ALBERT

Description: Fire plays an important role in structuring vegetation in fire-prone regions worldwide. Progress has been made towards documenting the effects of individual fire events and fire regimes on vegetation structure; less is known of how different fire history attributes (e.g., time-since-fire, fire frequency) interact to affect vegetation. Using the temperate eucalypt ‘foothill’ forests of south-eastern Australia as a case-study system, we examine two hypotheses about such interactions: 1) that post-fire vegetation succession (e.g., time-since-fire effects) is influenced by other fire regime attributes, and 2) that the severity of the most recent fire overrides the effect of preceding fires on vegetation structure. Empirical data on vegetation structure were collected from 540 sites distributed across central and eastern Victoria, Australia. Linear mixed models were used to examine these hypotheses, and determine the relative influence of fire and environmental attributes on vegetation structure. Fire history measures, particularly time-since-fire, affected several vegetation attributes including ground and canopy strata; others such as low and sub-canopy vegetation were more strongly influenced by environmental characteristics like rainfall. There was little support for the hypothesis that post-fire succession is influenced by fire history attributes other than time-since-fire: only canopy regeneration was influenced by another variable (‘fire type’, representing severity). Our capacity to detect an overriding effect of the severity of the most recent fire was limited by a consistently weak effect of preceding fires on vegetation structure. Overall, results suggest the primary way that fire affects vegetation structure in foothill forests is via attributes of the most recent fire, both its severity and time since its occurrence: other attributes of fire regimes (e.g., fire interval, frequency) have less influence. The strong effect of environmental drivers such as rainfall and topography on many structural features show that foothill forest vegetation is also influenced by factors outside human control. While fire is amenable to human management, results suggest that at broad scales, structural attributes of these forests are relatively resilient to the effects of current fire regimes. Nonetheless, the potential for more frequent severe fires at short intervals, associated with a changing climate and/or fire management, warrant further consideration. This article is protected by copyright. All rights reserved.

Description: Integral projection models (IPMs) have a number of advantages over matrix-model approaches for analyzing size-structured population dynamics, because the latter require parameter estimates for each age or stage transition. However, IPMs still require appropriate data. Typically they are parameterized using individual-scale relationships between body size and demographic rates, but these are not always available. Here we present an alternative approach for estimating demographic parameters from time series of size-structured survey data using a Bayesian state-space IPM (SSIPM). By fitting an IPM in a state-space framework, we estimate unknown parameters and explicitly account for process and measurement error in a dataset to estimate the underlying process model dynamics. We tested our method by fitting SSIPMs to simulated data; the model fit the simulated size distributions well and estimated unknown demographic parameters accurately. We then illustrated our method using 9 years of annual surveys of the density and size distribution of two fish species (blue rockfish, Sebastes mystinus , and gopher rockfish, S. carnatus ) at seven kelp forest sites in California. The SSIPM produced reasonable fits to the data, and estimated fishing rates for both species that were higher than our Bayesian prior estimates based on coast-wide stock assessment estimates of harvest. That improvement reinforces the value of being able to estimate demographic parameters from local-scale monitoring data. We highlight a number of key decision points in SSIPM development (e.g., open vs. closed demography, number of particles in the state-space filter) so that users can apply the method to their own datasets. This article is protected by copyright. All rights reserved.

Description: Extensive outbreaks of bark beetles have killed trees across millions of hectares of forests and woodlands in western North America. These outbreaks have led to spirited scientific, public and policy debates about consequential increases in fire risk, especially in the wildland-urban interface (WUI), where homes and communities are at particular risk from wildfires. At the same time, large wildfires have become more frequent across this region. Widespread expectations that outbreaks increase extent, severity and/or frequency of wildfires are based partly on visible and dramatic changes in foliar moisture content and other fuel properties following outbreaks, as well as associated modeling projections. A competing explanation is that increasing wildfires are driven primarily by climatic extremes, which are becoming more common with climate change. However, the relative importance of bark beetle outbreaks versus climate on fire occurrence has not been empirically examined across very large areas and remains poorly understood. The most extensive outbreaks of tree-killing insects across the western United States have been of mountain pine beetle (MPB; Dendroctonus ponderosae ), which have killed trees over 〉 650,000 km 2 , mostly in forests dominated by lodgepole pine ( Pinus contorta ). Here we show that outbreaks of MPB in lodgepole pine forests of the western United States have been less important than climatic variability for the occurrence of large fires over the past 29 years. In lodgepole pine forests in general, as well as those in the WUI, occurrence of large fires was determined primarily by current and antecedent high temperatures and low precipitation but was unaffected by preceding outbreaks. Trends of increasing co-occurrence of wildfires and outbreaks are due to a common climatic driver rather than interactions between these disturbances. Reducing wildfire risk hinges on addressing the underlying climatic drivers, rather than treating beetle-affected forests. This article is protected by copyright. All rights reserved.

Description: Extensive mortality of whitebark pine, beginning in the early to mid-2000s, occurred in the Greater Yellowstone Ecosystem (GYE) of the western US, primarily from mountain pine beetle but also from other threats such as white pine blister rust. The climatic drivers of this recent mortality and the potential for future whitebark pine mortality from mountain pine beetle are not well understood, yet are important considerations in whether to list whitebark pine as a threatened or endangered species. We sought to increase the understanding of climate influences on mountain pine beetle outbreaks in whitebark pine forests, which are less well understood than in lodgepole pine, by quantifying climate-beetle relationships, analyzing climate influences during the recent outbreak, and estimating the suitability of future climate for beetle outbreaks. We developed a statistical model of the probability of whitebark pine mortality in the GYE that included temperature effects on beetle development and survival, precipitation effects on host tree condition, beetle population size, and stand characteristics. Estimated probability of whitebark pine mortality increased with higher winter minimum temperature, indicating greater beetle winter survival; higher fall temperature, indicating synchronous beetle emergence; lower two-year summer precipitation, indicating increased potential for host tree stress; increasing beetle populations; stand age; and increasing percent composition of whitebark pine within a stand. The recent outbreak occurred during a period of higher-than-normal regional winter temperatures, suitable fall temperatures, and low summer precipitation. In contrast to lodgepole pine systems, area with mortality was linked to precipitation variability even at high beetle populations. Projections from climate models indicate future climate conditions will likely provide favorable conditions for beetle outbreaks within nearly all current whitebark pine habitat in the GYE by the middle of this century. Therefore, when surviving and regenerating trees reach ages suitable for beetle attack, there is strong potential for continued whitebark pine mortality due to mountain pine beetle. This article is protected by copyright. All rights reserved.

Description: The prediction of mosquito abundance is of central interest in addressing mosquito population dynamics and in forecasting the associated emerging and re-emerging diseases. However, little work has focused on the systematic evaluation of how well adult mosquito abundance can be predicted as a function of observational resolutions, aggregation scales, and prediction lead time. Here we use a state space reconstruction (SSR) approach to compare the predictability of mosquito population dynamics at weekly, biweekly, and monthly scales. We focus on the analysis of Aedes vexans and Culiseta melanura populations monitored in Brunswick County (NC – USA) and find that prediction over a 7-day lead time is improved when daily observations are used, compared to the commonly used once-per-week sample. Our results demonstrate that daily observations of mosquito abundance contribute to improving mosquito predictability in two ways: (1) daily observations better capture fluctuations over short time scales, which are missed when sampling at coarser resolutions, (2) the aggregation of daily abundance observations reduces the impact of noise, thereby increasing the predictability of mosquito population dynamics as the aggregation scale is increased. We show that the evaluation of population dynamical models based on observed and predicted abundance can lead to a spuriously high apparent performance, due to the high auto-correlation in the observations used to update the model state at each successive time step. We show that the comparison of predicted and observed population change, expressed through per capita growth rates, leads to a more informative performance measure. This article is protected by copyright. All rights reserved.

Description: Climate conditions, such as temperature or precipitation averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous U.S., and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability versus 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species’ potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs. This article is protected by copyright. All rights reserved.

Description: Increases in natural or non-crop habitat surrounding agricultural fields have been shown to be correlated with declines in insect crop pests. However, these patterns are highly variable across studies suggesting other important factors, such as abiotic drivers, which are rarely included in landscape models, may also contribute to variability in insect population abundance. The objective of this study was to explicitly account for the contribution of temperature and precipitation, in addition to landscape composition, on the abundance of a widespread insect crop pest, the soybean aphid ( Aphis glycines Matsumura), in Wisconsin soybean fields. We hypothesized that higher soybean aphid abundance would be associated with higher heat accumulation (e.g., growing degree days), and increasing non-crop habitat in the surrounding landscape, due to the presence of the overwintering primary hosts of soybean aphid. To evaluate these hypotheses, we used an ecoinformatics approach that relied on a large dataset collected across Wisconsin over a 9-year period (2003 – 2011), for an average of 235 sites per year (n=2,110 fields total). We determined surrounding landscape composition (1.5-km radius) using publicly available satellite-derived land cover imagery and interpolated daily temperature and precipitation information from the National Weather Service COOP weather station network. We constructed linear mixed models for soybean aphid abundance based on abiotic and landscape explanatory variables and applied model averaging for prediction using an information theoretic framework. Over this broad spatial and temporal extent in Wisconsin, we found that variation in growing season precipitation was positively related to soybean aphid abundance, while higher precipitation during the non-growing season had a negative effect on aphid populations. Additionally, we found that aphid populations were higher in areas with proportionally more forest, but were lower in areas where minor crops, such as small grains, were more prevalent. Thus, our findings support our hypothesis that including abiotic drivers increases our understanding of crop pest abundance and distribution. Moreover, by explicitly modeling abiotic factors, we may be able to explore how variable climate in tandem with land cover patterns may affect current and future insect populations, with potentially critical implications for crop yields and agricultural food webs. This article is protected by copyright. All rights reserved.

Description: Predator-prey interactions shape ecosystem structure and function, potentially limiting the productivity of valuable species. Simultaneously, stochastic environmental forcing affects species productivity, often through unknown mechanisms. The interacting effects of trophic and environmental conditions complicate management of exploited ecosystems and have motivated calls for more holistic management via ecosystem-based approaches, yet the limitations to these approaches are not widely appreciated. The Chignik salmon fishery in Alaska is managed to achieve maximum sustainable yield for sockeye salmon, though research suggests that predation by less economically valuable, and thus not targeted, coho salmon during juvenile rearing limits the productivity of sockeye salmon. We examined the relationship between historical sockeye salmon recruitment and coho salmon abundance observed in the Chignik system and could not detect a clear effect of coho salmon abundance on sockeye salmon productivity, given existing data. Using simulation models, we examined the probability of detecting a known predation effect on sockeye salmon recruitment in the presence of observation error in coho salmon abundance and stochasticity in sockeye salmon recruitment. Increased recruitment stochasticity reduced the ability to detect predator effects in recruitment, an effect further strengthened when low frequency environmental variation was added to the system. Further, increased observation error biased estimates of predator effects towards zero. Thus, in systems with high observation error on predator abundances, estimates of predation effects will be substantially weaker than true effects. We examined the effects of stochasticity on the ability of an adaptive management program to learn about ecosystem structure and detect an effect of management actions intended to release a prey species from its predators. Simulation models revealed that even under scenarios of large predation effects on sockeye salmon, stochastic recruitment masked detection of an effect of increased coho salmon harvest for nearly a decade. These results highlight the challenges inherent in ecosystem-based management of predator-prey systems due to mismatched time-scales of ecosystem dynamics and the willingness of stakeholders to risk losses in order to test uncertain hypotheses. It is critical for stakeholders considering EBFM and adaptive management strategies to be aware of the potential timelines of perceiving ecosystem change. This article is protected by copyright. All rights reserved.

Description: Timber harvest can adversely affect forest biota. Recent research and application suggest that retention of mature forest elements (‘retention forestry’), including unharvested patches (or ‘aggregates’) within larger harvested units, can benefit biodiversity compared to clearcutting. However, it is unclear whether these benefits can be generalized among the diverse taxa and biomes in which retention forestry is practiced. Lack of comparability in methods for sampling and analysing responses to timber harvest and edge creation presents a challenge to synthesis. We used a consistent methodology (similarly spaced plots or traps along transects) to investigate responses of vascular plants and ground-active beetles to aggregated retention at replicate sites in each of four temperate and boreal forest types on three continents: Douglas-fir forests in Washington, USA; aspen forests in Minnesota, USA; spruce forests in Sweden; and wet eucalypt forests in Tasmania, Australia. We assessed (i) differences in local (plot-scale) species richness and composition between mature (intact) and regenerating (previously harvested) forest; (ii) the lifeboating function of aggregates (capacity to retain species of unharvested forest); and whether intact forests and aggregates (iii) are susceptible to edge effects and (iv) influence the adjacent regenerating forest. Intact and harvested forests differed in composition but not richness of plants and beetles. The magnitude of this difference was generally similar among regions, but there was considerable heterogeneity of composition within and among replicate sites. Aggregates within harvest units were effective at lifeboating for both plant and beetle communities. Edge effects were uncommon even within the aggregates. In contrast, effects of forest influence on adjacent harvested areas were common and as strong for aggregates as for larger blocks of intact forest. Our results provide strong support for the widespread application of aggregated retention in boreal and temperate forests. The consistency of pattern in four very different regions of the world suggests that, for forest plants and beetles, responses to aggregated retention are likely to apply more widely. Our results suggest that through strategic placement of aggregates, it is possible to maintain the natural heterogeneity and biodiversity of mature forests managed for multiple objectives. This article is protected by copyright. All rights reserved.

Description: Distributions of foliar nutrients across forest canopies can give insight into their plant functional diversity and improve our understanding of biogeochemical cycling. We used airborne remote sensing and Partial Least Squares Regression (PLSR) to quantify canopy foliar nitrogen (N) across ~164 km 2 of wet lowland tropical forest in the Osa Peninsula, Costa Rica. We determined the relative influence of climate and topography on the observed patterns of canopy foliar N using a gradient boosting model (GBM) technique. At a local scale, where climate and substrate where constant, we explored the influence of slope position on canopy N by quantifying canopy N on remnant terraces, their adjacent slopes and knife edged ridges. In addition, we climbed and sampled 540 trees and analyzed foliar N in order to quantify the role of species identity (phylogeny) and environmental factors in predicting canopy N. Observed canopy N heterogeneity reflected environmental factors working at multiple spatial scales. Across the larger landscape, elevation and precipitation had the highest relative influence on predicting canopy foliar N (30 and 24%), followed by soils (15%), site exposure (9%), compound topographic index (8%), substrate (6%), and landscape dissection (6%). Phylogeny explained ~75% of the variation in the filed collected foliar N data, suggesting that phylogeny largely underpins the response to the environmental factors. Taken together, these data suggest that a large fraction of the variance in canopy N across the landscape is proximately driven by species composition, though ultimately this is likely a response to abiotic factors such as climate and topography. Future work should focus on the mechanisms and feedbacks involved, and how shifts in climate may translate to changes in forest function. This article is protected by copyright. All rights reserved.