Methods to account for spatial autocorrelation in the analysis of species distributional data: a review

Species distributional or trait data based on range map (extent‐of‐occurrence) or atlas survey data often display spatial autocorrelation, i.e. locations close to each other exhibit more similar values than those further apart. If this pattern remains present in the residuals of a statistical model based on such data, one of the key assumptions of standard statistical analyses, that residuals are independent and identically distributed (i.i.d), is violated. The violation of the assumption of i.i.d. residuals may bias parameter estimates and can increase type I error rates (falsely rejecting the null hypothesis of no effect). While this is increasingly recognised by researchers analysing species distribution data, there is, to our knowledge, no comprehensive overview of the many available spatial statistical methods to take spatial autocorrelation into account in tests of statistical significance. Here, we describe six different statistical approaches to infer correlates of species’ distributions, for both presence/absence (binary response) and species abundance data (poisson or normally distributed response), while accounting for spatial autocorrelation in model residuals: autocovariate regression; spatial eigenvector mapping; generalised least squares; (conditional and simultaneous) autoregressive models and generalised estimating equations. A comprehensive comparison of the relative merits of these methods is beyond the scope of this paper. To demonstrate each method's implementation, however, we undertook preliminary tests based on simulated data. These preliminary tests verified that most of the spatial modeling techniques we examined showed good type I error control and precise parameter estimates, at least when confronted with simplistic simulated data containing spatial autocorrelation in the errors. However, we found that for presence/absence data the results and conclusions were very variable between the different methods. This is likely due to the low information content of binary maps. Also, in contrast with previous studies, we found that autocovariate methods consistently underestimated the effects of environmental controls of species distributions. Given their widespread use, in particular for the modelling of species presence/absence data (e.g. climate envelope models), we argue that this warrants further study and caution in their use. To aid other ecologists in making use of the methods described, code to implement them in freely available software is provided in an electronic appendix.     

Retinoic acid–induced survival effects in SH-SY5Y neuroblastoma cells

Neuroblastoma is a malignant childhood cancer arising from the embryonic sympathoadrenal lineage of the neural crest. Retinoic acid (RA) is included in the multimodal therapy of patients with high-risk neuroblastoma to eliminate minimal residual disease. However, the formation of RA-resistant cells substantially lowers 5-year overall survival rates. To examine mechanisms that lead to treatment failure, we chose human SH-SY5Y cells, which are known to tolerate incubation with RA by activating the survival kinases Akt and extracellular signal-regulated kinase 1/2. Characterization of downstream pathways showed that both kinases increased the phosphorylation of the ubiquitin ligase mouse double minute homolog 2 (Mdm2) and thereby enhanced p53 degradation. When p53 signaling was sustained by blocking complex formation with Mdm2 or enhancing c-Jun N-terminal kinase (JNK) activation, cell viability was significantly reduced. In addition, Akt-mediated phosphorylation of the cell-cycle regulator p21 stimulated complex formation with caspase-3, which also contributed to cell protection. Thus, treatment with RA augmented survival signaling and attenuated basal apoptotic pathways in SH-SY5Y cells, which increased cell viability.     

The Dorsocross T-box genes are key components of the regulatory network controlling early cardiogenesis in Drosophila

Cardiac induction in Drosophila relies on combinatorial Dpp and Wg signaling activities that are derived from the ectoderm. Although some of the actions of Dpp during this process have been clarified, the exact roles of Wg, particularly with respect to myocardial cell specification, have not been well defined. Our present study identifies the Dorsocross T-box genes as key mediators of combined Dpp and Wg signals during this process. The Dorsocross genes are induced within the segmental areas of the dorsal mesoderm that receive intersecting Dpp and Wg inputs. Dorsocross activity is required for the formation of all myocardial and pericardial cell types, with the exception of the Eve-positive pericardial cells. In an early step, the Dorsocross genes act in parallel with tinman to activate the expression of pannier, a cardiogenic gene encoding a Gata factor. Our loss- and gain-of-function studies, as well as the observed genetic interactions among Dorsocross, tinman and pannier, suggest that co-expression of these three genes in the cardiac mesoderm, which also involves cross-regulation, plays a major role in the specification of cardiac progenitors. After cardioblast specification, the Dorsocross genes are re-expressed in a segmental subset of cardioblasts, which in the heart region develop into inflow valves (ostia). The integration of this new information with previous findings has allowed us to draw a more complete pathway of regulatory events during cardiac induction and differentiation in Drosophila.     

Predator–prey ratios on cocoa along a land-use gradient in Indonesia

Tropical landscapes are dominated by agroecosystems, but the potential value of agroecosystems for the survival of species is often overlooked. In agroecosystems, species conservation is especially important when functional groups such as predators are affected. In Central Sulawesi, we sampled arthropods on cocoa in a gradient of land-use intensity from extensively used forest gardens to intensively used agroforestry systems. The abundance and diversity of all arthropods did not correlate with land-use intensity, so human impact was not followed by high species losses. However, the number of species and abundance of the phytophagous arthropods increased and that of the entomophagous arthropods decreased with land-use intensity. The reduced predator–prey ratio in intensified systems can be related to their reduced species richness of shade trees and the changed microclimate (increased temperature, decreased humidity and canopy cover). In conclusion, transformation of traditional into intensified agroforestry systems had a great impact on arthropod community structure on cocoa. Since predator–prey ratios decreased with increasing land-use intensity, local farmers should have least pest problems in the traditionally diversified agroforestry systems.