Wiley M. Kitchens

MODELLING THE IMPACTS OF A RIVER DIVERSION ON BOTTOMLAND FOREST COMMUNITIES IN THE SANTEE RIVER FLOODPLAIN, SOUTH CAROLINA

Abstract To study the impact of an altered hydrologic regime on the growth and succession of a coastal forested floodplain in South Carolina, a bottomland hardwood succession model (FORFLO) was developed. Hydrologic parameters were used as major controls for seed germination, tree growth, and tree mortality. Individual species responses to these parameters were used to predict succession (species composition) on the simulated sites. Coupling the simulation model with a geographical information mapping system permitted rapid visual inspection of predicted bottomland community changes in the Santee River floodplain. The model predicted a loss of up to 97% of the existing bottomland forest. An alternative water release schedule may retain much of this area as cypress-tupelo forest.

Effects of landscape gradients on wetland vegetation communities: information for large-scale restoration

Projects of the scope of the restoration of the Florida Everglades require substantial information regarding ecological mechanisms, and these are often poorly understood. We provide critical base knowledge for Everglades restoration by characterizing the existing vegetation communities of an Everglades remnant, describing how present and historic hydrology affect wetland vegetation community composition, and documenting change from communities described in previous studies. Vegetation biomass samples were collected along transects across Water Conservation Area 3A South (3AS). Ten community types were present between November 2002 and 2005. Separate analyses for key a priori groups (slough, wet prairie, and sawgrass) provided detailed conclusions about effects of historic hydrology on the vegetation of 3AS. Communities were affected by hydrologic variables up to four years previous to the sample. We identified wet prairie/slough species such as Eleocharis spp. and Nymphaea odorata as short-term sentinel species of community change. Sawgrass and N. odorata should be monitored for long-term change. Comparisons to preceding studies indicated that many of the communities of previous times, when conditions were drier, no longer exist in our study area and have been replaced by deeper water community types.

Multi‐state succession in wetlands: a novel use of state and transition models

The complexity of ecosystems and mechanisms of succession are often simplified by linear and mathematical models used to understand and predict system behavior. Such models often do not incorporate multivariate, nonlinear feedbacks in pattern and process that include multiple scales of organization inherent within real-world systems. Wetlands are ecosystems with unique, nonlinear patterns of succession due to the regular, but often inconstant, presence of water on the landscape. We develop a general, nonspatial state and transition (S and T) succession conceptual model for wetlands and apply the general framework by creating annotated succession/management models and hypotheses for use in impact analysis on a portion of an imperiled wetland. The S and T models for our study area, Water Conservation Area 3A South (WCA3), Florida, U.S.A., included hydrologic and peat depth values from multivariate analyses and classification and regression trees. We used the freeware Vegetation Dynamics Development Tool as an exploratory application to evaluate our S and T models with different management actions (equal chance [a control condition], deeper conditions, dry conditions, and increased hydrologic range) for three communities: slough, sawgrass (Cladium jamaicense), and wet prairie. Deeper conditions and increased hydrologic range behaved similarly, with the transition of community states to deeper states, particularly for sawgrass and slough. Hydrology is the primary mechanism for multi-state transitions within our study period, and we show both an immediate and lagged effect on vegetation, depending on community state. We consider these S and T succession models as a fraction of the framework for the Everglades. They are hypotheses for use in adaptive management, represent the community response to hydrology, and illustrate which aspects of hydrologic variability are important to community structure. We intend for these models to act as a foundation for further restoration management and experimentation which will refine transition and threshold concepts.

Social network models predict movement and connectivity in ecological landscapes

Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

Modeling viable mammal populations in gap analyses

Gap analysis is an approach to conserving biological diversity that maps species richness and identifies sites that ought to be protected but are not in conservation networks. Gap analyses based on species richness may have high error rates when species models are based solely on species-habitat associations, because patches too small to support populations are still considered to be potential habitat. We incorporated information on the home range and dispersal distances of the mammals of Florida to estimate minimum critical areas (MCA) to support minimum viable populations for each mammal species. Incorporating MCA decreases the area occupied by the highest levels of species richness, and alters the mapped spatial distribution of potential species richness. For example, in St. Lucie and Okeechobee counties, Florida, the total area occupied by 15 or more species was 30,448 ha under simple mammal-habitat association models, but only 7820 ha under model conditions incorporating MCA. This reflects the fragmented condition of many landscapes, where most patches are too small to support viable populations of larger species. Incorporating minimum area requirements into maps of potential species richness produces more conservative and defensible maps.

Patterns of change in tree islands in Arthur R. Marshall Loxahatchee National Wildlife Refuge from 1950 to 1991.

Size, shape, orientation, and distribution of tree islands in a remnant of northern Everglades wetland were examined from 1950 and 1991 aerial photography. The objectives were to quantify the patterns of tree islands in Loxahatchee National Wildlife Refuge, to determine if the patterns of tree islands had changed between the two dates, and to relate the tree island patterns to modeled pre-and post-drainage hydrologic patterns. There was considerable variation in the patterns of tree islands spatially and temporally Changes in the size and shape of tree islands from 1950 to 1991 are consistent with changes in the modeled pre-and post-drainage hydrologic patterns. Photo plots along the edges of the refuge, where hydroperiods are longer and depths deeper than they were historically, show a decrease in tree island size and in overall area of tree islands in the plots. Photo plots in the interior, where hydroperiods are shorter than they were pre-drainage, show an increase in tree island area. Overall, there is a tendency for more tree islands to be irregularly shaped in the 1991 photo plots than in the 1950 plots, a reflection of the loss of water flow, reduction of pulse magnitude, and the ponding of water along the perimeter dikes. This study illustrates the importance of considering long-term changes in hydroperiod, depths, and water flows in the restoration of this area.

Habitat structure and plant community composition in a northern Everglades wetland landscape

The structure ofa priori-defined aquatic habitats was compared within the Arthur R. Marshall Loxahatchee National Wildlife Refuge, which comprises the northern remnant of the Everglades ecosystem. Total plant biomass, canopy height, water depth, and the relative abundance (percent cover) of plant species in adjacent sloughs (including alligator holes), wet prairies, and sawgrass stands were compared over a 30-month period. These habitats formed a mosaic of aquatic habitats of differing structure and plant community composition. Slough and alligator hole habitats were in deeper water with little or no canopy, and habitat structure was provided almost entirely by submersed bladderwort (Utricularia) and floating water lily (Nymphaea). Sawgrass stands were present in shallower water and had a well-developed canopy that was generated almost entirely byCladium. Wet prairies were intermediate in water depth and canopy stature, with emergent sedges (i.e.,Eleocharis, Rhynchospora) providing most habitat structure. Differences among adjacent habitats accounted for most of the observed variation in habitat structure and plant relative abundance, whereas differences among widely-separated areas in the Refuge (i.e., landscape-level differences) accounted for little of the observed variation. In contrast, water depth varied considerably among sampling areas, likely reflecting hydrologic gradients that occur across the Refuge landscape. Similarly, although differences among sampling months were minimal for most habitat features examined, most of the variation observed in water depth was accounted for by sampling month, as would be expected in a seasonally dynamic wetland such as the Everglades. Discriminant function analyses using plant relative abundance data, habitat structure data, or both sets of data combined correctly classified most sites with respect toa priori-defined habitat type, despite similarities in plant community composition in sloughs and wet prairies. Overall, it appears that sloughs, wet prairies, and sawgrass stands are distinct with respect to habitat structure and plant community composition and that differences among these habitats are persistent across the Refuge landscape.

Network modularity reveals critical scales for connectivity in ecology and evolution

For nearly a century, biologists have emphasized the profound importance of spatial scale for ecology, evolution and conservation. Nonetheless, objectively identifying critical scales has proven incredibly challenging. Here we extend new techniques from physics and social sciences that estimate modularity on networks to identify critical scales for movement and gene flow in animals. Using four species that vary widely in dispersal ability and include both mark-recapture and population genetic data, we identify significant modularity in three species, two of which cannot be explained by geographic distance alone. Importantly, the inclusion of modularity in connectivity and population viability assessments alters conclusions regarding patch importance to connectivity and suggests higher metapopulation viability than when ignoring this hidden spatial scale. We argue that network modularity reveals critical meso-scales that are probably common in populations, providing a powerful means of identifying fundamental scales for biology and for conservation strategies aimed at recovering imperilled species.

Exploring the effect of drought extent and interval on the Florida snail kite: interplay between spatial and temporal scales

The paper aims at exploring the viability of the Florida snail kite population under various drought regimes in its wetland habitat. The population dynamics of snail kites are strongly linked with the hydrology of the system due to the dependence of this bird species on one exclusive prey species, the apple snail, which is negatively affected by a drying out of habitat. Based on empirical evidence, it has been hypothesised that the viability of the snail kite population critically depends not only on the time interval between droughts, but also on the spatial extent of these droughts. A system wide drought is likely to result in reduced reproduction and increased mortality, whereas the birds can respond to local droughts by moving to sites where conditions are still favourable. This paper explores the implications of this hypothesis by means of a spatially-explicit individual-based model. The specific aim of the model is to study in a factorial design the dynamics of the kite population in relation to two scale parameters, the temporal interval between droughts and the spatial correlation between droughts. In the model high drought frequencies led to reduced numbers of kites. Also, habitat degradation due to prolonged periods of inundation led to lower predicted numbers of kites. Another main result was that when the spatial correlation between droughts was low, the model showed little variability in the predicted numbers of kites. But when droughts occurred mostly on a system wide level, environmental stochasticity strongly increased the stochasticity in kite numbers and in the worst case the viability of the kite population was seriously threatened.

SPECIES ASSOCIATION CHANGES ACROSS A GRADIENT OF FRESHWATER, OLIGOHALINE, AND MESOHALINE TIDAL MARSHES ALONG THE LOWER SAVANNAH RIVER

In the present study, plant species patterns and associated environmental factors of freshwater, oligohaline, and meschaline marshes of the Savannah National Wildlife Refuge were compared. DECORANA, an ordination method, was used to group vegetation classes. Discriminant function analysis was applied to resulting classes to quantify differences in salinity, elevation, and distance from tidal channels among classes. Nine vegetation classes across freshwater and brackish marshes corresponded significantly to salinity differences between sites. Combinations of elevation and distance from tidal channel were significant in separating vegetation classes within sites.Scirpus validus (Vahl) was the only species to occur over the entire range of measured physical parameters and accounted for much of the overlap between vegetation classes. The proportion of correctly classified vegetation classes between sites was 70%. Within each site, the proportion of correct classification was lower in the freshwater marsh (77% correct classifications) when compared with the oligohaline (82%), strongly oligohaline (83%), and mesohaline (85%) sites. Although overlap among classes was greater in the more diverse freshwater marsh, our results may reflect differences in the steepness of environmental gradients between sites and the scale at which physical parameters were measured rather than actual plant distribution overlap. Results suggest that resources are more finely divided among species in the freshwater marsh, resulting in a less distinct dominance hierarchy when compared with the mesohaline marsh.