Graph theory as a proxy for spatially explicit population models in conservation planning.

Spatially explicit population models (SEPMs) are often considered the best way to predict and manage species distributions in spatially heterogeneous landscapes. However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes.     

Aphid population response to agricultural landscape change: A spatially explicit,individual-based model

A spatially explicit individual-based simulation model has been developed to represent aphid population dynamics in agricultural landscapes. The application of the model to Rhopalosiphum padi (L.) population dynamics is detailed, including an outline of the construction of the model, its parameterisation and validation. Over time, the aphids interact with the landscape and with one another. The landscape is modified by varying a simple pesticide regime, and the multi-scale spatial and temporal implications for a population of aphids is analysed. The results show that a spatial modelling approach that considers the effects on the individual of landscape properties and factors such as wind speed and wind direction provides novel insight into aphid population dynamics both spatially and temporally. This forms the basis for the development of further simulation models that can be used to analyse how changes in landscape structure impact upon important species distributions and population dynamics.     

Estimation of some parameters of large fish populations by capture-recapture experiments

A certain number of tagged fish is liberated and assumed to be distributed randomly among a natural fish population. The fish are subjected to a number of fishing experiments within relatively short periods, and lie between equal intervening periods of durationT. Untagged fish are retained, while tagged fish are released during the fishing experiments. Denoting the catchability of untagged fish byq _u and that for tagged fish byq _t , it is assumed that they are related by the equation “q _u =cq _t ” wherec is a constant. Denoting the survival rates of tagged fish and the effective fishing effort of commerical fisheries per unit time from the (k-1)^th to thek ^th experiments by _t S _k andf _k , respectively, it is assumed that they vary from period to period. Assuming that during thek ^th experiment, the number of untagged fish captured and the experimental fishing rate of tagged fish are denoted by _u X _k and _t P _k , respectively, then $$\begin{array}{*{20}c} {\frac{{(_u X_k )^2 }}{{[_u X_{(k - 1)} ][_u X_{(k + 1)} ]}} = \frac{{_t S_k }}{{_t S_{(k + 1)} }} \cdot \frac{{e^{ - (1 - c)q_t f_{(k + 1)} T} }}{{e^{ - (1 - c)q_t f_k T} }} \cdot } \\ {\frac{{1 - c_t P_{(k - 1)} }}{{1 - c_t P_k }} \cdot \frac{{(_t P_k )^2 }}{{[_t P_{(k - 1)} ][_t P_{(k + 1)} ]}}.} \\ \end{array}$$ The above equation containsc as a single unknown, while all other terms are supplied by the capture-recapture experiments, exceptf _k andf _(k+1) which may be obtained from fisheries statistics. A number of the above equations are obtained from several experiments and can be combined into a single equation to obtain an overall estimate forc which can be used to derive estimates for experimental fishing rates, abundance, and instantaneous natural and fishing mortality rates for natural fish populations. These estimates are free from type (A) tagging errors, and have the advantage of taking into consideration the probable different behaviour of tagged and untagged fish.     

A spatially explicit estimate of avoided forest loss

With the potential expansion of forest conservation programs spurred by climate-change agreements, there is a need to measure the extent to which such programs achieve their intended results. Conventional methods for evaluating conservation impact tend to be biased because they do not compare like areas or account for spatial relations. We assessed the effect of a conservation initiative that combined designation of protected areas with payments for environmental services to conserve over wintering habitat for the monarch butterfly (Danaus plexippus) in Mexico. To do so, we used a spatial-matching estimator that matches covariates among polygons and their neighbors. We measured avoided forest loss (avoided disturbance and deforestation) by comparing forest cover on protected and unprotected lands that were similar in terms of accessibility, governance, and forest type. Whereas conventional estimates of avoided forest loss suggest that conservation initiatives did not protect forest cover, we found evidence that the conservation measures are preserving forest cover. We found that the conservation measures protected between 200 ha and 710 ha (3-16%) of forest that is high-quality habitat for monarch butterflies, but had a smaller effect on total forest cover, preserving between 0 ha and 200 ha (0-2.5%) of forest with canopy cover >70%. We suggest that future estimates of avoided forest loss be analyzed spatially to account for how forest loss occurs across the landscape. Given the forthcoming demand from donors and carbon financiers for estimates of avoided forest loss, we anticipate our methods and results will contribute to future studies that estimate the outcome of conservation efforts.     

Studying dispersal at the landscape scale: efficient combination of population surveys and capture-recapture data

Researchers often rely on capture-mark-recapture (CMR) data to study animal dispersal in the wild. Yet their spatial coverage often does not encompass the entire dispersal range of the study individuals, sometimes producing misleading results. Information contained in population surveys and variation in population spatial structure can be used to overcome this issue. We build an integrated model in a multisite context in which CMR data are only collected at a subset of sites, but numbers of breeding pairs are counted at all sites. In a Black-headed Gull Chroicocephalus ridibundus population, the integrated-modeling approach induces an increase in precision for the demographic parameters of interest (variances, on average, were decreased by 20%) and provides a more precise extrapolation of results from the CMR data to the whole population. Patterns of condition-dependent dispersal are therefore made easier to detect, and we obtain evidence for colony-size dependence in recruitment, dispersal, and breeding success. These results suggest that first-time breeders disperse to small colonies in order to recruit earlier. The exchange of experienced breeders between colonies appears as a main determinant of the observed variation in colony sizes.     

Design and validation of a spatially explicit simulation model for bottomland hardwood forests

Species composition in forests depends on the interaction of species traits and species availability. Yet many forest simulation models focus only on interactions of adult trees and saplings, ignoring how species become members of the community. We modify a published forest model for bottomland hardwood forests (program SWAMP [Phipps, R.L., 1979. Simulation of wetlands forest vegetation dynamics. Ecol. Modell. 7, 257–288]) to make it spatially explicit and incorporate explicit seed production and dispersal algorithms. The resulting individual-based, spatially explicit forest simulator (YAFSIM) combines mechanistic seed dispersal with growth and mortality of trees to track forest dynamics over time. We describe the structure of the model and test its validity for dynamics in small bottomland hardwood patches in the Mississippi Alluvial Valley. Dynamics of species composition and basal areas of trees predicted by Yazoo Forest Simulator (YAFSIM) were similar to those of natural second- and old-growth bottomland forests. However, diversity of simulated forest patches declined over time largely because of random dynamics acting on small, isolated populations.     

The need for spatially explicit quantification of benefits in invasive‐species management

Worldwide, invasive species are a leading driver of environmental change across terrestrial, marine, and freshwater environments and cost billions of dollars annually in ecological damages and economic losses. Resources limit invasive‐species control, and planning processes are needed to identify cost‐effective solutions. Thus, studies are increasingly considering spatially variable natural and socioeconomic assets (e.g., species persistence, recreational fishing) when planning the allocation of actions for invasive‐species management. There is a need to improve understanding of how such assets are considered in invasive‐species management. We reviewed over 1600 studies focused on management of invasive species, including flora and fauna. Eighty‐four of these studies were included in our final analysis because they focused on the prioritization of actions for invasive species management. Forty‐five percent (n = 38) of these studies were based on spatial optimization methods, and 35% (n = 13) accounted for spatially variable assets. Across all 84 optimization studies considered, 27% (n = 23) explicitly accounted for spatially variable assets. Based on our findings, we further explored the potential costs and benefits to invasive species management when spatially variable assets are explicitly considered or not. To include spatially variable assets in decision‐making processes that guide invasive‐species management there is a need to quantify environmental responses to invasive species and to enhance understanding of potential impacts of invasive species on different natural or socioeconomic assets. We suggest these gaps could be filled by systematic reviews, quantifying invasive species impacts on native species at different periods, and broadening sources and enhancing sharing of knowledge.     

Estimating the complexity of bird song by using capture-recapture approaches from community ecology

Repertoire size, the number of unique song or syllable types in the repertoire, is a widely used measure of song complexity in birds, but it is difficult to calculate this exactly in species with large repertoires. A new method of repertoire size estimation applies species richness estimation procedures from community ecology, but such capture-recapture approaches have not been much tested. Here, we establish standardized sampling schemes and estimation procedures using capture-recapture models for syllable repertoires from 18 bird species, and suggest how these may be used to tackle problems of repertoire estimation. Different models, with different assumptions regarding the heterogeneity of the use of syllable types, performed best for different species with different song organizations. For most species, models assuming heterogeneous probability of occurrence of syllables (so-called detection probability) were selected due to the presence of both rare and frequent syllables. Capture-recapture estimates of syllable repertoire size from our small sample did not differ significantly from previous estimates using larger samples of count data. However, the enumeration of syllables in 15 songs yielded significantly lower estimates than previous reports. Hence, heterogeneity in detection probability of syllables should be addressed when estimating repertoire size. This is neglected using simple enumeration procedures, but is taken into account when repertoire size is estimated by appropriate capture-recapture models adjusted for species-specific song organization characteristics. We suggest that such approaches, in combination with standardized sampling, should be applied in species with potentially large repertoire size. On the other hand, in species with small repertoire size and homogenous syllable usage, enumerations may be satisfactory. Although researchers often use repertoire size as a measure of song complexity, listeners to songs are unlikely to count entire repertoires and they may rely on other cues, such as syllable detection probability.Communicated by A. Cockburn     

The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation

This study aimed at understanding how landscape heterogeneity influences outbreaks of contagious diseases in southern Africa. Landscape attributes influence patterns of movement and behaviour of animal hosts, virus spread and survival, as well as land use practices. A multi-agent simulation was developed to represent the spatial and temporal dynamics of pathogens between human-livestock and wildlife interfaces at the fringe of large wildlife conservation areas. The model represents the three main elements associated with epidemics - populations, space, and time - to simulate direct contacts between wildlife and livestock. The dynamics of these populations emerge from interactions between agents and the landscape. The model was calibrated to represent the transmission of foot-and-mouth disease through direct contact at the border of the Kruger National Park in South Africa. In the region, African buffaloes (Syncerus caffer) act as reservoirs of the virus and spread the infection to domestic cattle bordering the park. We tested the sensitivity of various factors influencing contact rate between buffaloes and cattle, and thus the risk of foot-and-mouth disease transmission. Results show that cattle-buffalo contacts mostly depend on the range of displacements of cattle and buffaloes, as influenced by the landscape configuration, and on the number of fence breakages multiplied by the time between breakage and repair. Contacts take place not only close to water-points but also in grazing areas, within an area up to 6 km from the fence.     

A spatially explicit model to predict future landscape composition of aspen woodlands under various management scenarios

Quaking aspen (Populus tremuloides) is declining across the western United States. Aspen habitats are among the most diverse plant communities in this region and loss of these habitats can result in shifts in biodiversity, productivity, and hydrology across a range of spatial scales. Western aspen occurs on the majority of sites seral to conifer species, and long-term maintenance of these aspen woodlands requires periodic fire. Over the past century, fire intervals, extents, and intensities have been insufficient to regenerate aspen stands at historic rates; however the effects of various fire regimes and management scenarios on aspen vegetation dynamics at broad spatial and temporal scales are unexplored. Here we use field data, remotely sensed data, and fire atlas information to develop a spatially explicit landscape simulation model to assess the effects of current and historic wildfire regimes and prescribed burning programs on landscape vegetation composition across two mountain ranges in the Owyhee Plateau, Idaho. Model outputs depict the future structural makeup and species composition of the landscape at selected time steps under simulated management scenarios. We found that under current fire regimes and in the absence of management activities, loss of seral aspen stands will continue to occur over the next two centuries. However, a return to historic fire regimes (burning 12–14% of the modeled landscape per decade) would maintain the majority of aspen stands in early and mid seral woodland stages and minimizes the loss of aspen. A fire rotation of 70–80 years was estimated for the historic fire regime while the current fire regime resulted in a fire rotation of 340–450 years, underscoring the fact that fire is currently lacking in the system. Implementation of prescribed burning programs, treating aspen and young conifer woodlands according to historic fire occurrence probabilities, are predicted to prevent conifer dominance and loss of aspen stands.     

A nonparametric procedure for analyzing repeated measures of spatially correlated data

Many agricultural, biological, and environmental studies involve detecting temporal changes of a response variable, based on data observed at sampling sites in a spatial region and repeatedly over several time points. That is, data are repeated measures over time and are potentially correlated across space. The traditional repeated-measures analysis allows for time dependence but assumes that the observations at different sampling sites are mutually independent, which may not be suitable for field data that are correlated across space. In this paper, a nonparametric large-sample inference procedure is developed to assess the time effects while accounting for the spatial dependence using a block bootstrap. For illustration, the methodology is applied to describe the population changes of root-lesion nematodes over time in a production field in Wisconsin.     

The effects of disturbance based management on the dynamics of Mediterranean vegetation: A hierarchical and spatially explicit modeling approach

The eastern Mediterranean region has been subjected to intensive human disturbance in the past 10,000 years, mainly in the forms of agro-pastoral activities such as grazing, shrub clearing, and prescribed burning. This disturbance history resulted in the formation of highly heterogeneous landscapes, characterized by high biodiversity. Recent changes in human activities have resulted in a decrease of landscape heterogeneity, leading to decreasing biodiversity and increasing fire risk. To conserve heterogeneity, land managers apply disturbance based management practices, using the same activities that created and maintained landscape heterogeneity in the past. However, the long-term and large-scale outcomes of these disturbances are often unknown, due to the complex response of Mediterranean vegetation to disturbance. Here we report on a spatially explicit, hybrid, and spatially hierarchical ecological model developed by us. The model attempts to predict the outcome of various disturbance based management activities on the long-term spatio-temporal dynamics of five common Mediterranean vegetation types. The model uses a spatially explicit state and transition formulation, with continuous transition functions. Model simulations were conducted on a Mediterranean landscape in Northern Israel, incorporating various disturbance practices that are common in the region. Simulation results highlight the potential of disturbance based management as a tool for conserving landscape heterogeneity, as well as the complex interactions between disturbances and the spatial structure of the landscape in Mediterranean regions.     

Assessing plausible rates of population growth in humpback whales from life-history data

The rate of growth of any population is a quantity of interest in conservation and management and is constrained by biological factors. In this study, recent data on life-history parameters influencing rates of population growth in humpback whales, including survival, age at first parturition and calving rate are reviewed. Monte Carlo simulations are used to compute a distribution of rates of increase (ROIs) taking into account uncertainty in biological parameter estimates. Two approaches for computing juvenile survival are proposed, which taken into account along with other life-history data, resulted in the following estimates of the rate of population growth: Approach A: mean of 7.3%/year (95% CI = 3.5–10.5%/year) and Approach B: mean of 8.6%/year (95% CI = 5.0–11.4%/year). It is proposed that the upper 99% quantile of the resulting distribution of the ROI for Approach B (11.8%/year) be established as the maximum plausible ROI for humpback whales and be used in population assessment of the species. Possible sources of positive and negative biases in the present estimates are presented and include measurement error in estimation of life-history parameters, changes in the environment within the period these quantities are measured, density dependence or other natural factors. However, it is difficult to evaluate potential biases without additional data. The methods presented in this study can be applied to other species for which life-history parameters are available and are useful in assessing plausibility in the estimation of population growth rates from time series of abundance estimates.     

Estimating the functional form for the density dependence from life history data

Two contrasting approaches to the analysis of population dynamics are currently popular: demographic approaches where the associations between demographic rates and statistics summarizing the population dynamics are identified; and time series approaches where the associations between population dynamics, population density, and environmental covariates are investigated. In this paper, we develop an approach to combine these methods and apply it to detailed data from Soay sheep (Ovis aries). We examine how density dependence and climate contribute to fluctuations in population size via age- and sex-specific demographic rates, and how fluctuations in demographic structure influence population dynamics. Density dependence contributes most, followed by climatic variation, age structure fluctuations and interactions between density and climate. We then simplify the density-dependent, stochastic, age-structured demographic model and derive a new phenomenological time series which captures the dynamics better than previously selected functions. The simple method we develop has potential to provide substantial insight into the relative contributions of population and individual-level processes to the dynamics of populations in stochastic environments.     

A further contribution to the study of fish populations by capture-recapture experiments

In capture-recapture experiments, fish populations can be studied by two different sampling procedures. In both procedures, tagged fish are released on capture, but untagged fish are in one procedure released after tagging, in the second procedure they are retained. Using the two sampling techniques, Rafail (1971a,b) gave expressions for the estimation of an assumed constant (C) of proportionality between probabilities of capture of tagged to untagged fish which are simplified here to forms easier for calculation. The estimation of this constant (C) aids in estimation of abundance and mortality rates of untagged fish which are assumed to differ from those of tagged fish.     

Using the ECLPSS software environment to build a spatially explicit component-based model of ozone effects on forest ecosystems

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ecological processes by providing a growing library of reusable interchangeable components and automating many modeling tasks. To build a model, a user selects components from the library, and then writes new components as needed. Some of these components represent specific ecological processes, such as how environmental factors influence the growth of individual trees. Other components provide simulation support such as reading and writing files in various formats to allow inter-operability with other software. The framework manages components and variables, the order of operations, and spatial interactions. The framework provides only simulation support; it does not include ecological functions or assumptions. This separation allows biologists to build models without becoming computer scientists, while computer scientists can improve the framework without becoming ecologists. The framework is designed to operate on multiple platforms and be used across networks via a World Wide Web-based user interface. ECLPSS is designed for use with both single processor computers for small models, and multiple processors in order to simulate large regions with complex interactions among many individuals or ecological compartments. To test Version 1.0 of ECLPSS, we created a model to evaluate the effect of tropospheric ozone on forest ecosystem dynamics. This model is a reduced-form version of two existing models: , which represents an individual tree, and , which represents forest stand growth and succession. This model demonstrates key features of ECLPSS, such as the ability to examine the effects of cell size and model structure on model predictions.     

Integration of a fish bioenergetics model into a spatially explicit water quality model: Application to menhaden in Chesapeake Bay

Although fish are usually thought of as victims of water quality degradation, it has been proposed that some planktivorous species may improve water quality through consumption of algae and sequestering of nutrients via growth. Within most numerical water quality models, the highest trophic level modeled explicitly is zooplankton, prohibiting an investigation of the effect a fish species may be having on its environment. Conversely, numerical models of fish consumption do not typically include feedback mechanisms to capture the effects of fish on primary production and nutrient recycling. In the present study, a fish bioenergetics model is incorporated into CE-QUAL-ICM, a spatially explicit eutrophication model. In addition to fish consumption of algae, zooplankton, and detritus, fish biomass accumulation and nutrient recycling to the water column are explicitly accounted for. These developments advance prior modeling efforts of the impact of fish on water quality, many of which are based on integrated estimates over an entire system and which omit the feedback the fish have through nutrient recycling and excretion. To validate the developments, a pilot application was undertaken for Atlantic menhaden (Brevoortia tyrannus) in Chesapeake Bay. The model indicates menhaden may reduce the algal biomass while simultaneously increasing primary productivity.     

On estimating Hooded crow density from line transect data through exponential mixture models

Line transect sampling is a distance sampling method widely used for estimating wildlife population density. Since the usual approach assumes a model for the detection function, the estimate depends on the shape of such a function. In particular, the estimate is influenced by the so-called shoulder condition, which ensures that detection is nearly certain at small distances from the line transect. For instance, the half-normal model satisfies this condition, whereas the negative exponential model does not. The aim of this paper is to propose the exponential mixture model of the half-normal and the negative exponential in order to estimate the population density in the case where the shoulder condition is not guaranteed. Such a case study on Hooded crow is described in the paper.     

Estimation of population parameters from aerial counts of North American mallards: a cautionary tale.

The accuracy of population estimates strongly interferes with our ability to obtain unbiased estimates of population parameters based on analyses of time series of population fluctuations. Here we use long-term data on fluctuations in the size of Mallard populations collected as part of the May Breeding Waterfowl Survey covering a large section of North America. We assume a log-linear model of density dependence and use a hierarchical Bayesian state-space approach in which all parameters are assumed to be realizations from a common underlying distribution. Thus, parameters for different populations are not allowed to vary independently of each other. We then simulated independent time series of aerial counts, using the estimated parameters and adding various levels of observation error. These simulations showed that the estimates of stochastic population growth rate and strength of density dependence were biased even when moderate sampling errors were present. In contrast, the estimates of the environmental stochasticity and the carrying capacity were unbiased even for short time series and large observation error. Our results underline the importance of reducing the magnitude of sampling error in the design of large-scale monitoring programs of population fluctuations.