Effects of surrounding land use and water depth on seagrass dynamics relative to a catastrophic algal bloom

Seagrasses are the foundation of many coastal ecosystems and are in global decline because of anthropogenic impacts. For the Indian River Lagoon (Florida, U.S.A.), we developed competing multistate statistical models to quantify how environmental factors (surrounding land use, water depth, and time [year]) influenced the variability of seagrass state dynamics from 2003 to 2014 while accounting for time‐specific detection probabilities that quantified our ability to determine seagrass state at particular locations and times. We classified seagrass states (presence or absence) at 764 points with geographic information system maps for years when seagrass maps were available and with aerial photographs when seagrass maps were not available. We used 4 categories (all conservation, mostly conservation, mostly urban, urban) to describe surrounding land use within sections of lagoonal waters, usually demarcated by land features that constricted these waters. The best models predicted that surrounding land use, depth, and year would affect transition and detection probabilities. Sections of the lagoon bordered by urban areas had the least stable seagrass beds and lowest detection probabilities, especially after a catastrophic seagrass die‐off linked to an algal bloom. Sections of the lagoon bordered by conservation lands had the most stable seagrass beds, which supports watershed conservation efforts. Our results show that a multistate approach can empirically estimate state‐transition probabilities as functions of environmental factors while accounting for state‐dependent differences in seagrass detection probabilities as part of the overall statistical inference procedure.     

General methods for sensitivity analysis of equilibrium dynamics in patch occupancy models

Sensitivity analysis is a useful tool for the study of ecological models that has many potential applications for patch occupancy modeling. Drawing from the rich foundation of existing methods for Markov chain models, I demonstrate new methods for sensitivity analysis of the equilibrium state dynamics of occupancy models. Estimates from three previous studies are used to illustrate the utility of the sensitivity calculations: a joint occupancy model for a prey species, its predators, and habitat used by both; occurrence dynamics from a well-known metapopulation study of three butterfly species; and Golden Eagle occupancy and reproductive dynamics. I show how to deal efficiently with multistate models and how to calculate sensitivities involving derived state variables and lower-level parameters. In addition, I extend methods to incorporate environmental variation by allowing for spatial and temporal variability in transition probabilities. The approach used here is concise and general and can fully account for environmental variability in transition parameters. The methods can be used to improve inferences in occupancy studies by quantifying the effects of underlying parameters, aiding prediction of future system states, and identifying priorities for sampling effort.     

Inferring Metapopulation Dynamics from Patch-Level Incidence of Florida Scrub Plants

Spatial structure and dynamics of multiple populations may explain species distribution patterns in patchy communities with heterogeneous disturbance regimes, especially when species have poor dispersal. The endemic-rich Florida (U.S.A.) rosemary scrub occupies about 4% of the west portion of Archbold Biological Station and occurs scattered within a matrix of less xeric vegetation. Longer fire-return times and higher frequency of open patches in rosemary scrub provide favorable habitat for many plant species. Occupancy of 123 species of vascular plants and ground lichens in 89 patches was determined by repeated site surveys. About two-thirds of the species occurring at more than 14 patches had a significant logistic regression of presence on time-since-fire, patch size, patch isolation, or their interactions. Species with presence related to the interaction between patch isolation and patch size were primarily herbs and small shrubs specializing in rosemary scrub. These results suggest the importance of spatial characteristics of the landscape for population turnover of these species. An incidence-based metapopulation model was used to predict extinction and colonization probabilities of those species with presence in rosemary scrub patches related to the studied spatial variables. This is the first attempt to apply incidence-based metapopulation models to plants. The results showed stronger effects of patch size and patch isolation on extinction probabilities of herbs than on those of woody species. Because of their effect on spatial heterogeneity and habitat availability, fire suppression and habitat destruction may decrease persistence probabilities for these rosemary scrub specialists, many of which are endangered species.     

Indicators of ecosystem function identify alternate states in the sagebrush steppe

Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital. This study aims to (1) evaluate the utility of functional indicators (indicators of rangeland health, IRH) as proxies for more difficult ecosystem function measurements and (2) create a data-driven STM for the sagebrush steppe of Colorado, USA, that incorporates both ecosystem structure and function. We sampled soils, plant communities, and IRH at 41 plots with similar clayey soils but different site histories to identify potential states and infer the effects of management practices and disturbances on transitions. We found that many IRH were correlated with quantitative measures of functional indicators, suggesting that the IRH can be used to approximate ecosystem function. In addition to a reference state that functions as expected for this soil type, we identified four biotically and functionally distinct potential states, consistent with the theoretical concept of alternate states. Three potential states were related to management practices (chemical and mechanical shrub treatments and seeding history) while one was related only to ecosystem processes (erosion). IRH and potential states were also related to environmental variation (slope, soil texture), suggesting that there are environmental factors within areas with similar soils that affect ecosystem dynamics and should be noted within STMs. Our approach generated an objective, data-driven model of ecosystem dynamics for rangeland management. Our findings suggest that the IRH approximate ecosystem processes and can distinguish between alternate states and communities and identify transitions when building data-driven STMs. Functional indicators are a simple, efficient way to create data-driven models that are consistent with alternate state theory. Managers can use them to improve current model-building methods and thus apply state-and-transition models more broadly for land management decision-making.     

Comparison of Two Types of Metapopulation Models in Real and Artificial Landscapes

Abstract: Application of metapopulation models is becoming increasingly widespread in the conservation of species in fragmented landscapes. We provide one of the first detailed comparisons of two of the most common modeling techniques, incidence function models and stage-based matrix models, and test their accuracy in predicting patch occupancy for a real metapopulation. We measured patch occupancies and demographic rates for regional populations of the Florida scrub lizard (   Sceloporus woodi ) and compared the observed occupancies with those predicted by each model. Both modeling strategies predicted patch occupancies with good accuracy ( 77–80%) and gave similar results when we compared hypothetical management scenarios involving removal of key habitat patches and degradation of habitat quality. To compare the two modeling approaches over a broader set of conditions, we simulated metapopulation dynamics for 150 artificial landscapes composed of equal-sized patches (2–1024 ha) spaced at equal distances (50–750 m). Differences in predicted patch occupancy were small to moderate (<20%) for about 74% of all simulations, but 22% of the landscapes had differences openface> 50%. Incidence function models and stage-based matrix models differ in their approaches, assumptions, and requirements for empirical data, and our findings provide evidence that the two models can produce different results. We encourage researchers to use both techniques and further examine potential differences in model output. The feasibility of obtaining data for population modeling varies widely among species and limits the modeling approaches appropriate for each species. Understanding different modeling approaches will become increasingly important as conservation programs undertake the challenge of managing for multiple species in a landscape context.     

Combining multistate capture-recapture data with tag recoveries to estimate demographic parameters

Matrix population models that allow an animal to occupy more than one state over time are important tools for population and evolutionary ecologists. Definition of state can vary, including location for metapopulation models and breeding state for life history models. For populations whose members can be marked and subsequently reencountered, multistate mark-recapture models are available to estimate the survival and transition probabilities needed to construct population models. Multistate models have proved extremely useful in this context, but they often require a substantial amount of data and restrict estimation of transition probabilities to those areas or states subjected to formal sampling effort. At the same time, for many species, there are considerable tag recovery data provided by the public that could be modeled in order to increase precision and to extend inference to a greater number of areas or states. Here we present a statistical model for combining multistate capture-recapture data (e.g., from a breeding ground study) with multistate tag recovery data (e.g., from wintering grounds). We use this method to analyze data from a study of Canada Geese (Branta canadensis) in the Atlantic Flyway of North America. Our analysis produced marginal improvement in precision, due to relatively few recoveries, but we demonstrate how precision could be further improved with increases in the probability that a retrieved tag is reported.     

Representing mediating effects and species reintroductions in Ecopath with Ecosim

Ecosystem models play an important role in supporting ecosystem approaches to management. To improve the representation of how ecosystems work, ecosystem models should be able to represent mediating effects (e.g., habitat provision) that species provide to each other as well as species (re)introductions, both common situations that can strongly influence ecosystem dynamics. We examine how such processes can be incorporated into Ecopath with Ecosim (EwE), a widely used tool for represent aquatic ecosystems with the potential to support ecosystem-based management. We used the reintroduction of sea otters (Enhydralutris) to the west coast of Vancouver Island, British Columbia, Canada as a case study. The model demonstrates how to account for benefits provided by kelp forests by contributing to primary production, increased feeding areas and food availability through prey retention. It also demonstrates how the reintroduction and range expansion of sea otters can be represented in Ecospace, and the implications of these options.     

Estimating parameters of hidden Markov models based on marked individuals: use of robust design data

Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last 20 years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected-value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We have also implemented these models in program MARK. This general framework could also be used by practitioners to consider constrained models of particular interest, or to model the relationship between within-primary-period parameters (e.g., state structure) and between-primary-period parameters (e.g., state transition probabilities).     

Life and Death in the Fast Lane: Demographic Consequences of Road Mortality in the Florida Scrub-Jay

Abstract: We examined the demographic consequences of road mortality in the cooperatively breeding Florida Scrub-Jay (Aphelocoma coerulescens ), a threatened species restricted to the oak scrub of peninsular Florida. Between May 1986 and July 1995 we monitored the survival and reproductive success of a color-banded population of jays along a two-lane highway at Archbold Biological Station. Annual mortality of breeding adults was 0.38 on road territories, significantly higher than the rate of 0.23 for breeders on nonroad territories. High mortality on road territories appeared to be a direct result of automobile traffic per se and not a consequence of road-induced changes in habitat characteristics. Mortality was especially high for immigrants without previous experience living along the road: in their first two years as breeders on road territories, naive immigrants experienced annual mortality of 0.50 and 0.45. From year 3 onward, however, annual mortality dropped to 0.29, not significantly different from the rate for birds on nonroad territories. This experience-dependent decline in road mortality could be caused either by surviving jays learning to avoid automobiles or by selective mortality operating through time (demographic heterogeneity). Proximity to the road had no effect on nesting success beyond its indirect effects on breeder experience and group size. Because the mortality of 30- to 90-day-old fledglings was significantly higher on road territories than on nonroad territories, however, breeder mortality greatly exceeded production of yearlings on road territories. Roadside territories therefore are sinks that can maintain populations of Florida Scrub-Jays only via immigration. Because Florida Scrub-Jays do not avoid roadside habitats and may even be attracted to them, road mortality presents a difficult challenge for the management and conservation of this threatened and declining species.     

Increased spatial variance accompanies reorganization of two continental shelf ecosystems

Phase transitions between alternate stable states in marine ecosystems lead to disruptive changes in ecosystem services, especially fisheries productivity. We used trawl survey data spanning phase transitions in the North Pacific (Gulf of Alaska) and the North Atlantic (Scotian Shelf) to test for increases in ecosystem variability that might provide early warning of such transitions. In both time series, elevated spatial variability in a measure of community composition (ratio of cod [Gadus sp.] abundance to prey abundance) accompanied transitions between ecosystem states, and variability was negatively correlated with distance from the ecosystem transition point. In the Gulf of Alaska, where the phase transition was apparently the result of a sudden perturbation (climate regime shift), variance increased one year before the transition in mean state occurred. On the Scotian Shelf, where ecosystem reorganization was the result of persistent overfishing, a significant increase in variance occurred three years before the transition in mean state was detected. However, we could not reject the alternate explanation that increased variance may also have simply been inherent to the final stable state in that ecosystem. Increased variance has been previously observed around transition points in models, but rarely in real ecosystems, and our results demonstrate the possible management value in tracking the variance of key parameters in exploited ecosystems.     

Unintended Cultivation,Shifting Baselines,and Conflict between Objectives for Fisheries and Conservation

The effects of fisheries on marine ecosystems, and their capacity to drive shifts in ecosystem states, have been widely documented. Less well appreciated is that some commercially valuable species respond positively to fishing‐induced ecosystem change and can become important fisheries resources in modified ecosystems. Thus, the ecological effects of one fishery can unintentionally increase the abundance and productivity of other fished species (i.e., cultivate). We reviewed examples of this effect in the peer‐reviewed literature. We found 2 underlying ecosystem drivers of the effect: trophic release of prey species when predators are overfished and habitat change. Key ecological, social, and economic conditions required for one fishery to unintentionally cultivate another include strong top–down control of prey by predators, the value of the new fishery, and the capacity of fishers to adapt to a new fishery. These unintended cultivation effects imply strong trade‐offs between short‐term fishery success and conservation efforts to restore ecosystems toward baseline conditions because goals for fisheries and conservation may be incompatible. Conflicts are likely to be exacerbated if fisheries baselines shift relative to conservation baselines and there is investment in the new fishery. However, in the long‐term, restoration toward ecosystem baselines may often benefit both fishery and conservation goals. Unintended cultivation can be identified and predicted using a combination of time‐series data, dietary studies, models of food webs, and socioeconomic data. Identifying unintended cultivation is necessary for management to set compatible goals for fisheries and conservation. Cultivo Accidental, Líneas de Base Cambiantes y el Conflicto entre los Objetivos para las Pesquerías y la Conservación     

Lotka-Volterra competition models for sessile organisms

Markov models are widely used to describe the dynamics of communities of sessile organisms, because they are easily fitted to field data and provide a rich set of analytical tools. In typical ecological applications, at any point in time, each point in space is in one of a finite set of states (e.g., species, empty space). The models aim to describe the probabilities of transitions between states. In most Markov models for communities, these transition probabilities are assumed to be independent of state abundances. This assumption is often suspected to be false and is rarely justified explicitly. Here, we start with simple assumptions about the interactions among sessile organisms and derive a model in which transition probabilities depend on the abundance of destination states. This model is formulated in continuous time and is equivalent to a Lotka-Volterra competition model. We fit this model and a variety of alternatives in which transition probabilities do not depend on state abundances to a long-term coral reef data set. The Lotka-Volterra model describes the data much better than all models we consider other than a saturated model (a model with a separate parameter for each transition at each time interval, which by definition fits the data perfectly). Our approach provides a basis for further development of stochastic models of sessile communities, and many of the methods we use are relevant to other types of community. We discuss possible extensions to spatially explicit models.     

Modelling coral reef ecosystems with limited observational data

Ecosystem models represent potentially powerful tools for coral reef ecosystem managers. They can provide insight into ecosystem dynamics not achievable through alternative means allowing coral reef managers to assess the potential outcome of any given management decision. One of the main limitations in the applicability of ecosystem models is that they often require detailed empirical data and this can restrict their applicability to ecosystems that are either currently well studied or have the resources available to collect the required data. This study describes the development of a coral reef ecosystem model that can be calibrated to an ecosystem with limited empirical data. Based on the assumption that coral reef ecological structure is generic across all tropical coral reefs and that the magnitude of the interactions between ecological components is reef specific, the dynamics of the ecosystem can be replicated based on limited empirical data. The model successfully replicated the dynamics of three individual reef systems including an inshore and oceanic reef within the Great Barrier Reef and a Caribbean reef system. It highlighted the importance of understanding the specific dynamics of a given reef and that a positive management intervention in one system may result in a negative outcome for another. The model was also used to assess the importance of various interactions within coral reef ecosystems. It identified the interactions between hard corals and other non-algal benthic components as being an important (but currently understudied) facet of coral reef ecology. The development of this modelling approach provides access to ecosystem modelling tools for coral reef managers previously excluded due to a lack of resources or technical expertise.     

Exploring alternative states in ecological systems with a qualitative analysis of community feedback

Demonstrating and predicting the existence of alternative states in natural communities remains a challenge for ecologists and is essential for resource managers. Positive feedback is often presented as central in maintaining alternative ecosystem states, but no formal approach relates this part of theory to real world applications. Through qualitative modelling of community response to long-term perturbations, we define generic mechanistic links between positive feedback and the occurrence of alternative states. Positive feedback diminishes a system's overall resistance to change, and can create and maintain correlations in the relative abundance of variables that coincide with alternative states.Through specific models of the dynamics of Tasmanian rocky-reef communities, which are affected by climate and fishing and persist within alternative states, we demonstrate the ability of our theoretical framework to predict alternative states in ecosystems and inform management intervention. A qualitative knowledge of community structure permits a thorough analysis of system feedback and an assessment of the potential for an ecosystem to exhibit alternative states. We illustrate the usefulness of the approach to inform management priorities, and to focus monitoring and field research on the key drivers of ecosystem dynamics.     

Modeling survival and mark loss in molting animals: recapture, dead recoveries, and exuvia recoveries

Capture-mark-recapture (CMR) analyses aim primarily at estimating relevant life history parameters, despite the fact that some individuals are not always recaptured, even if alive on the study site. Applying such approaches to species with a complex life cycle, such as insects, remains challenging because each change of stage tends to cause mark loss through molting. We developed a multistate model based on three exclusive events ("dead", "surviving and molting", and "surviving and staying in the same larval stage") to estimate probabilities of survival and mark loss. Estimates of biologically relevant parameters were derived from those of the probabilities of transition between these states. The model was applied to data from radio-tracking diodes glued on grasshoppers. The estimates of recapture probabilities decreased throughout the season for animals remaining alive, while the detection of dead animals and lost diodes was exhaustive. The survival probability was higher for larvae than for adults (0.98 vs. 0.96), and mark loss was stronger in larvae than in adults (0.09 vs. 0.06). We show that the survival rate of a species with a high rate of mark loss can be estimated using multistate models, provided that marks can be recovered after being lost. These models are flexible enough to test for several effects that potentially affect survival and mark loss probabilities.     

流域水生态功能区划及其关键问题

作为流域生态系统管理和水资源保护的重要手段,如何科学合理地开展流域水生态功能区划,已成为世界各国可持续发展所面临的关键挑战之一.本文立足我国流域综合管理的特点和发展趋势,针对我国现行水功能区划的问题,结合国外流域水生态区划的经验,提出了基于流域生态学、地域分异规律、生态系统健康与生态完整性、流域生态系统管理等理论基础的,以恢复流域持续性、完整性生态系统健康为目标,反映流域水陆耦合体在不同时空尺度景观异质性的流域水生态功能区划及其原则,重点分析了流域水生态系统的空间格局、生态过程以及动态演替等3个区划的关键问题,并提出了区划的方法,以期为我国流域水生态功能区划和流域生态系统管理提供战略层次的科学依据.     

Postfire Management on Forested Public Lands of the Western United States

Abstract:  Forest ecosystems in the western United States evolved over many millennia in response to disturbances such as wildfires. Land use and management practices have altered these ecosystems, however, including fire regimes in some areas. Forest ecosystems are especially vulnerable to postfire management practices because such practices may influence forest dynamics and aquatic systems for decades to centuries. Thus, there is an increasing need to evaluate the effect of postfire treatments from the perspective of ecosystem recovery. We examined, via the published literature and our collective experience, the ecological effects of some common postfire treatments. Based on this examination, promising postfire restoration measures include retention of large trees, rehabilitation of firelines and roads, and, in some cases, planting of native species. The following practices are generally inconsistent with efforts to restore ecosystem functions after fire: seeding exotic species, livestock grazing, placement of physical structures in and near stream channels, ground-based postfire logging, removal of large trees, and road construction. Practices that adversely affect soil integrity, persistence or recovery of native species, riparian functions, or water quality generally impede ecological recovery after fire. Although research provides a basis for evaluating the efficacy of postfire treatments, there is a continuing need to increase our understanding of the effects of such treatments within the context of societal and ecological goals for forested public lands of the western United States.     

Linking irreplaceable landforms in a self‐organizing landscape to sensitivity of population vital rates for an ecological specialist

Irreplaceable, self‐organizing landforms and the endemic and ecologically specialized biodiversity they support are threatened globally by anthropogenic disturbances. Although the outcome of disrupting landforms is somewhat understood, little information exists that documents population consequences of landform disturbance on endemic biodiversity. Conservation strategies for species dependent upon landforms have been difficult to devise because they require understanding complex feedbacks that create and maintain landforms and the consequences of landform configuration on demography of species. We characterized and quantified links between landform configuration and demography of an ecological specialist, the dunes sagebrush lizard (Sceloporus arenicolus), which occurs only in blowouts (i.e., wind‐blown sandy depressions) of Shinnery oak (Quercus havardii) sand‐dune landforms. We used matrix models to estimate vital rates from a multisite mark‐recapture study of 6 populations occupying landforms with different spatial configurations. Sensitivity and elasticity analyses demonstrated demographic rates among populations varied in sensitivity to different landform configurations. Specifically, significant relationships between blowout shape complexity and vital rate elasticities suggested direct links between S. arenicolus demography and amount of edge in Shinnery oak sand‐dune landforms. These landforms are irreplaceable, based on permanent transition of disturbed areas to alternative grassland ecosystem states. Additionally, complex feedbacks between wind, sand, and Shinnery oak maintain this landform, indicating restoration through land management practices is unlikely. Our findings that S. arenicolus population dynamics depended on landform configuration suggest that failure to consider processes of landform organization and their effects on species’ population dynamics may lead to incorrect inferences about threats to endemic species and ineffective habitat management for threatened or endangered species. As such, successful conservation of these systems and the biodiversity they support must be informed by research linking process‐oriented studies of self‐organized landforms with studies of movement, behavior, and demography of species that dwell in them.