Macroecological Theory Research Articles

Conservation biogeography of mammals in the Cerrado biome under the unified theory of macroecology

Understanding what limits the distribution and abundance of species is critical for adopting optimal conservation planning strategies, although it is still difficult to obtain abundance data at broad spatial scales. Here we propose conservation priorities in the Brazilian Cerrado based on density values of 108 mammal species. These values were estimated by an abundant-centre model coupled with McGill and Collin's unified theory for macroecology. We assumed that species' densities decay with a Gaussian distribution towards the range borders from a maximum density placed at the centre of each species' range. We used allometric equations to estimate maximum densities, at the Cerrado region we corrected the estimated densities by the natural vegetation remnants. Then we used a Simulated Annealing algorithm to select alternative sets of areas that met several levels of minimum viable population sizes (MVPSs) for each species. With low MVPSs, there were a small number of highly irreplaceable areas located in the northwest region of the biome, whereas with high MVPSs, highly irreplaceable areas occurred in up to 95% of the biome. By incorporating principles from the unified theory of macroecology, we were able to generate a conservation network for the Cerrado biome aiming to prioritise species' persistence and not just their presence.

Predicting the future of species diversity: macroecological theory, climate change, and direct tests of alternative forecasting methods

Accurate predictions of future shifts in species diversity in response to global change are critical if useful conservation strategies are to be developed. The most widely used prediction method is to model individual species niches from point observations and project these models forward using future climate scenarios. The resulting changes in individual ranges are then summed to predict diversity changes; multiple models can be combined to produce ensemble forecasts. Predictions based on environment‐richness regressions are rarer. However, richness regression models, based on macroecological diversity theory, have a long track record of making reliable spatial predictions of diversity patterns. If these empirical theories capture true functional relationships between environment and diversity, then they should make consistent predictions through time as well as space and could complement individual species‐based predictions. Here, we use climate change throughout the 20th century to directly test the ability of these different approaches to predict shifts of Canadian butterfly diversity. We found that all approaches performed reasonably well, but the most accurate predictions were made using the single best richness‐environment regression model, after accounting for the effects of spatial autocorrelation. Spatially trained regression models based on macroecological theory accurately predict diversity shifts for large species assemblages. Global changes provide pseudo‐experimental tests of those macroecological theories that can then generate robust predictions of future conditions.

Application of macroecological theory to predict effects of climate change on global fisheries potential

Global changes are shaping the ecology and biogeography of marine species and their fisheries. Macroecology theory, which deals with large scale relationships between ecology and bio- geography, can be used to develop models to predict the effects of global changes on marine species that in turn affect their fisheries. First, based on theories linking trophic energetics and allometric scaling of metabolism, we developed a theoretical model that relates maximum catch potential from a species to its trophic level, geographic range, and mean primary production within the species' exploited range. Then, using this theoretical model and data from 1000 species of exploited marine fishes and invertebrates, we analyzed the empirical relationship between species' approximated maximum catch potential, their ecology, and biogeography variables. Additional variables are inclu- ded in the empirical model to correct for biases resulting from the uncertainty inherent in the origi- nal catch data. The empirical model has high explanatory power and agrees with theoretical expec- tations. In the future, this empirical model can be combined with a bioclimate envelope model to predict the socio-economic impacts of climate change on global marine fisheries. Such potential application is illustrated here with an example pertaining to the small yellow croaker Larimichthys polyactis (Sciaenidae) from the East China Sea.

Species Diversity in Local Neutral Communities

We extend the neutral theory of macroecology by deriving biodiversity models (relative species abundance and species-area relationships) in a local community-metacommunity system in which the local community is embedded within the metacommunity. We first demonstrate that the local species diversity patterns converge to that of the metacommunity as the size (scale) of the embedded local community increases. This result shows that in continuous landscapes no sharp boundaries dividing the communities at the two scales exist; they are an artificial distinction made by the current spatially implicit neutral theory. Second, we remove the artificial restriction that speciation cannot occur in a local community, even if the effects of local speciation are small. Third, we introduce stochasticity into the immigration rate, previously treated as constant, and demonstrate that local species diversity is a function not only of the mean but also of the variance in immigration rate. High variance in immigration rates reduces species diversity in local communities. Finally, we show that a simple relationship exists between the fundamental diversity parameter of neutral theory and Simpson's index for local communities. Derivation of this relationship extends recent work on diversity indices and provides a means of evaluating the effect of immigration on estimates of the fundamental diversity parameter derived from relative species abundance data on local communities.

Rare species, habitat diversity and functional redundancy in marine benthos

Macro-ecological theories relating species richness, abundance, range size, biological traits and environmental tolerance have rarely been tested in marine soft-sediments, despite the spatial extent of these habitats and the inherent richness of resident communities. This study examines the contribution of rare species to marine soft-sediment communities from New Zealand, focussing on the relationships of range size with abundance, environment, habitat diversity and life history traits. 54% of the 351 species sampled exhibited restricted ranges (found at ≤ 2 sites). In contrast to many terrestrial systems, we observed only a weak positive relationship between abundance and frequency of occurrence. Restricted-range species were not randomly distributed, with their distribution related to habitat characteristics, suggesting an important link between habitat diversity and rarity. They exhibited a similar range of traits to the total observed species pool, suggesting that they are not only important to biodiversity but could play a role in stability. Restricted range species were generally not small and this, together with the number of different biological traits represented, suggests that rare species are important to the functioning of marine systems. Thus, our results highlight the importance of considering rare species in habitat-based approaches to conservation.

Species Diversity in Local Neutral Communities

We extend the neutral theory of macroecology by deriving biodiversity models (relative species abundance and species‐area relationships) in a local community‐metacommunity system in which the local community is embedded within the metacommunity. We first demonstrate that the local species diversity patterns converge to that of the metacommunity as the size (scale) of the embedded local community increases. This result shows that in continuous landscapes no sharp boundaries dividing the communities at the two scales exist; they are an artificial distinction made by the current spatially implicit neutral theory. Second, we remove the artificial restriction that speciation cannot occur in a local community, even if the effects of local speciation are small. Third, we introduce stochasticity into the immigration rate, previously treated as constant, and demonstrate that local species diversity is a function not only of the mean but also of the variance in immigration rate. High variance in immigration rates reduces species diversity in local communities. Finally, we show that a simple relationship exists between the fundamental diversity parameter of neutral theory and Simpson’s index for local communities. Derivation of this relationship extends recent work on diversity indices and provides a means of evaluating the effect of immigration on estimates of the fundamental diversity parameter derived from relative species abundance data on local communities.

Niche breadth and geographical range: ecological compensation for geographical rarity in rainforest frogs

We investigated the relationship between diet specialization and geographical range in Cophixalus, a genus of microhylid frogs from the Wet Tropics of northern Queensland, Australia. The geographical ranges of these species vary from a few square kilometres in species restricted to a single mountain top to the entire region for the widespread species. Although macroecological theory predicts that species with broad niches should have the largest geographical ranges, we found the opposite: geographically rare species were diet generalists and widespread species were diet specialists. We argue that this pattern is a product of extinction filtering, whereby geographically rare and therefore extinction-prone species are more likely to persist if they are diet generalists.

Unusual abundance–range size relationship in an Afromontane bird community: the effect of geographical isolation?

AbstractAim To show that the frequently reported positive trend in the abundance–range‐size relationship does not hold true within a montane bird community of Afrotropical highlands; to test possible explanations of the extraordinary shape of this relationship; and to discuss the influence of island effects on patterns of bird abundance in the Cameroon Mountains.Location Bamenda Highlands, Cameroon, Western Africa.Methods We censused birds during the breeding season in November and December 2003 using a point‐count method and mapped habitat structure at these census points. Local habitat requirements of each species detected by point counts were quantified using canonical correspondence analysis, and the size of geographical ranges of species was measured from their distribution maps for sub‐Saharan Africa. We tested differences in abundance, niche breadth and niche position between three species groups: endemic bird species of the Cameroon Mountains, non‐endemic Afromontane species, and widespread species.Results We detected neither a positive nor negative abundance–range‐size relationship in the bird community studied. This pattern was caused by the similar abundance of widespread, endemic and non‐endemic montane bird species. Moreover, endemic and non‐endemic montane species had broader local niches than widespread species. The widespread species also used more atypical habitats, as indicated by the slightly larger values of their niche positions.Main conclusions The relationship detected between abundance and range size does not correspond with that inferred from contemporary macroecological theory. We suggest that island effects are responsible for the observed pattern. Relatively high abundances of montane species are probably caused by their adaptation to local environmental conditions, which was enabled by climatic stability and the isolation of montane forest in the Cameroon Mountains. Such a unique environment provides a less suitable habitat for widespread species. Montane species, which are abundant at present, may also have had large ranges in glacial periods, but their post‐glacial distribution may have become restricted after the retreat of the montane forest. On the basis of comparison of our results with studies describing the abundance structure of bird communities in other montane areas in the Afrotropics, we suggest that the detected patterns may be universal throughout Afromontane forests.

Fish abundance with no fishing: predictions based on macroecological theory

SummaryFishing changes the structure of fish communities and the relative impacts of fishing are assessed usefully against a baseline. A comparable baseline in all regions is fish community structure in the absence of fishing.The structure of unexploited communities cannot always be predicted from historical data because fisheries exploitation usually precedes scientific investigation and non‐fisheries impacts, such as climate change, modify ecosystems over time.We propose a method, based on macroecological theory, to predict the abundance and size‐structure of an unexploited fish community from a theoretical abundance–body mass relationship (size spectrum).We apply the method in the intensively fished North Sea and compare the predicted structure of the unexploited fish community with contemporary community data.We suggest that the current biomass of large fishes weighing 4–16 kg and 16–66 kg, respectively, is 97·4% and 99·2% lower than in the absence of fisheries exploitation. The results suggest that depletion of large fishes due to fisheries exploitation exceeds that described in many short‐term studies.Biomass of the contemporary North Sea fish community (defined as all fishes with body mass 64 g−66 kg) is 38% lower than predicted in the absence of exploitation, while the mean turnover time is almost twice as fast (falls from 3·5 to 1·9 years) and 70% less primary production is required to sustain it.The increased turnover time of the fish community will lead to greater interannual instability in biomass and production, complicating management action and increasing the sensitivity of populations to environmental change.This size‐based method based on macroecological theory may provide a powerful new tool for setting ecosystem indicator reference levels, comparing fishing impacts in different ecosystems and for assessing the relative impacts of fishing and climate change.

Strong and weak tests of macroecological theory

Macroecology is a rapidly growing branch of ecology. The essence of macroecology can be summarized as a two-step process: 1) find large-scale patterns and 2) find the explanations/mechanisms for those patterns. Much of the work on step 1 has focused on identifying the shape of various curves. This includes some of the most famous of all macroecological patterns: the power-law (S=cA) species area relationship (SPAR), the hollow curve distribution of species abundances (SAD), and the skewed-lognormal distribution of body size (BSD). A large number of papers have debated the correct curve shapes. For example it has been suggested that SPARs should really be logarithmic, sigmoidal, or asymptotic (such as the Michaelis–Menton) instead of the power law (Connor and McCoy 1979, Sugihara 1981, Connor et al. 1983, Williams 1995, Lomolino 2000, 2002, Lomolino and Weiser 2001, Williamson et al. 2001). Over two-dozen different distributions have been suggested for the SAD (Pielou 1977, Tokeshi 1993). Moreover, much of the work on step 2 has proceeded by testing theories according to whether they produce curves of the correct shape (i.e. the shape observed in nature). In short, it is fair to say that macroecology has been practiced as a study of curve shapes. I argue that this focus on curve shapes is unfortunate and even counterproductive for macroecology. To see why, let us explore in more detail how macroecological mechanisms are identified. Unfortunately, macroecological questions are, almost by definition, too large to perform the type of replicated, manipulative, controlled experiments that form the backbone of scientific progress in much of the rest of ecology. Thus, the search for mechanism usually proceeds through theory. A theory is built which suggests that if certain mechanisms are important, then certain predictions should be true. If the predictions fail, the mechanisms lose credence; if they succeed, the mechanisms accumulate support. Of course, the strength of this method depends on the quality of the predictions. In practice, often the sole prediction made is the shape of the curve (with parameters free to maximize fit). The weakness of this mode of testing is most painfully obvious in the search for mechanisms in one of the oldest and most well known patterns in macroecology: the species abundance distribution (SAD). The SAD describes the relative abundances of different species within a community – many rare species and a few highly abundant species (known as a hollow curve). Well over two dozen different curves have been suggested as the ‘‘right’’ curve with more coming every year (Pielou 1977, Tokeshi 1993, Sichel 1997, Harte et al. 1999, Dewdney 2000, Hubbell 2001). This work on SADs has proceeded as I previously described: a hypothesized mechanism leads to a theory that makes one prediction about curve shape. Macroecologists ought to worry that dozens of theories have been proposed and all fit the data. Macroecologists must also worry that few if any curves (and their mechanisms) have been decisively rejected. In short, this mode of testing has failed to reject most of the dozens of proposed theories. In the rest of this paper, I will first try to demonstrate that testing exclusively by curve fitting is very weak and a poor way for macroecology to proceed in the search for mechanisms. Then, I will look at some ways to make stronger tests.

SAMPLING THE SPECIES COMPOSITION OF A LANDSCAPE

The abundances and spatial distribution of species is central to biogeography and conservation. Several theories have been offered to explain landscape-scale species distribution patterns. The verification of biogeographic theories, as well as conservation decisions, must be based upon empirical data gathered from necessarily restricted censuses. It is necessary, therefore, to understand the relationship between an underlying landscape-scale pattern and the corresponding pattern it produces upon sampling small subregions. The similarity of species composition between two samples depends not only on the species composition of the underlying landscape from which the samples are drawn, but also on the underlying distribution of species abundances, the degree of conspecific spatial clustering, and sample size. In this paper, we investigate how sampling expectations change depending upon species abundance distributions and upon spatial distributions. We derive analytical results for the expected species overlap between two sampled regions under a wide range of conditions. We compare these results with data from a 50-ha tropical forest census. These methodologies provide useful tools for assessing beta diversity, for testing macro-ecological theory, and for designing landscape-scale sampling schemes.

Sampling the Species Composition of a Landscape

The abundances and spatial distribution of species is central to biogeography and conservation. Several theories have been offered to explain landscape-scale species distribution patterns. The verification of biogeographic theories, as well as conservation decisions, must be based upon empirical data gathered from necessarily restricted censuses. It is necessary, therefore, to understand the relationship between an underlying landscape-scale pattern and the corresponding pattern it produces upon sampling small subregions. The similarity of species composition between two samples depends not only on the species composition of the underlying landscape from which the samples are drawn, but also on the underlying distribution of species abundances, the degree of conspecific spatial clustering, and sample size. In this paper, we investigate how sampling expectations change depending upon species abundance distributions and upon spatial distributions. We derive analytical results for the expected species overlap between two sampled regions under a wide range of conditions. We compare these results with data from a 50-ha tropical forest census. These methodologies provide useful tools for assessing beta diversity, for testing macro-ecological theory, and for designing landscape-scale sampling schemes.