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Directly observing autotrophic biomass at ecologically relevant frequencies is difficult in many ecosystems, hampering our ability to predict productivity through time. Since disturbances can impart distinct reductions in river productivity through time by modifying underlying standing stocks of biomass, mechanistic models fit to productivity time series can infer underlying biomass dynamics. We incorporated biomass dynamics into a river ecosystem productivity model for six rivers to identify disturbance flow thresholds and understand the resilience of primary producers. The magnitude of flood necessary to disturb biomass and thereby reduce ecosystem productivity was consistently lower than the more commonly used disturbance flow threshold of the flood magnitude necessary to mobilize river bed sediment. The estimated daily maximum percent increase in biomass (a proxy for resilience) ranged from 5% to 42% across rivers. Our latent biomass model improves understanding of disturbance thresholds and recovery patterns of autotrophic biomass within river ecosystems.

 

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 porteriandC. 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.

 

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management. 

Effective conservation requires understanding species’ abundance patterns and demographic rates across space and time. Ideally, such knowledge should be available for whole communities because variation in species’ dynamics can elucidate factors leading to biodiversity losses. However, collecting data to simultaneously estimate abundance and demographic rates of communities of species is often prohibitively time intensive and expensive. We developed a multispecies dynamicN‐occupancy model to estimate unbiased, community‐wide relative abundance and demographic rates. In this model, detection–nondetection data (e.g., repeated presence–absence surveys) are used to estimate species‐ and community‐level parameters and the effects of environmental factors. To validate our model, we conducted a simulation study to determine how and when such an approach can be valuable and found that our multispecies model outperformed comparable single‐species models in estimating abundance and demographic rates in many cases. Using data from a network of camera traps across tropical equatorial Africa, we then used our model to evaluate the statuses and trends of a forest‐dwelling antelope community. We estimated relative abundance, rates of recruitment (i.e., reproduction and immigration), and apparent survival probabilities for each species’ local population. The antelope community was fairly stable (although 17% of populations [species–park combinations] declined over the study period). Variation in apparent survival was linked more closely to differences among national parks than to individual species’ life histories. The multispecies dynamicN‐occupancy model requires only detection–nondetection data to evaluate the population dynamics of multiple sympatric species and can thus be a valuable tool for examining the reasons behind recent biodiversity loss.

 

Many canyon‐bound rivers have been dammed and downstream flow and water temperatures modified. In some regions, climate change is expected to cause lower storage in reservoirs and warmer release temperatures, which may further alter downstream flow and thermal regimes. To anticipate potential future changes, we first need to understand the dominant heat transfer mechanisms in canyon‐bound river systems. Toward this end, we adapt a dynamic process‐based river routing and temperature model to account for complex shading and radiation characteristics found in canyon‐bound rivers. We apply the model to a 362 km segment of the Colorado River in Grand Canyon National Park, USA to simulate temperature over an 18‐year period. Extensive temperature and flow data sets from within the canyon were used to assess model performance. At the most downstream gaging location, root mean square errors of hourly flow routing and temperature predictions were 11.5 m³/s and 0.93°C, respectively. We found that heat fluxes controlling temperatures were highly variable over space and time, primarily due to shortwave radiation dynamics and hydropeaking flow conditions. Additionally, the large differences between air and water temperature during summer periods resulted in high sensible and latent heat fluxes. Sensitivity analyses indicate that reservoir release temperatures are most influential above the RM88 gage (141 km below Glen Canyon Dam), while a combination of discharge, shortwave radiation, and air temperature become more important farther downstream. This study illustrates the importance of understanding the spatial and temporal variability of topographic shading when predicting water temperatures in canyon‐bound rivers.

 

The increasing availability of high‐frequency freshwater ecosystem metabolism data provides an opportunity to identify links between metabolic regimes, as gross primary production and ecosystem respiration patterns, and consumer energetics with the potential to improve our current understanding of consumer dynamics (e.g., population dynamics, community structure, trophic interactions). We describe a conceptual framework linking metabolic regimes of flowing waters with consumer community dynamics. We use this framework to identify three emerging research needs: (1) quantifying the linkage of metabolism and consumer production data via food web theory and carbon use efficiencies, (2) evaluating the roles of metabolic dynamics and other environmental regimes (e.g., hydrology, light) in consumer dynamics, and (3) determining the degree to which metabolic regimes influence the evolution of consumer traits and phenology. Addressing these needs will improve the understanding of consumer biomass and production patterns as metabolic regimes can be viewed as an emergent property of food webs.

 

To understand how migratory behavior evolved and to predict how migratory species will respond to global environmental change it is important to quantify the fitness consequences of intra‐ and inter‐individual variation in migratory behavior. Intra‐individual variation includes behavioral responses to changing environmental conditions and hence behavioral plasticity in the context of novel or variable conditions. Inter‐individual variation determines the degree of variation on which selection can act and the rate of evolutionary responses to changes in average and extreme environmental conditions. Here we focus on variation in the partial migratory behavior of giant Galápagos tortoises (Chelonoidisspp.) and its energetic consequences. We evaluate the extent and mechanisms by which tortoises adjust migration timing in response to varying annual environmental conditions, and integrate movement data within a bioenergetic model of tortoise migration to quantify the fitness consequences of migration timing. We find strong inter‐individual variation in the timing of migration, which was not affected by environmental conditions prevailing at the time of migration but rather by average expectations estimated from multi‐annual averaged conditions. This variation is associated with an average annual loss in efficiency of ~15% relative to optimal timing based on year‐specific conditions. These results point towards a limited ability of tortoises to adjust the timing of their migrations based on prevailing (and, by extension, future) conditions, suggesting that the adaptability of tortoise migratory behavior to changing conditions is predicated more by past “normal” conditions than responses to prevailing, changing conditions. Our work offers insights into the level of environmental‐tuning in migratory behavior and a general framework for future research across taxa.