A rapid assessment of landscape biodiversity using diversity profiles of arthropod morphospecies

Context

The assessment of land-use impacts on biodiversity is one of the central themes of landscape ecology and conservation biology. However, due to the complexity of biodiversity, it is impossible to obtain complete information about the diversity of all species even for small areas, necessitating the selection of individual species or assemblages thereof as species surrogate. In parts of the world where taxonomic expertise is lacking, species identification has hindered progress in biodiversity conservation, and the only practical, relatively-accurate option, is the use of taxonomic minimalism.

Objective

We carried out a rapid biodiversity assessment based on three surrogates—land-use (driver-surrogate), terrestrial arthropods (species-surrogate) and morphospecies (taxonomic-surrogate)—to determine the impacts of land-use on biodiversity of the Western Region (Ghana), an area covering ~4 % of the West African biodiversity hotspot.

Method

We used diversity profiles to visualize the distribution of a total of 8848 arthropod individuals over seven land-use types which define the complete heterogeneity of the landscape.

Results

Here, we present both sample and asymptotic diversity profiles of arthropod morphospecies for each land-use type and the potential of each land-use type for conserving arthropods.

Conclusions

We conclude that (1) the morphospecies approach is useful for detecting differences in species diversity of land-use types; (2) the concept of asymptotic diversity may not be necessary for land-use based biodiversity comparison; and (3) maximum diversity profiles are useful for determining the land-use conservation values in cases where pristine areas are not available.

     

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

Context

Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process-based ecosystem and landscape models, respectively, were used concurrently on four regional climate change assessments in the eastern Unites States.

Objectives

We compared predictions for 30 species from TreeAtlas, Linkages, and LANDIS PRO, using two climate change scenarios on four regions, to derive a more robust assessment of species change in response to climate change.

Methods

We calculated the ratio of future importance or biomass to current for each species, then compared agreement among models by species, region, and climate scenario using change classes, an ordinal agreement score, spearman rank correlations, and model averaged change ratios.

Results

Comparisons indicated high agreement for many species, especially northern species modeled to lose habitat. TreeAtlas and Linkages agreed the most but each also agreed with many species outputs from LANDIS PRO, particularly when succession within LANDIS PRO was simulated to 2300. A geographic analysis showed that a simple difference (in latitude degrees) of the weighted mean center of a species distribution versus the geographic center of the region of interest provides an initial estimate for the species’ potential to gain, lose, or remain stable under climate change.

Conclusions

This analysis of multiple models provides a useful approach to compare among disparate models and a more consistent interpretation of the future for use in vulnerability assessments and adaptation planning.

     

Step-wise drops in modularity and the fragmentation of exploited marine metapopulations

Context

Many nearshore species are distributed in habitat patches connected only through larval dispersal. Genetic research has shown some spatial structure of such metapopulations and modeling studies have shed light onto possible patterns of connectivity and barriers. However, little is known about human impact on their spatial structure and patterns of connectivity.

Objectives

We examine the effects of fishing on the spatial and temporal dynamics of metapopulations of sedentary marine species (red sea urchin and red abalone) interconnected by larval dispersal.

Methods

We constructed a metapopulation model to simulate abalone and sea urchin metapopulations experiencing increasing levels of fishing mortality. We performed the modularity analysis on the yearly larval connectivity matrices produced by these simulations, and analyzed the changes of modularity and the formation of modules over time as indicators of spatial structure.

Results

The analysis revealed a strong modular spatial structure for abalone and a weak spatial signature for sea urchin. In abalone, under exploitation, modularity takes step-wise drops on the path to extinction, and modules breakdown into smaller fragments followed by module and later metapopulation collapse. In contrast, sea urchin showed high modularity variation, indicating high- and low-mixing years, but an abrupt collapse of the metapopulation under strong exploitation.

Conclusions

The results identify a disruption in larval connectivity and a pattern of collapse in highly modular nearshore metapopulations. These results highlight the ability of modularity to detect spatial structure in marine metapopulations, which varies among species, and to show early changes in the spatial structure of exploited metapopulations.

     

Environmental heterogeneity and biotic interactions as potential drivers of spatial patterning of shorebird nests

Context

Species distributions are driven by a wide variety of abiotic and biotic factors, including nest placement for breeding individuals. As such, the spatial distribution of nests within a landscape can reflect environmental heterogeneity, habitat preferences, or even interactions with predators and other species.

Objectives

We determined the extent to which environmental heterogeneity and predation risk accounted for the observed spatial distribution of nests.

Methods

We assessed the spatial distribution of 112 nests of a migratory shorebird, the Hudsonian Godwit (Limosa haemastica), at Beluga River, Alaska, from 2009 to 2012, and explicitly tested for the relative influence of habitat characteristics and predation risk on nest locations. We also evaluated the effect of nest location, distance to conspecific nests, and proximity to roads on nest fate using 64 nests that were monitored through completion.

Results

Hudsonian Godwit nests were clustered across the landscape despite a lack of significant spatial autocorrelation (i.e., patchiness) in vegetation characteristics at either the micro- or landscape scale. Nest fate also was not predicted by either the distance to the nearest conspecific neighbor or proximity to roads. Thus, neither habitat characteristics nor predation risk explained the clustering of godwit nests.

Conclusions

These results suggest that godwits may select nest locations based more on social cues than underlying heterogeneity in vegetation or predation risk. As such, intra- and inter-specific interactions should be considered when developing management plans for species of conservation concern.

     

A multi-method approach to delineate and validate migratory corridors

Context

Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models.

Objectives

We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania.

Methods

We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type.

Results

Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use.

Conclusions

The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.

     

Grassland songbird occurrence on remnant prairie patches is primarily determined by landscape characteristics

Context

North American grassland songbird populations have declined significantly due to habitat loss and fragmentation. Understanding the influence of the surrounding landscape on prairie fragment occupancy is vital for predicting the fate of grassland birds in these heavily altered landscapes.

Objectives

We examined the relative importance of local and landscape variables on grassland bird occupancy of prairie fragments using a focal-patch study. We also investigated the spatial scale at which landscape variables were most influential.

Methods

We surveyed birds on 29 unplowed prairie fragments in western Minnesota and eastern North and South Dakota. We quantified local habitat on the fragment using vegetation surveys and aerial photographs and the landscape surrounding the fragment out to 4 km using aerial photographs. We analyzed occupancy using multi-model approaches applied to multiple logistic regression.

Results

Of 38 species encountered, nine were neither too rare nor too abundant to be analyzed. Predictors of patch occupancy were unique for each bird species, yet general patterns emerged. For eight species, landscape variables were more important than local variables. Mostly, those landscape variables measured configuration (e.g., edge density) and not composition (e.g., percent cover of a particular matrix element). Landscape effects were mostly from variables measured at the greatest extents from the prairie fragment.

Conclusions

Using a focal-patch study design we demonstrated the importance of the surrounding landscape, often out to 4 km from the fragment edge, on prairie occupancy by grassland birds. Effective management of grassland songbirds will require attention to the landscape context of prairie fragments.

     

Spatial resilience of forested landscapes under climate change and management

Context

Resilience, the ability to recover from disturbance, has risen to the forefront of scientific policy, but is difficult to quantify, particularly in large, forested landscapes subject to disturbances, management, and climate change.

Objectives

Our objective was to determine which spatial drivers will control landscape resilience over the next century, given a range of plausible climate projections across north-central Minnesota.

Methods

Using a simulation modelling approach, we simulated wind disturbance in a 4.3 million ha forested landscape in north-central Minnesota for 100 years under historic climate and five climate change scenarios, combined with four management scenarios: business as usual (BAU), maximizing economic returns (‘EcoGoods’), maximizing carbon storage (‘EcoServices’), and climate change adaption (‘CCAdapt’). To estimate resilience, we examined sites where simulated windstorms removed >70% of the biomass and measured the difference in biomass and species composition after 50 years.

Results

Climate change lowered resilience, though there was wide variation among climate change scenarios. Resilience was explained more by spatial variation in soils than climate. We found that BAU, EcoGoods and EcoServices harvest scenarios were very similar; CCAdapt was the only scenario that demonstrated consistently higher resilience under climate change. Although we expected spatial patterns of resilience to follow ownership patterns, it was contingent upon whether lands were actively managed.

Conclusions

Our results demonstrate that resilience may be lower under climate change and that the effects of climate change could overwhelm current management practices. Only a substantial shift in simulated forest practices was successful in promoting resilience.

     

Assessing wild bees in perennial bioenergy landscapes: effects of bioenergy crop composition,landscape configuration,and bioenergy crop area

Context

Wild bee populations are currently under threat, which has led to recent efforts to increase pollinator habitat in North America. Simultaneously, U.S. federal energy policies are beginning to encourage perennial bioenergy cropping (PBC) systems, which have the potential to support native bees.

Objectives

Our objective was to explore the potentially interactive effects of crop composition, total PBC area, and PBC patches in different landscape configurations.

Methods

Using a spatially-explicit modeling approach, the Lonsdorf model, we simulated the impacts of three perennial bioenergy crops (PBC: willow, switchgrass, and prairie), three scenarios with different total PBC area (11.7, 23.5 and 28.8% of agricultural land converted to PBC) and two types of landscape configurations (PBC in clustered landscape patterns that represent realistic future configurations or in dispersed neutral landscape models) on a nest abundance index in an Illinois landscape.

Results

Our modeling results suggest that crop composition and PBC area are particularly important for bee nest abundance, whereas landscape configuration is associated with bee nest abundance at the local scale but less so at the regional scale.

Conclusions

Strategies to enhance wild bee habitat should therefore emphasize the crop composition and amount of PBC.