Showing papers in "Ecological Monographs in 2021"

A guide to state-space modeling of ecological time series

Abstract: State–space models (SSMs) are an important modeling framework for analyzing ecological time series. These hierarchical models are commonly used to model population dynamics, animal movement, and capture–recapture data, and are now increasingly being used to model other ecological processes. SSMs are popular because they are flexible and they model the natural variation in ecological processes separately from observation error. Their flexibility allows ecologists to model continuous, count, binary, and categorical data with linear or nonlinear processes that evolve in discrete or continuous time. Modeling the two sources of stochasticity separately allows researchers to differentiate between biological variation and imprecision in the sampling methodology, and generally provides better estimates of the ecological quantities of interest than if only one source of stochasticity is directly modeled. Since the introduction of SSMs, a broad range of fitting procedures have been proposed. However, the variety and complexity of these procedures can limit the ability of ecologists to formulate and fit their own SSMs. We provide the knowledge for ecologists to create SSMs that are robust to common, and often hidden, estimation problems, and the model selection and validation tools that can help them assess how well their models fit their data. We present a review of SSMs that will provide a strong foundation to ecologists interested in learning about SSMs, introduce new tools to veteran SSM users, and highlight promising research directions for statisticians interested in ecological applications. The review is accompanied by an in-depth tutorial that demonstrates how SSMs can be fitted and validated in R. Together, the review and tutorial present an introduction to SSMs that will help ecologists to formulate, fit, and validate their models.

Influence of climate, soil, and land cover on plant species distribution in the European Alps

Abstract: Although the importance of edaphic factors and habitat structure for plant growth and survival is known, both are often neglected in favor of climatic drivers when investigating the spatial patterns of plant species and diversity. Yet, especially in mountain ecosystems with complex topography, missing edaphic and habitat components may be detrimental for a sound understanding of biodiversity distribution. Here, we compare the relative importance of climate, soil and land cover variables when predicting the distributions of 2,616 vascular plant species in the European Alps, representing approximately two‐thirds of all European flora. Using presence‐only data, we built point‐process models (PPMs) to relate species observations to different combinations of covariates. We evaluated the PPMs through block cross‐validations and assessed the independent contributions of climate, soil, and land cover covariates to predict plant species distributions using an innovative predictive partitioning approach. We found climate to be the most influential driver of spatial patterns in plant species with a relative influence of ~58.5% across all species, with decreasing importance from low to high elevations. Soil (~20.1%) and land cover (~21.4%), overall, were less influential than climate, but increased in importance along the elevation gradient. Furthermore, land cover showed strong local effects in lowlands, while the contribution of soil stabilized at mid‐elevations. The decreasing influence of climate with elevation is explained by increasing endemism, and the fact that climate becomes more homogeneous as habitat diversity declines at higher altitudes. In contrast, soil predictors were found to follow the opposite trend. Additionally, at low elevations, human‐mediated land cover effects appear to reduce the importance of climate predictors. We conclude that soil and land cover are, like climate, principal drivers of plant species distribution in the European Alps. While disentangling their effects remains a challenge, future studies can benefit markedly by including soil and land cover effects when predicting species distributions.

The promise and the perils of resurveying to understand global change impacts

Abstract: Historical data sets can be useful tools to aid in understanding the impacts of global change on natural ecosystems. Resampling of historically sampled sites (“snapshot resampling”) has often been used to detect long‐term shifts in ecological populations and communities, because it allows researchers to avoid long‐term monitoring costs and investigate a large number of potential trends. But recent simulation‐based research has called the reliability of resampling into question, and its utility has not been comprehensively evaluated. Here we combine long‐term empirical data sets with novel community‐level simulations to explore the accuracy of snapshot resampling of both population‐ and community‐level metrics under a variety of conditions. We show that snapshot resampling often yields spurious conclusions, but the accuracy of results increases when inter‐annual variability in the response variable is low or the magnitude of change through time is high. Snapshot resampling also generally performs better for community‐level metrics (e.g., species richness) as opposed to population‐level metrics pertaining to a single species (e.g., abundance). Finally, we evaluate strategies to improve the accuracy of snapshot resampling, including sampling multiple years at the end of the study, but these produce mixed results. Ultimately, we find that snapshot resampling should be used with caution, but under certain circumstances, can be a useful for understanding long‐term global change impacts.

A critical comparison of integral projection and matrix projection models for demographic analysis

Abstract: Structured demographic models are among the most common and useful tools in population biology. However, the introduction of integral projection models (IPMs) has caused a profound shift in the way many demographic models are conceptualized. Some researchers have argued that IPMs, by explicitly representing demographic processes as continuous functions of state variables such as size, are more statistically efficient, biologically realistic, and accurate than classic matrix projection models, calling into question the usefulness of the many studies based on matrix models. Here, we evaluate how IPMs and matrix models differ, as well as the extent to which these differences matter for estimation of key model outputs, including population growth rates, sensitivity patterns, and life spans. First, we detail the steps in constructing and using each type of model. Second, we present a review of published demographic models, concentrating on size‐based studies, which shows significant overlap in the way IPMs and matrix models are constructed and analyzed. Third, to assess the impact of various modeling decisions on demographic predictions, we ran a series of simulations based on size‐based demographic data sets for five biologically diverse species. We found little evidence that discrete vital rate estimation is less accurate than continuous functions across a wide range of sample sizes or size classes (equivalently bin numbers or mesh points). Most model outputs quickly converged with modest class numbers (≥10), regardless of most other modeling decisions. Another surprising result was that the most commonly used method to discretize growth rates for IPM analyses can introduce substantial error into model outputs. Finally, we show that empirical sample sizes generally matter more than modeling approach for the accuracy of demographic outputs. Based on these results, we provide specific recommendations to those constructing and evaluating structured population models. Both our literature review and simulations question the treatment of IPMs as a clearly distinct modeling approach or one that is inherently more accurate than classic matrix models. Importantly, this suggests that matrix models, representing the vast majority of past demographic analyses available for comparative and conservation work, continue to be useful and important sources of demographic information.

The magnitude, direction, and tempo of forest change in Greater Yellowstone in a warmer world with more fire

Abstract: Author(s): Turner, Monica G; Braziunas, Kristin H; Hansen, Winslow D; Hoecker, Tyler J; Rammer, Werner; Ratajczak, Zak; Westerling, A Leroy; Seidl, Rupert

Energy landscape analysis elucidates the multistability of ecological communities across environmental gradients

Abstract: Compositional multistability is widely observed in multispecies ecological communities. Since differences in community composition often lead to differences in community function, understanding compositional multistability is essential to comprehend the role of biodiversity in maintaining ecosystems. In community assembly studies, it has long been recognized that the order and timing of species migration and extinction influence structure and function of communities. The study of multistability in ecology has focused on the change in dynamical stability across environmental gradients, and was developed mainly for low-dimensional systems. As a result, methodologies for studying the compositional stability of empirical multispecies communities is not well developed. Here, we show that models previously used in ecology can be analyzed from a new perspective the energy landscape to unveil compositional stability of multispecies communities in observational data. To show that our method can be applicable to real-world ecological communities, we simulated the assembly dynamics driven by population level processes, and show that results were mostly robust to different simulation conditions. Our method reliably captured the change of the overall compositional stability of multispecies communities over environmental change, and indicated a small fraction of community compositions that may be a channel for transition between stable states. When applied to mouse gut microbiota, our method showed the presence of two alternative states with change in age, and suggested the multiple mechanism by which aging impairs the compositional stability of the mouse gut microbiota. Our method will be a practical tool to study the compositional stability of multispecies communities in a changing world, and will facilitate empirical studies that integrate the concept of multistability developed in different fields of ecology in the past decades.

Host neighborhood shapes bacterial community assembly and specialization on tree species across a latitudinal gradient

Abstract: Phyllosphere bacterial diversity is shaped through interactions between hosts and microbes. Most studies having focused on pairwise associations between host taxa and their symbionts, little is yet understood about the influence of the host community as a whole in shaping these interactions. Envisioning phyllosphere bacterial communities as a spatially structured network of communities linked by dispersal (i.e., metacommunities) can help us better understand the relative importance of species sorting among host populations and species versus dispersal from the neighboring host community for bacterial community assembly in forest ecosystems. Here we investigate drivers of metacommunity structure of epiphytic bacteria of the phyllosphere among 33 tree host species distributed across a large‐scale transition from deciduous to boreal forest. We expect the identity and traits of hosts to play an important role in determining phyllosphere bacterial composition. We further hypothesize that bacterial dispersal from neighboring host species will modulate the match between a focal host species and its microbiota, and shape opportunities for host specialization of phyllosphere bacteria at local and regional scales. We defined specialization as the level of phylogenetic similarity among hosts that a bacterial symbiont associates with. We found that host taxonomic identity and traits were important drivers of bacterial community turnover and variation in host specialization across the landscape. Dispersal from neighboring communities further played a role in homogenizing bacterial communities. The microbiota of focal hosts such as sugar maple was thus increasingly similar to that of neighboring host species along the transition from deciduous to boreal forest. Specialization of bacterial taxa on sugar maple was further positively correlated with the relative abundance of this host in the landscape, revealing a role for the host community context in shaping evolutionary relationships between phyllosphere bacteria and their tree hosts. These results overall suggest that the dispersal of phyllosphere bacteria from the dominant tree community members may be constraining the match between tree species and their symbionts, particularly at their range limits. We also demonstrate that considering host‐associated microbial communities as part of metacommunities within the host landscape is a promising tool for improving our understanding of host‐symbiont matching.

Ecological and behavioral mechanisms of density-dependent habitat expansion in a recovering African ungulate population

Abstract: Major disturbances can temporarily remove factors that otherwise constrain population abundance and distribution. During such windows of relaxed top-down and/or bottom-up control, ungulate populations can grow rapidly, eventually leading to resource depletion and density-dependent expansion into less-preferred habitats. Although many studies have explored the demographic outcomes and ecological impacts of these processes, fewer have examined the individual-level mechanisms by which they occur. We investigated these mechanisms in Gorongosa National Park, where the Mozambican Civil War devastated largemammal populations between 1977 and 1992. Gorongosa’s recovery has been marked by proliferation of waterbuck (Kobus ellipsiprymnus), an historically marginal 200-kg antelope species, which is now roughly 20-fold more abundant than before the war. We show that after years of unrestricted population growth, waterbuck have depleted food availability in their historically preferred floodplain habitat and have increasingly expanded into historically avoided savanna habitat. This expansion was demographically skewed: mixed-sex groups of prime-age individuals remained more common in the floodplain, while bachelors, loners, and subadults populated the savanna. By coupling DNA metabarcoding and forage analysis, we show that waterbuck in these two habitats ate radically different diets, which were more digestible and protein-rich in the floodplain than in savanna; thus, although individuals in both habitats achieved positive net energy balance, energetic performance was higher in the floodplain. Analysis of daily activity patterns from high-resolution GPS-telemetry, accelerometry, and animal-borne video revealed that savanna waterbuck spent less time eating, perhaps to accommodate their tougher, lower-quality diets. Waterbuck in savanna also had more ectoparasites than those in the floodplain. Thus, plasticity in foraging behavior and diet selection enabled savanna waterbuck to tolerate the costs of density-dependent spillover, at least in the short term; however, the already poorer energetic performance of these individuals implies that savanna occupancy may become prohibitively costly as heterospecific competitors and predators continue to recover in Gorongosa. Our results suggest that behavior can provide a leading indicator of the onset of density-dependent limitation and the likelihood of subsequent population decline, but that reliable inference hinges on understanding the mechanistic basis of observed behavioral shifts. Manuscript received 23 September 2020; revised 30 March 2021; accepted 21 April 2021. Corresponding Editor: Justine A. Becker and Robert M. Pringle. J. A. Becker and M. C. Hutchinson are joint first authors on this work. 13 E-mail: justineabecker@gmail.com and rpringle@princeton.edu Article e01476; page 1 Ecological Monographs, 0(0), 2021, e01476 © 2021 by the Ecological Society of America

Translocation experiment reveals capacity for mountain pine beetle persistence under climate warming

Abstract: Predicting species response to climate change is a central challenge in ecology, particularly for species that inhabit large geographic areas. The mountain pine beetle (MPB) is a significant tree mortality agent in western North America with a distribution limited by climate. Recent warming has caused large-scale MPB population outbreaks within its historical distribution, in addition to migration northward in western Canada. The relative roles of genetic and environmental sources of variation governing MPB capacity to persist in place in a changing climate, and the migratory potential at its southern range edge in the United States, have not been investigated. We reciprocally translocated MPB populations taken from the core and southern edge of their range, and simultaneously translocated both populations to a warmer, low-elevation site near the southern range boundary where MPB activity has historically been absent despite suitable hosts. We found genetic variability and extensive plasticity in multiple fitness traits that would allow both populations to persist in a warming climate that resembles the thermal regime of our low-elevation site. We demonstrate, for the first time, that supercooling points in MPBs are influenced both by genetic and environmental factors. Both populations reproduced with seasonally appropriate univoltine generation times at all translocated sites, and bivoltinism was not observed. The highest reproductive success occurred at the warmest, out-of-range low-elevation site, suggesting that southward migration may not be temperature limited.

Interaction of hydric and thermal conditions drive geographic variation in thermoregulation in a widespread lizard

Abstract: Behavioral thermoregulation is an efficient mechanism to buffer the physiological effects of climate change. Thermal ecology studies have traditionally tested how thermal constraints shape thermoregulatory behaviors without accounting for the potential major effects of landscape structure and water availability. Thus, we lack a general understanding of the multifactorial determinants of thermoregulatory behaviors in natural populations. In this study, we quantified the relative contribution of elevation, thermal gradient, moisture gradient, and landscape structure in explaining geographic variation in thermoregulation strategies of a terrestrial ectotherm species. We measured field-active body temperature, thermal preferences, and operative environmental temperatures to calculate thermoregulation indices, including thermal quality of the habitat and thermoregulation efficiency for a very large sample of common lizards (Zootoca vivipara) from 21 populations over 3 yr across the Massif Central mountain range in France. We used an information-theoretic approach to compare eight a priori thermo-hydroregulation hypotheses predicting how behavioral thermoregulation should respond to environmental conditions. Environmental characteristics exerted little influence on thermal preference with the exception that females from habitats with permanent access to water had lower thermal preferences. Field body temperatures and accuracy of thermoregulation were best predicted by the interaction between air temperature and a moisture index. In mesic environments, field body temperature and thermoregulation accuracy increased with air temperature, but they decreased in drier habitats. Thermoregulation efficiency (difference between thermoregulation inaccuracy and the thermal quality of the habitat) was maximized in cooler and more humid environments and was mostly influenced by the thermal quality of the habitat. Our study highlights complex patterns of variation in thermoregulation strategies, which are mostly explained by the interaction between temperature and water availability, independent of the elevation gradient or thermal heterogeneity. Although changes in landscape structure were expected to be the main driver of extinction rate of temperate zone ectotherms with ongoing global change, we conclude that changes in water availability coupled with rising temperatures might have a drastic impact on the population dynamics of some ectotherm species.

Solving the fourth-corner problem: forecasting ecosystem primary production from spatial multispecies trait-based models

Abstract: The dataset contains environmental (Excel Sheet 1), species counts (Excel Sheet 2), and functional trait (Excel Sheet 3) data collected from the Sundarbans mangrove forest in Bangladesh.

Remotely detected aboveground plant function predicts belowground processes in two prairie diversity experiments

Abstract: Imaging spectroscopy provides the opportunity to incorporate leaf and canopy optical data into ecological studies, but the extent to which remote sensing of vegetation can enhance the study of belowground processes is not well understood. In terrestrial systems, aboveground and belowground vegetation quantity and quality are coupled, and both influence belowground microbial processes and nutrient cycling. We hypothesized that ecosystem productivity, and the chemical, structural and phylogenetic-functional composition of plant communities would be detectable with remote sensing and could be used to predict belowground plant and soil processes in two grassland biodiversity experiments: the BioDIV experiment at Cedar Creek Ecosystem Science Reserve in Minnesota and the Wood River Nature Conservancy experiment in Nebraska. We tested whether aboveground vegetation chemistry and productivity, as detected from airborne sensors, predict soil properties, microbial processes and community composition. Imaging spectroscopy data were used to map aboveground biomass, green vegetation cover, functional traits and phylogenetic-functional community composition of vegetation. We examined the relationships between the image-derived variables and soil carbon and nitrogen concentration, microbial community composition, biomass and extracellular enzyme activity, and soil processes, including net nitrogen mineralization. In the BioDIV experiment—which has low overall diversity and productivity despite high variation in each—belowground processes were driven mainly by variation in the amount of organic matter inputs to soils. As a consequence, soil respiration, microbial biomass and enzyme activity, and fungal and bacterial composition and diversity were significantly predicted by remotely sensed vegetation cover and biomass. In contrast, at Wood River—where plant diversity and productivity were consistently higher—belowground processes were driven mainly by variation in the quality of aboveground inputs to soils. Consequently, remotely sensed functional, chemical and phylogenetic composition of vegetation predicted belowground extracellular enzyme activity, microbial biomass, and net nitrogen mineralization rates but aboveground biomass (or cover) did not. The contrasting associations between the quantity (productivity) and quality (composition) of aboveground inputs with belowground soil attributes provide a basis for using imaging spectroscopy to understand belowground processes across productivity gradients in grassland systems. However, a mechanistic understanding of how above and belowground components interact among different ecosystems remains critical to extending these results broadly.

Multispecies integrated population model reveals bottom-up dynamics in a seabird predator–prey system

Abstract: Assessing the effects of climate and interspecific relationships on communities is challenging because of the complex interplay between species population dynamics, their interactions, and the need to integrate information across several biological levels (individuals – populations – communities). Usually used to quantify species interactions, integrated population models (IPMs) have recently been extended to communities. These models allow fitting multispecies matrix models to data from multiple sources while simultaneously accounting for various sources of uncertainty in each data source. We used multispecies IPMs accommodating climate conditions to quantify the relative contribution of climate vs. interspecific interactions on demographic parameters, such as survival and breeding success, in the dynamics of a predator-prey system. We considered a stage-structured predator–prey system combining 22 years of capture–recapture data and population counts of two seabirds, the Brown Skua (Catharacta lonnbergi) and its main prey the Blue Petrel (Halobaena caerulea) both breeding on the Kerguelen Islands in the Southern Ocean. Our results showed that climate and predator-prey interactions drive the demography of skuas and petrels in different ways. The breeding success of skuas appeared to be largely driven by the number of petrels and to a lesser extent by intraspecific density-dependence. In contrast, there was no evidence of predation effects on the demographic parameters of petrels, which were affected by oceanographic factors (chlorophyll a and sea surface temperature anomalies). We conclude that bottom-up mechanisms are the main drivers of this skua-petrel system. We discuss the mechanisms by which climate variability and predator-prey relationships may affect the demographic parameters of these seabirds. Taking into account both species interactions and environmental covariates in the same analysis improved our understanding of species dynamics.

Targeted predator defenses of sponges shape community organization and tropical marine ecosystem function

Abstract: Defenses that target particular consumers often influence community organization, ecosystem function, and diversity maintenance. In coral reef, mangrove, and seagrass ecosystems, sponges affect substratum stability, water clarity, diversity of associated species, and survival of habitat‐providing organisms, key roles not duplicated by other organisms. Whether and how predators control sponges are much disputed. Substantial ecosystem consequences of losing or gaining sponges motivated definitive experiments on how predators control sponge distribution and abundance. Caribbean sponges of 94 species representing 13 taxonomic orders and three linked habitats (coral reefs, mangroves, and seagrass meadows) were exposed to seven predator species representing different habitats and degrees of spongivory in 4,493 in situ trials. The resulting data force reassessment of popular interpretations of several patterns and processes. Contrary to extract pellet assays that declare most sponges deterrent, 78% of these 94 species were eaten by at least one predator. But “palatability” is consumer dependent: a sponge species eaten by one predator can be rejected by other predators, and predator species differed in what sponges they ate in 55.4% (214/392) of pairwise comparisons between predators. Because spongivore species are usually restricted to particular habitats, they impose abrupt boundaries on sponges’ habitat distributions, reflecting inverse relationships between accessibility and palatability to each predator. Thus a seagrass‐dwelling starfish eats only 9% of seagrass sponge species, but 70% of coral reef species, and 78% of mangrove species. Reef‐dwelling angelfishes completely consume only 13% of reef species, but 29% of seagrass species, and 63% of mangrove species. Defenses that target specific predators reveal that spongivore influence on community organization cannot be inferred from extract pellet/omnivore assays that assume defenses target all predators equally. In fact, pellet data wrongly predicted actual consumption of living sponges of that pellet's species in 43% of field experiments with spongivores. In contrast with herbivore–plant interactions, opportunistic spongivory is at least as important as routine spongivory for community organization and ecosystem function. Potential for loss of key functional roles of sponges, if opportunistic predators gain access to sponge species that lack defenses against them, must inform conservation plans for coral reef, mangrove, and seagrass ecosystems.

Autopolyploidy‐driven range expansion of a temperate‐originated plant to pan‐tropic under global change

Abstract: Angiosperms are believed to have emerged initially in the tropics and expanded their distribution range poleward through diverse mechanisms, for example polyploidization‐driven cold tolerance evolution. Reversed expansion from temperate to pan‐tropic climates through a polyploidization‐driven shift in heat tolerance remains largely unknown. Here, we found autopolyploidy in relation to the global expansion of Solidago canadensis from its temperate‐climate native range in North American to hot‐summer climate in an introduced range. Our cytogeographical study of 2,062 accessions from 471 locations worldwide demonstrates that ploidy levels correlate negatively with latitude and positively with average temperature. An isotherm‐dependent shift of the climate niches at the threshold of 20°–24°C between geo‐cytotypes can be attributed mainly to autopolyploidy‐driven differentiation of heat tolerance; only polyploids and not diploids are able to complete sexual reproduction, germinate, and grow in the hot‐summer climate of low latitudes. Ploidy‐dependent fertility appears to play a key role in the hot‐summer introduced range in the northern hemisphere through both pre‐adaptation and rapid post‐introduction adaptive evolution of delayed flowering and improved heat tolerance during embryo development. The MaxEnt model predicts continued expansion of this plant species under global change. These results provide new insights into the mechanisms governing autopolyploidy‐driven backward range expansion of plant species from temperate origins.