Marco D. Visser

Forest canopy structure regulates understorey light environments, with implications for microclimate, plant regeneration, and ecosystem functioning. Lianas (woody vines) are increasingly abundant in tropical forests and influence forest structure by reducing tree growth and survival and altering crown architecture, potentially affecting light penetration to the understorey. However, liana-specific structural and leaf-level traits suggest opposing effects on light penetration, and their net outcome on light extinction remains unclear. Here, we combine continuous understorey light measurements and bitemporal airborne laser scanning in a large-scale liana removal experiment in a secondary tropical forest in Panama to quantify how lianas influence canopy structure and below-canopy light availability. We show that lianas increase canopy structural heterogeneity by increasing variability in canopy height and creating ~12 times more gaps and a ~22 times greater total gap area. These structural changes were associated with higher light availability below the canopy in plots with lianas, with understorey light levels 11% and 37% higher than in liana-removal plots in the dry and wet seasons, respectively. Our findings indicate that liana-driven modifications of canopy structure outweigh liana leaf structural and optical traits in controlling light transmission and suggest that structural effects dominate over seasonal changes in leaf phenology. Our study highlights the importance of accounting for liana-induced structural changes on forest light regimes, as these conditions ultimately shape the functional composition of future forest communities. Incorporating liana effects on forest structure into vegetation models is therefore necessary to accurately simulate understorey light environments and their cascading ecological consequences now and under future global change.

We issue a call to action: in the context of safe design, all pesticides must be traceable via low-cost methods that are accessible for routine environmental monitoring by public institutions. Insights into the far-reaching impacts of pesticides depend on our ability to detect these chemicals in the environment. Once a pesticide is authorized for use, environmental monitoring serves as a critical warning system that complements risk assessments. Postregistration monitoring is recognized by different policy frameworks such as the Water Framework Directive and the European Green Deal. However, we highlight an urgent concern: despite formal requirements for detectability in registration, novel pesticides are becoming progressively undetectable in practice. We demonstrate how mandated reductions in pesticide use measured as volume can drive chemical innovations that unintentionally undermine environmental accountability and safety. For example, volume can be decreased while maintaining effectiveness by increasing the specificity or toxicity of the pesticide. This phenomenon is analogous to “analytical homeopathy,” where active ingredients remain effective even at extremely low dosages, rendering them undetectable by standard analytical chemistry. This issues a significant challenge: higher toxicity can imply lower environmental quality standards near detection limits. This leads to the troubling problem of “known unknowns,” risks posed by active ingredients whose emissions remain unquantified under current field monitoring conditions. In response to this emerging threat, we propose a foundational principle, that all synthetic pesticides should be detectable in the environment at the concentration of their active ingredients, enabling cost-effective and reliable monitoring. If neglected, then the credibility and function of monitoring as a warning system for unintended biodiversity harm is increasingly undermined, regardless of formal analytical capabilities.

The persistence of local populations exposed to climate change depends on their adaptive potential and on the ability of local individuals to compete with migrating conspecifics tracking environmental shifts. Modern coexistence theory (MCT) offers a framework for studying such competitive interactions among genotypes. However, MCT often focuses on emerging population‐level outcomes, aggregating over the underlying individual‐level interactions. We present a cross‐scale application of MCT, combining it with an Integral Projection Model (IPM), explicitly connecting individual performance to population‐level dynamics. We parameterise our model using experimental data on competing Daphnia genotypes from two latitudes. Consistent with observations, our model shows that higher temperatures increase the likelihood of competitive exclusion of Northern genotypes by Southern genotypes. Moreover, it reveals latitudinal variation in neonate sex ratios as a driver of temperature‐dependent evolutionary shifts. By identifying vital rates underlying population‐level competitive outcomes, our approach preserves the straightforward theoretical interpretability of MCT, while providing enhanced process‐level resolution through IPMs.

Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits.

Lianas profoundly affect tropical forests dynamics, reducing productivity and carbon storage, which underscores the importance of monitoring change in their abundance in projecting the future of the global terrestrial carbon store. While increasing liana populations are documented within the Neotropics, the global consistency of these patterns is questioned, and remains to be determined. To evaluate pantropical trends in liana abundance comprehensively and quantitatively, we conducted a systematic literature review and meta‐analysis. This approach allowed us to synthesize data from published longitudinal studies examining liana trends across the tropics. We calculated standardized effect sizes and standard errors, and applied a Bayesian hierarchical meta‐analytic model to adjust for publication bias. Our analysis reveals an overall pan‐tropical increase in lianas abundance, occurring at an average rate of 1.7 ± 0.7 SE% per year (~10% to 24% per decade). This upward trend, confirmed to be robust against publication bias, extends beyond Neotropical regions, indicating a widespread phenomenon. Although a global trend of increasing liana abundance is evident, significant local variation exist, attributable to differences in life cycle stages, abundance metrics, forest successional stages, and biogeographical realms. Notably, increases in stem density of saplings and biomass of canopy lianas, especially in old‐growth forests, point to global climatic drivers and heightened turnover rates in tropical forests as factors promoting sustained liana growth in the canopy and clonal colonization in the understory. These trends suggest that the rise in liana abundance may not only persist but could also intensify under climate change. Considering both previous and current research on lianas, our findings confirm growing concerns about lianas' expanding impact on pan‐tropical carbon storage, highlighting their significant potential effect on global carbon dynamics.

The future trajectory of global forests is closely intertwined with tree demography, and a major fundamental goal in ecology is to understand the key mechanisms governing spatio‐temporal patterns in tree population dynamics. While previous research has made substantial progress in identifying the mechanisms individually, their relative importance among forests remains unclear mainly due to practical limitations. One approach to overcome these limitations is to group mechanisms according to their shared effects on the variability of tree vital rates and quantify patterns therein. We developed a conceptual and statistical framework (variance partitioning of Bayesian multilevel models) that attributes the variability in tree growth, mortality, and recruitment to variation in species, space, and time, and their interactions – categories we refer to as organising principles (OPs). We applied the framework to data from 21 forest plots covering more than 2.9 million trees of approximately 6500 species. We found that differences among species, the species OP, proved a major source of variability in tree vital rates, explaining 28–33% of demographic variance alone, and 14–17% in interaction with space , totalling 40–43%. Our results support the hypothesis that the range of vital rates is similar across global forests. However, the average variability among species declined with species richness, indicating that diverse forests featured smaller interspecific differences in vital rates. Moreover, decomposing the variance in vital rates into the proposed OPs showed the importance of unexplained variability, which includes individual variation, in tree demography. A focus on how demographic variance is organized in forests can facilitate the construction of more targeted models with clearer expectations of which covariates might drive a vital rate. This study therefore highlights the most promising avenues for future research, both in terms of understanding the relative contributions of groups of mechanisms to forest demography and diversity, and for improving projections of forest ecosystems.

Numerous studies have shown reduced performance in plants that are surrounded by neighbours of the same species^1,2, a phenomenon known as conspecific negative density dependence (CNDD)³. A long-held ecological hypothesis posits that CNDD is more pronounced in tropical than in temperate forests^4,5, which increases community stabilization, species coexistence and the diversity of local tree species^6,7. Previous analyses supporting such a latitudinal gradient in CNDD^8,9 have suffered from methodological limitations related to the use of static data^10–12. Here we present a comprehensive assessment of latitudinal CNDD patterns using dynamic mortality data to estimate species-site-specific CNDD across 23 sites. Averaged across species, we found that stabilizing CNDD was present at all except one site, but that average stabilizing CNDD was not stronger toward the tropics. However, in tropical tree communities, rare and intermediate abundant species experienced stronger stabilizing CNDD than did common species. This pattern was absent in temperate forests, which suggests that CNDD influences species abundances more strongly in tropical forests than it does in temperate ones¹³. We also found that interspecific variation in CNDD, which might attenuate its stabilizing effect on species diversity^14,15, was high but not significantly different across latitudes. Although the consequences of these patterns for latitudinal diversity gradients are difficult to evaluate, we speculate that a more effective regulation of population abundances could translate into greater stabilization of tropical tree communities and thus contribute to the high local diversity of tropical forests.

The high tree diversity in tropical forests has long been a puzzle to ecologists. In the 1970s, Janzen and Connell proposed that tree species (hosts) coexist due to the stabilizing actions of specialized enemies. This Janzen–Connell hypothesis was subsequently supported by theoretical studies. Yet, such studies have taken the presence of specialized pathogens for granted, overlooking that pathogen coexistence also requires an explanation. Moreover, stable ecological coexistence does not necessarily imply evolutionary stability. What are the conditions that allow Janzen–Connell effects to evolve? We link theory from community ecology, evolutionary biology and epidemiology to tackle this question, structuring our approach around five theoretical frameworks. Phenomenological Lotka–Volterra competition models provide the most basic framework, which can be restructured to include (single‐ or multi‐)pathogen dynamics. This ecological foundation can be extended to include pathogen evolution. Hosts, of course, may also evolve, and we introduce a coevolutionary model, showing that host–pathogen coevolution can lead to highly diverse systems. Our work unpacks the assumptions underpinning Janzen–Connell and places theoretical bounds on pathogen and host ecology and evolution. The five theoretical frameworks taken together provide a stronger theoretical basis for Janzen–Connell, delivering a wider lens that can yield important insights into the maintenance of diversity in these increasingly threatened systems.