Two-year cyclicity in recruitment of a fish population is driven by an inter-stage effect

A 25-year time series for a vendace (Coregonus albula (L.)) population was analysed with mathematical models to reveal the factors that regulate its recruitment. The fitted recruitment model was an age-structured model incorporating the compensatory effects of the spawning population and the abundance of the previous year class. Wind forcing index was also added as an example of an external source of recruitment variability. The auto-correlation analysis revealed a tendency for 2-year generation cyclicity in recruitment. The compensatory effects of both spawning biomass and previous year class abundance on recruitment had to be incorporated into the model to remove cyclicity from residuals. Wind forcing during the larval and early juvenile periods negatively affected recruitment. Re-estimating the parameters of the Cushing recruitment function and the effect of previous year-class from simulated data revealed that the time series structure and measurement errors induce strong biases in parameters exaggerating the density independent population growth rate parameter and the amount of compensation. The negative effect of previous year class was also exaggerated but less severely. Simulations with the artificially perturbed deterministic model skeleton revealed a tendency for cyclicity in recruitment. The model typically generated dampening oscillations, but the dynamics appeared as limit cycles when assuming high mortality, a low level of compensation by spawning biomass and a considerable negative effect of the previous year-class. No single ultimate mechanism for inter-stage effects causing cyclicity can be presently designated despite the rather extensive studies on vendace population dynamics. Several of the suggested mechanisms may be operating in concert.     

Are the numbers adding up? Exploiting discrepancies among complementary population models

Large carnivores are difficult to monitor because they tend to be sparsely distributed, sensitive to human activity, and associated with complex life histories. Consequently, understanding population trend and viability requires conservationists to cope with uncertainty and bias in population data. Joint analysis of combined data sets using multiple models (i.e., integrated population model) can improve inference about mechanisms (e.g., habitat heterogeneity and food distribution) affecting population dynamics. However, unobserved or unobservable processes can also introduce bias and can be difficult to quantify. We developed a Bayesian hierarchical modeling approach for inference on an integrated population model that reconciles annual population counts with recruitment and survival data (i.e., demographic processes). Our modeling framework is flexible and enables a realistic form of population dynamics by fitting separate density-dependent responses for each demographic process. Discrepancies estimated from shared parameters among different model components represent unobserved additions (i.e., recruitment or immigration) or removals (i.e., death or emigration) when annual population counts are reliable. In a case study of gray wolves in Wisconsin (1980–2011), concordant with policy changes, we estimated that a discrepancy of 0% (1980–1995), −2% (1996–2002), and 4% (2003–2011) in the annual mortality rate was needed to explain annual growth rate. Additional mortality in 2003–2011 may reflect density-dependent mechanisms, changes in illegal killing with shifts in wolf management, and nonindependent censoring in survival data. Integrated population models provide insights into unobserved or unobservable processes by quantifying discrepancies among data sets. Our modeling approach is generalizable to many population analysis needs and allows for identifying dynamic differences due to external drivers, such as management or policy changes.     

Empirical orthogonal function regression: Linking population biology to spatial varying environmental conditions using climate projections

Ecologists and oceanographers inform population and ecosystem management by identifying the physical drivers of ecological dynamics. However, different research communities use different analytical tools where, for example, physical oceanographers often apply rank‐reduction techniques (a.k.a. empirical orthogonal functions [EOF]) to identify indicators that represent dominant modes of physical variability, whereas population ecologists use dynamical models that incorporate physical indicators as covariates. Simultaneously modeling physical and biological processes would have several benefits, including improved communication across sub‐fields; more efficient use of limited data; and the ability to compare importance of physical and biological drivers for population dynamics. Here, we develop a new statistical technique, EOF regression, which jointly models population‐scale dynamics and spatially distributed physical dynamics. EOF regression is fitted using maximum‐likelihood techniques and applies a generalized EOF analysis to environmental measurements, estimates one or more time series representing modes of environmental variability, and simultaneously estimates the association of this time series with biological measurements. By doing so, it identifies a spatial map of environmental conditions that are best correlated with annual variability in the biological process. We demonstrate this method using a linear (Ricker) model for early‐life survival (“recruitment”) of three groundfish species in the eastern Bering Sea from 1982 to 2016, combined with measurements and end‐of‐century projections for bottom and sea surface temperature. Results suggest that (a) we can forecast biological dynamics while applying delta‐correction and statistical downscaling to calibrate measurements and projected physical variables, (b) physical drivers are statistically significant for Pacific cod and walleye pollock recruitment, (c) separately analyzing physical and biological variables fails to identify the significant association for walleye pollock, and (d) cod and pollock will likely have reduced recruitment given forecasted temperatures over future decades.     

Multiple sources of evidence for density dependence in the endangered Hawaiian stilt (Himantopus mexicanus knudseni)

Hawaiian stilts (Himantopus mexicanus knudseni) are an endangered subspecies of the Black-necked stilt endemic to the Hawaiian Islands. Despite long-term study, the main drivers of Hawaiian stilt population dynamics are poorly understood. We tested for density dependence using two sources of evidence: a 30-year time series of annual estimated range-wide abundance, and two 15+ year time series of reproductive success. Using separate methods with independent data, sources allowed us to make up for the potentially positive bias of one approach with the more conservative nature of the second. We compared nonlinear density-dependent and density-independent population model fits to our time-series data, using both frequentist and Bayesian state-space approaches. Across both approaches, density-dependent models best fit observed population dynamics, with lower AICc and cross-validation statistics compared to density-independent models. Among density-dependent models, a conditional model in which density-independent dynamics occur below a population size threshold (~850–1,000 birds), and then density-dependent dynamics occur above that threshold, performed best across Bayesian and frequentist model comparisons, with the Ricker model ranked next or equivalently. Our analysis of reproduction data revealed a strong negative effect of local adult density on nest success (proportion of nests hatching at least one chick) at Kealia National Wildlife Refuge on Maui, where few alternative breeding habitats are available, but no such effect at another site where many nearby alternative wetlands are available. These congruent results across independent datasets and analytical approaches support the hypothesis that Hawaiian stilts exhibit density dependence across their range.     

Big‐sized trees overrule remaining trees' attributes and species richness as determinants of aboveground biomass in tropical forests

Large‐diameter, tall‐stature, and big‐crown trees are the main stand structures of forests, generally contributing a large fraction of aboveground biomass, and hence play an important role in climate change mitigation strategies. Here, we hypothesized that the effects of large‐diameter, tall‐stature, and big‐crown trees overrule the effects of species richness and remaining trees attributes on aboveground biomass in tropical forests (i.e., we term the “big‐sized trees hypothesis”). Specifically, we assessed the importance of: (a) the “top 1% big‐sized trees effect” relative to species richness; (b) the “99% remaining trees effect” relative to species richness; and (c) the “top 1% big‐sized trees effect” relative to the “99% remaining trees effect” and species richness on aboveground biomass. Using environmental factor and forest inventory datasets from 712 tropical forest plots in Hainan Island of southern China, we tested several structural equation models for disentangling the relative effects of big‐sized trees, remaining trees attributes, and species richness on aboveground biomass, while considering for the full (indirect effects only) and partial (direct and indirect effects) mediation effects of climatic and soil conditions, as well as interactions between species richness and trees attributes. We found that top 1% big‐sized trees attributes strongly increased aboveground biomass (i.e., explained 55%–70% of the accounted variation) compared to species richness (2%–18%) and 99% remaining trees attributes (6%–10%). In addition, species richness increased aboveground biomass indirectly via increasing big‐sized trees but via decreasing remaining trees. Hence, we show that the “big‐sized trees effect” overrides the effects of remaining trees attributes and species richness on aboveground biomass in tropical forests. This study also indicates that big‐sized trees may be more susceptible to atmospheric drought. We argue that the effects of big‐sized trees on species richness and aboveground biomass should be tested for better understanding of the ecological mechanisms underlying forest functioning.     

Plant litter feedback and population dynamics in an annual plant,<Emphasis Type="Italic"> Cardamine pensylvanica</Emphasis>

The presence of litter has the potential to alter the population dynamics of plants. In this paper, we explore the effects of litter on population dynamics using a simple experimental laboratory system with populations of the annual crucifer, Cardamine pensylvanica. Using a factorial experiment with four densities and three litter levels, we determined the effect of litter on biomass and plant fecundity, and the life stages responsible for these changes in yield. Although litter had significant effects on seed germination and on seedling survivorship, we show, using a population dynamics model, that these effects were not demographically significant. Rather, the potential effect of litter on population dynamics resulted almost entirely from its effect on biomass. Persistent litter suppressed plant biomass and apparently removed the direct density effect present in the absence of litter. Thus, litter changed the shape of the recruitment curve from slightly humped to asymptotic. In addition to changing the shape of the recruitment curve, litter reduced the carrying capacity of the populations. Thus, the population dynamics model indicated that not all statistically significant responses were dynamically significant. Given the potential complexity of litter effects, simple population models provide a powerful tool for understanding the potential consequences of short-term responses. Received: 8 September 1999 / Accepted: 5 April 2000     

Quantifying the links between land use and population growth rate in a declining farmland bird

Land use is likely to be a key driver of population dynamics of species inhabiting anthropogenic landscapes, such as farmlands. Understanding the relationships between land use and variation in population growth rates is therefore critical for the management of many farmland species. Using 24 years of data of a declining farmland bird in an integrated population model, we examined how spatiotemporal variation in land use (defined as habitats with “Short” and “Tall” ground vegetation during the breeding season) and habitat‐specific demographic parameters relates to variation in population growth taking into account individual movements between habitats. We also evaluated contributions to population growth using transient life table response experiments which gives information on contribution of past variation of parameters and real‐time elasticities which suggests future scenarios to change growth rates. LTRE analyses revealed a clear contribution of Short habitats to the annual variation in population growth rate that was mostly due to fledgling recruitment, whereas there was no evidence for a contribution of Tall habitats. Only 18% of the variation in population growth was explained by the modeled local demography, the remaining variation being explained by apparent immigration (i.e., the residual variation). We discuss potential biological and methodological reasons for high contributions of apparent immigration in open populations. In line with LTRE analysis, real‐time elasticity analysis revealed that demographic parameters linked to Short habitats had a stronger potential to influence population growth rate than those of Tall habitats. Most particularly, an increase of the proportion of Short sites occupied by Old breeders could have a distinct positive impact on population growth. High‐quality Short habitats such as grazed pastures have been declining in southern Sweden. Converting low‐quality to high‐quality habitats could therefore change the present negative population trend of this, and other species with similar habitat requirements.     

Recruitment as a driver of production dynamics in stream-resident brown trout (Salmo trutta)

1. The objective was to assess the role of recruitment as a determinant of the production dynamics of stream-resident brown trout ( Salmo trutta ) across replicate habitats of contrasting quality and population attributes. A total of 128-year-classes (YC) at 12 stream sites were examined along four tributaries of the Rio Esva drainage (northwestern Spain).
2. A meta-comparison revealed that growth, density, mortality and production were essentially site-specific. However, when all data were pooled, recruitment (as a delayed density-dependent process) affected both growth and mortality in a way such that individuals in YC with high recruitment grew less and had higher mortality.
3. The value of total YC production recorded covered the global range of variation in the production of stream salmonids reported in the literature. Linear regressions of log-transformed data revealed that 89.0%, 58.9% and 70.7% of the variation in YC density, biomass and production, respectively, were explained by variations in recruitment.
4. The inclusion of growth and mortality, together with recruitment, into a multiple regression increased the variance explained of the total YC production by 13.3%, from 70.7% to 84.0%.
5. The functional relationships between recruitment and the population attributes elucidated in this study appear to provide a useful tool for management applications, including forecasting population status.     

Snow tussocks, chaos, and the evolution of mast seeding

One hitherto intractable problem in studying mast seeding (synchronous intermittent heavy flowering by a population of perennial plants) is determining the relative roles of weather, plant reserves, and evolutionary selective pressures such as predator satiation. We parameterize a mechanistic resource-based model for mast seeding in Chionochloa pallens (Poaceae) using a long-term individually structured data set. Each plant's energy reserves were reconstructed using annual inputs (growing degree days), outputs (flowering), and a novel regression technique. This allowed the estimation of the parameters that control internal plant resource dynamics, and thereby allowed different models for masting to be tested against each other. Models based only on plant size, season degree days, and/or climatic cues (warm January temperatures) fail to reproduce the pattern of autocovariation in individual flowering and the high levels of flowering synchrony seen in the field. This shows that resource-matching or simple cue-based models cannot account for this example of mast seeding. In contrast, the resource-based model pulsed by a simple climate cue accurately describes both individual-level and population-level aspects of the data. The fitted resource-based model, in the absence of environmental forcing, has chaotic (but often statistically periodic) dynamics. Environmental forcing synchronizes individual reproduction, and the models predict highly variable seed production in close agreement with the data. An evolutionary model shows that the chaotic internal resource dynamics, as predicted by the fitted model, is selectively advantageous provided that adult mortality is low and seeds survive for more than 1 yr, both of which are true for C. pallens. Highly variable masting and chaotic dynamics appear to be advantageous in this case because they reduce seed losses to specialist seed predators, while balancing the costs of missed reproductive events.     

The “deduction” approach: A non-invasive method for estimating secondary production of earthworm communities

Secondary production is an important parameter for the study of population dynamics and energy flow through animal communities. Secondary production of earthworm communities has been determined with the size-frequency and instantaneous growth rate methods, whereby earthworm populations are repeatedly sampled at regular intervals and the change in biomass of cohorts or individuals between sampling dates is determined. The major disadvantage of repeated sampling is that it disturbs the soil and permanently removes earthworms from the study area. The “deduction” approach is a theoretical model that partitions individuals into defined pools and makes assumptions about the growth, recruitment and mortality of each pool. In 2004 and 2005, earthworms were added to undisturbed field enclosures and the “deduction” approach was used to estimate secondary production of the indigenous and added earthworm populations during the crop growing period (17–18 weeks) in each year. Secondary production estimates made by the “deduction” approach were similar to estimates from direct earthworm sampling in temperate agroecosystems. The “deduction” approach is an indirect method that estimates population dynamics and secondary production, and is appropriate for manipulation experiments where removal of organisms and physical disturbance of the habitat by repeated sampling could bias results.     

Islands of water in a sea of dry land: hydrological regime predicts genetic diversity and dispersal in a widespread fish from Australia's arid zone, the golden perch (Macquaria ambigua)

Rivers provide an excellent system to study interactions between patterns of biodiversity structure and ecological processes. In these environments, gene flow is restricted by the spatial hierarchy and temporal variation of connectivity within the drainage network. In the Australian arid zone, this variability is high and rivers often exist as isolated waterholes connected during unpredictable floods. These conditions cause boom/bust cycles in the population dynamics of taxa, but their influence on spatial genetic diversity is largely unknown. We used a landscape genetics approach to assess the effect of hydrological variability on gene flow, spatial population structure and genetic diversity in an Australian freshwater fish, Macquaria ambigua. Our analysis is based on microsatellite data of 590 samples from 26 locations across the species range. Despite temporal isolation of populations, the species showed surprisingly high rates of dispersal, with population genetic structure only evident among major drainage basins. Within drainages, hydrological variability was a strong predictor of genetic diversity, being positively correlated with spring-time flow volume. We propose that increases in flow volume during spring stimulate recruitment booms and dispersal, boosting population size and genetic diversity. Although it is uncertain how the hydrological regime in arid Australia may change under future climate scenarios, management strategies for arid-zone fishes should mitigate barriers to dispersal and alterations to the natural flow regime to maintain connectivity and the species' evolutionary potential. This study contributes to our understanding of the influence of spatial and temporal heterogeneity on population and landscape processes.     

Habitat aging and degradation in terrestrialized floodplains: a need to rejuvenate processes for sustaining freshwater mussel populations

Progressive floodplain terrestrialization leads to the deterioration of floodplain ecosystems. Although the importance of hydrological connectivity between floodplain habitats and river channels for floodplain-dependent organisms has been emphasized, less attention has been paid to the temporal relationship between habitat degradation and aquatic organisms. In this study, we examined temporal changes in mussel population structures and the hydrological connectivity of pond-like floodplain water bodies (FWBs) in the terrestrialized floodplains of a lowland river in Japan. We tested the hypothesis that FWB habitats for mussels degrade over time, while newly formed FWBs contribute to providing recruitment sites for mussels. The habitat age for 53 FWBs was determined as of 2018, using historical aerial photographs. Inundation frequency, mussel abundance, and size structures (shell length) were also investigated in the FWBs in 2007 and 2018. Mussel abundance decreased with FWB aging (6–36 years), which coincided with a decrease in inundation frequency. In most existing FWBs, mussel abundance in all size classes decreased over the decade (2007–2018). In contrast, small individuals occurred in the newly formed FWBs at age 6, and in the existing FWBs where inundation frequency slightly increased over the decade (2007–2018), such FWBs were rare. In conclusion, the “young” and “rejuvenated” FWBs were found to be critically important for the recruitment and persistence of mussel populations. This suggests that the floodplain management strategy of “cyclic floodplain rejuvenation” could be applicable for mussel conservation in terrestrialized floodplains of lowland rivers.     

AN “ENVIRO‐INFORMATIC” ASSESSMENT OF SAGINAW BAY (LAKE HURON,USA) PHYTOPLANKTON: DATA‐DRIVEN CHARACTERIZATION AND MODELING OF MICROCYSTIS (CYANOPHYTA)1

Phytoplankton and Microcystis aeruginosa (Kütz.) Kütz. biovolumes were characterized and modeled, respectively, with regard to hydrological and meteorological variables during zebra mussel invasion in Saginaw Bay (1990–1996). Total phytoplankton and Microcystis biomass within the inner bay were one and one‐half and six times greater, respectively, than those of the outer bay. Following mussel invasion, mean total biomass in the inner bay decreased 84% but then returned to its approximate initial value. Microcystis was not present in the bay during 1990 and 1991 and thereafter occurred at/in 52% of sample sites/dates with the greatest biomass occurring in 1994–1996 and within months having water temperatures >19°C. With an overall relative biomass of 0.03 ± 0.01 (mean + SE), Microcystis had, at best, a marginal impact upon holistic compositional dynamics. Dynamics of the centric diatom Cyclotella ocellata Pant. and large pennate diatoms dominated compositional dissimilarities both inter‐ and intra‐annually. The environmental variables that corresponded with phytoplankton distributions were similar for the inner and outer bays, and together identified physical forcing and biotic utilization of nutrients as determinants of system‐level biomass patterns. Nonparametric models explained 70%–85% of the variability in Microcystis biovolumes and identified maximal biomass to occur at total phosphorus (TP) concentrations ranging from 40 to 45 μg · L^?1. From isometric projections depicting modeled Microcystis/environmental interactions, a TP concentration of <30 μg · L^?1 was identified as a desirable contemporary “target” for management efforts to ameliorate bloom potentials throughout mussel‐impacted bay waters.     

Swimming against the tide: resilience of a riverine turtle to recurrent extreme environmental events

Extreme environmental events (EEEs) are likely to exert deleterious effects on populations. From 1996 to 2012 we studied the nesting dynamics of a riverine population of painted turtles (Chrysemys picta) that experienced seven years with significantly definable spring floods. We used capture–mark–recapture methods to estimate the relationships between more than 5 m and more than 6 m flood events and population parameters. Contrary to expectations, flooding was not associated with annual differences in survival, recruitment or annual population growth rates of the adult female segment of the population. These findings suggest that female C. picta exhibit resiliency to key EEE, which are expected to increase in frequency under climate change.     

Integrated Population Modeling for White-Tailed Deer in Saskatchewan,Canada

Monitoring annual change and long-term trends in population structure and abundance of white-tailed deer (Odocoileus virginianus) is an important but challenging component of their management. Many monitoring programs consist of count-based indices of relative abundance along with a variety of population structure information. Analyzed separately these data can be difficult to interpret because of observation error in the data collection process, missing data, and the lack of an explicit biological model to connect the data streams while accounting for their relative imprecision. We used a Bayesian age-structured integrated population model to integrate data from a fall spotlight survey that produced a count-based index of relative abundance and a volunteer staff and citizen classification survey that generated a fall recruitment index. Both surveys took place from 2003–2018 in the parkland ecoregion of southeast Saskatchewan, Canada. Our approach modeled demographic processes for age-specific (0.5-, 1.5-, ≥2.5-year-old classes) populations and was fit to count and recruitment data via models that allowed for error in the respective observation processes. The Bayesian framework accommodated missing data and allowed aggregation of transects to act as samples from the larger management unit population. The approach provides managers with continuous time series of estimated relative abundance, recruitment rates, and apparent survival rates with full propagation of uncertainty and sharing of information among transects. We used this model to demonstrate winter severity effects on recruitment rates via an interaction between winter snow depth and minimum temperatures. In years with colder than average temperatures and above average snow depth, recruitment was depressed, whereas the negative effect of snow depth reversed in years with above average temperatures. This and other covariate information can be incorporated into the model to test relationships and provide predictions of future population change prior to setting of hunting seasons. Likewise, post hoc analysis of model output allows other hypothesis tests, such as determining the statistical support for whether population status has crossed a management trigger threshold. © 2020 The Wildlife Society.     

An integrated population model sheds light on the complex population dynamics of a unique colonial breeder

Climate models forecast increasing climatic variation and more extreme events, which could increase the variability in animal demographic rates. More variable demographic rates generally lead to lower population growth and can be detrimental to wild populations, especially if the particular demographic rates affected are those to which population growth is most sensitive. We investigated the population dynamics of a metapopulation of 25 colonies of a semi-arid bird species, the sociable weaver Philetairus socius, and how it was influenced by seasonal weather during 1993–2014. We constructed an integrated population model which estimated population sizes similar to observed population counts, and allowed us to estimate annual fecundity and recruitment. Variance in fecundity contributed most to variance in population growth, which showed no trend over time. No weather variables explained overall demographic variation at the population level. However, a separate analysis of the largest colony showed a clear decline with a high extinction probability (0.05 to 0.33) within 5 years after the study period. In this colony, juvenile survival was lower when summers were hot, and adult survival was lower when winters were cold. Rainfall was also negatively correlated with adult survival. These weather effects could be due to increased physiological demands of thermoregulation and rainfall-induced breeding activity. Our results suggest that the dynamics of the population on the whole are buffered against current weather variation, as individual colonies apparently react in different ways. However, if more and increasingly extreme weather events synchronize colony dynamics, they are likely to have negative effects.     

Biodiversity and climate determine the functioning of Neotropical forests

Aim

Tropical forests account for a quarter of the global carbon storage and a third of the terrestrial productivity. Few studies have teased apart the relative importance of environmental factors and forest attributes for ecosystem functioning, especially for the tropics. This study aims to relate aboveground biomass (AGB) and biomass dynamics (i.e., net biomass productivity and its underlying demographic drivers: biomass recruitment, growth and mortality) to forest attributes (tree diversity, community‐mean traits and stand basal area) and environmental conditions (water availability, soil fertility and disturbance).

Location

Neotropics.

Methods

We used data from 26 sites, 201 1‐ha plots and >92,000 trees distributed across the Neotropics. We quantified for each site water availability and soil total exchangeable bases and for each plot three key community‐weighted mean functional traits that are important for biomass stocks and productivity. We used structural equation models to test the hypothesis that all drivers have independent, positive effects on biomass stocks and dynamics.

Results

Of the relationships analysed, vegetation attributes were more frequently associated significantly with biomass stocks and dynamics than environmental conditions (in 67 vs. 33% of the relationships). High climatic water availability increased biomass growth and stocks, light disturbance increased biomass growth, and soil bases had no effect. Rarefied tree species richness had consistent positive relationships with biomass stocks and dynamics, probably because of niche complementarity, but was not related to net biomass productivity. Community‐mean traits were good predictors of biomass stocks and dynamics.

Main conclusions

Water availability has a strong positive effect on biomass stocks and growth, and a future predicted increase in (atmospheric) drought might, therefore, potentially reduce carbon storage. Forest attributes, including species diversity and community‐weighted mean traits, have independent and important relationships with AGB stocks, dynamics and ecosystem functioning, not only in relatively simple temperate systems, but also in structurally complex hyper‐diverse tropical forests.     

Individual heterogeneity in black brant survival and recruitment with implications for harvest dynamics

We examined individual heterogeneity in survival and recruitment of female Pacific black brant (Branta bernicla nigricans) using frailty models adapted to a capture–mark–recapture context. Our main objectives were (1) to quantify levels of heterogeneity and examine factors affecting heterogeneity, and (2) model the effects of individual heterogeneity on harvest dynamics through matrix models. We used 24 years of data on brant marked and recaptured at the Tutakoke River colony, AK. Multievent models were fit as hidden Markov chain using program E‐SURGE with an adequate overdispersion coefficient. Annual survival of individuals marked as goslings was heterogeneous among individuals and year specific with about 0.23 difference in survival between “high” (0.73)‐ and “low” (0.50)‐quality individuals at average survival probability. Adult survival (0.85 ± 0.004) was homogeneous and higher than survival of both groups of juveniles. The annual recruitment probability was heterogeneous for brant >1‐year‐old; 0.56 (±0.21) and 0.31 (±0.03) for high‐ and low‐quality individuals, respectively. Assuming equal clutch sizes for high‐ and low‐quality individuals and that 80% of offspring were in the same quality class as the breeding female resulted in reproductive values about twice as high for high‐quality individuals than low‐quality individual for a given class of individuals producing differential contributions to population growth among groups. Differences in reproductive values greatly increased when we assumed high‐quality individuals had larger clutch sizes. When we assumed that 50% of offspring were in the same quality class as their mothers and clutches were equal, differences in reproductive values between quality classes were greatly reduced or eliminated (breeders [BRs]). We considered several harvest scenarios using the assumption that 80% of offspring were in the same quality class as their mothers. The amount of compensation for harvest mortality declined as the proportion of high‐quality individuals in the harvest increased, as differences in clutch sizes between groups decreased and as the proportion of BRs in the harvest increased. Synthesis and applications. Harvest at the same proportional level of the overall population can result in variable responses in population growth rate when heterogeneity is present in a population. λ was <1.0 under every scenario when harvest rates were >10%, and heterogeneity caused as much as +2% difference in growth rates at the highest levels of proportional harvest for low‐quality individuals and the greatest differences in qualities between classes of individuals, a critical difference for a population with λ near 1.0 such as the brant. We observed less response in overall survival in the presence of heterogeneity because we did not observe heterogeneity in the annual survival of BRs. This analysis provides a comprehensive view of overall compensation at the population level and also constitutes the first example of a survival‐recruitment model with heterogeneity. Individual heterogeneity should be more explicitly considered in harvest management of vertebrates.