scholarly journals Physical habitat simulation for small-sized characid fish species from tropical rivers in Brazil

2018 ◽  
Vol 16 (4) ◽  
Author(s):  
Hersília de Andrade e Santos ◽  
Cecília Gontijo Leal ◽  
Paulo Santos Pompeu ◽  
Ceceo Chaves ◽  
Stephanie Fernandes Cunha

ABSTRACT Physical habitat simulation (PHABSIM) is an important step of the instream flow incremental methodology (IFIM), which is applied to establish environmental flow regimes. This study applied the PHABSIM in two reaches of the Velhas river basin, whose long-term discharges are similar but are under different degrees of impact. Suitability curves were obtained for fish species using traditional methods (Astyanax sp., Piabarchus stramineus, Piabina argentea and Serrapinnus heterodon) and generalized additive models for fish density (Astyanax sp., P. argentea and S. heterodon). The results of habitat use depended on the method for curves generation. Applying the suitability curves by traditional methods, different discharge scenarios were simulated. The flow increasing from a dry scenario to a discharge of 1 year of return promotes a possible habitat increase for all species. However, the same hydrological flow percentiles produce different habitat proportions in different rivers. This work demonstrates that regardless of how suitability curves for the Neotropical species are generated, caution should be taken when applying them. However, the PHABSIM method allows more complex analyses than the traditional approaches based on minimal flow estimations, which is usually applied in South America.

2021 ◽  
Author(s):  
Iva Hunova ◽  
Marek Brabec ◽  
Marek Malý ◽  
Alexandru Dumitrescu ◽  
Jan Geletič

<p>Fog is a very complex phenomenon (Gultepe et al., 2007). In some areas it can contribute substantially to hydrological and chemical inputs and is therefore of high environmental relevance (Blas et al., 2010). Fog formation is affected by numerous factors, such as meteorology, air pollution, terrain (geomorphology), and land-use.</p><p>In our earlier studies we addressed the role of meteorology and air pollution on fog occurrence (Hůnová et al., 2018) and long-term trends in fog occurrence in Central Europe (Hůnová et al., 2020). This study builds on earlier model identification of year-to-year and seasonal components in fog occurrence and brings an analysis of the deformation of the above components due to the individual explanatory variables. The aim of this study was to indicate the geographical and environmental factors affecting the fog occurrence.</p><p>       We have examined the data on fog occurrence from 56 meteorological stations of various types from Romania reflecting different environments and geographical areas. We used long-term records from the 1981–2017 period. </p><p>       We considered both the individual explanatory variables and their interactions. With respect to geographical factors, we accounted for the altitude and landform. With respect to environmental factors,   we accounted for proximity of large water bodies, and proximity of forests. Geographical data from Copernicus pan-European (e.g. CORINE land cover, high resolution layers) and local (e.g. Urban Atlas) projects were used. Elevation data from EU-DEM v1.1 were source for morphometric analysis (Copernicus, 2020).</p><p>        We applied a generalized additive model, GAM (Wood, 2017; Hastie & Tibshirani, 1990) to address nonlinear trend shapes in a formalized and unified way. In particular, we employed penalized spline approach with cross-validated penalty coefficient estimation. To explore possible deformations of annual and seasonal components with various covariates of interest, we used (penalized) tensor product splines to model (two-way) interactions parsimoniously, Wood (2006).</p><p>       The fog occurrence showed significant decrease over the period under review. In general the selected explanatory variables significantly affected the fog occurrence and their effect was non-linear. Our results indicated that, the geographical and environmental variables affected primarily the seasonal component of the model. Of the factors which were accounted for, it was mainly the altitude showing the clear effect on seasonal component deformation (Hůnová et al., in press).</p><p>      </p><p> </p><p>References:</p><p>Blas, M, Polkowska, Z., Sobik, M., et al. (2010). Atmos. Res. 95, 455–469.</p><p>Copernicus Land Monitoring Service (2020). Accessed online at: https://land.copernicus.eu/.</p><p>Gultepe, I., Tardif, R., Michaelidis, S.C., Cermak, J., Bott, A. et al. (2007). Pure Appl Geophys, 164, 1121-1159.</p><p>Hastie, T.J., Tibshirani, R.J. (1990). Generalized Additive Models. Boca Raton, Chapman & Hall/CRC.</p><p>Hůnová, I., Brabec, M., Malý, M., Dumitrescu, A., Geletič, J. (in press) Sci. Total Environ. 144359.</p><p>Hůnová, I., Brabec, M., Malý, M., Valeriánová, A. (2018) Sci. Total Environ. 636, 1490–1499.</p><p>Hůnová, I., Brabec, M., Malý, M., Valeriánová, A. (2020) Sci. Total Environ. 711, 135018.</p><p>Wood, S.N. (2006) Low rank scale invariant tensor product smooths for generalized additive mixed models. Biometrics 62(4):1025-1036</p><p>Wood, S.N. (2017). Generalized Additive Models: An Introduction with R (2nd ed). Boca Raton, Chapman & Hall/CRC.</p><p> </p>


2020 ◽  
Vol 77 (4) ◽  
pp. 741-751 ◽  
Author(s):  
Steven M. Lombardo ◽  
Jeffrey A. Buckel ◽  
Ernie F. Hain ◽  
Emily H. Griffith ◽  
Holly White

We analyzed four decades of presence–absence data from a fishery-independent survey to characterize the long-term phenology of river herring (alewife, Alosa pseudoharengus; and blueback herring, Alosa aestivalis) spawning migrations in their southern distribution. We used logistic generalized additive models to characterize the average ingress, peak, and egress timing of spawning. In the 2010s, alewife arrived to spawning habitat 16 days earlier and egressed 27 days earlier (peak 12 days earlier) relative to the 1970s. Blueback herring arrived 5 days earlier and egressed 23 days earlier (peak 13 days earlier) in the 2010s relative to the 1980s. The changes in ingress and egress timing have shortened the occurrence in spawning systems by 11 days for alewife over four decades and 18 days for blueback herring over three decades. We found that the rate of vernal warming was faster during 2001–2016 relative to 1973–1988 and is the most parsimonious explanation for changes in spawning phenology. The influence of a shortened spawning season on river herring population dynamics warrants further investigation.


2013 ◽  
Vol 71 (3) ◽  
pp. 672-680 ◽  
Author(s):  
Göran Sundblad ◽  
Ulf Bergström ◽  
Alfred Sandström ◽  
Peter Eklöv

Abstract Habitat protection is a strategy often proposed in fisheries management to help maintain viable populations of exploited species. Yet, quantifying the importance of habitat availability for population sizes is difficult, as the precise distribution of essential habitats is poorly known. To quantify the contribution from coastal nursery habitats to exploited fish population sizes, we related adult density to the amount of nursery habitat available for 12 populations of the two dominant predatory fish species in a 40 000-km2 archipelago area of the Baltic Sea. Habitat distribution was mapped using three conceptually different techniques, Maxent, generalized additive models, and random forest, using spawning and 0-group point samples. Adult densities were estimated from gillnet surveys. Regressions demonstrated no evident effect from fishing, whereas habitat availability had a positive effect, explaining almost half of the variation in population sizes of both species. This result shows that a substantial proportion of the potential production of adult fish can be estimated by mapping essential nursery habitats distribution. Responses were non-linear, indicating that habitat protection has largest effects where there is little available habitat. By demonstrating the importance of habitat limitation of two exploited fish species, we provide quantitative support to the benefits of habitat protection for fisheries.


2015 ◽  
Vol 13 (4) ◽  
pp. 685-698 ◽  
Author(s):  
Marcus Rodrigues da Costa ◽  
Tailan Moretti Mattos ◽  
Victor Hugo Fernandes ◽  
Francisco Martínez-Capel ◽  
Rafael Muñoz-Mas ◽  
...  

ABSTRACT The physical habitat simulation sub-routine of the Instream Flow Incremental Methodology (IFIM) uses hydraulic modeling and suitability indices of target fish species to predict how differences in-stream flows affect the microhabitat occupation by fish species. This habitat modelling approach was adopted to assess the ecological effects of running flows on three neotropical fish species of different orders (Bryconamericus ornaticeps , Ancistrus multispinis and Geophagus brasiliensis ).The study encompassed two reaches of an Atlantic Forest stream in Southeastern Brazil where topographic and hydraulic (depth, velocity and type of substrate) characteristics were measured to implement one-dimensional hydraulic simulation. Sub aquatic observation of fish was performed to collect data on microhabitat use and these data were used to develop habitat suitability curves that were used in the habitat simulation to obtain the habitat suitability index (HSI) and weighted usable area (WUA) versus flow curves. Upon these curves minimum and optimum environmental flows for the target fish species were proposed. Bryconamericus ornaticeps and A. multispinis selected microhabitats around 0.6 m depth, whereas G. brasiliensis showed a wider suitable range (0.35-0.9 m). All the three species were mainly observed in microhabitat with low flow velocity (0.1 m/s). Bryconamericus ornaticeps selected more frequently coarse substrate (e.g. boulders) but it appeared also over sandy substrate, whereas A. multispinis and G. brasiliensis selected preferably boulders. The range of 0.65-0.85 m3/s was found as the optimum to meet the needs of the three fish species. Our results agree with the necessary objective information to perform grounded management actions in the frame of a management program aiming at ecosystem conservation. Thereby it can be considered a successful pilot study in environmental flow assessment in an Atlantic Forest stream of Brazil.


1995 ◽  
Vol 52 (3) ◽  
pp. 566-577 ◽  
Author(s):  
Larry D. Jacobson ◽  
Alec D. MacCall

We used generalized additive models to study the recruitment of Pacific sardine (Sardinops sagax) along western North America and to compare the effects of fishing and environmental factors on the stock. We found significant relationships between the logarithm of sardine reproductive success (recruits per unit of spawning biomass) and average sea surface temperature (SST), as well as between sardine recruitment, spawning biomass, and average SST. Simulation and time series analyses were used to evaluate bias, variance, and statistical power for one of our models. Correlation with log reproductive success was highest when average SST data included temperatures after the period of larval development, indicating that recruitment estimates were affected by environmentally driven changes in availability of older sardine to the fishery. Predicted equilibrium biomass and MSY for sardine are lower under environmental conditions that prevail when temperatures are colder. Long-term fluctuations in the environment may cause long-term fluctuations in sardine productivity, and little or no sardine harvest may be sustainable during periods of adverse environmental conditions and cold temperatures.


2021 ◽  
Author(s):  
Francesco Battaglioli ◽  
Pieter Groenemeijer ◽  
Tomas Pucik ◽  
Uwe Ulbrich ◽  
Henning Rust ◽  
...  

<p>Convective hazards such as large hail, severe wind gusts, tornadoes, and heavy rainfall cause high economic damages, fatalities, and injuries across Europe. There are insufficient observations to determine whether trends in such local phenomena exist, however recent studies suggest that the conditions supporting such hazards have become more frequent across large parts of Europe in recent decades.</p><p>We model the occurrence of these hazards using Generalized Additive Models (GAM) to investigate the existence of such long-term trends, and to enable objective probabilistic forecasts of these hazards. The models are trained with storm reports from the European Severe Weather Database (ESWD), lightning observations from the EUCLID network, and predictor parameters derived from the ERA5 reanalysis. Our work is based on the framework AR-CHaMo (Additive Regression Convective Hazard Models), previously developed at ESSL.</p><p>Preliminary results include a spatial depiction of the environmental conditions giving rise to convective hazards at a higher resolution than was possible before. The skill of hail models developed using AR-CHaMo has been shown to be superior to composite parameters used by weather forecasters for the occurrence of large hail, such as the Supercell Composite Parameter (SCP) and the Significant Hail Parameter (SHP). Likewise, for tornadoes, more skillful models can be constructed using the AR-CHaMo framework than predictors such as the Significant Tornado Parameter (STP).</p><p>The developed models have use both in climate studies and in medium-range severe weather forecasting. We will report on initial efforts to detect long term (1979-2019) trends of convective hazards and present how these models can be used to support severe weather forecasting using medium-range ensemble forecasts.</p>


2021 ◽  
Author(s):  
Samuel M. Bashevkin ◽  
Brian Mahardja ◽  
Larry R. Brown

Temperature is a key controlling variable from subcellular to ecosystem scales. Thus, climatic warming is expected to have broad impacts, especially in economically and ecologically valuable systems such as estuaries. The heavily managed upper San Francisco Estuary (SFE) supplies water to millions of people and is home to fish species of high conservation, commercial, and recreational interest. Despite a long monitoring record (> 50 years), we do not yet know how water temperatures have already changed or how trends vary spatially or seasonally. We fit generalized additive models on an integrated database of discrete water temperature observations to estimate long-term trends with spatio-seasonal variability. We found that water temperatures have increased 0.017 °C/year on average over the past 50 years. Rates of temperature change have varied over time, but warming was predominant. Temperature increases were most widespread in the late-fall to winter (November to February) and mid-spring (April to June), coinciding with the winter development of juvenile Chinook Salmon and spring spawning window of the endangered Delta Smelt. Warming was fastest in the northern regions, a key fish migration corridor with important tidal wetland habitat. However, no long-term temperature trends were detected in October and were only observed in some regions in May, July, and August. These results can help identify optimal areas for restoration or refugia to buffer the effects of a warming climate, and the methods can be leveraged to understand the spatiotemporal variability in climate warming patterns in other aquatic systems.


2017 ◽  
Vol 74 (3) ◽  
pp. 306-315 ◽  
Author(s):  
David B. Bunnell ◽  
Tomas O. Höök ◽  
Cary D. Troy ◽  
Wentao Liu ◽  
Charles P. Madenjian ◽  
...  

In the Great Lakes region, multiple fish species display intraspecific spatial synchrony in recruitment success, with interannual climate variation hypothesized as the most likely driver. In Lake Michigan, we evaluated whether climatic or other physical variables could also induce spatial synchrony across multiple species, including bloater (Coregonus hoyi), rainbow smelt (Osmerus mordax), yellow perch (Perca flavescens), and alewife (Alosa pseudoharengus). The residuals from stock–recruitment relationships revealed yellow perch recruitment to be correlated with recruitment of both rainbow smelt (r = 0.37) and alewife (r = 0.36). Across all four species, higher than expected recruitment occurred in 5 years between 1978 and 1987 and then switched to lower than expected recruitment in 5 years between 1996 and 2004. Generalized additive models revealed warmer spring and summer water temperatures and lower wind speeds corresponded to higher than expected recruitment for the nearshore-spawning species, and overall variance explained ranged from 14% (yellow perch) to 61% (alewife). For all species but rainbow smelt, higher recruitment also occurred in extremely high or low years of the North Atlantic Oscillation index. Future development of indices that describe the physical Great Lakes environment could improve understanding of how climate can synchronize fish populations within and across species.


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