Downscaling species occupancy from coarse spatial scales

The measurement and prediction of species' populations at different spatial scales is crucial to spatial ecology as well as conservation biology. An efficient yet challenging goal to achieve such population estimates consists of recording empirical species' presence and absence at a specific regional scale and then trying to predict occupancies at finer scales. So far the majority of the methods have been based on particular species' distributional features deemed to be crucial for downscaling occupancy. However, only a minority of them have dealt explicitly with specific spatial features. Here we employ a wide class of spatial point processes, the shot noise Cox processes (SNCP), to model species occupancies at different spatial scales and show that species' spatial aggregation is crucial for predicting population estimates at fine scales starting from coarser ones. These models are formulated in continuous space and locate points regardless of the arbitrary resolution that one employs to study the spatial pattern. We compare the performances of nine models, calibrated at regional scales and demonstrate that a very simple class of SNCP, the Thomas process, is able to outperform other published models in predicting occupancies down to areas four orders of magnitude smaller than the ones employed for the parameterization. We conclude by explaining the ability of the approach to infer spatially explicit information from spatially implicit measures, the potential of the framework to combine niche and spatial models, and the possibility of reversing the method to allow upscaling.

Between geometry and biology: the problem of universality of the species-area relationship

The species-area relationship (SAR) is considered to be one of a few generalities in ecology, yet a universal model of its shape and slope has remained elusive. Recently, Harte et al. argued that the slope of the SAR for a given area is driven by a single parameter, the ratio between total number of individuals and number of species (i.e., the mean population size across species at a given scale). We provide a geometric interpretation of this dependence. At the same time, however, we show that this dependence cannot be universal across taxa: if it holds for a taxon composed from two subsets of species and also for one of its subsets, it cannot simultaneously hold for the other subset. Using three data sets, we show that the slope of the SAR considerably varies around the prediction. We estimate the limits of this variation by using geometric considerations, providing a theory based on species spatial turnover at different scales. We argue that the SAR cannot be strictly universal, but its slope at each particular scale varies within the constraints given by species' spatial turnover at finer spatial scales, and this variation is biologically informative.

Comparing organic farming and land sparing: optimizing yield and butterfly populations at a landscape scale

Organic farming aims to be wildlife-friendly, but it may not benefit wildlife overall if much greater areas are needed to produce a given quantity of food. We measured the density and species richness of butterflies on organic farms, conventional farms and grassland nature reserves in 16 landscapes. Organic farms supported a higher density of butterflies than conventional farms, but a lower density than reserves. Using our data, we predict the optimal land-use strategy to maintain yield whilst maximizing butterfly abundance under different scenarios. Farming conventionally and sparing land as nature reserves is better for butterflies when the organic yield per hectare falls below 87% of conventional yield. However, if the spared land is simply extra field margins, organic farming is optimal whenever organic yields are over 35% of conventional yields. The optimal balance of land sparing and wildlife-friendly farming to maintain production and biodiversity will differ between landscapes.

Scale matters: the impact of organic farming on biodiversity at different spatial scales

There is increasing recognition that ecosystems and their services need to be managed in the face of environmental change. However, there is little consensus as to the optimum scale for management. This is particularly acute in the agricultural environment given the level of public investment in agri-environment schemes (AES). Using a novel multiscale hierarchical sampling design, we assess the effect of land use at multiple spatial scales (from location-within-field to regions) on farmland biodiversity. We show that on-farm biodiversity components depend on farming practices (organic vs. conventional) at farm and landscape scales, but this strongly interacts with fine- and coarse-scale variables. Different taxa respond to agricultural practice at different spatial scales and often at multiple spatial scales. Hence, AES need to target multiple spatial scales to maximize effectiveness. Novel policy levers may be needed to encourage multiple land managers within a landscape to adopt schemes that create landscape-level benefits.

Establishment of a cross-European field site network in the ALARM project for assessing large-scale changes in biodiversity

The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals.

Variation at range margins across multiple spatial scales: environmental temperature, population genetics and metabolomic phenotype

Range margins are spatially complex, with environmental, genetic and phenotypic variations occurring across a range of spatial scales. We examine variation in temperature, genes and metabolomic profiles within and between populations of the subalpine perennial plant Arabidopsis lyrata ssp. petraea from across its northwest European range. Our surveys cover a gradient of fragmentation from largely continuous populations in Iceland, through more fragmented Scandinavian populations, to increasingly widely scattered populations at the range margin in Scotland, Wales and Ireland. Temperature regimes vary substantially within some populations, but within-population variation represents a larger fraction of genetic and especially metabolomic variances. Both physical distance and temperature differences between sites are found to be associated with genetic profiles, but not metabolomic profiles, and no relationship was found between genetic and metabolomic population structures in any region. Genetic similarity between plants within populations is the highest in the fragmented populations at the range margin, but differentiation across space is the highest there as well, suggesting that regional patterns of genetic diversity may be scale dependent.

Geographical variation in the response to nitrogen deposition in Arabidopsis lyrata petraea

The adaptive responses to atmospheric nitrogen deposition for different European accessions of Arabidopsis lyrata petraea were analysed using populations along a strong atmospheric N-deposition gradient. Plants were exposed to three N-deposition rates, reflecting the rates at the different locations, in a full factorial design. Differences between accessions in the response to N were found for important phenological and physiological response variables. For example, plants from low-deposition areas had higher nitrogen-use efficiencies (NUE) and C : N ratios than plants from areas high in N deposition when grown at low N-deposition rates. The NUE decreased in all accessions at higher experimental deposition rates. However, plants from high-deposition areas showed a limited capacity to increase their NUE at lower experimental deposition rates. Plants from low-deposition areas had faster growth rates, higher leaf turnover rates and shorter times to flowering, and showed a greater increase in growth rate in response to N deposition than those from high-deposition areas. Indications for adaptation to N deposition were found, and results suggest that adaptation of plants from areas high in N deposition to increased N deposition has resulted in the loss of plasticity.

Parallel Declines in Pollinators and Insect-Pollinated Plants in Britain and the Netherlands

Despite widespread concern about declines in pollination services, little is known about the patterns of change in most pollinator assemblages. By studying bee and hoverfly assemblages in Britain and the Netherlands, we found evidence of declines (pre-versus post-1980) in local bee diversity in both countries; however, divergent trends were observed in hoverflies. Depending on the assemblage and location, pollinator declines were most frequent in habitat and flower specialists, in univoltine species, and/or in nonmigrants. In conjunction with this evidence, outcrossing plant species that are reliant on the declining pollinators have themselves declined relative to other plant species. Taken together, these findings strongly suggest a causal connection between local extinctions of functionally linked plant and pollinator species.

Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands

Despite widespread concern about declines in pollination services, little is known about the patterns of change in most pollinator assemblages. By studying bee and hoverfly assemblages in Britain and the Netherlands, we found evidence of declines (pre-versus post-1980) in local bee diversity in both countries; however, divergent trends were observed in hoverflies. Depending on the assemblage and location, pollinator declines were most frequent in habitat and flower specialists, in univoltine species, and/or in nonmigrants. In conjunction with this evidence, outcrossing plant species that are reliant on the declining pollinators have themselves declined relative to other plant species. Taken together, these findings strongly suggest a causal connection between local extinctions of functionally linked plant and pollinator species.

Spatial patterns in species distributions reveal biodiversity change

Interpretation of global biodiversity change is hampered by a lack of information on the historical status of most species in most parts of the world. Here we show that declines and increases can be deduced from current species distributions alone, using spatial patterns of occupancy combined with distribution size. Declining species show sparse, fragmented distributions for their distribution size, reflecting the extinction process; expanding species show denser, more aggregated distributions, reflecting colonization. Past distribution size changes for British butterflies were deduced successfully from current distributions, and former distributions had some power to predict future change. What is more, the relationship between distribution pattern and change in British butterflies independently predicted distribution change for butterfly species in Flanders, Belgium, and distribution change in British rare plant species is similarly related to spatial distribution pattern. This link between current distribution patterns and processes of distribution change could be used to assess relative levels of threat facing different species, even for regions and taxa lacking detailed historical and ecological information.

Coherence and discontinuity in the scaling of species' distribution patterns

The spatial distribution of a species can be characterized at many different spatial scales, from fine-scale measures of local population density to coarse-scale geographical-range structure. Previous studies have shown a degree of correlation in species' distribution patterns across narrow ranges of scales, making it possible to predict fine-scale properties from coarser-scale distributions. To test the limits of such extrapolation, we have compiled distributional information on 16 species of British plants, at scales ranging across six orders of magnitude in linear resolution (1 m to 100 km). As expected, the correlation between patterns at different spatial scales tends to degrade as the scales become more widely separated. There is, however, an abrupt breakdown in cross-scale correlations across intermediate (ca. 0.5 km) scales, suggesting that local and regional patterns are influenced by essentially non-overlapping sets of processes. The scaling discontinuity may also reflect characteristic scales of human land use in Britain, suggesting a novel method for analysing the 'footprint' of humanity on a landscape.

Extinction risk and the 1/f family of noise models

In order to predict extinction risk in the presence of reddened, or correlated, environmental variability, fluctuating parameters may be represented by the family of 1/f noises, a series of stochastic models with different levels of variation acting on different timescales. We compare the process of parameter estimation for three 1/f models (white, pink and brown noise) with each other, and with autoregressive noise models (which are not 1/f noises), using data from a model time-series (length, T) of population. We then calculate the expected increase in variance and the expected extinction risk for each model, and we use these to explore the implication of assuming an incorrect noise model. When parameterising these models, it is necessary to do so in terms of the measured ("sample") parameters rather than fundamental ("population") parameters. This is because these models are non-stationary: their parameters need not stabilize on measurement over long periods of time and are uniquely defined only over a specified "window" of timescales defined by a measurement process. We find that extinction forecasts can differ greatly between models, depending on the length, T, and the coefficient of variability, CV, of the time series used to parameterise the models, and on the length of time into the future which is to be projected. For the simplest possible models, ones with population itself the 1/f noise process, it is possible to predict the extinction risk based on CV of the observed time series. Our predictions, based on explicit formulae and on simulations, indicate that (a) for very short projection times relative to T, brown and pink noise models are usually optimistic relative to equivalent white noise model; (b) for projection timescales equal to and substantially greater than T, an equivalent brown or pink noise model usually predicts a greater extinction risk, unless CV is very large; and (c) except for very small values of CV, for timescales very much greater than T, the brown and pink models present a more optimistic picture than the white noise model. In most cases, a pink noise is intermediate between white and brown models. Thus, while reddening of environmental noise may increase the long-term extinction probability for stationary processes, this is not generally true for non-stationary processes, such as pink or brown noises.

Extrapolating species abundance across spatial scales

The analysis, measurement, and management of species abundance is central to ecology and conservation biology, but it has proved difficult to find a single index that adequately reflects the commonness or rarity of species across a range of spatial scales. Here, a scale-independent measure of species abundance is developed, using presence-absence maps at varying spatial resolutions. By extrapolating such "scale-area" curves, species abundance can be estimated accurately even at scales finer than those used to parameterize the model, a task that had previously been deemed impossible in principle.

Biodiversity at the edge: a test of the importance of spatial "mass effects" in the Rothamsted Park Grass experiments

The coexistence of many plant species competing for a few resources is one of the central puzzles of community ecology. One explanation is that different species may be competitively superior in different microhabitats. Many species could then coexist within each piece of a mosaic landscape by what has been termed "mass effects," because subpopulations in areas with negative growth rates would be supplemented by propagules from areas with reproductive surpluses. If mass effects are important, plant species diversity should increase near habitat boundaries, especially where habitat differences are moderate. In the first experimental test of this prediction, plants were censused on 54 transects within the long-established Rothamsted Park Grass plots. Very few showed significant declines in species richness with distance from subplot boundaries. Nonetheless, the regression coefficients were negative much more often than expected by chance, suggesting that weak mass effects operated. The effect was strongest where neighboring subplots differed greatly, with no evidence of the predicted decline where differences were extreme. Detailed analyses of transects with apparent mass effects revealed few species that behaved as predicted. This study serves both to provide evidence of the existence of mass effects and to question their importance in the maintenance of local plant diversity in this system.