To investigate the latitudinal variations in biomass allocation and reproduction investment, we conducted field survey across latitude. The study locations encompassed a stretch of the Pacific coast in China, covering a distance exceeding 2000 km. Ten specific locations were chosen to represent the majority of S. alterniflora distribution in China ( Figure 1 ). These 10 study locations ranged from Danzhou, Hainan (19.73°N), in the south to Dongying, Shandong (37.82°N), in the north ( Table 1 ). Since the introduced in 1979, rapid spread of S. alterniflora happened in China coastal, the invasion history of S. alterniflora in each location was range from 1985 to 2000 (An et al., 2007), except Hannan in 2015 (Zhang et al., 2017). We conducted field surveys from August to October 2021, which represented the end of the growing season at all locations (Chen et al., 2021). At this time, the peak of flowering had passed and plants were beginning to senesce.

At each location, we worked at two sites, 2-3 km apart (except Danzhou). At each site, we sampled three to five 0.5*0.5 m quadrats, with at least 30 m spacing between quadrats. To standardized elevation effects across all sites, we defined the best-growing as the tallest plants at each site. And study showed that plant height of S. alterniflora have a humped relationships with elevation (Li et al., 2018), tallest plants usually growing at mid/low marsh. All quadrats were sampled in the mid/low marsh, where S. alterniflora had the tallest plant and grows best (Liu et al., 2020b). In each quadrat, all plants (including adult plants and seedlings) were counted and used as an asexual reproduction trait (Xue et al., 2018). Then flowering culms were counted and used to calculate the ratio of flowering culms to adult plants, which served as a sexual reproduction trait (Liu et al., 2016). All the aboveground parts were harvested at ground level and immediately weighed in the field. A single representative shoot, which was tallest with complete inflorescence (Liu et al., 2022b), from each quadrat was taken to the laboratory, dried at 60 °C to constant mass, and weighed. The dry mass: fresh mass ratio of these shoots in each site (total 3-5 shoots) was used to calculate aboveground dry mass for each quadrat, served as aboveground biomass (AGB). Furthermore, the inflorescence biomass was determined for each representative shoot, served as another reproduction trait (Sun et al., 2001). A cylindrical soil core (15 cm diameter and 20 cm height) containing roots was removed and washed from each quadrat, most of the belowground organs was in the upper 20 cm soil profile (Darby and Turner, 2008). Belowground organs were divided into roots and rhizomes, and were taken to the laboratory dried at 60 °C for 72 h to determine the root biomass and rhizome biomass. All biomass data, including aboveground biomass, root biomass, and rhizome biomass were calculated proportionally to biomass per square meter. The belowground biomass (BGB) is equal to the sum of root biomass and rhizome biomass. The total biomass is equal to the sum of AGB and BGB. The ratio of rhizome biomass to belowground biomass (referred to as Rhizome: BGB ratio) serves as an indicator of asexual reproduction trait (Kaldy and Dunton, 2000), and the ratio of belowground biomass to aboveground biomass (referred to as the BGB: AGB ratio) serves as an indicator of biomass allocation strategy.

To investigate the relationship between S. alterniflora biomass allocation and local environmental factors, we collected three surface soil samples (under 5-10 cm from soil surface) near the quadrats at each site. Soil water content (WC) and soil porewater salinity (PS) were measured using the soil rehydration method (Pennings and Richards, 1998). We also collocated surface soil with a 100 cm³ ring knife at the same quadrats to measure soil bulk density (BD) by the bulk density ring method (Yang et al., 2018). The annual mean tidal range (MTR), which served as a local environmental factor, was obtained from the stations closest to each local in the National Marine Data and Information Service (http://www.nmdis.gov.cn).

To analyze the relationship between S. alterniflora biomass allocation and climate environmental factors, we collected daily meteorological data, including daily mean temperature and daily rainfall, from the city closest to each site during 2012 to 2021 (Nearly 10 years) in Climate Information for the China Meteorological Data Sharing Service System (https://data.cma.cn/). Mean annual temperature (MAT), annual number of growing days (> 10 °C) and mean annual precipitation (MAP) were calculated to represent the climate differences at each site. Growing degree days (GDD) measure the number of degrees that daily temperatures exceed a threshold temperature (10 °C) necessary for significant plant growth and therefore reflect both the temperature and duration of the growing season (Kirwan et al., 2009).

For statistical analysis purposes, we assumed that S. alterniflora in each quadrat was derived from an independent patch, so that each quadrat was a replicate. Thus, we have 5-10 replicates at each location. Regression analyses, including linear regression and polynomial regression, were used to identify the latitudinal trend of total biomass, AGB, BGB, BGB: AGB ratio, inflorescence biomass, flowering culm, shoot number and Rhizome: BGB ratio, furthermore used to identify the relationships between BGB: AGB ratio and reproduction traits, which include inflorescence biomass, flowering culm, shoot number and Rhizome: BGB ratio.

We used structural equation modeling (SEM) to explore the pathways of how environmental variables affected the BGB: AGB ratio. The SEM was based on the following hypotheses: 1) environmental factors can affect BGB: AGB ratio directly or indirectly by regulating reproductive investment (e.g., sexual reproduction and asexual reproduction) that drive biomass allocation. 2) environmental factors should divide in two parts, climate environmental factors (named climate environment) and non-climate environmental factors (named local environment), which have different effects on BGB: AGB ratio and reproductive investment. Owing to the large number of explanatory variables and strong correlations among variables ( Supplementary Tables S1 , S2 ), we developed multivariate functional indices through principal component analysis (PCA) before SEM. The first principal component (PC1) from the PCA conducted for the MAT, MAP and GDD were introduced in the SEMs to represent the climate environment. The first principal component (PC1) from the PCA conducted for the MTR, WC, PS and BD were introduced in the SEMs to represent the local environment. The first principal component (PC1) from the PCA conducted for the flowering culm and inflorescence biomass were introduced in the SEMs to represent the sexual investment. The first principal component (PC1) from the PCA conducted for the ratio of Rhizome: BGB ratio and shoot number were introduced in the SEMs to represent the asexual investment. We used Fisher’s C test, the Akaike information criteria (AIC) value, and P value to evaluate the goodness of these models. All statistical analyses were performed on raw data from each quadrat, and were conducted using R version 4.1.2 with the ‘vegan’ package for RDA analysis (Dixon, 2003), and the ‘piecewiseSEM’ package for SEM analyses (Lefcheck, 2016).

Niche theory posits that plants perform optimally in middle latitudes, with performance decreasing below or above these middle latitudes (Cody, 1991). Our findings corroborate this theory, as we observed that AGB, BGB, and total biomass were highest in the mid-latitudes. The latitudinal trend in AGB is consistent with previous studies on AGB of S. alterniflora in China (Liu et al., 2016; Xu et al., 2020). However, the latitudinal trends in AGB and BGB are inconsistent with earlier studies in S. alterniflora in its native range, where AGB decreased linearly from low to high latitude (Kirwan et al., 2009; Liu et al., 2020a). Due to the methodological challenges inherent in observing and quantifying BGB, there is a limited body of research investigating the latitudinal patterns of BGB in S. alterniflora in China. However, the available studies indicate a linear increase in BGB with latitude in its native range (Crosby et al., 2017; Gross et al., 1991). Overall, the difference in latitudinal trends between invasive and native ranges of BGB may depend on the distribution and the differences in environmental factors along latitudes (Liu et al., 2020a). Research conducted across a broader latitudinal gradient suggests that the decline in productivity of S. alterniflora at low and high latitude regions may translate to marshes more susceptible to the effects of sea level rise.

In this study, AGB and BGB were associated with most of environmental factors ( Supplementary Figure S1 , Supplementary Table S3 ), but the mean annual temperature, which decreases linearly with latitude, is the most important environment factor. The results suggest an optimal temperature for S. alterniflora growth, which is consistent with the law of limiting factors, that plants often perform better in favorable environmental conditions (Singh and Lal, 1935), and that deviations from these optimal conditions plant performance reduce plant size and biomass (Liu et al., 2016; Liu and Pennings, 2019). The result of AGB was consistent with previous studies (Liu et al., 2016, 2020a), as both high and low temperatures inhibit plant growth and physiological metabolism (Hatfield and Prueger, 2015). The effect of temperature on BGB was also well studied in a manipulative warming experiment, where a moderate amount of warming maximized root growth (Noyce et al., 2019). The warming experiment and our latitudinal investment suggest that global warming may have different impacts on salt marsh productivity across different latitudes. At lower latitudes, high temperatures exceed the optimal temperature of S. alterniflora, so that climate warming will reduce the growth of S. alterniflora. This reduction in biomass may result in lower latitude salt marshes being more vulnerable to sea level rise.

High BGB: AGB ratios at high latitudes in terrestrial ecosystems have been attributed to cold winter temperatures (Vogel et al., 2008), though complex vegetation types and various controlling factors obscure a consistent pattern in BGB: AGB ratio with latitude (Jin et al., 2022; Qi et al., 2019; Tedla et al., 2019). In contrast, we found that BGB: AGB ratios were highest in low latitudes, and decreased linearly with increasing latitude, indicating that S. alterniflora allocated relatively more biomass to belowground in southern than northern marshes in China. The latitudinal trend in BGB: AGB ratio is also inconsistent with an earlier study in S. alterniflora in its native range, in which BGB: AGB ratio increased linearly from low to high latitude (Crosby et al., 2017). This may be attributed to variances in the lowest latitudes between the two studies: 19.73°N in our study and 32.55°N in Crosby’s study. Additionally, there appears to be a linearly increasing trend from RD (32.46°N) to DY (37.82°N). Discrepancies in temperature, precipitation and other environment factors between the native and invasive ranges could also contribute to differential responses (Poorter et al., 2012). Biomass allocation in plants confirms to optimal partitioning theory (Mccarthy and Enquist, 2007) and is influenced by a variety of environmental factors, such that BGB: AGB ratio typically decreases with temperature, and exhibits a humped relationship with precipitation (Qi et al., 2019). Our study found BGB: AGB ratio decreased linearly from low to high latitude. The decreasing temperature with latitude may be the most important factor in our study ( Supplementary Figure S3 ). The results are consistent with a previous study, where four seagrass species showed a higher BGB: AGB ratio with temperature increases, because higher temperatures increase leaf respiration but decrease leaf photosynthesis, made them reallocate more AGB to BGB (George et al., 2018). Furthermore, early research showed first flowering day earlier at low latitude with higher temperature (Chen et al., 2021), earlier flowering had positive effect on BGB: AGB ratio (Liu et al., 2021), because most of photosynthetic products will transfer to belowground after flowering (Crosby et al., 2015). However, a warming experiment in a C4 Spartina patens marsh suggests that temperature had a non-linear effect on BGB and the BGB: AGB ratio, where BGB: AGB ratios were maximized for temperatures only slightly higher than ambient (Noyce et al., 2019). The effect of temperature on biomass allocation is also affected by other environmental factors (Ma et al., 2021). Our study found that both climate and local environments affect the BGB: AGB ratio of S. alterniflora. The salinity decreasing along the latitudinal gradient also affected the BGB: AGB ratio ( Supplementary Figure S1 ), consistent with a previous study (Zhou et al., 2021) that illustrated the increase in soil salinity inhibits the absorption of nitrogen by plant roots, more biomass allocates to belowground is needed to absorption of nitrogen (Tang et al., 2022). Even though the results corroborate the optimal partitioning theory. But the effect of different invasion history on latitudinal biomass allocation is not clearly. Future studies need to test the effects of different invasion history on biomass allocation of S. alterniflora in different latitudes, which can help to better understand the underly mechanisms of latitudinal biomass allocation.

Our results may indicate that, in the future, although global warming will reduce the productivity of S. alterniflora, rising temperatures may encourage the plant to allocate more biomass into the belowground part, which could partly mitigate the decline in ground elevation and the erosion from sea level rising. And studies showed that S. alterniflora growth better than native species under flooding and salinity stress (Xue et al., 2018; Xu et al., 2020), suggest that S. alterniflora was more tolerant than natives in future scenarios of increased sea-level and saltwater intrusion (Borges et al., 2021), the maintaining of S. alterniflora may help for costal erosion control under future climate change (Strong and Ayres, 2013). However, S. alterniflora had negative impact on the native coastal ecosystems (An et al., 2007). Many native species, including salt marshes and mangroves, endangered birds and benthonic animal are threatened by S. alterniflora invasion (Ma et al., 2003; Zhang et al., 2012). Furthermore, the widely spread of S. alterniflora in China also had damage in maricultural activities, soil formation, and accumulation of nutrients (Gao et al., 2016), harm of S. alterniflora may out weights its benefits.

Previous work in a salt marsh warming experiment suggests that biomass allocation of plants responds to temperature warming through internal changes in nitrogen supply and demand (Noyce et al., 2019; Bruns et al., 2024). This work finds that root:shoot ratios are maximized at intermediate temperatures because plants must allocate biomass to roots to satisfy high nitrogen demand even as nitrogen supplied by mineralization is relatively low (Noyce et al., 2019; Bruns et al., 2024). Our finding that BGB: AGB ratios increase linearly with temperature differs from the findings of an optimum (non-linear) response observed in the warming experiment, and suggests additional mechanisms may be at play. For example, the latitudinal gradient in aboveground biomass ( Figure 2 ) suggests that N demand should be lowest at low latitudes (i.e. low AGB), yet has the highest BGB: AGB ratio.

Previous studies indicate that reproductive investment also affects BGB: AGB ratio, such that increased sexual reproduction will reduce the BGB: AGB ratio (Sun et al., 2001; Skarpaas et al., 2016). In this study, the latitudinal patterns of sexual reproduction traits and asexual reproduction were contrasted in S. alterniflora. The latitudinal trend in sexual reproduction traits was also found in previous studies (Chen et al., 2021; Liu et al., 2016), which was embodied in the advance of flowering phenology (Crosby et al., 2015; Liu et al., 2022a) and the increase in seed set with increases in latitude (Liu et al., 2016). These increases may be due to shorter growth cycles and higher synchronization of flowering phenology at higher latitudes (Qiu et al., 2018). The latitudinal trends of asexual reproduction traits show that plants use the same resource pool for reproduction, and an increase in the investment in sexual reproduction inevitably reduces the investment in asexual reproduction (Thompson and Eckert, 2004). Furthermore, sexual reproduction cost more than asexual reproduction, consumes a lot of energy in individual growth to support flowering, cause less investment in asexual reproduction (Skarpaas et al., 2016).

Plants that favor sexual reproduction usually exhibit increased plant size and larger above-ground biomass (Liu and Pennings, 2019). Sexual reproduction requires substantial energy and this inhibits plant energy reserves in the belowground part of the plant (Liu et al., 2022a). In this study, the increasing sexual reproduction investment led to a decrease in the BGB: AGB ratio. On the other hand, asexual reproduction components, such as rhizomes, are an important part of belowground biomass, so that belowground biomass allocation decreases with the decrease in asexual reproduction (Xie et al., 2016). Furthermore, in the asexual reproduction stage, plants allocate more resources to the asexual reproductive organs which leads to a decrease in total biomass (Chen et al., 2019), resulting in a high BGB: AGB ratio at low latitudes. Overall, the lower input of sexual reproduction but the higher input of asexual reproduction resulted in a higher BGB: AGB ratio in low-latitude populations. Although the reasons for the difference in the reproductive investment of S. alterniflora along the latitude gradient remain to be studied, the higher investment in sexual reproduction in high latitude and the higher investment in asexual reproduction in low latitude contribute to a better understanding of the latitudinal biomass allocation pattern, indicating that the latitudinal trends of reproductive investment should be considered in the calculation of saltmarsh productivity on ecosystem function in the future.