Balancing Energy Development and Conservation: A Method Utilizing Species Distribution Models

Alternative energy development is increasing, potentially leading to negative impacts on wildlife populations already stressed by other factors. Resource managers require a scientifically based methodology to balance energy development and species conservation, so we investigated modeling habitat suitability using Maximum Entropy to develop maps that could be used with other information to help site energy developments. We selected one species of concern, the Lesser Prairie-Chicken (LPCH; Tympanuchus pallidicinctus) found on the southern Great Plains of North America, as our case study. LPCH populations have been declining and are potentially further impacted by energy development. We used LPCH lek locations in the state of Kansas along with several environmental and anthropogenic parameters to develop models that predict the probability of lek occurrence across the landscape. The models all performed well as indicated by the high test area under the curve (AUC) scores (all >0.9). The inclusion of anthropogenic parameters in models resulted in slightly better performance based on AUC values, indicating that anthropogenic features may impact LPCH lek habitat suitability. Given the positive model results, this methodology may provide additional guidance in designing future survey protocols, as well as siting of energy development in areas of marginal or unsuitable habitat for species of concern. This technique could help to standardize and quantify the impacts various developments have upon at-risk species.     

A Quantitative Climate-Match Score for Risk-Assessment Screening of Reptile and Amphibian Introductions

Assessing climatic suitability provides a good preliminary estimate of the invasive potential of a species to inform risk assessment. We examined two approaches for bioclimatic modeling for 67 reptile and amphibian species introduced to California and Florida. First, we modeled the worldwide distribution of the biomes found in the introduced range to highlight similar areas worldwide from which invaders might arise. Second, we modeled potentially suitable environments for species based on climatic factors in their native ranges, using three sources of distribution data. Performance of the three datasets and both approaches were compared for each species. Climate match was positively correlated with species establishment success (maximum predicted suitability in the introduced range was more strongly correlated with establishment success than mean suitability). Data assembled from the Global Amphibian Assessment through NatureServe provided the most accurate models for amphibians, while ecoregion data compiled by the World Wide Fund for Nature yielded models which described reptile climatic suitability better than available point-locality data. We present three methods of assigning a climate-match score for use in risk assessment using both the mean and maximum climatic suitabilities. Managers may choose to use different methods depending on the stringency of the assessment and the available data, facilitating higher resolution and accuracy for herpetofaunal risk assessment. Climate-matching has inherent limitations and other factors pertaining to ecological interactions and life-history traits must also be considered for thorough risk assessment. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Reduced complexity models for regional aquatic habitat suitability assessment

Generalizable methods that identify suitable aquatic habitat across large river basins and regions are needed to inform resource management. Habitat suitability models intersect environmental variables to predict species occurrence, but are often data intensive and thus are typically developed at small spatial scales. This study estimated mean monthly aquatic habitat suitability throughout Utah (USA) for Bonneville Cutthroat Trout (Oncorhynchus clarkii utah) and Bluehead Sucker (Catostomus discobolus) with publicly available, geospatial datasets. We evaluated 15 habitat suitability models using unique combinations of percent of mean annual discharge, velocity, gradient, and stream temperature. Environmental variables were validated with observed conditions and species presence observations to verify habitat suitability estimates. Stream temperature, gradient, and discharge best predicted Bonneville Cutthroat Trout presence, and gradient and discharge best predicted Bluehead Sucker presence. Simple aquatic habitat suitability models outperformed models that used only streamflow to estimate habitat for both species, and are useful for conservation planning and water resources decision-making. This modeling approach could enable resource managers to prioritize stream restoration across vast regions within their management domain, and is potentially compatible with water management modeling to improve ecological objectives in management models.     

Model-Based Selection of Areas for the Restoration of Acrocephalus paludicola Habitats in NE Germany

The global Aquatic Warbler (Acrocephalus paludicola, Vieillot, 1817) population has suffered a major decline due to the large-scale destruction of its natural habitat (fen mires). The species is at risk of extinction, especially in NE Germany/NW Poland. In this study, we developed habitat suitability models based on satellite and environmental data to identify potential areas for habitat restoration on which further surveys and planning should be focused. To create a reliable model, we used all Aquatic Warbler presences in the study area since 1990 as well as additional potentially suitable habitats identified in the field. We combined the presence/absence regression tree algorithm Cubist with the presence-only algorithm Maxent since both commonly outperform other algorithms. To integrate the separate model results, we present a new way to create a metamodel using the initial model results as variables. Additionally, a histogram approach was applied to further reduce the final search area to the most promising sites. Accuracy increased when using both remote sensing and environmental data. It was highest for the integrated metamodel (Cohen’s Kappa of 0.4, P < 0.001). The final result of this study supports the selection of the most promising sites for Aquatic Warbler habitat restoration.     

Assessing the Effects of Management Alternatives on Habitat Suitability in a Forested Landscape of Northeastern China

Forest management often has cumulative, long-lasting effects on wildlife habitat suitability and the effects may be impractical to evaluate using landscape-scale field experiments. To understand such effects, we linked a spatially explicit landscape disturbance and succession model (LANDIS) with habitat suitability index (HSI) models to assess the effects of management alternatives on habitat suitability in a forested landscape of northeastern China. LANDIS was applied to simulate future forest landscape changes under four management alternatives (no cutting, clearcutting, selective cutting I and II) over a 200-year horizon. The simulation outputs were linked with HSI models for three wildlife species, the red squirrel (Sciurus vulgaris), the red deer (Cervus elaphus) and the hazel grouse (Bonasa bonasia). These species are chosen because they represent numerous species that have distinct habitat requirements in our study area. We assessed their habitat suitability based on the mean HSI values, which is a measure of the average habitat quality. Our simulation results showed that no one management scenario was the best for all species and various forest management scenarios would lead to conflicting wildlife habitat outcomes. How to choose a scenario is dependent on the trade-off of economical, ecological and social goals. Our modeling effort could provide decision makers with relative comparisons among management scenarios from the perspective of biodiversity conservation. The general simulation results were expected based on our knowledge of forest management and habitat relationships of the species, which confirmed that the coupled modeling approach correctly simulated the assumed relationships between the wildlife, forest composition, age structure, and spatial configuration of habitat. However, several emergent results revealed the unexpected outcomes that a management scenario may lead to.     

Effective Control of Aquatic Invasive Species in Tropical Australia

Often ecologists and natural resource managers can easily access data on invasive species occurrence across a region. Yet, collecting species abundance data over a large area is arguably more important for decision making, but inherently costly, so methods which can provide robust information at low-cost are particularly valuable. Studies of species distribution often use occurrence data to build models of the environmental niche. Environmental suitability derived from such models may be used to predict the potential distributions of species. The ability of such models to predict spatial patterns in abundance have recently been demonstrated. Here we tested the relationship of environmental suitability with local abundance of an aquatic invasive species, olive hymenachne (Hymenachne amplexicaulis) in the Wet Tropics of Australia. Ordinary least squares and quantile regressions revealed a positive relationship between environmental suitability and local abundance of olive hymenachne. We expand on this and use the relationship between environmental suitability and local abundance to quantify the effectiveness of management (reduction in local abundance) under four different management investments. We show that the upper limit of abundance can be used to evaluate management effectiveness based on varying investments, and that ongoing management is the most effective at reducing local abundance. We discuss implications of this in addressing important problems in invasive species management.     

Resource Selection Probability Functions for Gopher Tortoise: Providing a Management Tool Applicable Across the Species’ Range

The gopher tortoise (Gopherus polyphemus) is protected by conservation policy throughout its range. Efforts to protect the species from further decline demand detailed understanding of its habitat requirements, which have not yet been rigorously defined. Current methods of identifying gopher tortoise habitat typically rely on coarse soil and vegetation classifications, and are prone to over-prediction of suitable habitat. We used a logistic resource selection probability function in an information-theoretic framework to understand the relative importance of various environmental factors to gopher tortoise habitat selection, drawing on nationwide environmental datasets, and an existing tortoise survey of the Ft. Benning military base. We applied the normalized difference vegetation index (NDVI) as an index of vegetation density, and found that NDVI was strongly negatively associated with active burrow locations. Our results showed that the most parsimonious model included variables from all candidate model types (landscape features, topography, soil, vegetation), and the model groups describing soil or vegetation alone performed poorly. These results demonstrate with a rigorous quantitative approach that although soil and vegetation are important to the gopher tortoise, they are not sufficient to describe suitable habitat. More widely, our results highlight the feasibility of constructing highly accurate habitat suitability models from data that are widely available throughout the species’ range. Our study shows that the widespread availability of national environmental datasets describing important components of gopher tortoise habitat, combined with existing tortoise surveys on public lands, can be leveraged to inform knowledge of habitat suitability and target recovery efforts range-wide.     

Assessing Land-Use Impacts on Natural Resources

/ Much information is available on changes that occur in natural resources from both spatially-explicit data on environmental conditions and models of the interactions of these conditions and resources with human activities. The strategy for assessing land-use impacts on natural resources developed in this paper provides a framework for using relevant data and models to address questions of how management practices can promote both use and protection of resources. This assessment strategy integrates spatially explicit environmental data using geographic information systems (GIS) with computer models that simulate changes in land cover in response to land-use impacts. The computer models also simulate susceptibility of species to changes in habitat suitability and landscape patterns. The approach is applied to management of limestone barrens on the Oak Ridge Reservation in East Tennessee. Potential limestone barrens habitats are identified by overlaying appropriate soils, geology, slope, and land-use/land-cover conditions. Their validity is tested against known sites containing rare species that occur in these habitats. The location of habitats at risk in the aftermath of human activities is determined by using an available area model that identifies the size and proximity of sites that particular types of species can no longer use as habitat. The resulting risk map can be used in land management planning. The approach uses readily available in situ and remotely sensed data and is applicable to a wide range of locations and land-use scenarios. This approach can be refined based on needs identified by land managers and on the sensitivity of the results to the resolution of available resource information.KEY WORDS: Land management; Assessment; Habitat characterization; Limestone barrens; Ecological modeling; Geographic information systems     

Modeling Habitat Suitability for Complex Species Distributions by Environmental-Distance Geometric Mean

This paper presents a new habitat suitability modeling method whose main properties are as follows: (1) It is based on the density of observation points in the environmental space, which enables it to fit complex distributions (e.g. nongaussian, bimodal, asymmetrical, etc.). (2) This density is modeled by computing the geometric mean to all observation points, which we show to be a good trade-off between goodness of fit and prediction power. (3) It does not need any absence information, which is generally difficult to collect and of dubious reliability. (4) The environmental space is represented either by an expert-selection of standardized variables or the axes of a factor analysis [in this paper we used the Ecological Niche Factor Analysis (ENFA)].We first explain the details of the geometric mean algorithm and then we apply it to the bearded vulture (Gypaetus barbatus) habitat in the Swiss Alps. The results are compared to those obtained by the median algorithm and tested by jack-knife cross-validation. We also discuss other related algorithms (BIOCLIM, HABITAT, and DOMAIN). All these analyses were implemented into and performed with the ecology-oriented GIS software BIOMAPPER 2.0.The results show the geometric mean to perform better than the median algorithm, as it produces a tighter fit to the bimodal distribution of the bearded vulture in the environmental space. However, the median algorithm being quicker, it could be preferred when modeling more usual distribution.     

Modeling Protected Species Habitat and Assigning Risk to Inform Regulatory Decisions

In the United States, environmental regulatory agencies are required to use “best available” scientific information when making decisions on a variety of issues. However, agencies are often hindered by coarse or incomplete data, particularly as it pertains to threatened and endangered species protection. Stakeholders often agree that more resolute and integrated processes for decision-making are desirable. We demonstrate a process that uses species occurrence data for a federally endangered insect (Karner blue butterfly), a readily available habitat modeling tool, and spatially explicit information about an important Michigan commodity (tart cherries). This case study has characteristics of many protected species regulatory decisions in that species occurrence data were sparse and unequally distributed; regulatory decisions (on pesticide use) were required with potentially significant impacts on a viable agricultural industry; and stakeholder relations were diverse, misinformed, and, in some situations, unjustly contentious. Results from our process include a large-scale, empirically derived habitat suitability map for the focal species and a risk ranking of tart cherry orchards with risk based on the likelihood that pesticide applications will influence the focal protected species. Although the majority (77%) of pesticide-influence zones overlapped Karner blue butterfly habitat, risk scores associated with each orchard were low. Through our process we demonstrated that spatially explicit models can help stakeholders visualize and quantify potential protected species effects. In addition, model outputs can serve to guide field activities (e.g., species surveys and implementation of pesticide buffer zones) that help minimize future effects.     

A method to create simplified versions of existing habitat suitability index (HSI) models

The habitat evaluation procedures (HEP), developed by the US Fish and Wildlife Service, are widely used in the United States to determine the impacts of major construction projects on fish and wildlife habitats. HEP relies heavily on habitat suitability index (HSI) models that use measurements of important habitat characteristics to rate habitat quality for a species on a scale of 0 (unsuitable) to 1.0 (optimal). This report describes a method to simplify existing HSI models to reduce the time and expense involved in sampling habitat variables. Simplified models for three species produced HSI values within 0.2 of those predicted by the original models 90% of the time. Simplified models are particularly useful for rapid habitat inventories and evaluations, wildlife management, and impact assessments in extensive areas or with limited time and personnel.     

Prioritizing Stream Barrier Removal to Maximize Connected Aquatic Habitat and Minimize Water Scarcity

Instream barriers, such as dams, culverts, and diversions, alter hydrologic processes and aquatic habitat. Removing uneconomical and aging instream barriers is increasingly used for river restoration. Historically, selection of barrier removal projects used score‐and‐rank techniques, ignoring cumulative change and the spatial structure of stream networks. Likewise, most water supply models prioritize either human water uses or aquatic habitat, failing to incorporate both human and environmental water use benefits. Here, a dual‐objective optimization model identifies barriers to remove that maximize connected aquatic habitat and minimize water scarcity. Aquatic habitat is measured using monthly average streamflow, temperature, channel gradient, and geomorphic condition as indicators of aquatic habitat suitability. Water scarcity costs are minimized using economic penalty functions while a budget constraint specifies the money available to remove barriers. We demonstrate the approach using a case study in Utah's Weber Basin to prioritize removal of instream barriers for Bonneville cutthroat trout, while maintaining human water uses. Removing 54 instream barriers reconnects about 160 km of quality‐weighted habitat and costs approximately US$10 M. After this point, the cost‐effectiveness of removing barriers to connect river habitat decreases. The modeling approach expands barrier removal optimization methods by explicitly including both economic and environmental water uses.     

Conservation and Management for Multiple Species: Integrating Field Research and Modeling into Management Decisions

Multiple-species reserves aim at supporting viable populations of selected species. Population viability analysis (PVA) is a group of methods for predicting such measures as extinction risk based on species-specific data. These methods include models that simulate the dynamics of a population or a metapopulation. A PVA model for the California gnatcatcher in Orange County was developed with landscape (GIS) data on the habitat characteristics and requirements and demographic data on population dynamics of the species. The potential applications of this model include sensitivity analysis that provides guidance for planning fieldwork, designing reserves, evaluating management options, and assessing human impact. The method can be extended to multiple species by combining habitat suitability maps for selected species with weights based on the threat faced by each species, and the contribution of habitat patches to the persistence of each species. These applications and extensions, together with the ability of the model to combine habitat and demographic data, make PVA a powerful tool for the design, conservation, and management of multiple species reserves.     

An analytical platform for cumulative impact assessment based on multiple futures: the impact of petroleum drilling and forest harvesting on moose (Alces alces) and marten (Martes americana) habitats in northeastern British Columbia

The combined influence on the environment of all projects occurring in a single area is evaluated through cumulative impact assessments (CIA), which consider the consequences of multiple projects, each insignificant on its own, yet important when evaluated collectively. Traditionally, future human activities are included in CIA using an analytical platform, commonly based on complex models that supply precise predictions but with reduced accuracy. To compensate for the lack of accuracy in current CIA approaches, we propose a shift in the paradigm governing CIA. The paradigm shift involves a change in the focus of CIA investigations from the detailed analysis of one unlikely future to the identification of the patterns describing multiple potential future changes in the environment. To illustrate the approach, a set of 144 possible and equally likely futures were developed that aimed to identify the potential impacts of forest harvesting and petroleum drilling on the habitat suitability of moose and marten in northeast British Columbia, Canada. The evolution of two measures of habitat suitability (average habitat suitability index and surface of the stands with habitat suitability index >0.5) revealed that the human activities could induce cycles in the habitat dynamics of moose and marten. The planning period of 100 years was separated into three distinct periods following a sinusoidal pattern (i.e., increase - constant - decrease in the habitat suitability measures). The attributes that could induce significant changes in the assessment of environment are the choice of harvesting age and species.     

Morphodynamic Effects on the Habitat of Juvenile Cyprinids (<Emphasis Type="Italic">Chondrostoma nasus</Emphasis>) in a Restored Austrian Lowland River

At the Sulm River, an Austrian lowland river, an ecologically orientated flood protection project was carried out from 1998-2000. Habitat modeling over a subsequent 3-year monitoring program (2001-2003) helped assess the effects of river bed embankment and of initiating a new meander by constructing a side channel and allowing self-developing side erosion. Hydrodynamic and physical habitat models were combined with fish-ecological methods. The results show a strong influence of riverbed dynamics on the habitat quality and quantity for the juvenile age classes (0+, 1+, 2+) of nase (Chondrostoma nasus), a key fish species of the Sulm River. The morphological conditions modified by floods changed significantly and decreased the amount of weighted usable areas. The primary factor was river bed aggradation, especially along the inner bend of the meander. This was a consequence of the reduced sediment transport capacity due to channel widening in the modeling area. The higher flow velocities and shallower depths, combined with the steeper bank angle, reduced the Weighted Useable Areas (WUAs) of habitats for juvenile nase. The modeling results were evaluated by combining results of mesohabitat-fishing surveys and habitat quality assessments. Both, the modeling and the fishing results demonstrated a reduced suitability of the habitats after the morphological modifications, but the situation was still improved compared to the pre-restoration conditions at the Sulm River.     

Testing a GIS Model of Habitat Suitability for a Declining Grassland Bird

Demand for information that can be used to manage loggerhead shrikes has recently increased because of concern over declining populations and loss of open, non-forested habitat. A previously-developed habitat model was modified to predict shrike habitat quality on Fort Riley Military Reservation (FRMR) in Kansas. Shrike habitat suitability indices were calculated based on the amount of potential and usable foraging habitat, and the number of potential nesting sites within a specified area. Interpretation of high quality digital photographs was used to delineate land cover classes, hedgerows and tree counts. These data were entered into a geographic information system (GIS) as individual data sets. The shrike habitat model was then employed to produce a GIS database predicting low, moderate, and high quality shrike habitat throughout the Reservation. Model results indicated that 67% of the Reservation was suitable habitat for loggerhead shrikes. Although over 80% of FRMR was mapped as grassland, the presence of few to several isolated trees or hedgerows was identified as a key factor in modeling habitat suitability. The accuracy of the GIS model was 82% in predicting suitable (moderate and high quality) loggerhead shrike habitat using an independent set of 66 recent shrike observations. The number of potential nesting sites and percent cover of usable foraging habitat were significantly related to habitat suitability of the sites occupied by shrikes.     

Management of the Spring Snowmelt Recession in Regulated Systems

In an effort to restore predictable ecologically relevant spring snowmelt recession flow patterns in rivers regulated by dams, this study defined a methodology by which spring flow regimes can be modeled in regulated systems from the quantifiable characteristics of spring snowmelt recessions in unregulated rivers. An analysis of eight unregulated rivers across the Sierra Nevada mountain range in California found that unregulated systems behaved similarly with respect to seasonal spring patterns and recession limb curvature, and thus prescribed flows could be designed in a manner that mimics those predictable characteristics. Using the methodology to quantify spring recession flows in terms of a daily percent decrease in flow, a series of flow recession scenarios were created for application in an existing hydrodynamic model for the regulated Rubicon River. The modeling results showed that flow recessions with slow ramping rates similar to those observed in unregulated rivers (less than 10% per day) were likely to be protective of native aquatic species, such as the Foothill yellow‐legged frog, while flows that receded at greater rates would likely result in desiccation of egg masses and potential stranding of tadpoles and fry. Furthermore, recession rates of less than 10% per day provided the most spatially diverse hydraulic habitat in the modeled domain for an appropriate duration in spring to support all native species guilds and maximize aquatic biodiversity.     

Using a Down-Scaled Bioclimate Envelope Model to Determine Long-Term Temporal Connectivity of Garry oak (<Emphasis Type="Italic">Quercus garryana</Emphasis>) Habitat in Western North America: Implications for Protected Area Planning

Under the Canadian Species at Risk Act (SARA), Garry oak (Quercus garryana) ecosystems are listed as “at-risk” and act as an umbrella for over one hundred species that are endangered to some degree. Understanding Garry oak responses to future climate scenarios at scales relevant to protected area managers is essential to effectively manage existing protected area networks and to guide the selection of temporally connected migration corridors, additional protected areas, and to maintain Garry oak populations over the next century. We present Garry oak distribution scenarios using two random forest models calibrated with down-scaled bioclimatic data for British Columbia, Washington, and Oregon based on 1961–1990 climate normals. The suitability models are calibrated using either both precipitation and temperature variables or using only temperature variables. We compare suitability predictions from four General Circulation Models (GCMs) and present CGCM2 model results under two emissions scenarios. For each GCM and emissions scenario we apply the two Garry oak suitability models and use the suitability models to determine the extent and temporal connectivity of climatically suitable Garry oak habitat within protected areas from 2010 to 2099. The suitability models indicate that while 164 km² of the total protected area network in the region (47,990 km²) contains recorded Garry oak presence, 1635 and 1680 km² of climatically suitable Garry oak habitat is currently under some form of protection. Of this suitable protected area, only between 6.6 and 7.3% will be “temporally connected” between 2010 and 2099 based on the CGCM2 model. These results highlight the need for public and private protected area organizations to work cooperatively in the development of corridors to maintain temporal connectivity in climatically suitable areas for the future of Garry oak ecosystems.     

Identifying Conservation and Restoration Priorities for Saproxylic and Old-Growth Forest Species: A Case Study in Switzerland

Saproxylic (dead-wood-associated) and old-growth species are among the most threatened species in European forest ecosystems, as they are susceptible to intensive forest management. Identifying areas with particular relevant features of biodiversity is of prime concern when developing species conservation and habitat restoration strategies and in optimizing resource investments. We present an approach to identify regional conservation and restoration priorities even if knowledge on species distribution is weak, such as for saproxylic and old-growth species in Switzerland. Habitat suitability maps were modeled for an expert-based selection of 55 focal species, using an ecological niche factor analyses (ENFA). All the maps were then overlaid, in order to identify potential species’ hotspots for different species groups of the 55 focal species (e.g., birds, fungi, red-listed species). We found that hotspots for various species groups did not correspond. Our results indicate that an approach based on “richness hotspots” may fail to conserve specific species groups. We hence recommend defining a biodiversity conservation strategy prior to implementing conservation/restoration efforts in specific regions. The conservation priority setting of the five biogeographical regions in Switzerland, however, did not differ when different hotspot definitions were applied. This observation emphasizes that the chosen method is robust. Since the ENFA needs only presence data, this species prediction method seems to be useful for any situation where the species distribution is poorly known and/or absence data are lacking. In order to identify priorities for either conservation or restoration efforts, we recommend a method based on presence data only, because absence data may reflect factors unrelated to species presence.     

Quantifying Florida Bay Habitat Suitability for Fishes and Invertebrates Under Climate Change Scenarios

The Florida Bay ecosystem supports a number of economically important ecosystem services, including several recreational fisheries, which may be affected by changing salinity and temperature due to climate change. In this paper, we use a combination of physical models and habitat suitability index models to quantify the effects of potential climate change scenarios on a variety of juvenile fish and lobster species in Florida Bay. The climate scenarios include alterations in sea level, evaporation and precipitation rates, coastal runoff, and water temperature. We find that the changes in habitat suitability vary in both magnitude and direction across the scenarios and species, but are on average small. Only one of the seven species we investigate (Lagodon rhomboides, i.e., pinfish) sees a sizable decrease in optimal habitat under any of the scenarios. This suggests that the estuarine fauna of Florida Bay may not be as vulnerable to climate change as other components of the ecosystem, such as those in the marine/terrestrial ecotone. However, these models are relatively simplistic, looking only at single species effects of physical drivers without considering the many interspecific interactions that may play a key role in the adjustment of the ecosystem as a whole. More complex models that capture the mechanistic links between physics and biology, as well as the complex dynamics of the estuarine food web, may be necessary to further understand the potential effects of climate change on the Florida Bay ecosystem.