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Graph-theoretic evaluations of habitat connectivity often rely upon least-cost path analyses to evaluate connectedness of habitat patches, based on an underlying cost surface. We present two improvements upon these methods. As a case study to test these methods, we evaluated habitat connectivity for the endangered San Martin titi monkey (Plecturocebus oenanthe) in north-central Peru, to prioritize habitat patches for conservation. First, rather than using a single least-cost path between habitat patches, we analyzed multigraphs made up of multiple low-cost paths. This allows us to differentiate between patches connected through a single narrow corridor, and patches connected by a wide swath of traversable land. We evaluate potential movement pathways by iteratively removing paths and recomputing connectivity metrics. Second, instead of performing a sensitivity analysis by varying costs uniformly across the landscape, we generated landscapes with spatially varying costs. This approach produced a more informative assessment of connectivity than standard graph analyses. Of the 4340 habitat patches considered across the landscape, we identified the most important 100, those frequently ranked highly through repeated network modifications, for multiple metrics and cost surfaces. These methods represent a novel approach for assessing connectivity, better accounting for spatial configurations of habitat patches and uncertainty in cost surfaces. The ability to identify habitat patches with more possible routes to other patches is of interest for resiliency planning and prioritization in the face of continued habitat loss and climate change. These methods should be broadly applicable to conservation planning for other wildlife species.

Watershed urbanization increases the concentrations of major ions in downstream freshwater ecosystems. Non-point source ions from human activities and the chemical weathering of infrastructure are efficiently transported by stormwater runoff through subsurface pipes directly into streams. While the increase in mean streamwater solute concentrations in urban watersheds because of non-point source loading is a commonly documented phenomenon, the temporal dynamics of urban streamwater solute chemistry and its relationship to development patterns is less well understood. We continuously monitored streamflow, temperature, and conductivity as well as bimonthly variation in the solute chemistry of 24 watershed outlets in the Raleigh-Durham-Chapel Hill metropolitan area in North Carolina, USA for two years. Watersheds were selected to have similar proportions of development (10–36% development) while spanning the full measured range in road and stormwater pipe density for urban watersheds in this metropolitan area. We found remarkable temporal variation in the chemical regimes of the urban streams draining this set of watersheds, despite their similar proportion of development. For multiple major ions (SO42−, Cl−, NO3−), bimonthly concentrations varied tenfold across the study streams and temporal variation in streamwater chemical composition increased across watershed road and stormwater pipe density gradients. Total temporal variation in baseflow and stormflow dissolved ions, as measured by the coefficient of variation of specific conductance, was highly correlated with road density after accounting for underlying geology (R2 > 0.60). Using structural equation modeling, we found that subsurface piping mediates the relationship between roads and stream chemistry. In watersheds with high stormwater pipe density, streamwater ionic strength was low at baseflow while high and highly variable during event flow. This ‘flashy’ chemical signal in those watersheds, mirrors their more responsive hydrographs. In contrast, in our urban watersheds with the lowest pipe density, baseflow ionic strengths were higher, and event flow ionic strengths were lower and less variable. These results suggest that the extent to which pavement is drained by pipes creates a tradeoff between routing urban salts directly to streams via pipes versus indirectly to streams via loading to groundwater. Results of this study demonstrate the importance of considering altered temporal chemical variability, not just elevated solute concentrations, as a key feature of the impact of urbanization on streams. Future urban development design which minimizes the extent of roads and stormwater pipes in watersheds through denser development may be an effective strategy to abate impacts on downstream water quality.

Ongoing urban development has significant effects on ecosystems, including changes to land cover, environmental conditions, and species' distributions. These various impacts may have opposing or interacting effects on plant communities, making it difficult to predict how plant biodiversity will respond to urban development. A frequently cited conceptual framework predicts how urban development influences plant taxonomic, functional, and phylogenetic diversity by simplifying multiple coincident effects of urbanization into four primary filters of biodiversity: habitat transformation, fragmentation, the urban environment, and human preferences. Each filter prevents some plant species from persisting in urban areas while promoting others, but species introductions according to human preferences are expected to cause a net increase in biodiversity while the other filters limit diversity. In this study, we used structural equation modeling to test these predictions and examine the relative importance of each filter on the taxonomic, functional, and phylogenetic diversity of riparian forest plant species sampled along an urban-to-rural gradient in the Research Triangle area of North Carolina. Most diversity measures declined with urbanization, but some (e.g., functional Rao's Q) increased with urbanization. We found support for some of the predicted relationships between urbanization filters and biodiversity, as well as some unexpected relationships, including positive effects of urban environments. Overall, urban environments and human preferences were stronger predictors than habitat transformation and fragmentation. Our approach could be used to test a general framework predicting the effects of urbanization on plant diversity across multiple cities and contribute to a more synthetic understanding of urban biodiversity.

Windthrow plays a critical role in maintaining species diversity in temperate forests. Do large-scale strong wind events (i.e., tropical cyclones, including hurricanes, typhoons and severe cyclonic storms) increase tree diversity in severely damaged forest areas? Do hurricanes (tropical cyclones that occurs in the Atlantic Ocean and northeastern Pacific Ocean) lead to altered relative abundance of shade-tolerant and shade-intolerant species? Did historic hurricanes alter the succession trajectory of the damaged forests? We used nearly 70-year tree demographic data to assess the effects of two major hurricanes on woody species diversity in Piedmont forests, North Carolina, USA. Species richness (S) and Shannon–Wiener’s diversity index (H′) were used to evaluate the changes in tree diversity. The changes in composition were assessed with Nonmetric Multidimensional Scaling. The pre-hurricane successional phase can strongly influence both the damage severity and subsequent responses. Although there is often an immediate drop in diversity following a hurricane, understory tree diversity quickly increases to levels that exceed those prior to the disturbance. This leads to an increase in diversity in stands that were substantially damaged. Hurricanes significantly decrease the dominance of shade-intolerant canopy species while increasing pre-established, more shade-tolerant species. We conclude that large, and infrequent hurricanes help to maintain local tree diversity, but also accelerate the increase in dominance of understory species such as red maple and beech.

The persistence of freshwater degradation has necessitated the growth of an expansive stream and wetland restoration industry, yet restoration prioritization at broad spatial extents is still limited and ad-hoc restoration prevails. The River Basin Restoration Prioritization tool has been developed to incorporate vetted, distributed data models into a catchment scale restoration prioritization framework. Catchment baseline condition and potential improvement with restoration activity is calculated for all National Hydrography Dataset stream reaches and catchments in North Carolina and compared to other catchments within the river subbasin to assess where restoration efforts may best be focused. Hydrologic, water quality, and aquatic habitat quality conditions are assessed with peak flood flow, nitrogen and phosphorus loading, and aquatic species distribution models. The modular nature of the tool leaves ample opportunity for future incorporation of novel and improved datasets to better represent the holistic health of a watershed, and the nature of the datasets used herein allow this framework to be applied at much broader scales than North Carolina.

Identifying adaptive loci can provide insight into the mechanisms underlying local adaptation. Genotype-environment association (GEA) methods, which identify these loci based on correlations between genetic and environmental data, are particularly promising. Univariate methods have dominated GEA, despite the high dimensional nature of genotype and environment. Multivariate methods, which analyze many loci simultaneously, may be better suited to these data since they consider how sets of markers covary in response to environment. These methods may also be more effective at detecting adaptive processes that result in weak, multilocus signatures. Here, we evaluate four multivariate methods, and five univariate and differentiation-based approaches, using published simulations of multilocus selection. We found that Random Forest performed poorly for GEA. Univariate GEAs performed better, but had low detection rates for loci under weak selection. Constrained ordinations showed a superior combination of low false positive and high true positive rates across all levels of selection. These results were robust across the demographic histories, sampling designs, sample sizes, and levels of population structure tested. The value of combining detections from different methods was variable, and depended on study goals and knowledge of the drivers of selection. Reanalysis of genomic data from gray wolves highlighted the unique, covarying sets of adaptive loci that could be identified using redundancy analysis, a constrained ordination. Although additional testing is needed, this study indicates that constrained ordinations are an effective means of detecting adaptation, including signatures of weak, multilocus selection, providing a powerful tool for investigating the genetic basis of local adaptation.

There is a growing movement in government, environmental non-governmental organizations and the private sector to include ecosystem services in decision making. Adding ecosystem services into assessments implies measuring how much a change in ecological conditions affects people, social benefit, or value to society. Despite consensus around the general merit of accounting for ecosystem services, systematic guidance on what to measure and how is lacking. Current ecosystem services assessments often resort to biophysical proxies (e.g., area of wetland in a floodplain) or even disregard services that seem difficult to measure. Valuation, an important tool for assessing trade-offs and comparing outcomes, is also frequently omitted due to lack of data on social preferences, lack of expertise with valuation methods, or mistrust of valuation methods for non-market services. To address these shortcomings, we propose the use of a new type of indicator that explicitly reflects an ecosystem’s capacity to provide benefits to society, ensuring that ecosystem services assessments measure outcomes that are demonstrably and directly relevant to human welfare. We call these Benefit-relevant indicators (BRIs) and describe a process for developing them using causal chains that link management decisions through ecological responses to effects on human well-being. BRIs identify what is valued and by whom, but stop short of valuation. A BRI for the ability of wetlands to ameliorate flooding would connect measures of the quantity and quality of wetland in a floodplain, as affected by wetlands management decisions, to the number of people or properties downstream that are vulnerable to flooding. BRIs can support monetary or non-monetary valuation, but are particularly useful when valuation will not be conducted; in such cases they serve as stand-alone measures of “what is valued” by particular beneficiaries. BRIs are valid measures of ecosystem services in that they are directly linked to human well-being. Flexibility in the development of BRIs helps to ensure that they are broadly applicable across practitioner and stakeholder communities and decision contexts.

Sustainability challenges for nature and people are complex and interconnected, such that effective solutions require approaches and a common theory of change that bridge disparate disciplines and sectors. Causal chains offer promising approaches to achieving an integrated understanding of how actions affect ecosystems, the goods and services they provide, and ultimately, human well-being. Although causal chains and their variants are common tools across disciplines, their use remains highly inconsistent, limiting their ability to support and create a shared evidence base for joint actions. In this article, we present the foundational concepts and guidance of causal chains linking disciplines and sectors that do not often intersect to elucidate the effects of actions on ecosystems and society. We further discuss considerations for establishing and implementing causal chains, including nonlinearity, trade-offs and synergies, heterogeneity, scale, and confounding factors. Finally, we highlight the science, practice, and policy implications of causal chains to address real-world linked human–nature challenges.

In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling.

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers' actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

Streams draining urban heat islands tend to be hotter than rural and forested streams at baseflow because of warmer urban air and ground temperatures, paved surfaces, and decreased riparian canopy. Urban infrastructure efficiently routes runoff over hot impervious surfaces and through storm drains directly into streams and can lead to rapid, dramatic increases in temperature. Thermal regimes affect habitat quality and biogeochemical processes, and changes can be lethal if temperatures exceed upper tolerance limits of aquatic fauna. In summer 2009, we collected continuous (10-min interval) temperature data in 60 streams spanning a range of development intensity in the Piedmont of North Carolina, USA. The 5 most urbanized streams averaged 21.1°C at baseflow, compared to 19.5°C in the 5 most forested streams. Temperatures in urban streams rose as much as 4°C during a small regional storm, whereas the same storm led to extremely small to no changes in temperature in forested streams. Over a kilometer ...

At global and regional scales, tree mortality rates are positively correlated with forest net primary productivity (NPP). Yet causes of the correlation are unknown, in spite of potentially profound implications for our understanding of environmental controls of forest structure and dynamics and, more generally, our understanding of broad-scale environmental controls of population dynamics and ecosystem processes. Here we seek to shed light on the causes of geographic patterns in tree mortality rates, and we consider some implications of the positive correlation between mortality rates and NPP. To reach these ends, we present seven hypotheses potentially explaining the correlation, develop an approach to help distinguish among the hypotheses, and apply the approach in a case study comparing a tropical and temperate forest. Based on our case study and literature synthesis, we conclude that no single mechanism controls geographic patterns of tree mortality rates. At least four different mechanisms may be at play, with the dominant mechanisms depending on whether the underlying productivity gradients are caused by climate or soil fertility. Two of the mechanisms are consequences of environmental selection for certain combinations of life-history traits, reflecting trade-offs between growth and defense (along edaphic productivity gradients) and between reproduction and persistence (as manifested in the adult tree stature continuum along climatic and edaphic gradients). The remaining two mechanisms are consequences of environmental influences on the nature and strength of ecological interactions: competition (along edaphic gradients) and pressure from plant enemies (along climatic gradients). For only one of these four mechanisms, competition, can high mortality rates be considered to be a relatively direct consequence of high NPP. The remaining mechanisms force us to adopt a different view of causality, in which tree growth rates and probability of mortality can vary with at least a degree of independence along productivity gradients. In many cases, rather than being a direct cause of high mortality rates, NPP may remain high in spite of high mortality rates. The independent influence of plant enemies and other factors helps explain why forest biomass can show little correlation, or even negative correlation, with forest NPP.

Graph theory is a body of mathematics dealing with problems of connectivity, flow, and routing in networks ranging from social groups to computer networks. Recently, network applications have erupted in many fields, and graph models are now being applied in landscape ecology and conservation biology, particularly for applications couched in metapopulation theory. In these applications, graph nodes represent habitat patches or local populations and links indicate functional connections among populations (i.e. via dispersal). Graphs are models of more complicated real systems, and so it is appropriate to review these applications from the perspective of modelling in general. Here we review recent applications of network theory to habitat patches in landscape mosaics. We consider (1) the conceptual model underlying these applications; (2) formalization and implementation of the graph model; (3) model parameterization; (4) model testing, insights, and predictions available through graph analyses; and (5) potential implications for conservation biology and related applications. In general, and for a variety of ecological systems, we find the graph model a remarkably robust framework for applications concerned with habitat connectivity. We close with suggestions for further work on the parameterization and validation of graph models, and point to some promising analytic insights.

Aims Large hurricanes have profound impacts on temperate forests, but owing to their infrequent nature these effects have rarely been examined in detail. In 1996, Hurricane Fran significantly damaged many long-term tree census plots in the Duke Forest on the North Carolina Piedmont, thereby providing an exceptional opportunity to examine pre- and post-hurricane forest compositional trajectories. Our goal was to examine immediate, short-term (0–4 years) and longer term (;5 year) hurricane-induced structural, spatial and compositional changes in the tree population (stem d.b.h > 1 cm) in the context of our detailed, long-term knowledge of the dynamics of these forests. Methods We surveyed stem damage and tree mortality in 34 long-term permanent plots (ca. 70-year record; 404–1 012 m 2 ) and 7 large mapped tree stands (ca. 20-year record; 5 250–65 000 m 2 ) representing both transition-phase, even-aged pine stands and uneven-aged upland hardwood forests. We employed three types of damage measures to quantify stand-level damage severity: percentage of stems damaged, percentage of basal area lost and a ‘stand-level damage index’. Second-order spatial analysis (Ripley’s K-function) was used to investigate patterns in tree mortality. Important findings Our study found hurricane effects on the structural attributes of Piedmont forests to be variable and patchy. Changes in tree species composition, however, were modest. Uprooting was the major damage type for the overstory trees [diameter at breast height (d.b.h.) >10 cm] apparently due to the exposure of the crowns to high wind combined with heavy rainfall prior to and during the storm. Saplings, juvenile trees and small trees (1–10 cm d.b.h.) of the understory and midstory were mainly damaged by being pinned or bent by their damaged large neighbors. Hurricane-induced tree mortality varied weakly among species, was positively correlated with pre-hurricane tree size and remained up to 2-fold higher than pre-hurricane background mortality 5 years after the hurricane. Spatial point pattern analysis revealed a patchy distribution of tree mortality during the hurricane sampling interval. Hurricane Fran resulted in a dramatic increase in average gap size from ca. 400 m 2 pre-hurricane to ca 1100 m 2 after the hurricane, whereas maximum gap sizes reached 18–34 times larger than the pre-hurricane levels.

Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A). We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.

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.

The dispersal of individuals among marine populations is of great importance to meta- population dynamics, population persistence, and species expansion. Understanding this connectivity between distant populations is key to their effective conservation and management. For many marine species, population connectivity is determined largely by ocean currents transporting larvae and juveniles between distant patches of suitable habitat. Recent work has focused on the biophysics of marine larval dispersal and its importance to population dynamics, although few studies have evaluated the spatial and temporal patterns of this potential dispersal. Here, we show how an Eulerian advection-diffusion approach can be used to model the dispersal of coral larvae between reefs throughout the Tropical Pacific. We illustrate how this connectivity can be analyzed using graph theory—an effective approach for exploring patterns in spatial connections, as well as for determining the importance of each site and pathway to local and regional connectivity. Results indicate that the scale (average distance) of dispersal in the Pacific is on the order of 50-150 km, consistent with recent studies in the Caribbean (Cowen, et al. 2006). Patterns in the dispersal graphs highlight pathways for larval dispersal along major ocean currents and through island chains. A series of critical island 'stepping stones' are discovered providing potential pathways across the equatorial currents and connect- ing distant island groups. Patterns in these dispersal graphs highlight possible pathways for species expansions, reveal connected upstream/downstream populations, and suggest areas that might be priori- tized for marine conservation efforts.

Neutral landscape models were originally developed to test the hypothesis that human-induced fragmentation produces patterns distinctly different from those associated with random processes. Other uses for neutral models have become apparent, including the development and testing of landscape metrics to characterize landscape pattern. Although metric development proved to be significant, the focus on metrics obscured the need for iterative hypothesis testing fundamental to the advancement of the discipline. We present here an example of an alternative neutral model and hypothesis designed to relate the process of landscape change to observed landscape patterns. The methods and program, QRULE, are described and options for statistical testing outlined. The results show that human fragmentation of landscapes results in a non-random association of land-cover types that can be describe by simple statistical methods. Options for additional landscape studies are discussed and access to QRULE described in the hope that these methods will be employed to advance our understanding of the processes that affect the structure and function in human dominated landscapes.

Understanding of spatial pattern and scale has been identified as a key issue in ecology, yet ecology has traditionally lacked necessary tools for making inference about relationships between scale-specific patterns. We introduce wavelet-coefficient regression, in which the dependent and independent variables are wavelet transformed prior to analysis, as a means to formalize scale-specific relationships in ecological data. We apply this method to data on vegetation and environmental factors related to water availability from Sequoia-Kings Canyon National Park (California, USA). We find that the wavelet transform and wavelet-coefficient regression efficiently characterize scale-specific pattern in these data. We also find that different environmental factors show up as good predictors of vegetation growth at different scales and that these differences in scale greatly facilitate interpretation of the mechanisms relating water availability to vegetation growth.

The issue of scaling impinges on every aspect of landscape ecology and much of ecology in general. Consequently, the topic has invited a vast commentary. One result of scaling research is so-called scaling laws that describe how observations scale (e.g., as power laws). Importantly, such scaling rules seldom derive from a process-based understanding of why they emerge. Alternatively, the task of scaling is often addressed via simulation models. This is a scaling operation about which we are somewhat less confident, although recent advances in computing power and computational statistics provide for some promising new solutions. Here, I focus on methods for scaling simulations developed at fine grain and small extent, to their implications over much larger extent. The intent in scaling is to simplify the model while retaining those details essential for larger-scale applications. This approach should lead to scaling rules that are well founded in fine-scale ecological process and yet useful for making predictions at the larger scales of management and environmental policy.

Goslee, S. C. (Nicholas School of the Environment and Earth Sciences, Duke University, Durham, NC 27708), W. A. Niering (Department of Botany, Connecticut College, New London, CT 06320), D. L. Urban and N. L. Christensen (Nicholas School of the Environment and Earth Sciences, Duke University, Durham, NC 27708). Influence of environment, history and vegetative interactions on stand dynamics in a Connecticut forest. J. Torrey Bot. Soc. 132: 471–482. 2005.—We examined the changing influence of environmental factors and land use history on the composition of the canopy tree, shrub, herb and tree seedling strata of a Connecticut forest over 45 years. The many herb and shrub species initially found in post-agricultural areas of this site declined or disappeared as the forest canopy closed. Tsuga canadensis ([L.] Carriere) increased in importance in the forest canopy until the introduction of the hemlock woolly adelgid (Adelges tsugae Annand). Shade-intolerant understory species are now increasing in ab...

Design of protected areas has focused on setting targets for representation of biodiversity, but often these targets do not include prescriptions as to how large protected areas should be or where they should be located. Principles of island biogeography theory have been applied with some success, but they have limitations. The so-called SLOSS (single large or several small reserves) debate hinged on applications of island biogeography theory to protected areas but was resolved only to the point that parties agreed there might be different approaches in different situations. Although proponents on both sides of the SLOSS debate generally agree that replicating protected areas is desirable, it is difficult to determine how to replicate reserves in terms of number and spatial arrangement. More important, many targets for representation often do not address issues of species persistence. Here, we used a geographic information system in a study of disturbance-sensitive mammals of the Yukon Territory, Canada, to design a protected-areas network that maintains a historical assemblage of species goals for component ecoregions. We simultaneously determined patterns of diversity as Whittaker's beta and compositional turnover and examined how these two measures can give further insights into reserve location and spatial arrangement. Both regional heterogeneity and compositional turnover between nonadjacent sites were significant predictors of the number of protected areas necessary to represent mammals within each ecoregion. Thus, protected-area planners can use diversity measures to identify number and spacing of protected areas within ecologically bounded regions. Resumen: El diseno de areas protegidas se ha enfocado a definir blancos para la representacion de biodiversidad, pero a menudo estos blancos no incluyen recomendaciones en cuanto al tamano que deben tener de las areas protegidas o donde deberan situarse. Los principios de la teoria de biogeografia de islas se han aplicado con cierto exito, pero tienen limitaciones. El debate denominado SLOSS (una reserva grande o varias pequenas) articulaba aplicaciones de la teoria de biogeografia de islas pero solo fue resuelto hasta el punto en que las diferentes opiniones acordaron que puede haber enfoques diferentes en situaciones diferentes. Aunque los proponentes de ambos puntos de vista del debate SLOSS generalmente estan de acuerdo en que es deseable la replicacion de areas protegidas, es dificil determinar como replicar reservas en terminos de numero y arreglo espacial. Mas notablemente, muchos blancos para representacion a menudo no abordan aspectos de la persistencia de especies. Aqui, utilizamos un sistema de informacion geografica (SIG) en un estudio de mamiferos sensibles a la perturbacion en el Territorio Yukon, Canada, para disenar una red de areas protegidas que mantenga un ensamble historico de especies en las ecoregiones que lo componen. Simultaneamente determinamos los patrones de biodiversidad beta de Whittaker y de recambio de composicion y examinamos como estas dos medidas pueden proporcionar mayor entendimiento sobre la localizacion de reservas y su arreglo espacial. Tanto la heterogeneidad regional como el recambio en la composicion entre sitios no adyacentes fueron predictores significativos del numero de areas protegidas necesario para representar a los mamiferos en cada ecoregion. Por lo tanto, los planificadores de areas protegidas pueden utilizar medidas de diversidad para identificar el numero y espaciamiento de areas protegidas en regiones limitadas ecologicamente.

Radiation is one of the primary influences on vegetation composition and spatial pattern. Topographic orientation is often used as a proxy for relative radiation load due to its effects on evaporative demand and local temperature. Common methods for incorporating this information (i.e., site measures of slope and aspect) fail to include daily or annual changes in solar orientation and shading effects from local topography. As a result, these static measures do not incorporate the level of spatial and temporal heterogeneity required to examine vegetation patterns at the landscape level. We developed a widely applicable method for estimating potential relative radiation (PRR) using digital elevation data and a widely used geographic information system (Arc/Info). We found significant differences among four increasingly comprehensive radiation proxies. Our GIS-based proxy compared well with estimates from more data-intensive and computationally rigorous radiation models. We note that several recent studies have not found strong correlations between vegetation pattern and landscape-scale differences in radiation. We suggest that these findings may be due to the use of proxies that were not accurately capturing variability in radiation, and we recommend PRR or similar measures for use in future vegetation analyses.

Forest fragmentation is a common process in forests worldwide, with implications for tree species composition and abundance. In particular, the effects of forest– non-forest edges on microclimate are often profound, usually resulting in increased light available to plants along the forest–non-forest edge. Using dendrochronological techniques, we assessed the effect of edges on the growth rates of four overstory species common in the North Carolina Piedmont: Acer rubrum, Liriodendron tulipifera, Liquidambar styraciflua, and Pinus taeda. Transects from the edge into the forest interior were established on 62 edges of varying aspect and ages in the Duke Forest (Durham, North Carolina, USA). Within a transect, all stems >10 cm in diameter were cored, and their spatial positions relative to the edge were recorded. Along each transect, a set of environmental and edaphic variables was measured including soil texture, soil concentrations of plant nutrients, and percentage of canopy closure. All transects were geo...

Management and restoration of vegetation patterns in ecosystems depends on an understanding of allogenic environmental factors that organize species assemblages and autogenic processes linked to assemblages. However, our ability to make strong inferences about vegetation–environment linkages in field studies is often limited due to correlations among environmental variables, spatial autocorrelation, and scale dependency of observations. This is particularly true in large, heterogeneous ecosystems such as the Everglades. Here, an extensive canal-and-levee system has modified historical fire regimes and hydropatterns while contributing large inputs of surface-water phosphorus (P), nitrogen (N) and cations such as sodium (Na). Some of these anthropogenic influences have been implicated as factors leading to the shift of sawgrass (Cladium jamaicense Crantz) and slough communities to an assemblage of weedy species such as cattail (Typha domingensis Pers.). To untangle the independent effect of multiple variables, we used a spatially explicit, multivariate approach to identify linkages among spatial patterns, environmental factors, and vegetation composition along a 10-km gradient of anthropogenic influence in the Everglades, an area immediately downstream from canal inflow structures. Clusters of plots were stratified among three zones (Impacted, Transition, and Reference), a design that allowed us to contrast vegetation–environment linkages and spatial patterns at multiple scales and degrees of ecosystem alteration. Along the 10-km gradient, partial Mantel tests showed that nutrients (phosphorus, nitrogen, and potassium) and hydropattern (frequency of dryness) were independently linked to patterns in fine-scale vegetation composition, but phosphorus was the only environmental variable linked to patterns of coarse-scale composition. Regardless of scale, the effect of distance from canal inflows accounted for variation in vegetation that could not be explained by other variables. A significant residual effect of spatial proximity among sampling locations also was detected and was highly suggestive of dispersal or other spatial determinants of vegetation pattern. However, this pure spatial effect was significantly stronger in the Transition and Impacted zones than in the Reference zone—fine-scale environmental variables explained all of the spatial structure in vegetation in the Reference zone. A further examination of spatial patterns in vegetation by using Mantel correlograms revealed significant heterogeneity at fine, local scales in the Reference zone, but this pattern progressively degraded toward homogeneity among closely neighboring locations in the Impacted zone. However, the fine-scale vegetation pattern in the Reference zone was hierarchically nested at a broader scale and yielded a similar coarse pattern across the landscape, whereas the coarse pattern in the Transition and Impacted zones was relatively heterogeneous and fragmented. Collectively, these results indicate that allogenic spatial and environmental factors related to the canal system have disrupted the coupling between pattern and process by altering fine-scale vegetation–environment linkages and spatial patterns characteristic of the natural Everglades ecosystem.

Landscape-level spatial estimates of soil water content are critical to understanding ecological processes and predicting watershed response to environmental change. Because soil moisture influences are highly variable at the landscape scale, most meteorological datasets are not detailed enough to depict spatial trends in the water balance at these extents. We propose a tactical approach to gather high-resolution field data for use in soil moisture models. Using these data, we (1) describe general soil moisture trends for a 6400 ha watershed in the Oregon Western Cascades, USA (2) use this description to identify environmental variables to stratify across in collecting data for a statistical explanatory model of soil moisture spatial pattern at the onset of seasonal drought, and (3) examine the spatial scale of variability in soil moisture measurements compared to the scale of variability in potential explanatory factors. The results indicate that soil moisture dynamics and controls are different for different soil depths across this mountainous watershed. Soil moisture variability exhibits complex spatial patterns that can be partially estimated (up to 50 percent of the variation accounted) with easily measurable climatic and terrain variables. The analysis incorporates both macroscale (climate) and mesoscale (topographic drainage and radiation) influences on the water balance. Without additional data on the distribution of edaphic and biotic factors, we are not able to model the variability of soil moisture at the microscale. The regression approach can be used to extrapolate field measurements across similar topographic areas to examine spatial patterns in forest vegetation and moisture-controlled ecological processes.

Across eastern North America, there is a temporal trend from open Quercus forests to closed forests with increased Acer rubrum in the understory. We used a series of Ripley's K(d) analyses to examine changes in the spatial pattern of Quercus and Acer rubrum stems greater than 2.5 cm DBH over 45 yr in a 2-ha mapped stand. Specifically, we asked whether changes over time were consistent with the hypothesis that Quercus is being competitively replaced by Acer rubrum. Both Acer rubrum and Quercus stems are spatially clumped, but have become less clumped over time. Stem mortality from Hurricane Fran (1996) was more clumped in all strata of the forest, at all spatial scales, than expected if damage had occurred to stems at random. Acer rubrum ingrowth occurred more often near established trees (all species) in the midstory, whereas Quercus ingrowth occurred less often near established trees in the midstory. The specific hypothesis that stems of Acer rubrum in the midstory of the forest are associated w...

As detailed terrain data becomes available, GIS terrain applications target larger geographic areas at finer resolutions. Processing the massive datasets involved in such applications presents significant challenges to GIS systems and demands algorithms that are optimized for both data movement and computation. In this paper we present efficient algorithms for flow routing on massive grid terrain datasets, extending our previous work on flow accumulation. Our algorithms are developed in the framework of external memory algorithms and use I/O-techniques to achieve efficiency. We have implemented the algorithms in the Terraflow system, which is the first comprehensive terrain flow software system designed and optimized for massive data. We compare the performance of Terraflow with that of state-of-the-art commercial and open-source GIS systems. On large terrains, Terraflow outperforms existing systems by a factor of 2 to 1,000, and is capable of solving problems no system was previously able to solve.

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers' actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.

Our society faces the pressing challenge of increasing agricultural production while minimizing negative consequences on ecosystems and the global climate. Indonesia, which has pledged to reduce greenhouse gas (GHG) emissions from deforestation while doubling production of several major agricultural commodities, exemplifies this challenge. Here we focus on palm oil, the world's most abundant vegetable oil and a commodity that has contributed significantly to Indonesia's economy. Most oil palm expansion in the country has occurred at the expense of forests, resulting in significant GHG emissions. We examine the extent to which land management policies can resolve the apparently conflicting goals of oil palm expansion and GHG mitigation in Kalimantan, a major oil palm growing region of Indonesia. Using a logistic regression model to predict the locations of new oil palm between 2010 and 2020 we evaluate the impacts of six alternative policy scenarios on future emissions. We estimate net emissions of 128.4-211.4 MtCO2 yr(-1) under business as usual expansion of oil palm plantations. The impact of diverting new plantations to low carbon stock land depends on the design of the policy. We estimate that emissions can be reduced by 9-10% by extending the current moratorium on new concessions in primary forests and peat lands, 35% by limiting expansion on all peat and forestlands, 46% by limiting expansion to areas with moderate carbon stocks, and 55-60% by limiting expansion to areas with low carbon stocks. Our results suggest that these policies would reduce oil palm profits only moderately but would vary greatly in terms of cost-effectiveness of emissions reductions. We conclude that a carefully designed and implemented oil palm expansion plan can contribute significantly towards Indonesia's national emissions mitigation goal, while allowing oil palm area to double.

Conservation organizations are increasingly employing representative-based conservation strategies to overcome the limits of a species-by-species approach and to expand the focus of conservation to include overall biodiversity and ecosystem processes. To compare focal-species, community-level, and physical-proxy approaches in terms of their ability to predict vegetation communities and capture rare species, we used plot-level data from the Amphibolite Mountains of North Carolina. We identified diagnostic species via indicator-species analysis to calculate predictability and capture rates at the focal-species and community levels. We performed classification and regression-tree analysis to determine whether the biotic communities could effectively be characterized by their physical environment and to assess community predictability at this scale. At both the focal-species level and the community level, common indicator species were most reliable when the indicator species were themselves habitat specialists occurring in distinct sites. In most cases, rare-species capture was maximized with a focal-species approach, but this approach required high levels of investment. Alternatively, conservation strategies based on physical proxies were not dependent on intense field surveys, but were less effective in capturing rare species. This approach may still provide an important first cut for narrowing down the number of sites requiring intense field surveys and finer-scale analysis. Both coarse-filter approaches provided effective mechanisms for targeting and protecting large-scale ecological processes and overall biodiversity, and community-level conservation also recognized the inherent value of communities beyond their capacity as representative indicators. An effective and efficient conservation-design strategy might employ each of these three conservation targets in a multistage approach. Conservation efforts could also benefit from further research into the ecological characteristics that regulate the distribution of rare species and the implications for species capture with these different conservation approaches. Resumen: Con mayor frecuencia, las organizaciones de conservacion utilizan estrategias de conservacion para superar los limites de un enfoque especie-por-especie y para expandir el enfoque de la conservacion para incluir procesos generales de biodiversidad y procesos. Para comparar los enfoques de especies focales, nivel comunidad e indicadores fisicos en terminos de su capacidad de predecir comunidades vegetales y capturar especies raras, utilizamos datos a nivel de parcela de las Montanas Amphibolite, Carolina del Norte. Identificamos especies diagnostico por medio de analisis de especies indicadoras para calcular la predictibilidad y capturar tasas en los niveles de especies focales y comunidad. Realizamos analisis de clasificacion y regresion para determinar si las comunidades bioticas podrian efectivamente caracterizarse por su ambiente fisico y para evaluar la predictibilidad de la comunidad a esta escala. Tanto en el nivel de especie focal como en el de comunidad, las especies indicadoras comunes fueron mas confiables cuando las especies indicadoras eran especialistas de habitat ocurriendo en distintos sitios. En la mayoria de los casos, la captura de especies raras se maximizo con la aproximacion de especie focal, pero esta aproximacion requirio altos niveles de inversion. Por otro lado, las estrategias de conservacion basadas en indicadores fisicos no dependieron de muestreos de campo intensivos, pero fueron menos efectivas en la captura de especies raras. Esta aproximacion aun puede proporcionar un importante primer corte para reducir el numero de sitios que requieren muestreos intensivos de campo y analisis a menor escala. Ambas aproximaciones de filtro grueso proporcionaron mecanismos efectivos para identificar y proteger procesos ecologicos a gran escala y biodiversidad en general, y la conservacion a nivel de comunidad reconocio ademas el valor inherente de las comunidades que se extienden mas alla de su capacidad como indicadores representativos. Un diseno de estrategia de conservacion efectiva y eficienta podria emplear cada uno de estos tres niveles de conservacion en un enfoque de multiples. Los esfuerzos de conservacion tambien podrian beneficiarse de mayor investigacion de los patrones de las caracteristicas ecologicas que regulan la distribucion de especies raras y las implicaciones de la captura de especies con estos enfoques de conservacion diferentes.

A goal of landscape ecology is to infer processes or constraints that generate spatial pattern in communities and ecosystems. The rich tradition of plant community ecology is now being extended to ...

An algorithm to estimate the parameter values of a transition forest landscape model (MOSAIC) from a gap model (FACET) is presented here. MOSAIC is semi-Markov; it includes random distributed holding times and fixed or deterministic delays in addition to transition probabilities. FACET is a terrain-sensitive version of ZELIG, a spatially explicit gap model. For each topographic class, the input to the algorithm consists of gap model tracer files identifying the cover type of each plot through time. These cover types or states are defined a priori. The method, based on individual plots of the FACET model, requires one FACET run initialized from the “gap” cover type and follows the time history of each plot. The algorithm estimates the transition probability by counting the number of transitions between each pair of states and estimates the fixed lags and the parameters of the probability density functions of the distributed delays by recording the times at which these transitions are made. These density functions are assumed to be Erlang; its two parameters, order and rate, are estimated using a nonlinear least squares procedure. Thus, as output, the algorithm produces four matrices at each terrain class: transition probabilities, fixed delays, and the two parameters for the Erlang distributions. The algorithm is illustrated by its application to two sites, high and low elevation, from the H.J. Andrews Forest in the Oregon Cascades. This scaling-up method helps to bridge the conceptual breach between landscape- and stand-scale models. To reflect landscape heterogeneity, the algorithm can be executed repetitively for many different terrain classes. While the method developed here focuses on FACET and MOSAIC, this general approach could be extended to use other fine-scale models or other forms of meta-models.

Ecologists are familiar with two data structures commonly used to represent landscapes. Vector-based maps delineate land cover types as polygons, while raster lattices represent the landscape as a grid. Here we adopt a third lattice data structure, the graph. A graph represents a landscape as a set of nodes (e.g., habitat patches) connected to some degree by edges that join pairs of nodes functionally (e.g., via dispersal). Graph theory is well developed in other fields, including geography (transportation networks, routing ap- plications, siting problems) and computer science (circuitry and network optimization). We present an overview of basic elements of graph theory as it might be applied to issues of connectivity in heterogeneous landscapes, focusing especially on applications of metapo- pulation theory in conservation biology. We develop a general set of analyses using a hypothetical landscape mosaic of habitat patches in a nonhabitat matrix. Our results suggest that a simple graph construct, the minimum spanning tree, can serve as a powerful guide to decisions about the relative importance of individual patches to overall landscape con- nectivity. We then apply this approach to an actual conservation scenario involving the

While ecologists have long recognized the key role of monitoring programs in natural-resource management, we have only recently come to appreciate the logistical difficulties of designing powerful yet efficient schemes for monitoring large, heterogeneous landscapes. Such designs are especially challenging if the signal to be monitored is uncertain, such as in the case of ecosystem response to climate change. I illustrate an approach in which a simulation model is used to design a monitoring scheme that focuses on application-specific sensitivities or uncertainties. Formal model analysis defines these sensitivities in the model's parameter space. These parametric domains are then mapped into geographic space by regressing model sensitivity on terrain variables in a geographic information system. Specific sites for monitoring are then selected by sampling with a two-stage stratified-cluster design from these parametrically sensitive or uncertain locations. As an example, I use a forest simulation model to d...

We use focal-species analysis to apply a graph-theoretic approach to landscape connectivity in the Coastal Plain of North Carolina. In doing so we demonstrate the utility of a mathematical graph as an ecological construct with respect to habitat connectivity. Graph theory is a well established mainstay of information technology and is concerned with highly efficient network flow. It employs fast algorithms and compact data structures that are easily adapted to landscape-level focal species analysis. American mink (Mustela vison) and prothonotary warblers (Protonotaria citrea) share the same habitat but have different dispersal capabilities, and therefore provide interesting comparisons on connections in the landscape. We built graphs using GIS coverages to define habitat patches and determined the functional distance between the patches with least-cost path modeling. Using graph operations concerned with edge and node removal we found that the landscape is fundamentally connected for mink and fundamentally unconnected for prothonotary warblers. The advantage of a graph-theoretic approach over other modeling techniques is that it is a heuristic framework which can be applied with very little data and improved from the initial results. We demonstrate the use of graph theory in a metapopulation context, and suggest that graph theory as applied to conservation biology can provide leverage on applications concerned with landscape connectivity.

Decades of fire exclusion have led to hazardous fuel accumulations and the deterioration of fire-dependent ecosystems, particularly in the American West. Managers are striving to return the ecological role of fire to many ecosystems and would benefit from a much better understanding of how forest structure and composition might change if fires were reintroduced. We used a forest gap model, developed for forests in the Sierra Nevada, California, USA, that integrates climate, fire, and forest dynamics to investigate forest response to changes in the fire regime. The model simulates a spatially heterogeneous fuel bed that is responsive to changes in forest condition, making it well suited for examining alternative management approaches for restoring Sierra Nevada forests after a century of fire exclusion. Presuppression forest basal area, species composition, and spatial autocor- relation structure were restored quickly, if simulated disturbances that caused substantial tree mortality were reintroduced. Simulations of harvest induced the highest levels of mortality and, thus, most effectively restored forest structure and composition. However, prescribed fires were just as effective in restoring forest structure and composition if they were sufficiently severe.

The connectivity of a landscape can influence the dynamics of disturbances such as fire. In fire-adapted ecosystems, fire suppression may increase the connectivity of fuels and could result in qualitatively different fire patterns and behavior. We used a spatially explicit forest simulation model developed for the Sierra Nevada to investigate how the frequency of surface fires influences the connectivity of burnable area within a forest stand, and how this connectivity varies along an elevation gradient. Connectivity of burnable area was a function of fuel loads, fuel moisture, and fuel bed bulk density. Our analysis isolated the effects of fuel moisture and fuel bed bulk density to emphasize the influence of fuel loads on connectivity. Connectivity was inversely related to fire frequency and generally increased with elevation. However, certain conditions of fuel moisture and fuel bed bulk density obscured these relationships. Nonlinear patterns in connectivity across the elevation gradient occurred as a result of gradients in fuel loads and fuel bed bulk density that are simulated by the model. Changes in connectivity with elevation could affect how readily fires can spread from low elevation sites to higher elevations.

Vegetation pattern on landscapes is the manifestation of physical gradients, biotic response to these gradients, and disturbances. Here we focus on the physical template as it governs the distribution of mixed-conifer forests in California’s Sierra Nevada. We extended a forest simulation model to examine montane environmental gradients, emphasizing factors affecting the water balance in these summer-dry landscapes. The model simulates the soil moisture regime in terms of the interaction of water supply and demand: supply depends on precipitation and water storage, while evapotranspirational demand varies with solar radiation and temperature. The forest cover itself can affect the water balance via canopy interception and evapotranspiration. We simulated Sierran forests as slope facets, defined as gridded stands of homogeneous topographic exposure, and verified simulated gradient response against sample quadrats distributed across Sequoia National Park. We then performed a modified sensitivity analysis of abiotic factors governing the physical gradient. Importantly, the model’s sensitivity to temperature, precipitation, and soil depth varies considerably over the physical template, particularly relative to elevation. The physical drivers of the water balance have characteristic spatial scales that differ by orders of magnitude. Across large spatial extents, temperature and precipitation as defined by elevation primarily govern the location of the mixed conifer zone. If the analysis is constrained to elevations within the mixed-conifer zone, local topography comes into play as it influences drainage. Soil depth varies considerably at all measured scales, and is especially dominant at fine (within-stand) scales. Physical site variables can influence soil moisture deficit either by affecting water supply or water demand; these effects have qualitatively different implications for forest response. These results have clear implications about purely inferential approaches to gradient analysis, and bear strongly on our ability to use correlative approaches in assessing the potential responses of montane forests to anthropogenic climatic change.

In the Sierra Nevada, distributions of forest tree species are largely controlled by the soil-moisture balance. Changes in temperature or precipitation as a result of increased greenhouse gas concentrations could lead to changes in species distributions. In addition, climatic change could increase the frequency and severity of wildfires. We used a forest gap model developed for Sierra Nevada forests to investigate the potential sensitivity of these forests to climatic change, including a changing fire regime. Fuel moisture influences the fire regime and couples fire to climate. Fires are also affected by fuel loads, which accumulate according to forest structure and composition. These model features were used to investigate the complex interactions between climate, fire, and forest dynamics. Eight hypothetical climate-change scenarios were simulated, including two general circulation model (GCM) predictions of a2 3CO2 world. The response of forest structure, species composition, and the fire regime to these changes in the climate were examined at four sites across an elevation gradient. Impacts on woody biomass and species composition as a result of climatic change were site specific and depended on the environmental constraints of a site and the environmental tolerances of the tree species simulated. Climatic change altered the fire regime both directly and indirectly. Fire frequency responded directly to climate’s influence on fuel moisture, whereas fire extent was affected by changes that occurred in either woody biomass or species composition. The influence of species composition on fuel-bed bulk density was particularly important. Future fires in the Sierra Nevada could be both more frequent and of greater spatial extent if GCM predictions prove true.

A spatially explicit forest gap model was developed for the Sierra Nevada, California, and is the first of its kind because it integrates climate, fire and forest pattern. The model simulates a forest stand as a grid of 15×15 m forest plots and simulates the growth of individual trees within each plot. Fuel inputs are generated from each individual tree according to tree size and species. Fuel moisture varies both temporally and spatially with the local site water balance and forest condition, thus linking climate with the fire regime. Fires occur as a function of the simulated fuel loads and fuel moisture, and the burnable area is simulated as a result of the spatially heterogeneous fuel bed conditions. We demonstrate the model’s ability to couple the fire regime to both climate and forest pattern. In addition, we use the model to investigate the importance of climate and forest pattern as controls on the fire regime. Comparison of model results with independent data indicate that the model performs well in several areas. Patterns of fuel accumulation, climatic control of fire frequency and the influence of fuel loads on the spatial extent of fires in the model are particularly well-supported by data. This model can be used to examine the complex interactions among climate, fire and forest pattern across a wide range of environmental conditions and vegetation types. Our results suggest that, in the Sierra Nevada, fuel moisture can exert an important control on fire frequency and this control is especially pronounced at sites where most of the annual precipitation is in the form of snow. Fuel loads, on the other hand, may limit the spatial extent of fire, especially at elevations below 1500 m. Above this elevation, fuel moisture may play an increasingly important role in limiting the area burned.

A linkage between the two major modeling approaches to forest dynamics, transition Markovian models and jabowa-foret type simulators, is generated by developing a compact model of forest dynamics. This patch transition model utilizes functional roles instead of species. The roles or types are based on the regeneration and mortality characteristics of tree species; specifically, the requirements of canopy gaps for regeneration and the capacity to create canopy gaps upon death. A gap-size plot can be assigned to each of a set of states defined according to dominance of one of the roles. Transition probabilities among these states and mean holding times in each transition lead to semi-Markovian analytical calculations of the stationary state probabilities. Forest dynamics, as the proportions of total canopy space occupied by each role in a collection of gap-size plots, can be analyzed and simulated using a chain of first-order differential equations to emulate the distributed time-delays. Additional fixed time-delays in the transition of every pair of states is also included to account for long latencies. In addition to simplifying the simulations, the resulting model can also utilize available results of the theory of semi-Markov processes; and therefore, can provide analytical guidance to the simulations, the feasibility of direct exploration of hypothesis and the possibility of fast computation from closed-form solutions and formulae. These advantages can especially be useful in the simulation of landscape dynamics and species-rich tropical forests.

Industrial-scale oil palm cultivation is rapidly expanding in Gabon, where it has the potential to drive economic growth, but also threatens forest, biodiversity and carbon resources. The Gabonese government is promoting an ambitious agricultural expansion strategy, while simultaneously committing to minimize negative environmental impacts of oil palm agriculture. This study estimates the extent and location of suitable land for oil palm cultivation in Gabon, based on an analysis of recent trends in plantation permitting. We use the resulting suitability map to evaluate two proposed approaches to minimizing negative environmental impacts: a High Carbon Stock (HCS) approach, which emphasizes forest protection and climate change mitigation, and a High Conservation Value (HCV) approach, which focuses on safeguarding biodiversity and ecosystems. We quantify the forest area, carbon stock, and biodiversity resources protected under each approach, using newly developed maps of priority species distributions and forest biomass for Gabon. We find 2.7–3.9 Mha of suitable or moderately suitable land that avoid HCS areas, 4.4 million hectares (Mha) that avoid HCV areas, and 1.2–1.7 Mha that avoid both. This suggests that Gabon's oil palm production target could likely be met without compromising important ecosystem services, if appropriate safeguards are put in place. Our analysis improves understanding of suitability for oil palm in Gabon, determines how conservation strategies align with national targets for oil palm production, and informs national land use planning.

We describe and apply a correspondence between two major modeling ap- proaches to forest dynamics: transition markovian models and gap models or JABOWA- FORET type simulators. A transition model can be derived from a gap model by defining states on the basis of species, functional roles, vertical structure, or other convenient cover types. A gap-size plot can be assigned to one state according to dominance of one of these cover types. A semi-Markov framework is used for the transition model by considering not only the transition probabilities among the states, but also the holding times in each transition. The holding times are considered to be a combination of distributed and fixed time delays. Spatial extensions are possible by considering collections of gap-size plots and the proportions of these plots occupied by each state. The advantages of this approach include: reducing simulation time, analytica-l guidance to the simulations, direct analytical exploration of hypothesis and the possibility of fast computation from closed-form solutions and formulae. These advantages can be useful in the simulation of landscape dynamics and of species-rich forests, as well as in designing management strategies. A preliminary ap- plication to the H. J. Andrews forest in the Oregon Cascades is presented for demonstration.