scholarly journals Density dependence and its impact on individual growth rates in an age-structured stream salmonid population

Ecosphere ◽  
2015 ◽  
Vol 6 (12) ◽  
pp. art281 ◽  
Author(s):  
K. M. Myrvold ◽  
B. P. Kennedy
Keyword(s):  
Density Dependence ◽  
Growth Rates ◽  
Individual Growth ◽  
Age Structured ◽  
Stream Salmonid

Density-dependent habitat use and growth of an estuarine fish

2012 ◽  
Vol 69 (11) ◽  
pp. 1734-1747 ◽  
Author(s):  
Nathan M. Bacheler ◽  
Jeffrey A. Buckel ◽  
Lee M. Paramore
Keyword(s):  
Habitat Use ◽  
Density Dependence ◽  
Growth Rates ◽  
Environmental Variability ◽  
Red Drum ◽  
Individual Growth ◽  
Estuarine Fish ◽  
Feedback Controls ◽  
Density Dependent ◽  
Spatial And Temporal Scales

Density dependence can stabilize or destabilize population size through negative or positive feedback controls operating over different spatial and temporal scales. While many species have been shown to exhibit density dependence, the topic has received little attention in estuaries where environmental variability and larval supply are often considered to be the primary drivers of population dynamics. We used multiple long-term, fishery-independent data sets and a unique modeling approach to test the hypothesis that juvenile red drum ( Sciaenops ocellatus ) exhibit density-dependent habitat use and growth rates in estuaries in North Carolina, USA. Age-1 red drum exhibited density-dependent habitat use after accounting for environmental and landscape variables, disproportionately increasing northward and coastward in the study area at high abundance. Apparent individual growth rates of age-0 and age-1 red drum were generally negatively related to the abundance of their own age classes, but evidence of density-dependent growth rates for age-2 red drum was weak to nonexistent. Changes in spatial distribution of red drum when overall abundance was high did not overcome density-dependent effects on individual growth rates. Thus, density-dependent effects have potential negative feedbacks on population growth in estuaries and should not be ignored in future theoretical or empirical estuarine studies.

Geostatistically modeling stem size and increment in an old-growth forest

1994 ◽  
Vol 24 (7) ◽  
pp. 1354-1368 ◽  
Author(s):  
Franco Biondi ◽  
Donald E. Myers ◽  
Charles C. Avery
Keyword(s):  
Spatial Patterns ◽  
Growth Rates ◽  
Spatial Dependence ◽  
Basal Area ◽  
Tree Density ◽  
Individual Growth ◽  
Old Growth ◽  
Model Estimate ◽  
Stem Size ◽  
Old Growth Forest

Geostatistics provides tools to model, estimate, map, and eventually predict spatial patterns of tree size and growth. Variogram models and kriged maps were used to study spatial dependence of stem diameter (DBH), basal area (BA), and 10-year periodic basal area increment (BAI) in an old-growth forest stand. Temporal variation of spatial patterns was evaluated by fitting spatial stochastic models at 10-year intervals, from 1920 to 1990. The study area was a naturally seeded stand of southwestern ponderosa pine (Pinusponderosa Dougl. ex Laws. var. scopulorum) where total BA and tree density have steadily increased over the last decades. Our objective was to determine if increased stand density simply reduced individual growth rates or if it also altered spatial interactions among trees. Despite increased crowding, stem size maintained the same type of spatial dependence from 1920 to 1990. An isotropic Gaussian variogram was the model of choice to represent spatial dependence at all times. Stem size was spatially autocorrelated over distances no greater than 30 m, a measure of average patch diameter in this forest ecosystem. Because patch diameter remained constant through time, tree density increased by increasing the number of pine groups, not their horizontal dimension. Spatial dependence of stem size (DBH and BA) was always much greater and decreased less through time than that of stem increment (BAI). Spatial dependence of BAI was close to zero in the most recent decade, indicating that growth rates in 1980–1990 varied regardless of mutual tree position. Increased tree crowding corresponded not only to lower average and variance of individual growth rates, but also to reduced spatial dependence of BAI. Because growth variation was less affected by intertree distance with greater local crowding, prediction of individual growth rates benefits from information on horizontal stand structure only if tree density does not exceed threshold values. Simulation models and area estimates of tree performance in old-growth forests may be improved by including geostatistical components to summarize ecological spatial dependence.

Wintertime growth in Atlantic salmon under changing climate: the importance of ice cover for individual growth dynamics

2021 ◽  
Author(s):  
Laura Härkönen ◽  
Pauliina Louhi ◽  
Riina Huusko ◽  
Ari Huusko
Keyword(s):  
Climate Change ◽  
Atlantic Salmon ◽  
Growth Rates ◽  
Growth Dynamics ◽  
Ice Cover ◽  
Individual Growth ◽  
Late Winter ◽  
Dynamic Nature ◽  
Individual Level ◽  
Growth Variation

Understanding the dynamic nature of individual growth in stream-dwelling salmonids may help forecast consequences of climate change on northern fish populations. Here, we performed an experimental capture-mark-recapture study in Atlantic salmon to quantify factors influencing wintertime growth variation among juveniles under different scenarios for ice cover reduction. We applied multiple imputation to simulate missing size observations for unrecaptured fish, and to account for individual-level variation in growth rates. The salmon parr exhibited substantial body length shrinkage in early winter, suppressed growth through mid-winter, and increasing growth rates in late winter and particularly in spring. Unexpectedly, the presence of ice cover had no direct effects on wintertime growth. Instead, our results implied increasing energetic costs with reducing ice cover: individuals exposed to absent or shortened ice-covered period gained mass at a lowered rate in spring whereas the present, long ice-covered period was followed by rapid growth. This study emphasizes natural resilience of Atlantic salmon to wintertime environmental variation which may help the species to cope with the reductions in ice cover duration due to climate change.

scholarly journals The Effect of Conspecific Density on Emergence ofLestes bipupillatusCalvert, 1909 (Odonata: Lestidae)

2014 ◽  
Vol 2014 ◽  
pp. 1-3 ◽  
Author(s):  
Ricardo Cardoso-Leite ◽  
Gabriel C. Vilardi ◽  
Rhainer Guillermo-Ferreira ◽  
Pitágoras C. Bispo
Keyword(s):  
Population Dynamics ◽  
Density Dependence ◽  
Social Environment ◽  
Growth Rates ◽  
High Density ◽  
Conspecific Density ◽  
Simulated Environments ◽  
The Social ◽  
Emergence Date

Conspecific density may influence adult recruitment and consequently population dynamics. Several studies have shown the density dependence of larvae growth rates in Odonata. However, few studies studied how conspecific density influence final instar larvae emergence date decisions. Considering that larvae may choose the date of emergence, the present study investigated if density affects larvae choice. For this, we reared eight final instar larvae in individual aquaria and other 24 larvae in aquaria with three larvae each. This way, we simulated environments with low and high larval densities. We then noted the days that larvae took to emerge and compared it between low and high density groups. The results showed that larvae seem to emerge earlier when in high densities (Mann-Whitney,U=10.000,P=0.03). These results support the hypothesis that damselfly last instar larvae may postpone or hasten emergence in response to the social environment and related constraints.

Mangroves as Fish Habitat

2015 ◽  
Keyword(s):  
Growth Rates ◽  
Fish Habitat ◽  
Individual Growth ◽  
Baja California Sur ◽  
Bivalve Species ◽  
Anthropogenic Pressures ◽  
La Paz ◽  
Frequency Distributions ◽  
Mass Increment ◽  
Secondary Productivity

<em>Abstract</em>.—To measure secondary productivity of mangrove systems, we estimated the abundance (individuals/m<sup>2</sup>) and mass increment (g/month) of the two bivalve species: the black ark <em>Anadara tuberculosa </em>and palmate oyster <em>Saccostrea palmula</em>. Mass increments were based on individual growth rates derived from length-frequency distributions analyses. Samples were collected at three mangrove estuaries in a sand barrier at Ensenada de La Paz from August 2007 to July 2009. The average abundance was 1.27 individuals/m<sup>2</sup> for black ark and 510 individuals/m<sup>2</sup> for palmate oysters. Estimated growth rates were 3.67 g/month for black ark and 0.18 g/month for palmate oysters. The average secondary productivity of the black ark was 4.51 g•m<sup>-2</sup>•month<sup>-1</sup> and peaked during the spring, while for the palmate oyster <em>Saccostrea palmula </em>it was 97.9 g•m<sup>-2</sup>•month<sup>-1</sup>, with peak productivity recorded during the summer. The findings of this investigation constitute a necessary element for establishing a baseline to evaluate the consequences of the various natural and anthropogenic pressures that the mangrove systems of El Mogote of La Paz Bay, Baja California Sur, Mexico.

Size-structured models

2019 ◽  
pp. 122-144
Author(s):  
Louis W. Botsford ◽  
J. Wilson White ◽  
Alan Hastings
Keyword(s):  
Mortality Rates ◽  
Structured Populations ◽  
Individual Growth ◽  
Integral Projection Model ◽  
Projection Model ◽  
Future Projections ◽  
State Variable ◽  
Recent Approach ◽  
Model Size ◽  
Age Structured

This chapter begins by revisiting the M’Kendrick/von Foerster model, but using size instead of age as the state variable. It then uses the lessons from that model to describe how individual growth and mortality rates determine both stand distributions (a population of mixed ages) and cohort distributions (all one age). In particular, incorporating variability in growth trajectories is shown to be important in obtaining realistic results—though it is not without pitfalls. Ultimately, the numerical calculations required to model size-structured populations for future projections are more challenging than those needed for age structure, so the chapter closes by discussing some mathematical tools that have been developed to accomplish this. These include the integral projection model, a recent approach that is very useful because, while more complex, it has a lot in common with the age-structured models examined in Chapters 3 and 4.

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