Distribution of plant functional types along gradients of disturbance intensity and resource supply in an agricultural landscape

Abstract. In this study, plant functional types are understood as groups of plants with similar biological traits displaying significant optima or maxima on a gradient plane of resource supply and disturbance intensity. The biological traits refer to expansion, vegetative regeneration, generative reproduction, dispersal and seed bank longevity. 129 vegetation samples were taken in an agricultural landscape in southwestern Germany, covering a wide range of terrestrial vegetation types – but with the exception of forests and wetlands. For each site, also soil data were recorded. Mean daily soil moisture was estimated with a simple model. Soil moisture, balanced nitrogen supply and available phosphorus were combined into a factor ‘resource supply’. In addition, disturbance intensity was estimated for each site. This factor was based on (1) frequency of disturbance, (2) disturbance depth below or above the soil surface, and (3) proportion of the area affected by a discrete disturbance event. 30 plant groups with similar biological characteristics resulted from a cluster analysis, based on a compilation of 19 biological traits for a regional species pool. Logistic regression on a gradient plane of disturbance intensity and resource supply yielded response curves for 28 groups. The dependent variable was defined as the probability of encountering all members of a group in a sample. 17 groups display a significant response curve on the gradient plane. Plants with a potential for long- range dispersal are concentrated on sites with low or high disturbance intensities (e.g. fallow land, fields, lawns). On sites with medium disturbance intensity (e.g. meadows) and low to medium resource supply, small-range dispersal predominates. There are no distinct trends concerning seed bank longevity. The potential for vertical and lateral expansion increases with decreasing disturbance intensity. Only at medium disturbance intensities does vertical expansion correlate positively with resource supply. Rapid detachment of daughter individuals occurs more often on productive sites than on less productive sites. Diversity of groups with similar biological traits is highest on sites with medium disturbance intensities.     

Spatial metrics for detecting ecosystem degradation in the ridge-slough patterned landscape

Indicators of landscape condition should be selected based on their sensitivity to environmental changes and their capacity to provide early warning detection of those changes. We assessed the performance of a suite of spatial-pattern metrics selected to quantify the condition of the ridge-slough landscape in the Everglades (South Florida, USA). Spatial pattern metrics (n = 14) that describe landscape composition, geometry and hydrologic connectivity were enumerated from vegetation maps of twenty-five 2 × 2 km primary sampling units (PSUs) that span a gradient of hydrologic and ecological condition across the greater Everglades ecosystem. Metrics were assessed in comparison with field measurements from each PSU of landscape condition obtained from regional surveys of soil elevation, which have previously been shown to capture dramatic differences between conserved and degraded locations. Elevation-based measures of landscape condition included soil elevation bi-modality (BI_SE), a binary measure of landscape condition, and also the standard deviation of soil elevation (SD_SE), a continuous measure of condition. Metric performance was assessed based on the strength (sensitivity) and shape (leading vs. lagging) of the relationship between spatial pattern metrics and these elevation-based measures. We observed significant logistic regression slopes with BI_SE for only 4 metrics (slough width, ridge density, directional connectivity index – DCI, and least flow cost – LFC). More significant relationships (n = 8 metrics) were observed with SD_SE, with the strongest associations for slough density, mean ridge width, and the average length of straight flow, as well as for a suite of hydrologic connectivity metrics (DCI, LFC and landscape discharge competence – LDC). Leading vs. lagging performance, inferred from the curvature of the association obtained from the exponent of fitted power functions, suggest that only DCI was a leading metric of the loss of soil elevation variation; most metrics were indeterminate, though some were clearly lagging. Our findings support the contention that soil elevation changes from altered peat accretion dynamics precede changes in landscape pattern, and offer insights that will enable efficient monitoring of the ridge-slough landscape as part of the ongoing Everglades restoration effort.     

Can landscape properties predict occurrence of grey-sided voles?

There has been a long-term decline in spring and fall numbers of Clethrionomys rufocanus in boreal Sweden in 1971–2005. Previous studies on permanent sampling plots in the centre of 2.5 × 2.5 km landscapes suggested that habitat fragmentation (sensu destruction) could have contributed to the decline. Therefore, we tested these findings in a field study and compared trapping results on the central sampling plots of landscapes with a low degree of fragmentation (LDF) and of “hot spot” type with trapping results in managed forest landscapes with a high degree of fragmentation (HDF). We predicted that C. rufocanus would be more common on the LDF plots. We used our permanent plots supplemented with a new sample of plots, mainly of the rare LDF type, inside or just outside the long-term study area. Very few voles were trapped on both plot types, and no difference was found. However, a subsequent pilot study with trapping in a national park with large areas of pristine, unfragmented forest yielded more voles than in the managed, more fragmented, areas. Consequently, the initial field study data and some other recent data were also re-analysed from a “local patch quality” perspective. This alternative approach revealed the positive importance of large focal patches of forest >60 years old and their content of old-growth (pine) forest (>100 years). Interestingly, at the landscape level, the frequency distribution of patches of forest >60 years old, old-growth (>100 years), and especially of old-growth pine forest (>100 years), relative to the properties of plots with C. rufocanus, suggested that there are few forest patches left that are suitable for C. rufocanus. Our current results suggest that habitat fragmentation cannot be excluded as a contributing cause to the long-term decline of C. rufocanus in boreal Sweden.     

To aggregate or not? Capturing the spatio-temporal complexity of the thermal regime

Freshwater stream systems are under immense pressure from various anthropogenic impacts, including climate change. Stream systems are increasingly being altered by changes to the magnitude, timing, frequency, and duration of their thermal regimes, which will have profound impacts on the life-history dynamics of resident biota within their home range. Although temperature regimes have a significant influence on the biology of instream fauna, large spatio-temporal temperature datasets are often reduced to a single metric at discrete locations and used to describe the thermal regime of a system; potentially leading to a significant loss of information crucial to stream management. Models are often used to extrapolate these metrics to unsampled locations, but it is unclear whether predicting actual daily temperatures or an aggregated metric of the temperature regime best describes the complexity of the thermal regime. We fit spatial statistical stream-network models (SSNMs), random forest and non-spatial linear models to stream temperature data from the Upper Condamine River in QLD, Australia and used them to semi-continuously predict metrics describing the magnitude, duration, and frequency of the thermal regime through space and time. We compared both daily and aggregated temperature metrics and found that SSNMs always had more predictive ability than the random forest models, but both models outperformed the non-spatial linear model. For metrics describing thermal magnitude and duration, aggregated predictions were most accurate, while metrics describing the frequency of heating events were better represented by metrics based on daily predictions generated using a SSNM. A more comprehensive representation of the spatio-temporal thermal regime allows researchers to explore new spatio-temporally explicit questions about the thermal regime. It also provides the information needed to generate a suite of ecologically meaningful metrics capturing multiple aspects of the thermal regime, which will increase our scientific understanding of how organisms respond to thermal cues and provide much-needed information for more effective management actions.