The broken window: An algorithm for quantifying and characterizing misleading trajectories in ecological processes

Bahlai, Christie A.; White, Easton R.; Perrone, Julia; Cusser, Sarah; Whitney, Kaitlin Stack

doi:10.1016/j.ecoinf.2021.101336

Cited by 10 publications

(16 citation statements)

References 40 publications

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“…In addition, since the four source datasets have different taxonomic scopes or different spatial scales, we expect that residual variance (𝜎 2 ) will be strongly structured by the source dataset. Finally, the baseline year also affects the number of abundance estimates in time series, which is expected to affect the stochasticity of abundance trends (Bahlai et al 2021). We modelled the dependence of variance of the residuals (σ²) on standard error associated to abundance trends of truncated time serie j (𝐴𝑇 𝑗 ), on source dataset s and on the number of years with data in each truncated time series (ny):…”

Section: Evaluating the Importance Of The Effect Of Baseline Year In ...mentioning

confidence: 99%

Controversy over the decline of arthropods: a matter of temporal baseline?

Duchenne

Mihoub

Loïs

et al. 2022

Preprint

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Recently, a number of studies have reported somewhat contradictory patterns of temporal trends in arthropod abundance, from decline to increase. Arthropods often exhibit non-monotonous abundance variations over time, making it important to account for temporal coverage in interpretation of abundance trends, which is often overlooked in statistical analysis. Combining four recently analysed datasets that led to contrasting outcomes, we first show that temporal abundance variations of arthropods are non-monotonous. Using simulations, we show non-monotony is likely to bias estimated linear abundance trends. Finally, analysing empirical data, we show that heterogeneity in estimated abundance trends is significantly related to the variation in temporal baseline of analysed time series. Once differences in baseline years, habitats and continents are accounted for, we do not find any statistical difference in estimated linear abundance trends among the four datasets. We also show that short time series produce more stochastic abundance trends than long series, making the dearth of old and long-term time series a strong limitation in the assessment of temporal trends in arthropod abundance. The lack of time series with a baseline year anterior to global change acceleration is likely to lead to an underestimation of global change effects on biodiversity.

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Section: Evaluating the Importance Of The Effect Of Baseline Year In ...mentioning

confidence: 99%

Controversy over the decline of arthropods: a matter of temporal baseline?

Duchenne

Mihoub

Loïs

et al. 2022

Preprint

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“…To analyze the stability of the abundance trends of these datasets, we used the 'broken window' algorithm (Bahlai et al 2021) using RStudio and R statistical software (RStudio Team, 2020;R Core Team, 2020). This non-random resampling approach uses subsamples (i.e.…”

Section: Moving Window Analysismentioning

confidence: 99%

“…This non-random resampling approach uses subsamples (i.e. 'windows') of the time series data to gain insights into patterns of how data behaves in arbitrarily selected time periods (Bahlai et al 2021). Non-random resampling of existing monitoring data is a powerful and underused tool to understand trends (White and Bahlai 2021).…”

Section: Moving Window Analysismentioning

confidence: 99%

“…We then ran a 'moving window' function in the algorithm, which iterates through all subsets in the data greater than 2 years, and subjects each 'window' to a linear model, which calculates the slope statistic (change of standardized density over change in year), standard error of this slope, p-value, and R 2 . Then we ran the 'stability time' function in the same package to calculate the number of years to reach stability (Bahlai et al, 2021). The number of years to reach stability is calculated in the function by using the summary statistics previously calculated for each dataset to compute the proportion correct for each window within the standard deviation of the longest slope, and returns the number of windows whose slope are within said standard deviation (95% CI).…”

Section: Moving Window Analysismentioning

confidence: 99%

“…This is especially important as climatic conditions and ecosystems change in stark and unpredictable ways, requiring scientists to tease apart drivers of population and community trends from the past to understand possible futures (Bahlai et al, 2021). Many biological and field studies are short term and limited in scope, leading to concerns about how to interpret the many short-term studies in comparison with the relatively fewer long term ecological studies (Wauchope et al, 2019;Bahlai et al, 2021). Shorter term studies increase the likelihood of finding misleading trends, potentially leading to misinformed management approaches (White and Bahlai, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Longer study length, standardized sampling techniques, and broader geographic scope leads to higher likelihood of detecting stable abundance patterns in long term black-legged tick studies

Christie

Whitney

Perrone

et al. 2021

Preprint

Self Cite

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Ixodes scapularis (deer ticks) are a taxon of ecological and human health concern due to their status as primary vectors of Borrelia burgdorferi, the bacteria that transmits Lyme disease. Deer ticks are thought to be expanding in geographic range and population size across the eastern US, leading to concern that tick-vectored illness will correspondingly rise. However, because of wide variability in deer tick monitoring strategies, synthesis efforts may be limited by the sensitivity and reliability of data produced by existing long term studies, especially to inform forecasting and proactive deer tick management. To address this, we explicitly examined the role of how study design parameters affect the likelihood of observing temporal trends in deer tick studies. We used a moving window approach to investigate the temporal stability of deer tick population trajectories across the US. We found several study factors can have an impact on the likelihood of a study reaching stability and the likelihood of tick abundance data leading to misleading results if the study does not reach stability. Our results underscore the need for longer studies of deer ticks when trying to assess long term or broad spatial patterns. Moreover, our results showcase the importance of study length, sampling technique, life stage, and geographic scope in shaping the inferences from deer tick studies. This is especially important for synthesizing across the variety of existing surveys and for potential ecological forecasting.

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Microgeographic variation in demography and thermal regimes stabilize regional abundance of a widespread freshwater fish

Gallagher,

Fraser

2023

Ecological Applications

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Predicting the persistence of species under climate change is an increasingly important objective in ecological research and management. However, biotic and abiotic heterogeneity can drive asynchrony in population responses at small spatial scales, complicating species‐level assessments. For widely distributed species consisting of many fragmented populations, such as brook trout (Salvelinus fontinalis), understanding the drivers of asynchrony in population dynamics can improve the predictions of range‐wide climate impacts. We analyzed the demographic time series from mark–recapture surveys of 11 natural brook trout populations in eastern Canada over 13 years to examine the extent, drivers, and consequences of fine‐scale population variation. The focal populations were genetically differentiated, occupied a small area (~25 km2) with few human impacts, and experienced similar climate conditions. Recruitment was highly asynchronous, weakly related to climate variables and showed population‐specific relationships with other demographic processes, generating diverse population dynamics. In contrast, individual growth was mostly synchronized among populations and driven by a shared positive relationship with stream temperature. Outputs from population‐specific models were unrelated to four of the five hypothesized drivers (recruitment, growth, reproductive success, phylogenetic distance), but variation in groundwater inputs strongly influenced stream temperature regimes and stock–recruitment relationships. Finally, population asynchrony generated a portfolio effect that stabilized regional species abundance. Our results demonstrated that population demographics and habitat diversity at microgeographic scales can play a significant role in moderating species responses to climate change. Moreover, we suggest that the absence of human activities within study streams preserved natural habitat variation and contributed to asynchrony in brook trout abundance, while the small study area eased monitoring and increased the likelihood of detecting asynchrony. Therefore, anthropogenic habitat degradation, landscape context, and spatial scale must be considered when developing management strategies to monitor and maintain populations that are diverse, stable, and resilient to climate change.

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The broken window: An algorithm for quantifying and characterizing misleading trajectories in ecological processes

Cited by 10 publications

References 40 publications

Controversy over the decline of arthropods: a matter of temporal baseline?

Controversy over the decline of arthropods: a matter of temporal baseline?

Longer study length, standardized sampling techniques, and broader geographic scope leads to higher likelihood of detecting stable abundance patterns in long term black-legged tick studies

Microgeographic variation in demography and thermal regimes stabilize regional abundance of a widespread freshwater fish

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