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1.
Glob Chang Biol ; 29(9): 2478-2492, 2023 05.
Article in English | MEDLINE | ID: mdl-36734695

ABSTRACT

Declining body size is believed to be a universal response to climate warming and has been documented in numerous studies of marine and anadromous fishes. The Salmonidae are a family of coldwater fishes considered to be among the most sensitive species to climate warming; however, whether the shrinking body size response holds true for freshwater salmonids has yet to be examined at a broad spatial scale. We compiled observations of individual fish lengths from long-term surveys across the Northern Hemisphere for 12 species of freshwater salmonids and used linear mixed models to test for spatial and temporal trends in body size (fish length) spanning recent decades. Contrary to expectations, we found a significant increase in length overall but with high variability in trends among populations and species. More than two-thirds of the populations we examined increased in length over time. Secondary regressions revealed larger-bodied populations are experiencing greater increases in length than smaller-bodied populations. Mean water temperature was weakly predictive of changes in body length but overall minimal influences of environmental variables suggest that it is difficult to predict an organism's response to changing temperatures by solely looking at climatic factors. Our results suggest that declining body size is not universal, and the response of fishes to climate change may be largely influenced by local factors. It is important to know that we cannot assume the effects of climate change are predictable and negative at a large spatial scale.


Subject(s)
Salmonidae , Animals , Fishes , Climate Change , Temperature , Fresh Water , Body Size
2.
PLoS One ; 16(8): e0255497, 2021.
Article in English | MEDLINE | ID: mdl-34339467

ABSTRACT

The three-spined stickleback Gasterosteus aculeatus invaded Lake Contance in the 1940s and expanded in large numbers from an exclusively shoreline habitat into the pelagic zone in 2012. Stickleback abundance is very high in the pelagic zone in winter near the spawning time of pelagic whitefish Coregonus wartmanni, and it is hypothesized that this is triggered by the opportunity to consume whitefish eggs. Field sampling has qualitatively confirmed predation of whitefish eggs by stickleback, but quantification has proven difficult due to stormy conditions that limit sampling. One fundamental unknown is if freshwater stickleback, known as visual feeders, can successfully find and eat whitefish eggs during twilight and night when whitefish spawn. It is also unknown how long eggs can be identified in stomachs following ingestion, which could limit efforts to quantify egg predation through stomach content analysis. To answer these questions, 144 individuals were given the opportunity to feed on whitefish roe under daylight, twilight, and darkness in controlled conditions. The results showed that stickleback can ingest as many as 100 whitefish eggs under any light conditions, and some individuals even consumed maximum numbers in complete darkness. Furthermore, eggs could be unambiguously identified in the stomach 24 hours after consumption. Whitefish eggs have 28% more energy content than the main diet of sticklebacks (zooplankton) based on bomb-calorimetric measurements, underlining the potential benefits of consuming eggs. Based on experimental results and estimates of stickleback abundance and total egg production, stickleback could potentially consume substantial proportions of the total eggs produced even if relatively few sticklebacks consume eggs. Given the evidence that stickleback can feed on eggs during nighttime spawning and may thereby hamper recruitment, future studies aimed at quantifying actual egg predation and resulting effects on the whitefish population are urgently needed.


Subject(s)
Diet/veterinary , Eggs/analysis , Light , Predatory Behavior , Salmonidae/physiology , Seasons , Smegmamorpha/physiology , Animals , Ecosystem
3.
Sci Rep ; 11(1): 10520, 2021 05 18.
Article in English | MEDLINE | ID: mdl-34006900

ABSTRACT

Monitoring fish populations in large, deep water bodies by conventional capture methodologies requires intensive fishing effort and often causes mass mortality of fish. Thus, it can be difficult to collect sufficient data using capture methods for understanding fine scale community dynamics associated with issues such as climate change or species invasion. Hydroacoustic monitoring is an alternative, less invasive technology that can collect higher resolution data over large temporal and spatial scales. Monitoring multiple species with hydroacoustics, however, usually requires conventional sampling to provide species level information. The ability to identify the species identity of similar-sized individuals using only hydroacoustic data would greatly expand monitoring capabilities and further reduce the need for conventional sampling. In this study, wideband hydroacoustic technology was used in a mesocosm experiment to differentiate between free swimming, similar-sized individuals of two swim-bladdered species: whitefish (Coregonus wartmanni) and stickleback (Gasterosteus aculeatus). Individual targets were identified in echograms and variation in wideband acoustic responses among individuals, across different orientations, and between species was quantified and visually examined. Random forest classification was then used to classify individual targets of known species identity, and had an accuracy of 73.4% for the testing dataset. The results show that species can be identified with reasonable accuracy using wideband hydroacoustics. It is expected that further mesocosm and field studies will help determine capabilities and limitations for classifying additional species and monitoring fish communities. Hydroacoustic species differentiation may offer novel possibilities for fisheries managers and scientists, marking the next crucial step in non-invasive fish monitoring.


Subject(s)
Acoustics , Salmonidae/physiology , Smegmamorpha/physiology , Animals , Ecosystem , Environmental Monitoring/methods , Machine Learning , Species Specificity
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