Linking the concept of scale to studies of biological diversity: evolving approaches and tools

Species Richness Responses to Structural or Compositional Habitat Diversity between and within Grassland Patches: A Multi-Taxon Approach

Habitat diversity (spatial heterogeneity within and between habitat patches in a landscape, HD) is often invoked as a driver of species diversity at small spatial scales. However, the effect of HD on species richness (SR) of multiple taxa is not well understood. We quantified HD and SR in a wet-dry gradient of open grassland habitats in Hortobágy National Park (E-Hungary) and tested the effect of compositional and structural factors of HD on SR of flowering plants, orthopterans, true bugs, spiders, ground beetles and birds. Our dataset on 434 grassland species (170 plants, 264 animals) showed that the wet-dry gradient (compositional HD at the between-patch scale) was primarily related to SR in orthopterans, ground-dwelling arthropods, and all animals combined. The patchiness, or plant association richness, of the vegetation (compositional HD at the within-patch scale) was related to SR of vegetation-dwelling arthropods, whereas vegetation height (structural HD at the within-patch scale) was related to SR of ground-dwelling arthropods and birds. Patch area was related to SR only in birds, whereas management (grazing, mowing, none) was related to SR of plants and true bugs. All relationships between HD and SR were positive, indicating increasing SR with increasing HD. However, total SR was not related to HD because different taxa showed similar positive responses to different HD variables. Our findings, therefore, show that even though HD positively influences SR in a wide range of grassland taxa, each taxon responds to different compositional or structural measures of HD, resulting in the lack of a consistent relationship between HD and SR when taxon responses are pooled. The idiosyncratic responses shown here exemplify the difficulties in detecting general HD-SR relationships over multiple taxa. Our results also suggest that management and restoration aimed specifically to sustain or increase the diversity of habitats are required to conserve biodiversity in complex landscapes.

Identifying Suitable Locations for Mesophotic Hard Corals Offshore of Maui, Hawai'i

Mesophotic hard corals (MHC) are increasingly threatened by a growing number of anthropogenic stressors, including impacts from fishing, land-based sources of pollution, and ocean acidification. However, little is known about their geographic distributions (particularly around the Pacific islands) because it is logistically challenging and expensive to gather data in the 30 to 150 meter depth range where these organisms typically live. The goal of this study was to begin to fill this knowledge gap by modelling and predicting the spatial distribution of three genera of mesophotic hard corals offshore of Maui in the Main Hawaiian Islands. Maximum Entropy modeling software was used to create separate maps of predicted probability of occurrence and uncertainty for: (1) Leptoseris, (2) Montipora, and (3) Porites. Genera prevalence was derived from the in situ presence/absence data, and used to convert relative habitat suitability to probability of occurrence values. Approximately 1,300 georeferenced records of the occurrence of MHC, and 34 environmental predictors were used to train the model ensembles. Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) values were between 0.89 and 0.97, indicating excellent overall model performance. Mean uncertainty and mean absolute error for the spatial predictions ranged from 0.006% to 0.05% and 3.73% to 17.6%, respectively. Depth, distance from shore, euphotic depth (mean and standard deviation) and sea surface temperature (mean and standard deviation) were identified as the six most influential predictor variables for partitioning habitats among the three genera. MHC were concentrated between Hanaka'ō'ō and Papawai Points offshore of western Maui most likely because this area hosts warmer, clearer and calmer water conditions almost year round. While these predictions helped to fill some knowledge gaps offshore of Maui, many information gaps remain in the Hawaiian Archipelago and Pacific Islands. This approach may be used to identify other potentially suitable areas for MHCs, helping scientists and resource managers prioritize sites, and focus their limited resources on areas that may be of higher scientific or conservation value.

Retrieving nitrogen isotopic signatures from fresh leaf reflectance spectra: disentangling δ(15)N from biochemical and structural leaf properties

Linking remote sensing methodology to stable isotope ecology provides a promising approach to study ecological processes from small to large spatial scales. Here, we show that δ(15)N can be detected in fresh leaf reflectance spectra of field samples along a spatial gradient of increasing nitrogen input from an N2-fixing invasive species. However, in field data it is unclear whether δ(15)N directly influences leaf reflectance spectra or if the relationship is based on covariation between δ(15)N and foliar nitrogen content or other leaf properties. Using a (15)N-labeling approach, we experimentally varied δ(15)N independently of any other leaf properties in three plant species across different leaf developmental and physiological states. δ(15)N could successfully be modeled by means of partial least squares (PLSs) regressions, using leaf reflectance spectra as predictor variables. PLS models explained 53-73% of the variation in δ(15)N within species. Several wavelength regions important for predicting δ(15)N were consistent across species and could furthermore be related to known absorption features of N-containing molecular bonds. By eliminating covariation with other leaf properties as an explanation for the relationship between reflectance and δ(15)N, our results demonstrate that (15)N itself has an inherent effect on leaf reflectance spectra. Thus, our study substantiates the use of spectroscopic measurements to retrieve isotopic signatures for ecological studies and encourages future development. Furthermore, our results highlight the great potential of optical measurements for up-scaling isotope ecology to larger spatial scales.

Ecological niche transferability using invasive species as a case study

Species distribution modeling is widely applied to predict invasive species distributions and species range shifts under climate change. Accurate predictions depend upon meeting the assumption that ecological niches are conserved, i.e., spatially or temporally transferable. Here we present a multi-taxon comparative analysis of niche conservatism using biological invasion events well documented in natural history museum collections. Our goal is to assess spatial transferability of the climatic niche of a range of noxious terrestrial invasive species using two complementary approaches. First we compare species' native versus invasive ranges in environmental space using two distinct methods, Principal Components Analysis and Mahalanobis distance. Second we compare species' native versus invaded ranges in geographic space as estimated using the species distribution modeling technique Maxent and the comparative index Hellinger's I. We find that species exhibit a range of responses, from almost complete transferability, in which the invaded niches completely overlap with the native niches, to a complete dissociation between native and invaded ranges. Intermediate responses included expansion of dimension attributable to either temperature or precipitation derived variables, as well as niche expansion in multiple dimensions. We conclude that the ecological niche in the native range is generally a poor predictor of invaded range and, by analogy, the ecological niche may be a poor predictor of range shifts under climate change. We suggest that assessing dimensions of niche transferability prior to standard species distribution modeling may improve the understanding of species' dynamics in the invaded range.

Incorporating behavior-based indices of connectivity into spatially explicit population models

Measuring connectivity in fragmented landscapes remains a central problem in ecology. Connectivity metrics range from descriptors of landscape structure to direct observations of a species’ ability to move to and colonize a forest patch. We constructed individual-based spatially explicit population models for a guild of forest rodents in Indiana to test the ability of structural and actual, or behavioral, measures of connectivity to predict patch and landscape occupancy and abundance. Model accuracy was assessed using comparisons with data from trapping studies. Predicted abundances within patches correlated with empirical data for five out of six species, but predicted patterns of patch occupancy corresponded with observations for only one species. Discrepancies may be due to inaccurate parameter values or the absence from the models of ecological processes such as conspecific attraction and competition. Nonetheless, the models demonstrated the utility of patch immigration as a measure of connectivity in explaining population abundance in fragmented landscapes. We discuss potential methods of collecting these behavior-based data.

Spatiotemporal exploratory models for broad-scale survey data

The distributions of animal populations change and evolve through time. Migratory species exploit different habitats at different times of the year. Biotic and abiotic features that determine where a species lives vary due to natural and anthropogenic factors. This spatiotemporal variation needs to be accounted for in any modeling of species' distributions. In this paper we introduce a semiparametric model that provides a flexible framework for analyzing dynamic patterns of species occurrence and abundance from broad-scale survey data. The spatiotemporal exploratory model (STEM) adds essential spatiotemporal structure to existing techniques for developing species distribution models through a simple parametric structure without requiring a detailed understanding of the underlying dynamic processes. STEMs use a multi-scale strategy to differentiate between local and global-scale spatiotemporal structure. A user-specified species distribution model accounts for spatial and temporal patterning at the local level. These local patterns are then allowed to "scale up" via ensemble averaging to larger scales. This makes STEMs especially well suited for exploring distributional dynamics arising from a variety of processes. Using data from eBird, an online citizen science bird-monitoring project, we demonstrate that monthly changes in distribution of a migratory species, the Tree Swallow (Tachycineta bicolor), can be more accurately described with a STEM than a conventional bagged decision tree model in which spatiotemporal structure has not been imposed. We also demonstrate that there is no loss of model predictive power when a STEM is used to describe a spatiotemporal distribution with very little spatiotemporal variation; the distribution of a nonmigratory species, the Northern Cardinal (Cardinalis cardinalis).

African parasitoid fig wasp diversification is a function of Ficus species ranges

Host specificity is a fundamental property implicit in obligate insect-plant associations. Rigid life history constraints exhibited by parasitoid fig wasps are believed to select for specialization directed at fig trees and this is supported by evidence of phenotypic adaptation to figs and partial co-speciation with the fig wasps they attack. Conversely, the ability to colonize such novel communities occurs under relaxed specificity, a behavior typified by more generalist groups such as parasitoids. The specificity directed towards Ficus species by Sycoryctinae parasitoid fig wasps is important in order to understand how this form of specialization influences their diversification and interactions with other fig wasp guilds. We use genetic distance analyses and reconstruct ancestral patterns of Ficus trait association with two genera of Sycoryctinae parasitoid fig wasps to identify evolutionary conservatism in Ficus species utilization. Ancestral state reconstructions of (i) affiliate Ficus subsection and (ii) syconia diameters of natal Ficus species indicate contrasting Ficus species ranges between Arachonia and Sycoryctes parasitoid genera. This work demonstrates that parasitoid speciation is not tightly constrained to Ficus speciation and rather a function of Ficus range limitations. Ficus evolution, ecology, and functional compatibility between parasitoid and Ficus traits appear to constrain parasitoid Ficus utilization. These results suggest that contrasting ecological settings and potential number of hosts available impose different ramifications for the evolution of parasitoid host specificity and so to the species interactions within the communities to which they belong.

Forecasting the effects of land-use change on forest rodents in Indiana

Forest cover in the upper Wabash River basin in Indiana was fragmented due to agricultural conversion beginning more than 175 years ago. Currently, urban expansion is an important driver of land-use change in the basin. A land transformation model was applied to the basin to forecast land use from 2000 to 2020. We assessed the effect of this projected land-use change scenario on five forest rodent species at three scales: using occupancy models at the patch level, proportional occupancy models at the landscape level, and ecologically scaled landscape indices to assess the change in connectivity at the watershed level. At the patch and landscape scales, occupancy models had low predictability but suggest that gray squirrels are most susceptible to land-use change. At the watershed scale, declines in connectivity did not correspond with the decline of forest. This study highlights the importance of map resolution and consideration of matrix elements in constructing forecast models. Unforeseen drivers of land use, such as changing economic incentives, may also have important ramifications.

Does scale matter in predicting species distributions? case study with the Marbled Murrelet

Hierarchical selection orders (selection of microsite, patch, home range, population block, and geographic range) are ideal for dictating spatial grain and extent of animal habitat models, but the resultant conditional models are poor for creating predictive maps. I proposed a two-step approach for accurately mapping probability of animal use that incorporates a single-grain analysis of each selection order in the first step and creates a multi-grain model that combines key variables from each selection order in the second step. Such two-step multi-grain models are strongly recommended because they allow interpretation of the scale of selection for a variable. Using a large data set for the Marbled Murrelet (Brachyramphus marmoratus) as a case study and five selection orders, information theory criteria provided strong support that such models are superior to simpler one-step single-grain models for the murrelet. However, a single-grain model can produce high classification accuracy if it represents the most limiting scale. Notably, accuracy of the two-step multi-grain model was no better than a traditional one-step multi-grain model that ignores selection orders, indicating the advantage of two-step modeling is in elucidating scaling effects, not necessarily in improving accuracy of species distribution maps.