Search for: All records

Key Points We compared tools for describing streamflow timeseries, including streamflow metrics, wavelet, and Fourier analysis Each method indicated streamflow data are structured: variability at short timescales is negatively correlated with long timescales Globally, dams were less correlated with streamflow regime than catchment size and climate were 

Empirical evidence and theory suggest that climate warming and an increase in the frequency and duration of drying events will alter the metabolic balance of freshwater ecosystems. However, the impacts of climate change on ecosystem metabolism may depend on whether energy inputs are of autochthonous or allochthonous origin. To date, few studies have examined how warming and drying may interact to alter stream metabolism, much less how their impacts may depend on the energy‐base of the food web.

To address this research gap, we conducted a multi‐factorial experiment using outdoor mesocosms to investigate the individual and synergistic effects of warming and drought on metabolic processes in stream mesocosms with green (algal‐based) vs. mixed (algal‐ and detritus‐based) vs. brown (detritus‐based) energy pathways.

We set up 48 mesocosms with one of three different levels of shade and leaf litter input combinations to create mesocosms with different primary energy channels. In addition, we warmed half of the mesocosms by ~2–3°C. We assessed changes in ecosystem respiration (ER), gross primary production (GPP), net ecosystem production (NEP) and organic matter biomass in warmed and ambient temperature mesocosms before a 24 day drying event and after rewetting.

Surprisingly, experimental warming had little effect on metabolic processes. Drying, however, led to decreased rates of ER and GPP and led to an overall reduction in NEP. Although the effects of drying were similar across energy channel treatments, reductions in ER and GPP were primarily driven by decreases in biomass of benthic and filamentous algae.

Overall, we demonstrate that drying led to lower rates of NEP in mesocosms regardless of energy inputs. While warming showed little effect in our study, our results suggest that an increase in the frequency of stream drying events could greatly alter the metabolic balance of many aquatic ecosystems.

Read the freePlain Language Summaryfor this article on the Journal blog.

 

Ecosystems that are coupled by reciprocal flows of energy and nutrient subsidies can be viewed as a single “meta‐ecosystem.” Despite these connections, the reciprocal flow of subsidies is greatly asymmetrical and seasonally pulsed. Here, we synthesize existing literature on stream–riparian meta‐ecosystems to quantify global patterns of the amount of subsidy consumption by organisms, known as “allochthony.” These resource flows are important since they can comprise a large portion of consumer diets, but can be disrupted by human modification of streams and riparian zones. Despite asymmetrical subsidy flows, we found stream and riparian consumer allochthony to be equivalent. Although both fish and stream invertebrates rely on seasonally pulsed allochthonous resources, we find allochthony varies seasonally only for fish, being nearly three times greater during the summer and fall than during the winter and spring. We also find that consumer allochthony varies with feeding traits for aquatic invertebrates, fish, and terrestrial arthropods, but not for terrestrial vertebrates. Finally, we find that allochthony varies by climate for aquatic invertebrates, being nearly twice as great in arid climates than in tropical climates, but not for fish. These findings are critical to understanding the consequences of global change, as ecosystem connections are being increasingly disrupted.

 

DNA‐based aquatic biomonitoring methods show promise to provide rapid, standardized, and efficient biodiversity assessment to supplement and in some cases replace current morphology‐based approaches that are often less efficient and can produce inconsistent results. Despite this potential, broad‐scale adoption of DNA‐based approaches by end‐users remains limited, and studies on how these two approaches differ in detecting aquatic biodiversity across large spatial scales are lacking. Here, we present a comparison of DNA metabarcoding and morphological identification, leveraging national‐scale, open‐source, ecological datasets from the National Ecological Observatory Network (NEON). Across 24 wadeable streams in North America with 179 paired sample comparisons, we found that DNA metabarcoding detected twice as many unique taxa than morphological identification overall. The two approaches showed poor congruence in detecting the same taxa, averaging 59%, 35%, and 23% of shared taxa detected at the order, family, and genus levels, respectively. Importantly, the two approaches detected different proportions of indicator taxa like %EPT and %Chironomidae. DNA metabarcoding detected far fewer Chironomid and Trichopteran taxa than morphological identification, but more Ephemeropteran and Plecopteran taxa, a result likely due to primer choice. Overall, our results showed that DNA metabarcoding and morphological identification detected different benthic macroinvertebrate communities. Despite these differences, we found that the same environmental variables were correlated with invertebrate community structure, suggesting that both approaches can accurately detect biodiversity patterns across environmental gradients. Further refinement of DNA metabarcoding protocols, primers, and reference libraries–as well as more standardized, large‐scale comparative studies–may improve our understanding of the taxonomic agreement and data linkages between DNA metabarcoding and morphological approaches.

 

Habitat fragmentation drives biodiversity loss in rivers around the world. Although the effects of anthropogenic barriers on river connectivity are well known, there has been little research on the ways in which stream drying may alter connections among habitats and resources. Given that stream drying is increasing in many regions, there is a pressing need to understand the effects of drying on habitat fragmentation. Here, we quantify spatiotemporal drying patterns under current and future climate scenarios in the Upper Blue River Basin, Oklahoma. We used a hydrologic model to simulate daily streamflow for nine climate scenarios. For each scenario, we calculated metrics of streamflow temporal continuity (dry days, dry periods, and dry period duration) and spatial connectivity (wetted length, number of dry stream fragments, length of dry stream fragments, and dendritic connectivity index) from simulated daily streamflow. We found that stream drying is likely to increase in all future climate scenarios and that increases in stream drying reduce connectivity. However, the effects of stream drying on connectivity were highly nonlinear. Specifically, we observed a threshold around which a small increase in stream drying led to a rapid drop in connectivity. We also found that the greatest increases in stream drying were not associated with the highest emission scenarios, underscoring the complex linkages among climate, water availability, and connectivity. Given that connectivity is essential to ecosystem structure and function, we discuss water management strategies informed by impacts of stream drying.

 

Previous studies in urban desert ecosystems have reported a decline in avian diversity. Herein, we expand and improve these studies by disentangling the effect of land-use and land-cover (LULC) types (desert, riparian desert, urban, riparian urban, agriculture), vegetation greenness (normalized difference vegetation index—NDVI), climate, and their interactions on avian seasonal variation abundance and richness. Avian community data were collected seasonally (winter and spring) from 2001 to 2016. We used generalized linear mixed models (GLMM) and multimodel inference to investigate how environmental predictors explain patterns of avian richness and abundance. Avian abundance and richness oscillated considerably among the years. GLMM indicated that LULC was the most important predictor of avian abundance and richness. Avian abundance was highest in urban riparian and urban LULC types, followed by agriculture. In contrast, avian richness was the highest in riparian environments (urban and desert), followed by agriculture, urban, and desert. NDVI was also strongly related to avian abundance and richness, whereas the effect of temperature and precipitation was moderate. The importance of environmental predictors is, however, dependent on LULC. The importance of LULC, vegetation cover, and climate in influencing the seasonal patterns of avian distribution highlights birds’ sensitivity to changes in land use and cover and temperature. 

The “dimensional stability” approach measures different components of ecological stability to investigate how they are related. Yet, most empirical work has used small‐scale and short‐term experimental manipulations. Here, we apply this framework to a long‐term observational dataset of stream macroinvertebrates sampled between the winter flooding and summer monsoon seasons. We test hypotheses that relate variation among stability metrics across different taxa, the magnitude of antecedent (monsoon) and immediate (winter) floods to stability metrics, and the relative importance of disturbance magnitude and taxonomic richness on community dimensional stability. Cluster analysis revealed four distinct stability types, and we found that the magnitude of floods during the prior monsoon was more important in influencing stability than the winter flood itself. For dimensional stability at the community level, taxonomic richness was more important than disturbance magnitude. This work demonstrates that abiotic and biotic factors determine dimensional stability in a natural ecosystem.