Animal space use: distinguishing a two‐level superposition of scale‐specific walks from scale‐free Lévy walk

How to differentiate between scale‐free space use like Lévy walk and a two‐level scale‐specific process like composite random walk (mixture of intra‐ and inter‐patch habitat movement) is surrounded by controversy. Composite random walk may under some parameter conditions appear Lévy walk‐like from the perspective of the path’s distribution of step lengths due to superabundance of very long steps relative to the expectation from a classic (single‐level) random walk. However, a more explicit focus on the qualitative differences between studying movement at a high resolution mechanistic (behavioral) level and the more coarse‐grained statistical mechanical level may contribute to resolving both this and other issues related to scaling complexity. Specifically, a re‐sampling of a composite random walk at larger time lags than the micro‐level unit time step for the simulation makes a Lévy‐look‐alike step length distribution re‐shaping towards a Brownian motion‐like pattern. Conversely, a true Levy walk maintains its scaling characteristics upon re‐sampling. This result illustrates how a confusing pattern at the mechanistic level may be resolved by changing observational scale from the micro level to the coarser statistical mechanical meso‐ or macro‐scale. The instability of the composite random walk pattern under rescaling is a consequence of influence of the central limit theorem. I propose that a coarse‐graining test – studying simulated animal paths at a coarsened temporal scale by re‐sampling a series – should be routinely performed prior to comparing theoretical results with those patterns generated from GPS data describing animal movement paths. Fixes from terrestrial mammals are often collected at hourly intervals or larger, and such a priori coarse‐grained series may thus comply better with the statistical mechanical meso‐ or macro‐level of analysis than the behavioral mechanics observed at finer resolutions typically in the range of seconds and minutes. If fixes of real animals are collected at this high frequency, coarse graining both the simulated and real series is advised in order to bring the analysis into a temporal scale domain where analytical methods from statistical mechanics can be applied.     

Plant species richness and environmental heterogeneity in a mountain landscape: effects of variability and spatial configuration

The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history.     

Trees as islands: canopy ant species richness increases with the size of liana‐free trees in a Neotropical forest

The physical characteristics of habitats shape local community structure; a classic example is the positive relationship between the size of insular habitats and species richness. Despite the high density and proximity of tree crowns in forests, trees are insular habitats for some taxa. Specifically, crown isolation (i.e. crown shyness) prevents the movement of small cursorial animals among trees. Here, we tested the hypothesis that the species richness of ants (S_a) in individual, isolated trees embedded within tropical forest canopies increases with tree size. We predicted that this pattern disappears when trees are connected by lianas (woody vines) or when strong interactions among ant species determine tree occupancy. We surveyed the resident ants of 213 tree crowns in lowland tropical forest of Panama. On average, 9.2 (range = 2–20) ant species occupied a single tree crown. Average (± SE) S_a was ca 25% higher in trees with lianas (10.2 ± 0.26) than trees lacking lianas (8.0 ± 0.51). S_a increased with tree size in liana‐free trees (S_a = 10.99A^0.256), but not in trees with lianas. Ant species composition also differed between trees with and without lianas. Specifically, ant species with solitary foragers occurred more frequently in trees with lianas. The mosaic‐like pattern of species co‐occurrence observed in other arboreal ant communities was not found in this forest. Collectively, the results of this study indicate that lianas play an important role in shaping the local community structure of arboreal ants by overcoming the insular nature of tree crowns.     

Community‐based wildlife management area supports similar mammal species richness and densities compared to a national park

Community‐based conservation models have been widely implemented across Africa to improve wildlife conservation and livelihoods of rural communities. In Tanzania, communities can set aside land and formally register it as Wildlife Management Area (WMA), which allows them to generate revenue via consumptive or nonconsumptive utilization of wildlife. The key, yet often untested, assumption of this model is that economic benefits accrued from wildlife motivate sustainable management of wildlife. To test the ecological effectiveness (here defined as persistence of wildlife populations) of Burunge Wildlife Management Area (BWMA), we employed a participatory monitoring approach involving WMA personnel. At intermittent intervals between 2011 and 2018, we estimated mammal species richness and population densities of ten mammal species (African elephant, giraffe, buffalo, zebra, wildebeest, waterbuck, warthog, impala, Kirk's dik‐dik, and vervet monkey) along line transects. We compared mammal species accumulation curves and density estimates with those of time‐matched road transect surveys conducted in adjacent Tarangire National Park (TNP). Mammal species richness estimates were similar in both areas, yet observed species richness per transect was greater in TNP compared to BWMA. Species‐specific density estimates of time‐matched surveys were mostly not significantly different between BWMA and TNP, but elephants occasionally reached greater densities in TNP compared to BWMA. In BWMA, elephant, wildebeest, and impala populations showed significant increases from 2011 to 2018. These results suggest that community‐based conservation models can support mammal communities and densities that are similar to national park baselines. In light of the ecological success of this case study, we emphasize the need for continued efforts to ensure that the BWMA is effective. This will require adaptive management to counteract potential negative repercussions of wildlife populations on peoples' livelihoods. This study can be used as a model to evaluate the effectiveness of wildlife management areas across Tanzania.     

Impacts of a pesticide on pollinator species richness at different spatial scales

Pesticides are an important potential cause of biodiversity and pollinator decline. Little is known about the impacts of pesticides on wild pollinators in the field. Insect pollinators were sampled in an agricultural system in Italy with the aim of detecting the impacts of pesticide use. The insecticide fenitrothion was over 150 times greater in toxicity than other pesticides used in the area, so sampling was set up around its application. Species richness of wild bees, bumblebees and butterflies were sampled at three spatial scales to assess responses to pesticide application: (i) the ‘field’ scale along pesticide drift gradients; (ii) the ‘landscape’ scale sampling in different crops within the area and (iii) the ‘regional’ scale comparing two river basins with contrasting agricultural intensity. At the field scale, the interaction between the application regime of the insecticide and the point in the season was important for species richness. Wild bee species richness appeared to be unaffected by one insecticide application, but declined after two and three applications. At the landscape scale, the species richness of wild bees declined in vine fields where the insecticide was applied, but did not decline in maize or uncultivated fields. At the regional scale, lower bumblebee and butterfly species richness was found in the more intensively farmed basin with higher pesticide loads. Our results suggest that wild bees are an insect pollinator group at particular risk from pesticide use. Further investigation is needed on how the type, quantity and timing of pesticide application impacts pollinators.     

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S‐SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient. Location Two study areas in the Alps of Switzerland. Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S‐SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways – summing binary predictions, summing random draws of binomial trials and summing predicted probabilities – to obtain a final species count. Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S‐SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump‐shaped pattern of SR observed along the elevational gradient. The S‐SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S‐SDM approaches – the summed binomial trials based on predicted probabilities and summed predicted probabilities – do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S‐SDM approaches fail to appropriately reproduce the observed hump‐shaped patterns of SR along the elevational gradient. Main conclusions Macroecological approach and S‐SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S‐SDM by MEM predictions.     

Species–area relationships of butterflies in Europe and species richness forecasting

Species–area relationships (SARs) of European butterfly species (Rhopalocera) appear to follow power functions with Mediterranean butterflies having a much higher slope value (z=0.49) compared to the slope for the northern and eastern European countries (z=0.10). A simulated process of species extinction by a stepwise density dependent random elimination of species affected species–area patterns differently. For Mediterranean countries SAR slopes decreased, for other European countries slopes increased during the extinction process. Comparisons of species numbers before and after extinction with those predicted by a classical SAR approach differed widely and revealed that SARs are not able to predict future species numbers at local scales. For Mediterranean countries the classical SAR approach underestimated the number of species remaining after simulated extinction, for all other European countries SARs highly overestimated species numbers. These contrasting patterns indicate that changes in SAR patterns do not unequivocally point to changes in species diversity or community structure as assumed by current theory. On the other hand, the results strongly indicate that simplified applications of SARs for forecasting might give misimpressions about species loss and future biodiversity if the initial community structure, especially relative densities and numbers of species with restricted range size, are not taken into account.     

Scale‐dependent determinants of plant species richness in a semi‐arid fragmented agro‐ecosystem

Aims: (1) Understanding how the relationship between species richness and its determinants depends on the interaction between scales at which the response and explanatory variables are measured. (2) Quantifying the relative contributions of local, intermediate and large‐scale determinants of species richness in a fragmented agro‐ecosystem. (3) Testing the hypothesis that the relative contribution of these determinants varies with the grain size at which species richness is measured. Location: A fragmented agro‐ecosystem in the Southern Judea Lowland, Israel, within a desert–Mediterranean transition zone. Methods: Plant species richness was estimated using hierarchical nested sampling in 81 plots, positioned in 38 natural vegetation patches within an agricultural matrix (mainly wheat fields) among three land units along a sharp precipitation gradient. Explanatory variables included position along that gradient, patch area, patch isolation, habitat heterogeneity and overall plant density. We used general linear models and hierarchical partitioning of variance to test and quantify the effect of each explanatory variable on species richness at four grain sizes (0.0625, 1, 25 and 225 m²). Results: Species richness was mainly affected by position along a precipitation gradient and overall plant density, and to a lesser extent by habitat heterogeneity. It was also significantly affected by patch area and patch isolation, but only for small grain sizes. The contribution of each explanatory variable to explained variance in species richness varied with grain size, i.e. scale‐dependent. The influence of geographic position and habitat heterogeneity on species richness increased with grain size, while the influence of plant density decreased with grain size. Main conclusions: Species richness is determined by the combined effect of several scale‐dependent determinants. Ability to detect an effect and effect size of each determinant varies with the scale (grain size) at which it is measured. The combination of a multi‐factorial approach and multi‐scale sampling reveals that conclusions drawn from studies that ignore these dimensions are restricted and potentially misleading.     

Relationship between species richness and spatial and temporal distance from seed source in semi‐natural grassland

Question: How do traditional management practices of field margins maintain the biodiversity of native grassland species? Location: Semi‐natural grassland on the field margins of traditional and consolidated agricultural fields on Awaji Island, central Japan. Methods: The distance to the nearest traditional field margin to the study sites was determined because the traditional field was considered as a seed source of native vegetation to the semi‐natural grasslands under study. We selected field margins in consolidated fields of different ages and distances from seed sources. Indicator species for both field types were sought. Regression analysis and detrended correspondence analysis (DCA) were used to determine the effect of spatial and temporal distances on the species composition of native vegetation. Results: Species richness differed significantly between the margin of traditional and consolidated fields. We identified significant indicator species of traditional fields, but not of consolidated fields. In consolidated fields, species richness increased significantly with age and decreased significantly with increasing distance to the source. At younger sites, species richness decreased faster with distance to the source because of strong negative correlation, but not at older sites. DCA ordination plots similarly indicated that similarities of vegetation composition in consolidated and traditional fields decreased with distance, and the effect of distance decreased with age. Conclusions: The species composition of the grassland margins of consolidated field was more similar to the margins of traditional fields if the consolidated fields were older, and/or closer to traditional fields. This pattern suggests that dispersal may play a role in the establishment of species on field margins.     

The local‐regional species richness relationship: new perspectives on the null‐hypothesis

Despite considerable criticism in recent years, the use of local (SL) and regional species richness (SR) plots has a long tradition to test for community saturation. The traditional approach has been to compare linear and polynomial regression models of untransformed measures of SL and SR with a statistically significant linear or polynomial model indicating unsaturated and saturated communities, respectively. This approach has been the target of much controversy owing to statistical issues, the confounding effects of the arbitrary choice for the size of the local and regional area, and the difficulty in attributing ecological processes to the underlying SL SR pattern. The statistical issues and effects of scale stem from the lack of statistical independence and induced correlation between SL SR arising from the mathematical constraint, SL<SR. However, by removing this mathematical constraint by means of a logratio transformation, SL SR relationships can be calculated using ordinary linear regression and with a logical and definitive null‐hypothesis based solely on the presence of a statistically significant slope, which provides a quantitative measure of curvature. Simulations of SL SR relationships with varying curvature and SL:SR ratio demonstrate that the logratio model can accurately measure curvature independent of the SL:SR ratio. Therefore, the tendency for studies with high local:regional area ratio to result in linear SL SR trends when analysed by traditional regression methods may be mitigated by reanalysis by the logratio model. By alleviating the effects of scale, the logratio model offers a more statistically sound assessment of the SL SR relationship, which in turn can serve as an effective tool to complement emerging process‐based models.     

Predicted rarity‐weighted richness,a new tool to prioritize sites for species representation

Lack of biodiversity data is a major impediment to prioritizing sites for species representation. Because comprehensive species data are not available in any planning area, planners often use surrogates (such as vegetation communities, or mapped occurrences of a well‐inventoried taxon) to prioritize sites. We propose and demonstrate the effectiveness of predicted rarity‐weighted richness (PRWR) as a surrogate in situations where species inventories may be available for a portion of the planning area. Use of PRWR as a surrogate involves several steps. First, rarity‐weighted richness (RWR) is calculated from species inventories for a q% subset of sites. Then random forest models are used to model RWR as a function of freely available environmental variables for that q% subset. This function is then used to calculate PRWR for all sites (including those for which no species inventories are available), and PRWR is used to prioritize all sites. We tested PRWR on plant and bird datasets, using the species accumulation index to measure efficiency of PRWR. Sites with the highest PRWR represented species with median efficiency of 56% (range 32%–77% across six datasets) when q = 20%, and with median efficiency of 39% (range 20%–63%) when q = 10%. An efficiency of 56% means that selecting sites in order of PRWR rank was 56% as effective as having full knowledge of species distributions in PRWR's ability to improve on the number of species represented in the same number of randomly selected sites. Our results suggest that PRWR may be able to help prioritize sites to represent species if a planner has species inventories for 10%–20% of the sites in the planning area.     

Mollusc community patterns and species response curves along a mineral richness gradient: a case study in fens

Aim The goals of this study were to: (1) compare water conductivity and pH as proxy measures of mineral richness in relation to mollusc assemblages in fens, (2) examine the patterns of mollusc species richness along the gradient of mineral richness based on these factors, (3) model species–response curves and analyse calcicole–calcifuge behaviour of molluscs, and (4) compare the results with those from other studies concerning non‐marine mollusc ecology. Location Altogether, 135 treeless spring fen sites were sampled within the area of the Western Carpathians (east Czech Republic, north‐west Slovakia and south Poland; overall extent of study area was 12,000 km²). Methods Mollusc communities were recorded quantitatively from a homogeneous area of 16 m². Water conductivity and pH were measured in the field. The patterns of local species diversity along selected gradients, and species–response curves, were modelled using generalized linear models (GLM) and generalized additive models (GAM), both using the Poisson distribution. Results When the most acid sites (practically free of molluscs) were excluded, conductivity expressed the sites’ mineral richness and base saturation within the entire gradient, in contrast to pH. In the base‐rich sites, pH did not correlate with mineral richness. A unimodal response of local species diversity to mineral richness (expressed as conductivity) was found. In the extremely mineral‐rich, tufa‐forming sites (conductivity > 600 μS cm^?1) a decrease in species diversity was encountered. Response curves of the most common species showed clear differentiation of their niches. Significant models of either unimodal or monotonic form were fitted for 18 of the 30 species analysed. Species showed five types of calcicole–calcifuge behaviour: (1) a decreasing monotonic response curve and a preference for the really acid sites; (2) a skewed unimodal response curve with the optimum shifted towards the slightly acid sites; (3) a symmetrical unimodal model response curve with the optimum in the base‐rich sites, with no or slight tufa precipitation; (4) a skewed unimodal response curve but with the optimum shifted to the more mineral‐rich sites; and (5) an increasingly monotonic response curve, the optimum in the extremely base‐rich sites with strong tufa precipitation. Main conclusions Conductivity is the only reliable proxy measure of mineral richness across the entire gradient, within the confines of this study. This information is of great ecological significance in studies of fen mollusc communities. Species richness does not increase with increasing mineral richness along the entire gradient: only a few species are able to dwell in the extremely base‐rich sites. The five types of calcicole–calcifuge behaviour seen in species living in fens have a wider application: data published so far suggest they are also applicable to mollusc communities in other habitats.