Causality of the relationship between geographic distribution and species abundance

Relation between occupancy and abundance for a territorial species, the California spotted owl

Land and resource managers often use detection-nondetection surveys to monitor the populations of species that may be affected by factors such as habitat alteration, climate change, and biological invasions. Relative to mark-recapture studies, using detection-nondetection surveys is more cost-effective, and recent advances in statistical analyses allow the incorporation of detection probability, covariates, and multiple seasons. We examined the efficacy of using detection-nondetection data (relative to mark-recapture data) for monitoring population trends of a territorial species, the California Spotted Owl (Strix occidentalis occidentalis). We estimated and compared the finite annual rates of population change (λt ) and the resulting realized population change (Δt ) from both occupancy and mark-recapture data collected over 18 years (1993-2010). We used multiseason, robust-design occupancy models to estimate that territory occupancy declined during our study (Δt = 0.702, 95% CI 0.552-0.852) due to increasing territory extinction rates (ε(1993) = 0.019 [SE 0.012]; ε(2009) = 0.134 [SE 0.043]) and decreasing colonization rates (γ(1993) = 0.323 [SE 0.124]; γ(2009) = 0.242 [SE 0.058]). We used Pradel's temporal-symmetry model for mark-recapture data to estimate that the population trajectory closely matched the trends in territory occupancy (Δt = 0.725, 95% CI 0.445-1.004). Individual survival was constant during our study (φ(1993) = 0.816 [SE 0.020]; φ(2009) = 0.815 [SE 0.019]), whereas recruitment declined slightly (f(1993) = 0.195 [SE 0.032]; f(2009) = 0.160 [SE 0.023]). Thus, we concluded that detection-nondetection data can provide reliable inferences on population trends, especially when funds preclude more intensive mark-recapture studies.

Annual plants change in size over a century of observations

Studies have documented changes in animal body sizes over the last century, but very little is known about changes in plant sizes, even though reduced plant productivity is potentially responsible for declines in size of other organisms. Here, I ask whether warming trends in the Great Basin have affected plant size by measuring specimens preserved on herbarium sheets collected between 1893 and 2011. I asked how maximum and minimum temperatures, precipitation, and the Pacific Decadal Oscillation (PDO) in the year of collection affected plant height, leaf size, and flower number, and asked whether changes in climate resulted in decreasing sizes for seven annual forbs. Species had contrasting responses to climate factors, and would not necessarily be expected to respond in parallel to climatic shifts. There were generally positive relationships between plant size and increased minimum and maximum temperatures, which would have been predicted to lead to small increases in plant sizes over the observation period. While one species increased in size and flower number over the observation period, five of the seven species decreased in plant height, four of these decreased in leaf size, and one species also decreased in flower production. One species showed no change. The mechanisms behind these size changes are unknown, and the limited data available on these species (germination timing, area of occupancy, relative abundance) did not explain why some species shrank while others grew or did not change in size over time. These results show that multiple annual forbs are decreasing in size, but that even within the same functional group, species may have contrasting responses to similar environmental stimuli. Changes in plant size could have cascading effects on other members of these communities, and differential responses to directional change may change the composition of plant communities over time.

Incorporating the intraspecific occupancy-abundance relationship into zero-inflated models

Zero-inflated versions of standard distributions for count data are often required in order to account for excess zeros when modeling the abundance of organisms. Such distributions typically have as parameters lambda, the mean of the count distribution, and pi, the probability of an excess zero. Implementations of zero-inflated models in ecology typically model lambda using a set of predictor variables, and pi is fit either as a constant or with its own separate model. Neither of these approaches makes use of any relationship that might exist between pi and lambda. However, for many species, the rate of occupancy is closely and positively related to its average abundance. Here, this relationship was incorporated into the model for zero inflation by functionally linking pi to lambda, and was demonstrated in a study of snapper (Pagrus auratus) in and around a marine reserve. This approach has several potential practical advantages, including better computational performance and more straightforward model interpretation. It is concluded that, where appropriate, directly linking pi to lambda can produce more ecologically accurate and parsimonious statistical models of species abundance data.

Ecological niche structure and rangewide abundance patterns of species

Spatial abundance patterns across species' ranges have attracted intense attention in macroecology and biogeography. One key hypothesis has been that abundance declines with geographical distance from the range centre, but tests of this idea have shown that the effect may occur indeed only in a minority of cases. We explore an alternative hypothesis: that species' abundances decline with distance from the centroid of the species' habitable conditions in environmental space (the ecological niche). We demonstrate consistent negative abundance-ecological distance relationships across all 11 species analysed (turtles to wolves), and that relationships in environmental space are consistently stronger than relationships in geographical space.

Non-additive and non-stationary properties in the spatial distribution of a large marine fish population

Density-independent and density-dependent variables both affect the spatial distributions of species. However, their effects are often separately addressed using different analytical techniques. We apply a spatially explicit regression framework that incorporates localized, interactive and threshold effects of both density-independent (water temperature) and density-dependent (population abundance) variables, to study the spatial distribution of a well-monitored flatfish population in the eastern Bering Sea. Results indicate that when population biomass was beyond a threshold a further increase in biomass-promoted habitat expansion in a non-additive fashion with water temperature. In contrast, during years of low population size, habitat occupancy was affected positively only by water temperature. These results reveal the spatial signature of intraspecific abundance distribution relationships as well as the non-additive and non-stationary responses of species spatial dynamics. Furthermore, these results underscore the importance of implementing analytical techniques that can simultaneously account for density-dependent and density-independent sources of variability when studying geographical distribution patterns.

Efficient species-level monitoring at the landscape scale

Monitoring the population trends of multiple animal species at a landscape scale is prohibitively expensive. However, advances in survey design, statistical methods, and the ability to estimate species presence on the basis of detection-nondetection data have greatly increased the feasibility of species-level monitoring. For example, recent advances in monitoring make use of detection-nondetection data that are relatively inexpensive to acquire, historical survey data, and new techniques in genetic evaluation. The ability to use indirect measures of presence for some species greatly increases monitoring efficiency and reduces survey costs. After adjusting for false absences, the proportion of sample units in a landscape where a species is detected (occupancy) is a logical state variable to monitor. Occupancy monitoring can be based on real-time observation of a species at a survey site or on evidence that the species was at the survey location sometime in the recent past. Temporal and spatial patterns in occupancy data are related to changes in animal abundance and provide insights into the probability of a species' persistence. However, even with the efficiencies gained when occupancy is the monitored state variable, the task of species-level monitoring remains daunting due to the large number of species. We propose that a small number of species be monitored on the basis of specific management objectives, their functional role in an ecosystem, their sensitivity to environmental changes likely to occur in the area, or their conservation importance.

Species-specific responses of Late Quaternary megafauna to climate and humans

Despite decades of research, the roles of climate and humans in driving the dramatic extinctions of large-bodied mammals during the Late Quaternary period remain contentious. Here we use ancient DNA, species distribution models and the human fossil record to elucidate how climate and humans shaped the demographic history of woolly rhinoceros, woolly mammoth, wild horse, reindeer, bison and musk ox. We show that climate has been a major driver of population change over the past 50,000 years. However, each species responds differently to the effects of climatic shifts, habitat redistribution and human encroachment. Although climate change alone can explain the extinction of some species, such as Eurasian musk ox and woolly rhinoceros, a combination of climatic and anthropogenic effects appears to be responsible for the extinction of others, including Eurasian steppe bison and wild horse. We find no genetic signature or any distinctive range dynamics distinguishing extinct from surviving species, emphasizing the challenges associated with predicting future responses of extant mammals to climate and human-mediated habitat change.

Climate predictors of late quaternary extinctions

Between 50,000 and 3,000 years before present (BP) 65% of mammal genera weighing over 44 kg went extinct, together with a lower proportion of small mammals. Why species went extinct in such large numbers is hotly debated. One of the arguments proposes that climate changes underlie Late Quaternary extinctions, but global quantitative evidence for this hypothesis is still lacking. We test the potential role of global climate change on the extinction of mammals during the Late Quaternary. Our results suggest that continents with the highest climate footprint values, in other words, with climate changes of greater magnitudes during the Late Quaternary, witnessed more extinctions than continents with lower climate footprint values, with the exception of South America. Our results are consistent across species with different body masses, reinforcing the view that past climate changes contributed to global extinctions. Our model outputs, the climate change footprint dataset, provide a new research venue to test hypotheses about biodiversity dynamics during the Late Quaternary from the genetic to the species richness level.