behavior and abundance of sympatric predators can be affected by a complex dominance hierarchy. The strength of antagonistic interactions in predator communities is difficult to study and remains poorly understood for many predator assemblages. Predators directly and indirectly influence the broader ecosystem, so identifying the relative importance of competition, prey, and habitat in shaping predator interactions has broad conservation and management implications. We investigated space use among five predator species (black bear [ Ursus americanus ], bobcat [ Lynx rufus ], coyote [ Canis latrans ], mountain lion [ Puma concolor ], and gray wolf [ Canis lupus ]) across three temporal scales in northern Idaho, USA. We used camera trap data to test whether potentially subordinate predators spatially avoided dominant predators and how prey availability influenced those relationships. We found few instances of subordinate predators spatially avoiding dominant predators and only at the finest temporal scale of our analyses. Instead, habitat features generally influenced predator space use patterns at coarser scales whereas prey and competitor presence influenced space use patterns at finer scales. Co-occurrence was positively associated between coyotes and bobcats at coarser timescales and between mesopredators and apex predators at finer timescales. Bobcats and mountain lions temporarily delayed the use of sites recently visited by coyotes and black bears, respectively. And all predator species used sites sooner following the detection of a competitor in areas with higher relative abundances of prey (primarily white-tailed deer [ Odocoileus virginianus ]). Our results suggest attraction to shared habitats and prey resources influenced space use in the predator community more than avoidance of competitors. We propose that the effects of interspecific interactions on predator distributions were most evident for mesopredators because their trophic position requires balancing risks and rewards associated with prey, apex predators, and other mesopredators. In addition, relatively high densities of a common prey source likely facilitated the spatial coexistence in this predator community. Our study demonstrates the value of simultaneously assessing multiple interspecific interactions across different spatiotemporal scales to discern relationships within the predator guild.

Idaho↗