Patterns in Greater Sage‐grouse population dynamics correspond with public grazing records at broad scales

Monroe, Adrian P.; Aldridge, Cameron L.; Assal, Timothy J.; Veblen, Kari E.; Pyke, David A.; Casazza, Michael L.

doi:10.1002/eap.1512

Cited by 30 publications

(29 citation statements)

References 65 publications

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“…Although we observed negligible or null effects of SGI‐RGS on bare ground, litter, and herbaceous cover, these and other indicators of rangeland health may respond differently to grazing management treatments in regions differing in climate, vegetation community composition, and evolutionary history of grazing such as the Great Basin (Mack and Thompson ). Recently, Monroe et al () reported population‐level responses of sage‐grouse to timing of grazing interacted with primary productivity in Wyoming, such that negative responses to early season grazing were not evident in highly productive regions. Our finding of a lack of response to variation in grazing management or rest is consistent with this pattern because our study area was productive relative to sage‐grouse habitat in Wyoming.…”

Section: Discussionmentioning

confidence: 99%

Effects of rotational grazing management on nesting greater sage‐grouse

et al. 2017

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Grazing by domestic livestock is a ubiquitous land use in the sagebrush (Artemisia spp.) biome of western North America. Widespread, long-term population declines in greater sage-grouse (Centrocercus urophasianus) have elicited concern about potential negative effects of livestock management practices on sage-grouse populations. We evaluated how recently implemented rotational grazing systems affected sagegrouse nesting habitat quality as part of a large-scale, replicated, natural experiment in central Montana, USA. We used Bayesian methods to assess support for effects of rotational grazing management and rest from grazing on daily survival rates of nearly 500 sage-grouse nests monitored over 6 years, and mixed effects models to test for effects of rotational grazing and rest on vegetation structure. Though nests on rotationally grazed ranches displayed a trend toward greater daily survival rates, the evidence for an effect was weak. There was no evidence that rest from grazing (!12 months) increased daily survival rates. Furthermore, rotational grazing systems and rest had negligible effects on herbaceous vegetation height and cover relative to other grazing strategies used in the study area. Results do not support the hypothesis that rotational grazing systems or rest from grazing increase nest success in the northern Great Plains. Estimated nest success, however, was comparable to range-wide averages, suggesting concealing cover for nests is unlikely to be limiting growth of this population regardless of grazing strategy. In light of these results and recent research questioning reported relationships between grass height and nest survival, maximization of hiding cover may be overemphasized in grazing management guidelines and policies. Rather, our findings suggest a variety of locally appropriate grazing strategies focused on fundamental range health principles may provide adequate habitat quality for nesting sage-grouse. Ó 2017 The Wildlife Society.

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Section: Discussionmentioning

confidence: 99%

Effects of rotational grazing management on nesting greater sage‐grouse

et al. 2017

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“…, Monroe et al. ). In addition to their loss of resolution, average‐based approaches can be biased due to the 0‐bounded, 0‐inflated, non‐normal distribution of density and non‐uniform sampling effort, which may obscure the impact of environmental covariates on the underlying density (Robinson et al.…”

Section: Discussionmentioning

confidence: 98%

“…, Monroe et al. ). In estuarine systems, for example, freshwater flow influences habitat quality and quantity (Robins et al.…”

Section: Introductionmentioning

confidence: 98%

“…Given the central-and often contentiousrole of species conservation in water management, the decisions, policies, and legislation that underpin water allocation necessitate a contemporary, quantitative, and ecologically relevant understanding of the species being protected to optimally balance human and ecosystem demands (Pressey et al 2007, Yen et al 2013. Of particular significance in matching species conservation and resource use is the mobility and resulting spatiotemporal distribution of the target population (Guisan andThuiller 2005, Pressey et al 2007), which influence how management actions affect species abundances and may be leveraged to mitigate negative impacts of use (Arthington and Balcombe 2011, Bond et al 2015, Monroe et al 2017. In estuarine systems, for example, freshwater flow influences habitat quality and quantity (Robins et al 2005) and flow regimes can often be managed in near realtime through controlled water releases from reservoirs and modification of water diversions (Alber 2002, Ren€ of€ alt et al 2010.…”

Section: Introductionmentioning

confidence: 99%

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Prey availability, environmental constraints, and aggregation dictate population distribution of an imperiled fish

Simonis¹,

Merz

2019

Ecosphere

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Accelerated global loss of fish species underscores an urgent need to elucidate constraints on spatial and temporal population patterns and to mitigate human‐mediated impacts accordingly. We analyzed 20 yr of trawl data using a spatiotemporally explicit, hierarchically Bayesian model to define density distributions of an imperiled anadromous fish—the delta smelt, Hypomesus transpacificus—in the heavily modified and highly used San Francisco Estuary. To reduce management reliance on an estuary‐wide annual population index that minimizes data resolution and ignores uncertainty, our model took a spatiotemporal approach and explicitly accounted for sampling and observation variation through both stochastic and deterministic elements. Our model demonstrated that juvenile smelt density has decreased over annual time and displays a distinct seasonal pattern (the combination of growth into the sampled size class, mortality, and movement into and out of the sampling frame) of increases in March–June followed by decreases in June–August. Smelt density was highly spatiotemporally autocorrelated and strongly tracked prey availability yet was also constrained by local hydrological factors (salinity, turbidity, velocity). Specifically, juvenile smelt preferred slightly saline, turbid, generally slow‐moving water with ample copepod prey. However, poor swimming capabilities reduced the capacity of juvenile smelt to mix throughout the estuary and find optimal habitat, emphasizing the importance of accounting for spatiotemporal autocorrelation in species distribution models. Further, whole‐estuary outflow appeared to influence the spatial distribution of covariates and juvenile smelt, such that smelt densities tended to peak closer to the marine zone at a lower maximal value when outflow was high. The predictions of our model accurately matched observed patterns of juvenile delta smelt catch while embracing uncertainty (although the predictions tended to exaggerate the total smelt catch variation via over‐predicted tail values). These results highlight that data‐driven improvements can be made to the analytical methods currently used to guide delta smelt management and lay the groundwork for mitigating the impacts of water use, flow regimes, habitat alteration, and climate change on an endangered species in a highly impacted and economically consequential habitat.

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“…Although we simulated constant rates of annual lek attendance (p s ) across leks and years, attendance may vary systematically and could bias trend estimates from lek counts (Blomberg et al 2013). For example, density dependence was previously estimated using peak counts (Garton et al 2011, Monroe et al 2017, Edmunds et al 2018), but attendance also may be density-dependent (Blomberg et al 2013) and could confound estimates of density dependence ink. Similarly, cumulative winter precipitation influences soil moisture and productivity of semi-arid ecosystems dominated by sagebrush (Artemisia spp.…”

Section: Discussionmentioning

confidence: 99%

The importance of simulation assumptions when evaluating detectability in population models

et al. 2019

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Population monitoring is important for investigating a variety of ecological questions, and N‐mixture models are increasingly used to model population size (N) and trends (λ) while estimating detectability (p) from repeated counts within primary periods (when populations are closed to changes). Extending these models to dynamic processes with serial dependence across primary periods may relax the closure assumption, but simulations to evaluate models and inform effort (e.g., number of repeated counts) typically assume p is constant or random across sites and years. Thus, it is unknown how these models perform under scenarios where trends in p confound inferences on N and λ, and conclusions regarding effort may be overoptimistic. Here, we used global positioning system data from greater sage‐grouse (Centrocercus urophasianus) to inform simulations of the detection process for lek counts of this species, and we created scenarios with and without linear annual trends in p. We then compared estimates of N and λ from hierarchical population models either fit with single maximum counts or with detectability estimated from repeated counts (dynamic N‐mixture models). We also explored using auxiliary data to correct counts for variation in detectability. Uncorrected count models consistently underestimated N by >50%, whereas N‐mixture models without auxiliary data underestimated N to a lesser degree due to unmodeled heterogeneity in p such as age. Nevertheless, estimates of λ from both types of models were unbiased and similar for scenarios without trends in p. When p declined systematically across years, uncorrected count models underestimated λ, whereas N‐mixture models estimated λ with little bias when all sites were counted repeatedly. Auxiliary data also reduced bias in parameter estimates. Evaluating population models using scenarios with systematic variation in p may better reveal potential biases and inform effort than simulations that assume p is constant or random. Dynamic N‐mixture models can distinguish between trends in p and N, but also require repeated counts within primary periods for accurate estimates. Auxiliary data may be useful when researchers lack repeated counts, wish to monitor more sites less intensively, or require unbiased estimates of N.

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Patterns in Greater Sage‐grouse population dynamics correspond with public grazing records at broad scales

Cited by 30 publications

References 65 publications

Effects of rotational grazing management on nesting greater sage‐grouse

Effects of rotational grazing management on nesting greater sage‐grouse

Prey availability, environmental constraints, and aggregation dictate population distribution of an imperiled fish

The importance of simulation assumptions when evaluating detectability in population models

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